The Evolution of Adaptive Systems: The General Theory of Evolution

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The Evolution of Adaptive Systems

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The Evolution of Adaptive Systems James P. Brock

This book is printed on acid-free paper. Copyright 2000 by ACADEMIC PRESS All Rights Reserved.

No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Academic Press A Harcourt Science and Technology Company 525 B Street, Suite 1900, San Diego, California 92101-4495 http://www.academicpress.com Academic Press Harcourt Place, 32 Jamestown Road, London NW1 7BY http://www.hbuk.co.uk/ap/ Library of Congress Catalog Card Number: 00-102539 International Standard Book Number 0-12-134740-0 PRINTED IN THE UNITED STATES OF AMERICA 00 01 02 03 04 05 MM 9 8 7 6 5 4

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Dedicated to Diane and Melanie

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CONTENTS

FOREWORD ix PREFACE xi

1 2 3 4 5 6 7 8 9 10 11

Adaptation and the Adaptive System 1 Spatial Structure of the Adaptive Niche 27 Dynamics of the Adaptive Niche 43 The Selection Interface 53 Adaptive Equilibrium 67 The Cladogenetic Selection Interface 85 Adaptive Potential, Biophysical Paradigms, and the Selectional Attractor 121 Evolutionary Mode 145 Structural Paradigms of Development 161 Adaptive Capacity and Potential in the Mechanisms of Development 175 Developmental Genetics, Adaptive Capacity, and Potential 199 vii

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CONTENTS

12 13 14 15 16 17 18 19 20 21

Mutation and Realization of Adaptive Potential 231 Chromosome Structure and Adaptive Topography 275 Evolutionary Impediments and the Adaptive Substrate for Evolutionary Change 299 Darwinian versus Thompsonian Factors in Evolution 325 The Morphogenetic Topology of Evolutionary Change 351 Architecture of the Phyletic Lineage 401 Evolutionary Rate and Episodic Evolution 441 Stasis and the Adaptive Substrate 491 Extinction—Lineage to Clade 511 From Lineage to Taxon 531 EPILOGUE: AN OVERVIEW OF THE GENERAL THEORY 591 GLOSSARY 599 BIBLIOGRAPHY 619 INDEX 631

FOREWORD

The study of evolutionary biology is at an exciting time as many new ideas and new techniques are integrated into our understanding of the process. Too often the trend has been to take an extreme reductionist approach and pull everything apart into the smallest possible unit. The study of adaptations does not lend itself to that approach because natural adaptive systems evolve as a unit in response to an extremely wide range of external functions. Adaptation is also the fundamental process underlying the behavior of natural biotic systems. I therefore welcome this book that brings together a broad spectrum of data about the adaptive process in a well-integrated way. It also does a lot to deﬁne and clarify terms that have been used in so many different ways, but you will have to learn several new terms as you read this book. This is a timely volume written by a natural historian who has a broad view of biology and who draws examples from a large range of organisms from many different habitats and niches where interesting adaptations have evolved, yet the book probes deeply into the mechanisms of evolution such as developmental genetics, morphogenesis, chromosome structure and cladogenesis. The recent advance in these ﬁelds and especially in developmental genetics enables a much deeper analysis of adaptive systems and of the way in which natural selection works. Here we have an in-depth analysis of the adaptive side of evolution that will be of considerable use to all evolutionary biologists. Professor Sir Ghillean Prance FRS Director, Royal Botanic Gardens, Kew

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PREFACE

The data of evolutionary biology have changed in a very radical way since the 1960s, the most signiﬁcant input to this revolution perhaps having been the great advances made in developmental genetics. The dialetic of the ‘‘synthetic school’’ which preceded this explosion of information is now inadequate to serve as an analytical tool to assimilate these new data, and there thus exists a real need for provision of a ﬁrm basis for a fresh overview of contemporary knowledge in the context of the wider adaptive system. Another recent development is a noticeable shift away from the trend toward extreme specialization in evolutionary biology, and in this, we are perhaps to be reminded of the comments of George Gaylord Simpson: ‘‘Evolution is an incredibly complex but at the same time integrated and unitary process. Violence is done whenever we pick out one factor, process, or element of the pattern and attempt to consider this apart from the whole.’’ Indeed, evolution either is panmictic in biology or else is a loose set of unconnected populations with little or no gene migration between. This broader view should be the starting point from which any fresh analysis should proceed. The main objective of this book is to illustrate how natural adaptive systems evolve as a unity, with the particular objective of identifying and merging several ‘‘special theories’’ of evolution within the framework of a single general theory. The outlook thus follows an interdisciplinary ideal, looking at the ways in which diverse subject areas within biology interlink in their relationship to evolutionary theory with particular respect to large scale, longer term manifestations of the evolutionary process. The approach has been especially concerned with the dynamic behavior of biotic adaptive systems, with special reference

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PREFACE

to the question of innate capacities and potentials residing in such systems—an understanding of which latter may be incorporated into conceptual structures relating the static aspect to the dynamic. The methodology has been to look ﬁrstly at the fundamental structure of the adaptive system itself, following this with a deeper analysis of niche and environment with respect to the manner in which organism and environment interact in the state of adaptive equilibrium. This leads naturally to the question of the means by which innate evolutionary potential in adaptive systems is actually realized—a process which must be located in a ﬁrm understanding of development and of the mechanisms of genetic control over developmental events. The way in which major patterns of structural differentiation arise and are sculptured by selection during the course of long-term evolution thus forms the central core of the ensuing argument. Finally, I have looked brieﬂy at the criteria of phylogeny reconstruction in the light of constraints emerging from ﬁndings concerning the evolutionary process. The analytical approach throughout this study has concerned a search for minimum models within each area of investigation, rather than to follow each line of enquiry into specialized areas remote from the primary aims and objectives of the book. Each topic is thus given a broadly biosystematological treatment, and it will be fruitless to look for anything beyond that. In this, I have followed the maxim that ‘‘everything should be simpliﬁed as much as possible—but no more than desirable’’ (thus remaining wary of any assumption that the simplest explanation is necessarily the correct one!). So far as the raw data of evolutionary biology are concerned, I have not attempted to give a comprehensive coverage of observational data other than via the medium of brief cross-references to other sources. Attention must be drawn to the fact that it has been found necessary to introduce a certain amount of new terminology in this study. Too large a proportion of the existing dialectic is confused, with the same term at times being used to denote wholly different phenomena, or several terms encompassing merely a single mechanism. There has thus frequently been a difﬁcult choice to make between creation of new or revision of existing terminology. Wherever I have chosen the latter option, I have striven to indicate precisely where and why a revised usage of a term is used, and introduction of entirely new nomenclature has generally been the chosen option only with new or radically re-formed concepts. Owing to the fact that ﬁrst attempts at redeﬁnition of a term frequently resulted in the discovery that other terms used axiomatically in new deﬁnitions were themselves heterogeneous, redeﬁnition of terms has been designed to meet the criterion of interdisciplinary homogeneity, rather than to necessarily agree with any supposedly accepted or contemporary usage. So far as the reader is concerned, this means careful attention must be paid to the precise meaning of the nomenclature, for a clear understanding of the train of argument followed in this book. Resolving the semantic question is, of course, only a secondary goal to the reﬁnement and revision of earlier theoretical structures. In this endeavor, introduction of new concepts should, it is hoped, seek to avoid extreme polarization in the reassessment of earlier ideas, thus (wherever appropriate) following the viewpoint of G. L. Stebbins that ‘‘new facts require modiﬁcation and

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ampliﬁcation of accepted principles, rather than their rejection.’’ Nevertheless, the adaptive systems approach does in fact also lead to radically new conceptual structures, the relationships of which to some earlier models that are quite widely held to constitute mere observational data in disguise, must of course be rendered fully explicit. As a general rule, I have striven to distinguish between hypothesis and theory throughout, seeking an holistic view, rather than a standpoint biased toward any particular school of thought. Many apparent divergencies of opinion in evolutionary biology really reﬂect an intrinsic pluralism in the manner in which biotic adaptive systems exist and evolve in Nature. This pluralism lies not only in the deep dichotomy between unicells and higher organisms (which latter form the subject matter of the present work), but also between different lineages of multicellular organisms. Despite this problem, there must of course be many fundamental axioms which do apply more or less universally to the evolution of multicellular organisms, and discovering what these axioms are obviously constitutes a major objective in any work of this kind. Of even greater priority in the question of pluralism is the problem of ‘‘generality’’ itself. There are, indeed, several ‘‘special’’ theories of evolution. Quite apart from the question as to how these structures integrate in the context of a general theory, it is not at all clear what these components actually are. Even the widely held assumption that any general theory must constitute a further expansion of ‘‘neo-Darwinism’’ must be challenged most assidiously (and, indeed, the solution proposed in the present work plainly does not in fact fall into that category). Last, it is necessary to add the customary coda that all works of this size are inevitably shortcuts to what should have been a more extensive treatment, and all carry the same apology, namely, that omissions are at least in part due to the impossibility of encompassing everything in the time available.

ACKNOWLEDGMENTS Various institutions have provided facilities connected in one way or another with the groundwork which went into this study, most notably (and in chronological order), the Universities of Glasgow, Oxford, Liverpool, and London (Imperial College). Most signiﬁcantly, the Director and Trustees of the Horniman Museum played a lead role in provision of facilities for completion of the book. This help, along with that provided by the Horniman Library, Leaford Patrick (Deputy Keeper of Natural History at the Horniman Museum), and the libraries of The Linnean Society and Imperial College, is gratefully acknowledged. My wife Diane and daughter Melanie endured a great many privations during the writing period, and a special thank you goes to them. James P. Brock

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ADAPTATION AND THE ADAPTIVE SYSTEM

While it may be possible to conceive of a simple biotic system existing as a single organic entity, all life-forms really exist within the conﬁnes of a larger adaptive system in which competition occurs within and between gene pool boundaries, and where diverse means of cycling energy exist as a function of the strategy of interactivity within the system. The origins of evolutionary change lie in the fundamental structure of this adaptive system.

ADAPTATION AS A PROCESS Fundamental to any discussion of biological principles is the differential between process, mechanism, and emergent properties arising from the nature of the temporospatial matrix in which biotic adaptive systems operate. A process is deﬁned here in the context of an adaptive goal: the reason some biotic function is being carried out (namely, any activity directly involved in promoting survivorship). A functional mechanism then concerns the means by which a given process is actually realized (competition, natural selection, etc.). Additionally, an emergent evolutionary corollary constitutes some point of interest arising from a process or mechanism, but which is clearly neither: for example, a gene pool is holistically adapted to a varied external environment as a corollary of a mechanism operating at the level of individual selectional activity. A further term that has been used in a similar context is effect, which is seen here as constituting a corollary that is not a point of any evolutionary interest. Williams (1966) uses the ‘‘apple’s contribution to Newtonian inspiration’’ as an example of an effect—also, the red color of blood containing

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hemoglobin. An appreciation of the difference between the above gene pool example and those just given should sufﬁce to explain the differential between corollary and effect, and the fundamental signiﬁcance of the former compared to the irrelevance of the latter. In the past, theoretical structures in evolutionary biology have often been built around corollaries and effects, with the result that our understanding of process and mechanism has frequently been obscured (as with the Haeckelian doctrine of recapitulation, to name but one example). While many signiﬁcant evolutionary corollaries arise in the context of adaptational mechanisms (as with the architecture of the gene pool mentioned above), a great many ‘‘effects’’ (sensu Williams) are clearly of no biosystematological interest whatsoever. However, the existence of many mechanismic and processive corollaries in the evolution of adaptive systems does suggest that we need to concern ourselves with both primary and emergent aspects of the behavior of adaptive systems. It is a basic goal of this book to attempt to unravel the correct hierarchic relationship between process, mechanism, corollary, and effect, and in particular to dismember many of the heterogenies which still exist in evolutionary biology as a result of lack of clarity in this domain. In this study, the central process is clearly that of adaptation itself,* and this is affected by a complex hierarchy of mechanisms manifesting a range of functions. Secondary to the relationship between mechanism and process lies the question of the evolutionary corollary, in that many signiﬁcant biological phenomena are essentially levels of complexity arising from some mechanism or process operating at a lower level.

ADAPTATION AND ADAPTIVE CAPACITY Any attempt at an analysis of the behavior of adaptive systems clearly must begin with a deﬁnition of the term adaptation itself. In attempting to solve this problem, a useful approach would be to look ﬁrstly at the different ways in which ‘‘adaptation’’ has been characterized in the past. Using the term adaptation in the context in which it has previously been more loosely applied, it is quite possible to assemble the following statement: The horns of rhinos are an adaptation of the hair on the top of the head. This is an adaptation for defense; however, the character ‘‘number of horns’’ is nonadaptive. Any attempt to ﬁnd a consistent deﬁnition of the term adaptation that will easily resolve the above anomaly will reveal something of the confusion that has been wrought! How can we discuss (for example) the possibility of a nonadaptive input to evolution, when the term adaptation has not itself been adequately deﬁned?

Adaptation Deﬁned According to Rose and Lauder (1996), adaptation refers both to a process and to its product—the process of modifying one thing to another, and the condition * Adaptation clearly forms the true essence of the Darwinian thesis, in that selection has no meaning in any other context.

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of being adapted. Adaptation looks to the past and to a trait’s selective history, while ﬁtness points to future reproductive success. The process of adaptation (natural selection) is a cause of states of adaptation. It is also, however, quite widely agreed at the present time that there are disadvantages in using adaptation to mean both process of change and ﬁtness enhancing state. Thus, while it appears that there is general agreement that adaptation is concerned with survivorship, there is concern that the term is often used synonymously with others linked to the same propensity. Disentangling adaptation proper from this heterogeny therefore becomes a necessary prerequisite to any rigorous investigation of evolutionary theory. Various solutions have been proposed to the problem of adaptation. The following treatment begins with a brief survey of some variants of current and past usage, continuing with a solution linked to the analysis of adaptive systems (and accepting the link with survivorship as axiomatic): Adaptation as function

Adaptation as functional change

Adaptation as change of form

Adaptation as evolution Adaptation as specialization

Adaptation as differential in ﬁtness

Adaptation as absolute ﬁtness

The statement, ‘‘The wing is an adaptation for ﬂight,’’ can be equated with, ‘‘The function of a wing is ﬂight’’ (in that, depending on context, ﬂight may or may not manifest an actual input to survivorship). ‘‘The walking limb was adapted for ﬂight.’’ Adaptation is not exactly synonymous with functional change, since there is clearly also a static aspect to the adaptational process (the ‘‘nonadapted’’ walking limb must also serve an adaptive role!). Here, adaptive shift is the preferred description. ‘‘The planispiral cephalopod shell has been adapted to form a variety of different conﬁgurations.’’ Adaptation is not exactly synonymous with change of form, since (for example) vestigiating structures are changing form but not ‘‘adapting.’’ ‘‘The process through which adaptedness is acquired is called adaptation’’ (Cockburn, 1991). This is clearly an abbreviation for adaptive evolution. ‘‘The reduced form of many parasites is due to adaptation to mode of life.’’ Adaptation is not synonymous with ‘‘specialization,’’ since ‘‘generalized’’ structures clearly also express adaptation in terms of manifestation of propensity for survivorship. ‘‘Adaptation refers to a state of form that is more efﬁcient than some other, related state’’ (‘‘a ﬁtness enhancing trait which was produced by selection for its current ﬁtness beneﬁts,’’ following Fisher, 1930). This statement refers not to adaptation, but to an adaptational differential. The latter is in fact concerned with selection, which, again, is not exactly synonymous with adaptation. ‘‘Adaptation’’ must also have an absolute meaning if a comparative one exists. ‘‘Functional mechanisms manifest adaptation in their propensity for survivorship.’’ This again is only partly true, since survivorship is not manifested by function other than in certain closely speciﬁed contexts. It is possible to have ‘‘perfect function’’ yet no adaptation, in the absence of interaction with an appropriate external environment. Nevertheless, adaptation is clearly linked to absolute ﬁtness via function.

Adaptive Capacity Following on from the above argument, adaptation must now be deﬁned as: performance of function in the context of interaction between an organism

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and its external environment such that survivorship is maintained between generations. From this deﬁnition, it follows that organisms possess, only adaptive capacity and not adaptation, as such. The concept of adaptive capacity can readily be linked to certain past interpretations: West-Eberhard in Keller and Lloyd (1992) summarized that ‘‘adaptation’’ had been applied to propensity to survive and reproduce in a particular environment, following Mayr (1988), who proposed using adaptedness in this context. Dobzhansky (1970) also used ‘‘adaptedness’’ as ability to survive in a given environment. As will be argued at a later point, the term adaptive capacity also encompasses both ‘‘backward and forward looking’’ aspects of adaptation.* Adaptation is thus to be correctly understood as residing in that capacity through which survivorship is perpetuated, as manifested in that subset of the total functional activity actually contributing to survivorship in the organism– environment interaction. In general, then, the static view of adaptation (‘‘facility for’’ adaptation) can be said to constitute adaptive capacity, as a description of an innate propensity for survivorship which may or may not be realized. This accordingly encompasses both static and dynamic aspects of adaptation.

Mechanisms of Adaptive Capacity in the Function Ensemble and the Adaptation Interface Adaptive capacity is contained in a set of organic functions. What mechanisms are involved in this, and how do they interact with each other and with the external environment? Structure, Behavior, and Metabolism Continuing to analyze adaptation as our target process in the analysis of evolution, it is ﬁrst of all evident that several linked mechanisms interact to bring about realization of an adaptive goal. All organic systems express two fundamental functional mechanisms in structure and metabolism, and a third mechanism, behavior, is expressed to a greater or lesser extent in different lifeforms (or at different stages in the same organism). Structure is the organization of organic material for a range of functions (feeding, locomotion, reproduction, etc.) and is thus seen as having ‘‘inward and outward reaching’’ components, with respect to both external and internal environments. Metabolism incorporates the processes through which energy is cycled between external and internal environments and the manner in which it is used for work and growth in the latter. The role of behavior clearly lies in coordinating structure and function in the function ensemble (behavior– metabolism–structure) with the adaptive strategy of activity in the external environment. Function is therefore expressed in the integrated role of structure, behavior, and metabolism in providing capacity for survivorship. Function thus lies in all mechanisms contributing (either directly or indirectly) to the probability of survivorship of an organism. The capacity for expression of function accord* As noted by Begon et al. (1990), the preﬁx ab- in abaptation emphasizes that heritable characteristics of an organism are consequences of the past, not anticipation of the future or present, whereas ad- implies the latter.

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ingly lies in the function ensemble, in the interaction between the mechanisms of structure, behavior, and metabolism: The function ensemble in relation to ﬂight incorporates structure (wings and muscles), metabolism (enriched energy supply to ﬂight muscles and biochemical modiﬁcations for efﬁcient release of energy), and behavior, the manner in which ﬂight is performed in the context of interaction with the external environment. The function ensemble constitutes an open system facilitating energy exchange between internal and external environments, and adaptation is realized by interaction between the function ensemble and the external environment in the context of maintaining survivorship. In this situation, functional activity may or may not lead to adaptation (for example, not all ﬂight activity necessarily contributes to survivorship). Organic capacity for adaptation (adaptive capacity) clearly lies with the function ensemble, in its ongoing interaction with the external environment. The function ensemble thus becomes the adaptive ensemble, in its interaction with the external environment, at which point we also encounter the adaptation interface between organism and external environment.

FIGURE 1 The adaptive ensemble.

The dichotomy function interface/adaptation interface will also need to be explored further in relation to endogenous/extrinsic domains of natural selection at a later point (see Chapter 7).

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The Logistic Domain Clearly, the function ensemble cannot be considered to constitute a complete representation of the adaptive relationship between organism and environment in the absence of a logistic component. Populations and gene pools must also contain an appropriate survival strategy in terms of intrinsic rate of increase and generational structure if population crash and extinction are to be avoided. And it is pertinent to point out that a gene pool that is ‘‘perfectly adapted’’ in terms of behavior, structure, and metabolism may have no adaptive capacity whatsoever if its intrinsic rate of increase is too high in relation to size of some limiting resource (or too low with respect to competition/predation): The logistic component of adaptive capacity is easily illustrated by examples such as numbers of pollen grains produced by windpollinated plants, as well as by the Darwinian maxim that most organisms produce many more offspring than can hope to survive. The relationship between the structural and logistic components of adaptation forms an important theme in any discussion of the evolutionary behavior of adaptive systems.

Orientation of the Adaptive Ensemble The adaptive ensemble can clearly have a greater or lesser input from any chosen component mechanism (for example, the logistic component of adaptive capacity may tend to predominate in interactions between organism and environment in certain environments). The particular mechanism tending to dominate the adaptive response will clearly depend on the precise nature of the links between gene pool and external environment in relation to the leading effect component of the allelomorphic component of the gene pool. This situation reﬂects orientation of the adaptive ensemble, with which concept we are concerned whether the system tends to be structure, behavior, or logistics led, according to which of these components forms the principal component of adaptive capacity.

Locus of the Adaptation Interface To explore the adaptation interface concept in more detail it is ﬁrst of all necessary to investigate further the special meaning of the term adaptation in its biological context. It should be evident from the above discussion that structure does not always manifest function and also that all function does not constitute adaptation. The adaptation interface is that usually four-dimensional locus within the adaptive system deﬁned jointly by some aspect of the adaptive ensemble (structure, behavior, or metabolism) and the external environment, at which adaptational activity is directly expressed. Therefore, while a broader environment interface forms the locus of all interactions between organism and environment, our point of interest lies in the adaptation interface, at which such interactions also affect survivorship directly.

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Function Cycles and the Adaptation Interface Activity within any one mechanism of the adaptive ensemble is generally organized in function cycles that describe the mechanismic link between internal and external environment in terms of direct or indirect capacity for manifestation of adaptation. Function cycles are of two main types, according to relationships with generation time, primary cycles occurring within the domain of generation time (t) and epicycles lying in that of time ⱖt. Primary cycles also fall into two categories according to whether they are always completed or sometimes not, being either obligate (complete, as with many metabolic cycles) or facultative (need not be completed, as with much quasi-cyclic behavioral activity). Epicycles also fall into these same categories (development and reproduction are obligate epicycles, and dynamic equilibrium in the genome–environment interaction is a facultative epicycle). Some function cycles can also be regarded as being endogenous (e.g., development), whereas others are exogenous (as with behavior). Adaptation is directly expressed only in the latter. As we have seen, a function cycle may involve energy release without necessarily expressing truly adaptational activity, or else it may link function to adaptation. The adaptation interface therefore only exists at those loci in time and space at which activity in the adaptive system expresses some effect on survivorship, as a direct function of interaction between organism and external environment. Adaptation can thus be seen to be expressed at the end point of a function chain that can be any subset of a complete facultative function cycle: Flight mechanisms interact with the aerial environment and with other functional activity in a manner that is promotional to survival (location of food resources, evasion of predators, ﬁnding a mate, etc.). The relevant function chain involves metabolic and biomechanical activity directed to that end in the behavior–environment link. This situation can be broadly summarized as follows: Activity within function chain

Adaptation interface

May or may not contribute to survivorship; in that endogenous function alone need not constitute adaptational activity. Includes loci of energy usage:

Actual contribution to survivorship is affected by the direct interaction between organism and external environment. Includes loci of energy exchange with external environment: The act of feeding/taking shelter/ mating manifests energy exchange, mortality, reproduction, etc.

Muscles provide locomotion in search of food, locating shelter or mate, avoidance, etc.

A function chain involving locomotion could thus be described in terms of any one mechanism within the function ensemble, whereas adaptation is realized only in terms of interaction within the entire adaptive ensemble and between the latter and the external environment. The function ensemble is thus essentially ‘‘metabolism led’’—and the adaptive ensemble, ‘‘behavior led’’, in the context of the adaptation interface.

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FIGURE 2 Function and adaptive ensembles in the adaptation interface (S ⫽ structure, B ⫽ behavior, M ⫽ metabolism).

ENDOGENOUS AND EXOGENOUS DOMAINS IN ADAPTIVE CAPACITY As stated above, adaptation is not an intrinsic property of any part of the adaptive ensemble, but rather it is a process manifested in the dynamic relationship between certain intrinsic propensities of the organism and its external environment. These properties are • The endogenous component of adaptive capacity of the organism (namely, that element which resides within the function ensemble itself ) • A complementary extrinsic component of adaptive capacity lying in the external environment (the capacity of some subset of the external environment to be adapted to) Adaptive capacity can thus be deﬁned as being that capacity for survivorship residing in mechanisms of the function ensemble as these in turn link to complementary parameters existing in the external environment. We can thus view the adaptive system as a structure concerned with interactivity between gene pools and between living and nonliving environments, in terms of complementary endogenous and exogenous components of adaptive capacity.

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Since the mechanisms of adaptation interdigitate with the external environment, endogenous ‘‘adaptive capacity’’ is functionless in the absence of complementary capacity in the external environment. This endogenous component must therefore be seen as an extrinsic component of adaptive capacity, as a functional subset of a larger adaptive system: Endogenous adaptive capacity

Extrinsic adaptive capacity

Structure Metabolism Behavior Logistic activity

The limiting resource (K ) Competitors Predators Shelter sites Various abiotic factors

The extrinsic component of adaptive capacity is thus conﬁrmed as being the capacity of some subset of the external environment ‘‘to be adapted to’’ with respect to a given gene pool or population (limiting resource plus other gene pools of the same adaptive system). It is also highly signiﬁcant that the extrinsic complement of adaptive capacity has a large probabilistic input relating to spatial distribution and periodicity of resources, while the endogenous component is intrinsically deterministic in nature (although capable of responding to the probabilistic dimension within constraints imposed by the structure of the genotype, namely, through changing genotype frequencies and genetic mutation). Most signiﬁcantly of all, adaptive capacity must be deﬁned as being limited to the domain of structure as determined by the existing gene pool (although it may obviously come to be expanded in the context of mutational change). In summary, adaptation therefore correctly describes integrated activity between the function ensemble and the external environment. The ‘‘raw’’ function ensemble thus invariably expresses adaptive capacity—but not necessarily adaptation itself, unless integrated activity also involves positive interaction with the external environment.

Dynamic Aspects of Adaptive Capacity Adaptation clearly has both static and dynamic aspects. For example, color pattern may be said to express adaptedness with respect to camouﬂage, thermoregulation, etc., and it thus seems self-evident that for many traits, adaptive capacity is linked to genetic allelomorphism in order that there may be interdigitation with a changing external environment. The concept of adaptive capacity thus further serves to explain the dynamic nature of adaptation when extended to the population level. Following this approach, it is evident that the true epicenter of adaptive capacity lies with the gene pool, and that realization of adaptive capacity most usually describes a state of dynamic equilibrium between organism and environment, rather than either stasis or true evolutionary change. Adaptive capacity is thus not held solely by a single structural state, but also by the recombinative capacity of the allelomorphic component of the

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genome with respect to a minimum range of genotypes possessing the capacity to manifest a changing response in gene frequency in view of periodic variation in the external environment. Adaptive capacity is thus seen to be a dynamic structure, in the ongoing interaction between environmental ﬂuctuation and genetic variation, and is held by the gene pool rather than by the individual genotype. The concept of adaptive capacity can therefore be only incompletely understood from the activity of a single individual participating in the organism–environment interaction. Dynamics of the Logistic Component of Adaptive Capacity Structure and behavior alone cannot describe the totality of adaptational mechanisms, as shown by the important contribution made by the logistic domain. In the context of population structure, dynamic balance between N (population size) and K (the limiting resource) expresses an important dimension in the logistic component of adaptive capacity, this being expressed in an adjustability residing in such factors as variability of fecundity and generational time, in terms of matching intrinsic rate of increase with mortality factors in the external environment. Additionally, the concept of variation within the gene pool is meaningless in the absence of an active participation on the part of the logistic behavior of populations. The capacity for dynamic interaction between population growth rate, generational structure, and intrinsic limits in environmental resources also identiﬁes endogenous and extrinsic components within the logistic component of adaptive capacity, for population and resource, respectively: Endogenous logistic capacity

Extrinsic logistic capacity

Population size, N Intrinsic rate of population increase, r Growth rate Generational structure

Dimensions of the limiting resource, K Size of predator population Size of competitor population

The logistic component of adaptive capacity can thus be seen as a dynamic relationship existing between population size and dimensions of the limiting resource in a minimum model (in reality, usually expanding to include predator/ competitor interactions in addition). Behavior clearly also has a role to play in both logistic and structural mechanisms since the logistic activity of populations is partly a function of behavioral activity. In order to predict patterns of adaptational change, it is thus instructive to view all functional mechanisms as being capacities of the adaptive system and to also consider complementary capacities existing in the external environment. Structure possesses the capacity for function and behavior for niche realization (see Chapter 2). These, along with the logistic component of developmental capacity, identify and deﬁne the totality of the adaptive capacity of a gene pool in a dynamic context—and there is a signiﬁcant dynamic aspect to all of these propensities.

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THE LOCUS OF THE ADAPTIVE STATE The concept of ﬁtness is generally understood as relating to some differential in survivorship capacity, comparing one genotype or gene pool to another. Given that such relative states exist, then this must surely link to some absolute state residing in adaptive capacity of a genotype, gene pool, or species. What is ‘‘the adaptive state,’’ and where is it located in the adaptive system?

The Adaptive State Deﬁned Adaptation cannot be explicitly analyzed in the absence of some means of quantiﬁcation. As a preliminary step in this direction, it will be useful to consider the adaptive state (A) of an individual, population, genotype, gene pool, species, or lineage as being some function of its probability of survival in the context of the adaptive system. This is no more than a ﬁrst approximation, the signiﬁcance of which is not evident at ﬁrst sight. A value of A ⫽ 1.0 must relate to a complex reality, in that some values of A 씮 1.0 might well conceal adaptational strategies with lower long-term survivorship capacity (depending on the relative inﬂuence of structural as against logistic components), and indeed this casual observation indicates that A is also a function of time frame! In further investigation of the adaptive state, it is necessary to say that ﬁtness in A must not be misconstrued as constituting a question of maximizing reproduction in a single generation, bearing in mind the necessity of r (intrinsic rate of population increase) being adjusted to avoid ‘‘population crash.’’ Consequently, A as an absolute value for W (ﬁtness) concerns proximity to an optimum, rather than maximum reproductive capacity. The adaptive state must additionally be rationalized as containing contributions A1, A2, . . ., Aj from different elements within the adaptive ensemble (structure–behavior–logistic component–metabolism), and the logistic element in degree of ﬁt between a given genotype and its environment must allow for adjustment in fecundity geared to balancing against ‘‘unavoidable’’ mortality factors. Indeed, it will be shown that the degree to which the logistic component contributes is important to longer term adaptive strategies, as well as to shortterm ﬂexibility. The approximation A ⫽ probability of survival must therefore relate to incidence of stochastic mortality factors in the environment and to the differential contributions made by structure, metabolism, behavior, and logistic capacity in the adaptive strategy as a whole, and some suboptimum structural states may thus be tailored toward a high adaptive state in a gene pool predominantly through logistic capacity (see fundamental versus real adaptive states, Chapter 5). A must indeed be the integral of contributions from all loci; however, the dichotomy between structural and logistic components is the major question concerning ‘‘locus of the adaptive state,’’ in that the logistic component of the adaptive response effectively constitutes ‘‘the buffering zone’’ with respect to possible suboptimal states held in the structural component of adaptive capacity, as a corollary of dynamism in the external environment.

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THE EVOLUTION OF ADAPTIVE SYSTEMS

The Gene Pool as ‘‘Epicenter of the Adaptive State’’ We have already indicated that the gene pool is the most appropriate reference point from which to measure the adaptive state, owing to the dynamic nature of the organism–environment interaction. The adaptive state of a gene pool is determined by the balance between positive and negative survivorship factors—in limiting and other (positive) resource factors, and in a range of mortality factors. Some survivorship factors will be deterministic, some stochastic in nature. Survivorship of the species cannot, however, be determined by the fate of a single individual, other than in terms of its adaptive capacity to perpetuate the genotype, and success may therefore generally require some minimum subset of the gene pool for realization and perpetuation of adaptive capacity. Survivorship of the gene pool as a whole must therefore depend signiﬁcantly on the logistic component, and the adaptive state should therefore ideally be measured relative to the gene pool, as an ‘‘epicenter of adaptational activity.’’ Since adaptive capacity has been shown to be dynamic, so too must A lie in the gene pool. What matters, in the longer term, is not the probability of survival of an individual in a population, but that of the gene pool itself. Individuals compete to pass their genes to the next generation. For a gene pool to survive in the longer term, a certain proportion of the total gene pool of a species must be maintained in the population due to the variable incidence of niche parameters within a temporospatial matrix and the consequent need for maintenance of variation. At this point, it must be made clear that there must be no confusion between the concepts of gene pool as epicenter of the adaptive state and group selection. The gene pool is perpetuated by repeated genic selection (and not direct biotic adaptation; see Williams, 1966), so far as the per generation input is concerned, and higher level complexity arises in the greater context of the gene pool speciﬁcally as a mechanismic corollary of individual selection.* With further reference to the question of ‘‘the unit of adaptation,’’ Wright (1940) held the view that a factor N reﬂects the effective size of a breeding population, the effectiveness of selection tending to vary inversely with the value of this quantity. The population N is then seen as being greater than, and the deme smaller than, the effective level. Wright analyzed this situation via a factor m (representing genetic migration). However, Simpson (1953) criticized the deme concept/migration hypothesis of Wright, doubting whether m is generally low enough. Nevertheless, any reinterpretation of Wright’s hypothesis in terms of the precise level of N cannot escape the view that the adaptive state is held by the gene pool (albeit for quite different reasons than those proposed by Wright). The signiﬁcance of the ‘‘minimum subset’’ concept as seen here lies not so much in the effectiveness of selection, as in the survivorship capacity of a lineage as a function of the adaptive state contained by an array of individual genotypes within a population. The minimum subset in question is that capable of perpetuating the gene pool itself, and this constitutes the unit with which to investigate adaptational dynamics in natural populations. * Another view of ‘‘genome selection’’ (Lewontin, 1983) holds that individual genes are not the units of selection, so much as larger units. However, this also must not be interpreted as ‘‘group selection’’ (see Chapter 13).

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13

In this sense then, the gene pool is fully conﬁrmed as constituting ‘‘the locus of the adaptive state’’: The peppered moth Biston betularia demonstrates adaptive capacity as a function of maintenance of the carbonaria gene in the gene pool in regions where this morph holds some selective advantage apparently linked to presence of atmospheric pollution. The gastropod mollusc Cepaea has a more complex polymorphism, involving color and banding traits, that has similarly been shown to be correlated with several environmental variables (see Cockburn, 1991, for a review). Small populations of these species tending to monomorphism may lack sufﬁcient adaptive capacity to cope, either with changing external factors or with migration to a fresh habitat. There is no special reason to assume that the highly visible polymorphisms shown by the above animals are not mirrored in similar structural, metabolic, and behavioral polymorphisms in the vast majority of other species. The Gene Pool and Kin Selection The mechanism of kin selection apparently conﬂicts with the concept of a minimum subset gene pool in that matings based on kinship may appear to constitute a force favoring genetic uniformity. However, kin selection clearly cannot proceed as a simple linear function of degree of relatedness in the longer term, without incurring a tendency toward inbreeding depression. This merely extends the view that the locus of adaptational activity must be some minimum subset gene pool, to include the maxim that negative components of ‘‘shortsighted’’ selectional activity are balanced by forces positive to longer term maintenance of the adaptive state.* The apparent conﬂict between kin selection and the gene pool concept will be examined in more depth in the context of the isotropic selection interface (Chapter 4). Gene Pool, Gene Reservoir, and Population Owing to difﬁculties with the Wright deme concept (see above), it is now advisable to adopt a different nomenclature for components of the total gene pool of a species. The gene pool has been deﬁned as a subset of a larger structure, which latter must ultimately be the species itself. The gene reservoir can now usefully be deﬁned as constituting the genetic complement held by all gene pools of a species within the time frame of a single generation, in which context we could also chose to redeﬁne gene pool as being that minimum subset of the gene reservoir necessary to perpetuate adaptive capacity with respect to a changing external environment, also allowing for the effectiveness of selection. The adaptive state is then more usefully described as being held by the gene pool as a subset of the gene reservoir and superset of the population, and a population is then any natural subset of a gene pool (irrespective of adaptive state) that * The ultra-Darwinist view holds that no supraindividual selectional activity occurs other than through a corollary of individual selection, not that it does not occur at all!

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THE EVOLUTION OF ADAPTIVE SYSTEMS

is spatially (although not necessarily genetically or geographically) isolated from other populations of the same gene pool: Odum (1971) reviewed the contemporary concept of population as comprising a group of organisms of the same species with unique characteristics in density, mortality, age distribution, biotic potential, dispersion, growth form, and ﬁtness; an individual does not have a birth rate, death rate, or age ratio. The gene reservoir will be formed by the sum total of gene pools having the potential for gene ﬂow (although also including geographically discrete ‘‘races’’). The species is thus the gene reservoir in its four-dimensional (lineage) perspective, and it is clearly this larger structure which contains the adaptive potential for further evolution (see Chapter 7).

REALIZATION OF ADAPTIVE CAPACITY AND THE ADAPTIVE RESPONSE Given that adaptive capacity may vary from one generation to the next in terms of gene frequencies, it follows that a quasi-cyclic path is described by movement from capacity to realized response, in terms of the manner in which the allelomorphic component of the genome reacts to different selection regimes in the organism–environment interaction. The process of adaptation occurs through interaction between the population and limiting resource (endogenous adaptive capacity and an extrinsic complement residing in the external environment), and this activity constitutes realization of adaptive capacity. Behavior is thus more explicitly deﬁned as being a signiﬁcant component of that strategy of integrated activity in the function ensemble through which movement is translated into realization of adaptive capacity, essentially ‘‘the realization function’’ of adaptation. The adaptive response can now be deﬁned as being the altered complement of adaptive capacity following interactivity between the gene pool and environment within the time frame of a single generation, as expressed in a quasicyclic structure connecting adaptive capacity at time t with adaptive response at time t ⫹ 1 with respect to the behavior of a larger dynamic system. The adaptive response thus becomes the next state of adaptive capacity interacting with a subsequent selectional regime (Fig. 3). The adaptive response can therefore be manifested in such phenomena as stasis, dynamic equilibrium, and evolution: In the Cepaea example cited above, different shell color and banding morphs are known to hold the highest selective advantage in different kinds of terrain, and a gene pool subjected to a changing external environment will clearly express a changing sequence of adaptive capacity 씮 response structures from one generation to the next.

The Passive versus Active Adaptive Response There are two different modes of competition between individuals: (1) nonselective or ‘‘passive’’ competition corresponding to the sole inﬂuence of the

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15

FIGURE 3 The adaptive response: a–f ⫽ allelomorphic states held by the gene pool, of which a, d, and f are those selected in the generation in question.

(K ⫺ N/K ) factor in the Verhulst equation (see below) and manifesting no functional genetic difference between ‘‘winners’’ and ‘‘losers’’ such as could determine a survivorship differential; and (2) selective or ‘‘active’’ competition, relating to genetic deterministic factors linked to an adaptive differential between individuals: Failure of a pollen grain to reach its target is not ‘‘selection,’’ but adaptational failure—assuming that there is no heritable differential between winners and losers—and competition is thus ‘‘passive’’ in this context. On the other hand, survivorship of the melanic peppered moth relative to the wild type is ‘‘active,’’ since a heritable differential is involved in relation to differential mortality. Realized adaptive capacity thus manifests not only a range of active adaptational mechanisms (the apparently ‘‘true’’ adaptive response), but also passive logistic interactions between populations belonging to the same adaptive system.

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THE EVOLUTION OF ADAPTIVE SYSTEMS

The adaptive response can now be deﬁned more explicitly as any change in adaptive capacity due to differential mortality, whether passive or active, heritable or nonheritable, selectional or nonselectional in origin. This excludes only purely stochastic survivorship factors, which cannot be said to be part of adaptation at any level. Realization of adaptive capacity thus incorporates much activity in the adaptive response, in terms of the purely passive logistic behavior of populations. It is axiomatic that changes in population size (N ) due to mortality with no complement in heritable adaptational differential constitute a passive response within adaptive systems and thus relate to maintenance of, rather than change in, the adaptive state of a gene pool. It is clearly only with active responses that we identify that component expressed by selected logistic changes or through changes in structure and behavior—and it is also with the active adaptive response that we may encounter true evolutionary change. The respective inﬂuences of passive and active competition are further analyzed with respect to evolutionary rate in Chapter 18.

‘‘Stasis’’ and the Passive Response The inclusion of ‘‘stasis’’ in the adaptive process seems intrinsically unlikely. However, the latter seemingly prima facie conclusion is based on a misunderstanding of the nature both of adaptation and of stasis, since the primary objective of adaptation is simply maintenance of the adaptive state, dynamic change being a corollary arising from encounter with a changing external environment. Similarly, the concept of species stasis cannot be taken to exclude dynamic activity in the passive logistic component of adaptive capacity (see Chapter 19). Maintenance of stasis is a thus a passive dynamic process so far as the logistic component of adaptive capacity is concerned. The notion that dynamism may be restricted to passive logistic activity in the adaptive system may, however, be an illusion. Many variables expressing apparent ‘‘genetic unity’’ manifest phenotype plasticity as a result of varying environmental inﬂuences interacting with the genotype, and genetic variation is probably always maintained in a large number of gene alleles (probably including those affecting fecundity and thus, also, controllant to an active logistic adjustability of populations). This scenario may then generally incorporate much dynamism in the structural component of adaptation in relation to changing gene frequencies associated with polymorphism. Whether ‘‘stasis’’ in the sense of genetic stability is in any way a realistic concept is a question that will be explored further in Chapters 5 and 19.

Dynamic Equilibrium versus Evolution in the Adaptive Response The architecture of the adaptive response is clearly linked to certain reference time frames, since a trait exhibiting apparent stasis may in fact represent one stage in a larger trend when seen in the perspective of longer term evolution: thus, over n generations, the broad picture emerging of the adaptive response will be as follows:

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1. ADAPTATION AND THE ADAPTIVE SYSTEM

Maintenance role: stasis Dynamic role: adaptive equilibrium Evolution

Including passive logistic change Active logistic or structural change, generally involving quasi-cyclic changes in gene frequencies Active structural change, often acting in noncyclic mode, sometimes manifesting very long-term directionality

The adaptive response is thus expressed in the phenotypic variance of a gene pool or population, following realization of adaptive capacity (excluding the effects of stochastic processes), and it represents any arbitrarily chosen reference frame within the quasi-cyclic realization of adaptive capacity. Adaptive equilibrium between organism and environment (rather than true evolutionary activity) may thus form a very signiﬁcant part of this (see Chapter 5).

THE ADAPTIVE SYSTEM CONCEPT We have already identiﬁed several of the principal components of a biotic adaptive system in the preceding discussion. How are the various mechanisms of the adaptive ensemble linked in an interactive manner in the context of the greater adaptive system, and what are the principal coordinates of the behavior of such systems?

The Adaptive System Deﬁned The adaptive system incorporates all parameters of the niche of any chosen reference point gene pool, inclusive of both direct and indirect links to other trophic levels (primary and secondary consumers, competitors, etc.) and to the abiotic component of the external environment, excluding only stochastic interactions. It also encompasses the adaptive capacity and potential of all constituent gene pools, which latter thus form an integral part of the adaptive system: Following Frank (1996), an adaptive system satisﬁes the three conditions of natural selection. The inclusive entities vary, there is a heritability factor, and there is differential success. Information decay will occur in the system if mutation is too frequent, and the genetic system has to be capable of creating complex form from a limited set of instructions. The adaptive system thus explicitly describes interactivity between organism and environment on a multitiered basis, thereby incorporating endogenous and extrinsic components of the interaction between organism and environment within a single structure.

Toward an Equation Set of the Adaptive System In any biosystematological approach to the study of evolution we must consider the behavior of equations describing logistic and structural inputs to the adaptive system. Of these equations, the logistic component can readily be understood from the Verhulst equation.

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THE EVOLUTION OF ADAPTIVE SYSTEMS

The equation set of an adaptive system has to describe the various aspects of adaptive capacity, and it must therefore contain adjustable, interactive variables capable of maintaining a speciﬁc range of values in response to feedback mechanisms operating between interacting populations and between organic and abiotic resources. This ‘‘adjustability factor’’ therefore clearly brings the equations of population genetics into the equation set, and the essential nuclei of this larger equation set must lie in a relationship between the genetic equations in question and the familiar Verhulst and Lotka–Volterra equations. The Rate of Increase, r, in Adaptive Capacity The nature of the structural component of adaptive capacity is perhaps most overtly evident in allelomorphic variation within that domain. However, the role of the logistic component must form a signiﬁcant component of any equation modeling the behavior of adaptive systems. The logistic component of adaptation is clearly part of r as expressed in the Verhulst equation, and r is, furthermore, most deﬁnitely capable of structural adjustment through deterministic activity within the genome itself. The ‘‘backbone of the adaptive system’’ must therefore lie in its logistic structure, in that genes do not have the capacity to provide dynamic change other than in the context of interaction between populations and the external environment. In this interaction then, logistic activity must play a lead role in the dynamic relationship between components of the system. The Verhulst equation illustrates logistic activity in a simple dynamic system with two variables, N and K, with N being dependent on K in a density dependent manner in the context of a negative feedback loop: dN/dt ⫽ rN(K ⫺ N)/K Passive logistic activity in the adaptive system is thus explicit in (K ⫺ N)/K in the above equation. This passive response can clearly be demonstrated when there is no genetic variation in a population, or when variation is not a factor involved in competition. The Verhulst equation thus serves to deﬁne a major part of the functioning adaptive system in terms of purely passive logistic activity, and it also takes a ﬁrst step toward description of the active adaptive response in terms of the genetic component, since r must possess an essential adjustability in the face of variation in K. The model for an adaptive system must clearly contain a larger set of interacting equations, of which the Verhulst equation forms the central core in expressing logistic dynamics of (N ) population with limiting resource (K ). An organic dynamic system can, however, only become a true adaptive system through initial adjustment at the lowest variable pair (the abiotic resource with K, the carrying capacity of the external environment), which means that the abiotic resource must also be cyclically replenishable as a component of the dynamic system. The logistic aspect of adaptation is thus ideally expressed in a minimum model by the Verhulst equation, extended to include a differential which is in turn a function of the interaction between organic populations and an abiotic cycle. K and the Extrinsic Component of Adaptive Capacity As we have just seen, the logistic behavior of adaptive systems is expressed, not only in r, but also in K. The organic element in K must be some function

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19

of available energy resources, jointly determined by extrinsic adaptive capacity in the environment and by endogenous adaptive capacity of the consumer gene pool. K is thus not merely some intrinsic property of the external environment, but is partly determined by the gene pool in its interaction with the limiting resource. It must also be pointed out at this stage that K is not conﬁned to the energy resource of a gene pool, but additionally contains parameters relating to other density dependent interactions, including, for example, abiotic resources such as shelter and hiding places. The K factor is thus a heterogeny, some part of which may be prone to stochastic inﬂuences, and variation in K may thus serve to introduce a measure of instability into a dynamic system of this kind. Nucleus of the Structural Component of Adaptive Capacity The Lotka–Volterra equations describing interaction between competing populations suggest how a biotic adaptive system must differ from a simple dynamic one, when one considers the organic basis for differentiation between two genotypes in terms of relative adaptive states. This equation set thus clearly also encompasses the input from the structural component of adaptation into the equation set of the adaptive system (albeit in rudimentary fashion), in that the 움 factors in the Lotka–Volterra equations are clearly based on genotypic differentials rather than being determined by mere passive logistic behavior: dN1/dt ⫽ rn1 ⫻ N1 ⫻ (K ⫺ N1 ⫺ 움21 ⫻ N2)/K dN2/dt ⫽ rn2 ⫻ N2 ⫻ (K ⫺ N2 ⫺ 움12 ⫻ N1)/K Most signiﬁcantly, the Lotka–Volterra equations describe not only passive logistic activity, but also the interaction between the logistic component of adaptation and adjustability in the structural sector, therefore becoming transformed in the role of wider equations of adaptivity. The Lotka–Volterra equations do not describe adaptation directly, but this is nevertheless implicit in their relationship to the structural component of adaptive capacity. Certain implicit factors also identify adaptivity in the Verhulst and Lotka– Volterra equations by virtue of inferred capacity to counteract instability, manifested in adaptive capacity for • Adjustability of r in the face of variation in K • Adjustability of the 움 factors as indices of competitiveness (see also Chapter 4) Some portion of the active adjustability component is thus seen as being implicit in r, with reference to the genetic determination of fecundity and/or longevity. Hence r is also closely linked to adaptive strategy (see below), just as other components of the adaptive system (including the spectrum of genetic variation in the gene pool with respect to behavior, structure, and metabolism) are likewise ‘implicit’ in the 움 factors. The above equations describe fundamental inputs to adaptive capacity and also identify the extrinsic domain in the latter. However, the true adaptive response must be explicit in some as yet unexplored relationship between the Lotka–Volterra equations and those of population genetics. What that

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THE EVOLUTION OF ADAPTIVE SYSTEMS

relationship is, and why it is of great signiﬁcance for an understanding of adaptation and evolution, will be explored at a later stage. The Adaptive State in the Verhulst Equation It may appear at ﬁrst sight that the Verhulst model incorporates logistic interactions which encounter no active capacity for any heritable adaptive response, hence describing purely passive survivorship factors. However, this is due to the artiﬁciality of the logistic equation itself. In reality, delayed responses generally occur in the logistic equation, as incorporated, for example, in the Hutchinson model (1948) and in other, more realistic equations. This property was studied further by Wangersky and Cunningham (1956, 1957), who identiﬁed two kinds of time lags: time needed to start increasing when conditions are favorable (t ⫺ t1) and time required to react to unfavorable conditions (t ⫺ t2). Hutchinson equation: dN/dt ⫽ rNt(K ⫺ Nt⫺T )/K

(t ⫺ T expressing time shift)

Wangersky and Cunningham equation: dN(t)/dt ⫽ rN(t⫺t1)(K ⫺ N(t⫺t2))/K In the above equations, density overshoots and oscillates with decreasing amplitude in time, and this is thought to be a common behavior of real populations in Nature. May (1974) has shown also that when the artiﬁcialities of the Verhulst and Lotka–Volterra differential equations are replaced by equivalent difference equations describing a more realistic system in which generational structure is taken into account, characteristic oscillations appear in the graph of population growth, and these may approach chaos for certain conﬁgurations of the variables in question. Similarly, in the Hassell equation (see Hassell, 1976, and elsewhere), time delay is implicit in the context of discrete generations modeled by a difference equation which also describes the effects of extremes of contest to scramble competition on the basis of a parameter, b: Xt⫹1 ⫽ er Xt(1 ⫹ aXt) ⫺

b

X ⫽ N in successive generations

A sample output for a time delay equation should be compared with the usual logistic curve, as shown in Fig. 4. Following the more realistic models of population growth that have been proposed (and particularly in view of the likely prospect of stochastic variation occurring with respect to K itself !), it is clear that fecundity must be adjusted in order to avoid population crash. The adaptive state can thus be described in this context as ‘‘probability of survival in ongoing dynamic equilibrium of N.’’ If we consider the K씮N interaction to be an oscillatory or chaotic one, then the probability of survival (given an element of stochasticity in K ) becomes a function of the tendency for the periodicity of N to reach zero. It is thus evident that chaotic (rather than stochastic) interactions constitute that force demanding a variable adaptive response within the domain of adaptive capacity. The above, of course, only relates to the logistic component of activity in the adaptive system. However, a parallel element must nevertheless be signiﬁcant in

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FIGURE 4 Logistic curve following the Verhulst differential equation (left) compared to (right) an oscillatory trend based on a difference equation describing the discrete generations situation (Hassell equation).

determining A as a function of other components of adaptive capacity also (see Chapter 5). If the Verhulst equation can be linked to probability of survival in the logistic component of adaptation, then the same must consequently be true for the structural component as reﬂected in the Lotka–Volterra equations for competing genotypes, and very many facets of adaptive capacity may be linked to chaotic behavior of the external environment in a similar manner. Likewise, there may be rare events in which logistic bottlenecks may also tend to create the necessary substrate for novel evolutionary change (see Chapters 14 and 18).

Major and Minor Selectional Attractors in the Adaptive System Perhaps the most important property of dynamic systems from the viewpoint of evolving organic adaptive systems lies in a tendency to gravitate toward some particular type of behavior through possession of some intrinsic propensity for adjustment. The behavior toward which such systems gravitate is the attractor of the system. An attractor is, for example, easily identiﬁed in the behavior of the Verhulst equation, in that similar equilibrium states arise from various conﬁgurations of initial conditions. Of considerably greater interest is the concept of a selectional attractor deﬁned by an optimized state toward which biotic adaptive systems gravitate as a function of variation in the input variables to dynamic interactions between individuals and gene pools, a propensity which must be clearly implicit in the 움 factors of the Lotka–Volterra equation set. Following on from the concept of a selectional attractor, it is of interest at this point to consider whether or not there may perhaps be two fundamental entities of that kind operating in natural adaptive systems: a major selectional attractor in the structural adaptive response and a minor selectional attractor in the logistic domain. This hierarchy would appear perhaps to be indicated from evidence already discussed concerning the relative inﬂuence of structural versus logistic components of the adaptive ensemble, and this speculative question can be taken up in greater detail as we progress with the present analysis.

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In this context, orientation of the adaptive ensemble (see p. 6) must also be linked to the major–minor attractors theory, in connection with the question as to whether the leading adaptational function lies in the logistic versus structural component of adaptation. Here, we shall also be examining the question of the optimum balance between these two inputs.

The Reciprocity Principle in Adaptive Systems Adaptation can be analyzed through the organism–niche interaction in the analysis of a larger adaptive system, and a subject gene pool can be chosen as a convenient reference point for analysis of the state of adaptation (for example, a single consumer species interacting with a producer resource, so that other consumers are either competitors or predators in relation to that reference frame). The object resource is then the next lowest trophic level relative to the subject gene pool, forming the latter’s limiting resource. These terms constitute useful reference points when we come to deﬁne adaptive system, niche, and environment, and to analyze certain aspects of evolutionary activity, and we have in fact already adopted a similar approach in designation of N and K in the Verhulst equation. Designation of ‘‘subject’’ (N ) and ‘‘object’’ (K ) gene pools allows analysis of the adaptive state of any chosen genotype, population, or gene pool with respect to the relative contributions of structural and logistic activity and in terms of the entire adaptive system. Implicit in this relationship, however, is the observation that ‘‘adjustability’’ should not be seen as a propensity possessed solely by our chosen N point of interest, but as a feature capable of reciprocal adjustment at other points in the adaptive system also. From this, we arrive at the reciprocity principle, which states that there is generally a reciprocal adaptive response between gene pools of an adaptive system which interact at a mutual adaptation interface. Accordingly, it is easy to see that the adaptation interface itself is in fact a reciprocal structure that can be analyzed from any chosen reference point. Looking at the reciprocity principle more closely, we can observe, for example, that the Lotka–Volterra equations for predator–prey interaction can be stabilized by modulation of the intrinsic rate of increase of prey or, alternatively, by adjusting the behavior of a predator. And it is predictable that both adjustments may tend to evolve alternately in temporal sequence during the course of longer term evolutionary activity. It must therefore be one fundamental axiom of adaptive systems that change in any adaptational parameter of a predator species has the reciprocal effect of changing the adaptive state of its prey, so favoring some reciprocal change that might otherwise not have been selectively positive. This same principle, of course, applies in the relationship between consumer and limiting resource, etc. Specialization and Reciprocity It has already been suggested above that the structural component of adaptation also possesses the adaptive capacity for reciprocally generated activity, so that a reciprocal adaptive response may thus occur in either the logistic or structural component of adaptation. The reciprocal structural adaptive re-

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sponse may also be either positive or negative with respect to the subject–object interaction. The reciprocal logistic response between two gene pools thus also constitutes that force acting to favor reciprocal adaptation in the structural domain, leading thus to specialization, which latter propensity can clearly only be expressed in the organic component of the adaptive ensemble and not in the logistic. The term specialization is thus seen to be concerned with limitation to degrees of freedom in function. Any tendency for specialization in a gene pool thus creates selectional drive favoring reciprocal specialization in its organic limiting resource—and also in any higher trophic level for which the gene pool in question is itself a limiting resource: Modulation of ﬂoral structure correlated with haustellum elongation in a nectar feeding moth species is an example of a positive reciprocal adaptive response in the structural domain, whereas acquisition of toxic tissues in a plant species would constitute a negative adaptive response in the limiting resource with respect to consumer activity. The adaptive response is thus fundamentally complex in nature. The reciprocal adaptive response is most overtly manifested in a variety of symbiotic and mutualistic species interactions, reﬂected in all domains of the adaptive ensemble—not only in logistics, but also in behavior, structure, and metabolism. However, from the adaptive system concept, all biotic adaptation is fundamentally coadaptive, despite the fact that this may often be conﬁned to the logistic dimension; taking any subject and object pair in an adaptive system with an adaptive state of x, there will always be a contribution to that state from both subject and object population, even if only in the logistic dimension. Specialization and reciprocity are, however, only ‘‘inextricably linked’’ when there is adaptive potential (see Chapter 7) for reciprocal specialization to achieve this end. In summary, although adaptational activity can be analyzed with respect to any set of chosen reference points, the viewpoint from the adaptive system concept indicates a fundamental reciprocity in the adaptive response. Gene pool–environment interactions clearly express such reciprocity, and the adaptive state can be measured from any reference point within the system, depending on the particular focus of interest. ‘‘Subject’’ and ‘‘object’’ express reciprocity over the hierarchy of trophic levels, in that the ‘‘subject of interest’’ may also be the object with reference to some higher trophic level in the same adaptive system, and this interchangeability reﬂects the reciprocal nature of interacting adaptational mechanisms. The Reciprocity Principle in the Logistic Domain It is instructive to consider in slightly more detail how the reciprocity principle affects the logistic component of adaptation. The adaptive response in N is driven by the effect of (K ⫺ N)/K on rN. A reciprocal response in K could thus constitute an increase in dK/dt, relative to pressure from the N population. A simple reciprocal adaptive response can therefore be expressed in the Verhulst equation in avoidance of dangerously chaotic population interactions:

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THE EVOLUTION OF ADAPTIVE SYSTEMS

The oak (Quercus) has a spring regenerative growth which seems to be an adaptive response that is speciﬁcally linked to the very high levels of attack from several extremely abundant geometrid moth species which hatch from eggs in early spring. Increased production of regenerative foliage while at the same time protecting reproductive tissues is an example of a complex response in the limiting resource, involving both negative and positive adaptive responses. This reciprocal aspect of adaptational activity can be explained as follows. The logistic attractor (the state dN/dt ⫹ dK/dt ⫽ 0) is the state toward which adaptive systems must constantly tend, since if subject and object do not become reciprocally adapted, the system may become unstable and collapse. The reciprocity solution, as in, ‘‘Regeneration in K increased with protection of reproductive tissues,’’ is more stable than the scenario, ‘‘Consumer kills K,’’ and this situation may also entail a reciprocal adaptive response in the subject gene pool (for example, to consume regenerative and not reproductive parts): Dobzhansky (1970) discussed the evolution of pesticide resistance in Australian rabbit populations in relation to the pathogenic myxoma virus. The rabbits evolved resistance to the myxomatosis virus, and the virus also evolved the capacity not to kill the host. The reciprocity of much adaptational activity with respect to interactions between gene pools not only again conﬁrms adaptive capacity as being a property of the whole adaptive system but also serves to underline the signiﬁcance of the logistic behavior of such systems. It is axiomatic that, whatever the ‘‘polarity’’ of reciprocity appears to be from any chosen reference point, it has to be positive with respect to the adaptive state of the whole system. It is also true for evolutionary analysis in general that the adaptive response will tend toward a fundamental reciprocity for all constituent gene pools of an adaptive system. The response in question may be structural or logistic, active or passive—and it can be either phenoplastic or genetic in nature. For any given trophic level then, there may thus be some adaptive response (heritable or otherwise) that is linked to survivorship factors arising in the next inferior trophic level to equivalent or superior levels. Linking the concept of trophic levels to that of adaptive capacity and the adaptive state, it will be useful to propose an appropriate adjustment to the usual terminology: an enhancer (in contradistinction to a depressor or consumer) tends to raise the adaptive state of an interacting gene pool (as with ant species that cultivate certain insects or plants or in human agriculture, etc.). In this context, the principle of reciprocity is clearly conﬁned (a) to the biotic component of adaptive systems and (b) to that situation where two gene pools act directly as depressors or enhancers in relation to each other. These differentials are also implicit in the 움 factors of the Lotka–Volterra equations, for any system which reaches stable mutual equilibrium. From the above, the logistic behavior of populations can be analyzed from the total complement of the following: primary logistic mortality factors arising from intraspeciﬁc competition linked to inferior trophic levels; secondary factors, from interspeciﬁc factors (competition at equivalent trophic level); and tertiary factors, from predation, at a superior trophic level(s).

1. ADAPTATION AND THE ADAPTIVE SYSTEM

25

The complete adaptive system is the sum of all gene pools interacting with the subject population and its object resource, thus including all equivalent and superior trophic level gene pools, however interlinked within the system. In conclusion, the ‘‘orientation’’ of any equation expressing activity within a larger adaptive system depends on our chosen reference point within a fundamentally reciprocal structure. The Domain of Coevolution Van Valen (1973) views the evolutionary fate of a species as depending on what is happening simultaneously to all other species in the same ecological setting, proposing that coevolution may comprise most of evolution (van Valen, 1984): ‘‘Coevolution occurs when the direct or indirect interaction of two or more evolving units produces an evolutionary response in each.’’ At a later stage (Chapter 20), we shall examine these hypotheses more closely. At the present stage, it will be sufﬁcient to point out that, as already stated above, reciprocal adaptation can only relate to the biotic component in adaptive systems, and that much evolutionary change is clearly linked to the abiotic domain.*

MAIN POINTS FROM CHAPTER 1 1. Many important aspects of evolution arise as emergent corollaries of primary mechanisms and processes, rather than being direct outputs of either. 2. Adaptation (as propensity for survivorship) is the fundamental process underlying the behavior of natural biotic systems. 3. Organisms can be deemed to hold adaptive capacity by virtue of stable states of structure, behavior, and metabolism, as also in their allelomorphic genetic makeup. 4. Adaptive capacity has both extrinsic and endogenous components. The former lie in the external environment and the latter are held by that suite of endogenous mechanisms forming the function ensemble (behavior, structure, and metabolism), including also the logistic capacity of the genotype. 5. Realization of adaptive capacity occurs at the adaptation interface between organism and external environment. In this mechanism, we also observe the fundamentally dynamic nature of adaptive capacity. 6. A quasi-cyclic relationship exists between adaptive capacity and adaptive response. Orientation of the function ensemble forms an important input to this relationship, especially in the extent to which the adaptive response tends to be led by the logistic component. 7. The gene pool constitutes the epicenter of adaptive capacity, as a higher emergent property of selectional interactivity linked to differential survivorship between individuals. The gene pool is in turn a subset of a larger structure, the gene reservoir. * It should also be noted that coevolution can be confused with parallel adaptation, as apparently demonstrated with respect to the top-level predator Dimetrodon in the Carboniferous– Permian in Oklahoma and Texas (Olson, 1983).

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THE EVOLUTION OF ADAPTIVE SYSTEMS

8. The adaptive system holds all direct and indirect connections of the adaptive interface, including the ‘‘subject’’ (point of interest) gene pool itself together with all other gene pools linked to the same interface. 9. The Lotka–Volterra equations contain implicit links with those of population genetics, in modeling the logistic behavior of adaptive systems with respect to adaptive properties held by genetic differentials. 10. Adaptive systems gravitate toward logistic and structural attractors, following dual pathways of dynamic equilibrium and evolution with respect to the structural element. 11. Reciprocal adaptivity is commonly manifested in the biotic domain of an adaptive system.

2

SPATIAL STRUCTURE OF THE ADAPTIVE NICHE

Griesemer (1992) has written a useful historical account of the complex history of the niche concept, of which the following introduction is a brief summary. Grinell (1924 and elsewhere) and Elton (1927, etc.) both saw the niche as being a property of the environment into which species could ﬁt. They proposed the environmental niche concept, within which broad construct Grinell’s version is sometimes called the habitat niche and Elton’s, the functional niche: Niche speciﬁcity is exempliﬁed by such examples as the adaptive radiation of cichlid ﬁshes in the Great Lakes of Africa, each species having a distinctive pattern of habitat usage relating to such parameters as depth and feeding resources. Even species with similar niches have been shown from analysis of stomach contents to differ slightly in preferences of algal food (Reinthal and Meyer, 1997). The same situation has been shown to exist in very many other organisms, including the classical example of the geospizine ﬁnches studied by Darwin on the Galapagos Islands (see below). The existence of ‘‘ecological equivalents’’ in different phyletic lineages appears perhaps to support the environmental niche perspective; however, this view has lead in turn to the paradox of the ‘‘vacant niche.’’ The concept of a macroniche (on which the ecological equivalents concept is in turn based) clearly relates to adaptive specialization in terms of larger ‘‘environmental’’ niche parameters which tend to express stability in the temporal dimension (higher group limiting resource, aquatic habitat, etc.), a circumstance that is

27

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THE EVOLUTION OF ADAPTIVE SYSTEMS

often reﬂected in structural convergence between unrelated lineages. The latter observation can be readily misinterpreted as evidence of the existence of ‘‘vacant spaces’’ in adaptive systems. Gause (1934) later brought Elton’s niche concept and the Volterra equations together in the context of the competitive exclusion principle, so bringing the niche concept more into focus with contemporary evolutionary doctrine. Hutchinson (1957, 1965), in turn, further redeﬁned the niche as an attribute of the population or species expressed in relation to its environment, so deﬁning the population niche concept, which held that gene pools do not adapt to a niche, but create actual niche shifts. Hutchinson’s model incorporated all environmental factors acting on organisms, as well as rejecting the earlier concept of the vacant niche. Hutchinson also recognized the existence of a fundamental versus real niche, the former being the niche in the absence of competitors and predators. This model clearly constituted the deﬁnition of the niche of a species, rather than of a ‘‘macroniche’’ into which many species could ﬁt, but was nevertheless a static view which did not incorporate variability nor changes in space and time. Hutchinson additionally restated the competitive exclusion principle by saying that realized niches do not intersect, whereas Hardin’s more realistic axiom of inequality (1960) argued that some resource dimension will explain coexistence, so that niches may in fact intersect, provided there is also some element of independent adaptive capacity with respect to competing species: Lack’s study of the Galapagos ﬁnches (1947) led him at ﬁrst to propose nonadaptive differentiation between species, but he later found differences in resource utilization that were clearly correlated with bill size. MacArthur’s work on warblers (see MacArthur and Levins, 1967) also showed avoidance of competition on the slenderest of niche separations. More recent niche theory also concerns some reframing of the competitive exclusion principle. In the model of MacArthur and Levins (1967), emphasis is shifted from the permissive range of environmental conditions to actual resource utilization, thus indicating a more dynamic than static approach as compared with that of Hutchinson. In the following treatment, I have moved away from the strictly ‘‘ecological’’ deﬁnition of niche, toward a view more closely bound in with the structure of the adaptive system as a whole. In that sense, we are now effectively dealing with the concept of the adaptive niche.

NICHE AND ADAPTIVE SYSTEM Adaptation is not to the niche, but within the adaptive system as a whole, and this is a reciprocal activity in which there can clearly be no ‘‘vacant niche’’ (see Chapter 1). In this view, the true nature of the adaptive system in relation to the niche now becomes apparent.

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The Adaptive Niche Deﬁned To look more deeply into the adaptive niche concept, it is instructive to continue to examine points of interest in an adaptive system through the medium of a chosen subject gene pool. Following this approach, we can identify two domains within the adaptive system which might be said to jointly form the niche of the subject gene pool: 1. The major adaptive niche, linked directly or indirectly to the limiting resource 2. The minor niche, lying in that reciprocal interface for which the subject is itself the ‘‘object resource’’ for other gene pools, the latter domain furthermore containing any competitor gene pools sharing the same resource

FIGURE 5 Minor and major adaptive niche: subject ⫽ point of interest gene pool; object ⫽ limiting resource of subject gene pool.

The simpliﬁed scheme of Fig. 5 merely represents the trophic system, and not the whole of the direct interface between subject gene pool and adaptive system. In addition, the abiotic plane encompasses such parameters as temperature, pH, hiding places, and substrate, some of which latter are linked to the biotic plane and some not.

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In the above system, the total adaptive niche is simply the locus of ﬁrst level contact between gene pool and adaptive system. This is deﬁned by direct interaction between organism and external environment and is manifested in the adaptation interface, inclusive of the reciprocal aspect in activity of other gene pools of equivalent and superior trophic levels. We can now see also that the adaptation interface of a gene pool is formed by the adaptive niche plus the gene pool itself (alternatively, the adaptive niche is the adaptive interface minus the subject gene pool, and is essentially the same thing as the extrinsic component of adaptive capacity; see Chapter 1).

FIGURE 6 The adaptive niche in the context of the wider adaptive system.

The Major and Minor Adaptive Niche Colwell and Fuentes (1975) attempted to include predation, parasitism, mutualistic interactions, and competition in their niche concept, although this view has not received wide acceptance. In the scheme presented above, competitors and predators do not form part of the object niche of a gene pool; nevertheless, they hold secondary status as part of the adaptive system ‘‘orbit’’ of a chosen subject gene pool. In this system, shelter from predation (as a component of K ) clearly forms part of the major adaptive niche, whereas predators or competitors to which there is some element of adjustment in adaptive capacity belong to the minor niche domain (as indeed would be assumed from the Lotka–Volterra equations, as well as following the reciprocity principle; see Chapter 1). The major adaptive niche thus forms the system nucleus and is an

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active adaptational goal, while the minor niche belongs to the ‘‘system orbit’’ and is essentially ‘‘passive’’ in adaptational terms (notwithstanding the input from adaptational reciprocity which may be invoked). The major niche can thus be seen as ‘‘attracting,’’ while the minor niche ‘‘repels.’’ The adaptive response is ultimately to both major and minor adaptive niches; however, the passive (logistic) response may often predominate with respect to the latter: Clear evidence of the inﬂuence of the minor niche in provoking a structural adaptive response is seen in situations in which it is absent, as, for example, in the fresh colonization of remote islands. Evolutionary trends observed in such situations include such adaptive shifts as that toward dropped seeds from plants with ancestors utilizing a windborne strategy, a tendency toward loss of ﬂight in winged animals, and a reduced dispersal propensity in general (see Grant, 1998). Having decided which parameters do and do not belong to the adaptive niche, it is now necessary to consider scalar aspects of the model. A large weakness in the Hutchinson system clearly lies in its reliance on quantitative dimensions, whereas many important niche parameters are clearly deﬁned by such qualitative traits as taxonomic category of limiting resource, and so on. In this sense, the Hutchinson model appears biased toward the abiotic, and the Elton–Grinell models toward the biotic (qualitative) plane, and a general model thus clearly needs to incorporate all of these parameters. The solution to this problem lies in considering the real spatial distribution of both quantitative and qualitative parameters. Niche parameters can, of course, have no ﬁxed Cartesian coordinates in space or time, and we must therefore begin by plotting the intersect of all niche-directed behavior cycle activity in real space, extrapolating from this to a generalization based on all included qualitative and quantitative information. The adaptive niche is then the intersect of all parameter deﬁned volumes, and its dynamic structure is expressed in the fourth (temporal) dimension. Finally, it is necessary also to abstract volume intersects from real space, so that the latter becomes, in effect, ‘‘parameter space’’; it is a ‘‘generalized real space,’’ rather than any localized subset of the same: The adaptive niche of a typical holometabolous insect obviously manifests a temporal sequence, comparing niche parameters of larva with those of adult. Some of these parameters will be quantitative (for example, relative humidity), whereas others will be qualitative in nature (range of food plants, part of plant eaten, etc.).

Fundamental versus Real Adaptive Niche The fundamental adaptive niche as hereby deﬁned (and not sensu Hutchinson; see above) comprises all niche space for which adaptive capacity resides in the gene pool, whereas the real niche constitutes that component of the fundamental niche that is actually realized by a gene pool or population in the course of a single generation. With many dynamic niche parameters it is probable that there will be a large and variable differential between fundamental and real

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adaptive niche, owing to the inﬂuence of stochastic factors in the adaptive system, and it is also likely that greater levels of dynamism will appertain to minor than to major niche parameters. The true adaptive niche is thus viewed here as a partially dynamic structure, tending toward the fundamental state as a function of dynamic equilibrium between organism and environment. This (along with the incorporation of both scalar and taxonomic dimensions) unites the Grinell–Elton, Hutchinson, and MacArthur–Levins models, also removing the typological element inherent to some interpretations.

Niche Interface and Environment Realized adaptation (as distinct from the broader domain of adaptive capacity) occurs at the adaptation interface, which contains the loci in time and space of all deterministic organism–environment interactions manifesting an effect on survivorship (see Chapter 1). This concept allows the temporospatial loci of niche and of selectional activity to be deﬁned explicitly, an appreciation of the nature of each functional interface being essential to an understanding of the evolutionary behavior of adaptive systems. Here, we can also locate the niche interface, which contains any adaptation interface space external to the subject gene pool—including not only the limiting resource of the same, but all ﬁrst contact spatial parameters in the adaptive system of a subject gene pool with the capacity to be manifested in deterministic survivorship factors in the external environment. Following clariﬁcation of the domain of the adaptive niche, the environment of a gene pool can now be explicitly deﬁned as containing all interactive resources external to the gene pool itself, including stochastic survivorship and mortality factors (Fig. 7): The niche interface for a phytophagous insect species comprises the subject gene pool itself, its major niche (food plant) and minor niche (regular competitors, predators, and parasites). Its environment additionally includes sporadic predation, stochastic climatic effects, unpredictable geophysical events, and so on.

SPATIAL ARCHITECTURE OF THE ADAPTIVE NICHE At the epicenter of the niche interface lie those loci at which actual changes to K and N occur. However, the adaptive niche is obviously regarded as also containing more remote parameters such as general environmental cues which allow location of the limiting resource (including abiotic factors in temperature, humidity, pH, etc.). These broader horizons clearly lie in a probability gradient in terms of determination of capacity for survivorship, the adaptive state being affected directly or indirectly according to position of niche parameter in some hierarchic structure. A large question relating to the architecture of niche space thus lies with the varying functional role of different components of the niche interface in the way in which these reﬂect the link between structure, behavior, and function in the context of realization of adaptive capacity. In this respect, the central question now lies in the nature of the hierarchical structure of the niche as a dynamic entity. In this, we see the adaptational process itself manifested in a sequence of events, rather than in a single activity.

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FIGURE 7 The niche interface as a subset of the adaptation interface.

Behavior and the Hierarchic Structure of Niche Space Behavior has already been cited as having a leading role to play in realization of adaptive capacity (see Chapter 1), effectively constituting the realization function for niche. In the latter role, behavior should then also reﬂect the hierarchical organization of niche space. Firstly, it is essential to see that behavior not only directly affects positive survivorship, but it also has a crucial role to play in counteracting mortality in the adaptive system. An adequate analysis of niche space must therefore be concerned with the function of behavioral activity in relation to all survivorship factors, and not merely around the immediate boundaries of the limiting resource. We therefore need to categorize behavioral activity in terms of both direct and indirect functions in relation to the K and r factors in the equation set of the adaptive system (see Chapter 1). Certain of the generalizations that can be made regarding the role of behavior in niche realization are clearly of wider relevance to higher animals, especially because of the lack of a ‘‘central ofﬁce’’ directing activity in the plant kingdom (Stebbins, 1988). The Behavior–Niche Link and the Adaptive Orientation Strategy Hierarchy Behavioral activity is quasi-cyclic when viewed in relation to realization of adaptive capacity, and this is most clearly explicit in the central structure of behavior in its role as realization function for adaptive capacity. This structure, which may be referred to as the adaptive orientation strategy hierarchy, lies

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THE EVOLUTION OF ADAPTIVE SYSTEMS

in the trajectory of activity leading through kinetic 씮 taxic 씮 processive behavioral activity, where processive refers to the process of adaptation, equivalent to, for example, a sought limiting resource or predator to avoid. The processive element thus constitutes behavior involved in direct realization of adaptive capacity (therefore usually affecting ⌬K, r). In this system, kinesis constitutes a response to a stimulus invoking some change in behavior, but no change in orientation, whereas taxis involves some change in directionality, to or from a source of stimulus, and these activities must clearly relate to some other domain of niche space.* Where the major adaptive niche is concerned, we are clearly looking at positive polarity with respect to behavioral activity in general, as distinct from ‘‘behavioral polarity’’ in the usual sense of merely describing orientation relative to the source of stimulus. Here, we are clearly interested solely in polarity relative to probability of realization of adaptive capacity. Evidently, the existing repertoire of behavioral responses must form a key component of adaptive capacity. The ongoing balance between positive and negative behavioral activity will thus constitute an essential part of adaptive capacity with respect to environmental dynamism within the time frame of a generation, and the behavioral component of adaptive capacity must be linked to optimality strategies in that context. That the above repertoire of behavioral responses will tend to be quasicyclic implies that, from each category of activity, we can pass to any other (for example, returning to taxic or kinetic from any processive point), and the turning points between each activity in this cycle must link to stimuli (Fig. 8). What now requires clariﬁcation is the relationship between the behavior quasicycle and realization of adaptive capacity in terms of the hierarchy of spatial domains in the niche. In that context, any positive taxis will clearly be toward the major adaptive niche (the limiting resource), and away from the minor (competitors and predators).† In this scheme, kinesis follows the same polarity rule as taxis, some being ‘‘hopeful of locating a positive taxic stimulus,’’ some of avoiding negative interactivity. Clearly the functional hierarchy within the spatial dimension of the adaptive niche must then be identiﬁed on the basis of niche realization following a complete positive behavioral trajectory ending in direct adaptational activity (kinesis 씮 taxis 씮 process): The link between behavior and architecture of the adaptive niche can be demonstrated with reference to a parasitic wasp, which will probably display some form of positive kinetic locomotory activity initiated by broad abiotic parameters in the niche of the host’s food plant. This will in turn maximize the probability of detection of more speciﬁc clue signals such as odors from the food plant of its host, the latter in turn stimulating taxic behavior (directed locomotion on host’s food plant, probably following a gradient in some external stimulus), ﬁnally ending with processive behavior in oviposition into the host. * Transverse orientation also constitutes active orientational behavior, and is here regarded as being taxic in nature. † This identiﬁes an abiotic component in the minor adaptive niche also.

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FIGURE 8 Movement between processive, taxic, and kinetic behavior.

Although the above relationships are perhaps self-evident in the animal kingdom, they are rather less so in plants. However, wind and animals may form the subparametric niche of plants, in links with pollination and seed dispersal—and this at least constitutes ‘‘parataxic behavior’’ (in the same way, some component of phenoplasticity in plant growth may be construed as being ‘‘parakinetic behavior’’). The adaptive niche has already been deﬁned as being circumscribed by the loci of positive deterministic interactions in terms of capacity for survivorship, and these are now seen as constituting those loci in time and space at which behavioral activity manifests some change in probability of survival of the gene pool. These are not merely those loci of adaptational activity at sites of encounter with limiting resources in K, but also include ‘‘indirect’’ behavioral activity leading to the latter, plus ‘‘r-directed’’ behavioral activity lying deeper in the same function chain, so that any behavioral target in the adaptive niche that is not N or K must in fact form part of a function cycle leading to one or other of these categories. All function cycles thus have a processive ‘‘end target’’ or turning point at the effect on K or N deﬁning the niche interface. Processive behavior can thus be linked to either N (oviposition) or to K (for example; feeding), these ‘‘targets’’ being reached through activity in the logistic and structural components of adaptation, respectively.

FIGURE 9 Sequence of functions brought into action through a temporospatial cascade of behavioral activity in the role of niche realization.

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THE EVOLUTION OF ADAPTIVE SYSTEMS

The Niche Space Hierarchy Using the term ‘‘parametric’’ in the sense of a functional boundary to that component within which direct realization of adaptive capacity is contained, the above-mentioned link between the hierarchies expressed by behavioral activity and adaptive niche may be encapsulated through adoption of the following nomenclature: • Parametric niche space, in which K and other direct resources are located, is deﬁned by positive processive behavioral activity directed toward realization of adaptive capacity. • The subparametric component of the adaptive niche is similarly realized through positive taxic behavior, a secondary-level boundary in the tripartite hierarchy with a relatively high probability function for location of parametric niche space. • Hypoparametric niche space is determined via positive kinetic behavior, thus deﬁning the outermost boundary of the adaptive niche in the lowest probability zone for realization of adaptive capacity. Behavior determines niche realization following a hierarchic pattern of activity, and we have now encountered a complementary hierarchy of functional levels in niche space, identiﬁed as parametric (the actual sites of adaptational activity) to infraparametric (which latter would collectively include those loci of sub- and hypoparametric niche space converging on parametric niche space loci via a behavioral function chain directed toward change in K or N ). The pathway between different levels in the adaptive niche hierarchy can also be linked to the question of energy ﬂow in the adaptive system.

FIGURE 10 Links between levels in niche space hierarchy and direction of energy ﬂow.

The functional hierarchy in adaptive niche space has now been categorized in concrete terms, utilizing the stimulus ‘‘turning points’’ in behavioral activity to explicitly deﬁne each functional domain of niche space: the processive–taxic boundary deﬁning parametric from subparametric, and the taxic–kinetic boundary delimiting hypo- from subparametric niche space. Given that processive, taxic, and kinetic behaviors are also expressed in relation to competitors

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and predators, it follows that the above spatial hierarchy applies to both the major and minor domains of the adaptive niche. Limiting Factors in the Niche Space Hierarchy Within the niche space hierarchy, it is further instructive to investigate the distribution of limiting factors, since there is clearly an overt relationship between category of niche space and locus of the K limit. Following the behavioral quasi-cycle, and from the starting point of a random encounter scenario, there will be a probability gradient for encounter with limiting factors with respect to kinetic, taxic, and processive niche parameters, and this in turn will be linked to a correspondence between category of niche space and trophic level in the adaptive system. Parametric niche space is both ﬁnite and reducible, whereas at the other end of the spectrum, hypoparametric niche space may tend toward the status of being inﬁnite and nonreducible. Bearing this in mind, the probability of a limiting factor being encountered in a given niche space domain will be approximately inversely proportional to the dimensions of that domain in real space. A large proportion of behavioral activity in kinetic or taxic niche space will thus come into the category of ‘‘function expressed, but no adaptation interface actually encountered,’’ and much of this exploratory activity will relate to large spatial dimensions within the abiotic environment. However, it is important to see that some component of sub- or hypoparametric niche space may also hold a limiting factor, since the same resource can be limiting at high population densities and not at low. In this respect, status in the niche space hierarchy must be linked to optimum population density, to which both logistic and behavioral components of adaptive capacity will tend to be adjusted (accordingly, any attempted typological view of the adaptive niche must consider this dynamic aspect most carefully!).

FIGURE 11 Probability pyramid for size of spatial dimension and probability of encounter with K limit within the niche space hierarchy (links to trophic levels also indicated).

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The main points of the above discussion can be summarized in tabular form: Category of niche space

Category of behavioral activity

Role in equations of population dynamics

Principal direction of energy ﬂow

Probability of holding the K limit

Parametric Subparametric Hypoparametric

Processive Taxic Kinetic

⌬K or ⌬N Usually indirect Usually indirect

In Out Out

High Low Rarely

Thus, hypoparametric niche space seldom holds the K limit, subparametric sometimes does so, and parametric niche space is generally the focus for the activity of limiting factors in the adaptive niche. Parametric Niche Space Processive behavior lies at those spatial parameters in the adaptive system at which there is capacity for energy exchange or for mortality avoidance (capacity for increment in N or for avoidance of decrement to N ), and this deﬁnes parametric niche space explicitly. Parametric niche space will thus be described by at least one parameter related to energy exchange, reproduction, or mortality avoidance sites in the normal limiting resource, where such activities carry a direct function in modulating K or N. This level in the niche space hierarchy is thus ultimately deﬁnable as a spatial locus containing some limiting resource that is described by survivorship-directed processive behavior linked to direct manifestation of adaptation, taking into account both major and minor niche: Returning to the example of the parasitic wasp, the host species (or host range) of a particular parasite species clearly forms part of its parametric niche space. Parametric niche space is obviously important for the principle of reciprocal specialization, since it is generally trophic behavior which manifests the greatest degree of mutual evolutionary change between closely interacting gene pools of an adaptive system (see below). It is also the locus of the equation set of the adaptive system (see Chapter 1) for most ambient selectional activity. The situation in which other categories of niche space may enter these equations is best understood in terms of nonregular upward ﬂuctuations in population density (or in the context of adaptive shifts; see Chapters 17–19). Subparametric Niche Space Subparametric niche space is realized through the function of positive taxic (search) behavior, in that it tends to lie ‘‘below’’ the actual sites of change in K or N in the context of ambient population densities. This category is nevertheless directed toward the location of parametric niche space, thus holding some probability function for survivorship activity. Abiotic niche space may also come into this domain: The limiting resource of a parasitic wasp’s host species may often form the subparametric niche space of the parasite itself, given that visual or olfactory stimuli from that source may be involved in host detection.

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The hyperparasitic wasp Pseudorhyssa searches for the oviposition borings of its host, Rhysella, the primary parasite of a wood-boring sawﬂy larva. Species of the ichneumonid genus Ophion tend to have several host species, but these tend to be linked to a particular microhabitat such as larvae of arboreal host species (Brock, 1981a). Hypoparametric Niche Space Hypoparametric niche space is that component of niche space corresponding to positive kinetic behavior in the niche realization function, as deﬁned by the nondirectionalized activity of kinetic behavior. This mechanism is linked to the domain of a function cycle leading to modulation of K or N via an increase in the probability of encounter with taxic stimulus points. Taxic behavior is clearly deterministic in nature by virtue of being conﬁned to a certain subset of the environment, and thus we may feel conﬁdent in attaching this category of ‘‘adaptation space’’ to the niche itself: Continuing with the example of the hyperparasitic wasp Pseudorhyssa and host (see above), certain biotic factors linked to the distribution space of the host’s own limiting resource (trees of the genera Betula and Alnus) might offer a suitable pabulum for some form of taxic response, so constituting the hypoparametric niche space of the parasite. Taxic behavior is thus performed within certain deﬁnable boundaries intrinsic to the adaptive system. The primary goals of behavioral activity in niche realization are thus those of locating hypoparametric within subparametric niche space, and parametric within subparametric.

Niche Hyperspace Owing to the fact that all niche space is to a greater or lesser extent ‘‘repetitive’’ by virtue of recurrent behavioral patterns over the time span of a generation, the temporal summation of realization for a given set of niche parameters at any hierarchic level creates a four-dimensional construct, niche hyperspace. Niche hyperspace can clearly be manifested in parametric, subparametric, and hypoparametric domains in both major and minor adaptive niches: The signiﬁcance of niche hyperspace for adaptation can be demonstrated from a ‘‘time and motion’’ comparison between two species competing to locate the same limiting resource, as with two parasitic wasp species seeking the same host. That species with the greatest efﬁciency in host location (e.g., through ability to ﬁnd the host more rapidly and more often than a competitor) clearly manifests the highest adaptive state within the niche intersect zone. This is fundamental to an understanding of the fact that no two species may occupy exactly the same niche—especially in that it is not the qualitative or quantitative nature of niche parameters that matter here, but some aspect of activity that may either lie exclusively in behavioral strategy itself or else be connected with structure through biomechanical efﬁciency.

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Thus, if one species can search n times the total volume of major adaptive niche space than another within the same time frame, then it has the greater probability of locating the shared limiting resource. Parametric niche space is of particular signiﬁcance with respect to niche hyperspace differentials, since active competition is concentrated here, and sub- or hypoparametric niche space tends by way of contrast to be much less ﬁnite or reducible. The value of the niche hyperspace concept lies in differentiation of adaptive strategies of different gene pools exploiting the same adaptive niche, namely, in that it is hypothetically possible for two gene pools to overlap with respect to niche, while having different adaptational states with respect to niche hyperspace. In that circumstance, one gene pool may simply be more efﬁcient at exploiting the same niche space than another, and this will be crucial in deciding the outcome of competition. In this, we observe that competition occurs in the speciﬁc context of niche hyperspace.* It also follows that niche hyperspace is reﬂected both in r and in the 움 factors of the Lotka–Volterra equations.

The Adaptive Niche and the Reciprocity Principle In the previous chapter, we saw that the reciprocity principle applied to the biotic adaptive niche alone, for gene pools expressing mutual depressor or enhancer properties. We can now add that the particular biotic element favoring reciprocal adaptivity also tends to lie with parametric niche space. This means that coadaptive evolution in general will tend to be expressed in some sequences of structural change and not in others (for example, there is no ‘‘reciprocity’’ between the functional activity of a wing and the abiotic aerial environment!): The reciprocal relationship between angiosperm reproduction and insect feeding habits has been understood since the late nineteenth century, and this clearly played a decisive role in the origin of the ﬂower (Takhtajan, 1954). The same is obviously true in the relationship between plant fruiting bodies and dispersal mediated by birds and mammals.

MAIN POINTS FROM CHAPTER 2 1. The adaptive niche is deﬁned according to the ‘‘locus of ﬁrst contact’’ between gene reservoir and external environment, and is thus linked to the extrinsic component of adaptive capacity. 2. The adaptive niche contains major and minor components, the former being linked to the limiting resource, the latter lying in gene pools of equivalent and superior trophic level. 3. There are fundamental versus real domains in the adaptive niche, respectively constituting the total possible versus per-generation realized complements of extrinsic adaptive capacity. * However, see Chapter 17 for a discussion of niche space in view of a major adaptive shift.

2. SPATIAL STRUCTURE OF THE ADAPTIVE NICHE

41

4. The niche interface concept links to a revised deﬁnition of environment, which latter additionally encompasses stochastic interactions impinging on adaptive systems. 5. An orientation strategy hierarchy reﬂects the central role of behavior in realization of adaptive capacity, identifying a complementary hierarchy of functional domains in the adaptive niche which in turn carry signiﬁcant links to the dynamic behavior and evolution of adaptive systems. The niche space hierarchy in question is parametric–subparametric–hypoparametric, as respectively deﬁned by positive processive, taxic, and kinetic behavior. 6. Limiting factors tend to reside in parametric niche space, which latter thus forms the principal focus of the equation set of the adaptive system. Parametric niche space is also linked to inﬂux of energy. 7. Niche hyperspace exists as a function of repeated behavioral patterns in niche realization. This aspect of niche space forms an important contribution to ﬁtness differentials existing between genotypes and gene pools.

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3

DYNAMICS OF THE ADAPTIVE NICHE

It is axiomatic that the value and polarity of selection are frequently a variable, owing to the periodic behavior of many adaptive niche parameters. Consequently, an understanding of niche periodicity is essential in order to investigate the capacity of a gene pool for dynamic activity. The niche forming the extrinsic adaptive capacity of a given gene pool is clearly not a ﬁxed entity, but has a probabilistic structure within a temporospatial matrix. To understand the effect of such variation on the nature of the adaptive response, it is useful to begin by examining the manner in which the niche is distributed in terms of the adaptive response, before proceeding to look into temporal ﬂuctuations and spatial dynamism in the distribution of niche parameters.

TEMPORAL AND SPATIAL REFERENCE FRAMES OF THE ADAPTIVE NICHE Certain temporal and spatial reference frames are crucial to the analysis of niche structure, particularly because the dichotomy between dynamic equilibrium in adaptive capacity and true evolutionary behavior is reﬂected in such factors (see Chapter 5).

Temporal Reference Frames of the Adaptive Response It is instructive to deﬁne some preliminary reference frames which effectively ‘‘set the clock’’ on the basis of major parameters of the adaptive response, as

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THE EVOLUTION OF ADAPTIVE SYSTEMS

a typological starting point from which to explore niche dynamism. In the following system, certain ‘‘temporal landmarks’’ are identiﬁed as being strategic to the discussion in hand: 1. t ⱕ life span of an individual: Obviously, much dynamic activity at this primary level can only be met by metabolic or behavioral adjustment, since genetic adjustment based on allelomorphism can only be manifested within the intergenerational time frame. This reference frame is therefore pivotal in distinguishing the direct genetic response from the apparently nongenetic, and it also holds quite different implications for logistic and structural components of adaptation. It is here that behavioral activity and phenoplasticity allow an adaptive response to be made to variables operating within the narrow time frame of t itself. 2. T ⫽ time taken for ﬁxation of a given allele of W ⫽ 1.0 and its dispersal through subpopulations of a sympatric gene pool: This reference frame will serve as a useful guideline for assessment of the nature of the adaptive response to a dynamic external environment. Much genetic adjustment will in fact be transitory, expressing dynamic equilibrium within a relatively short time frame, rather than manifesting directionalized evolutionary change. Any allelic change that expresses reversibility to the point of transient elimination within time frame T is clearly also of dynamic equilibrium. 3. Tc ⫽ ‘‘ambient speciation time,’’ that is, time for accumulated genetic changes in geographically mobile gene pools of a gene reservoir to reach that point at which sympatry–rejoin with the parent lineage (or divergence in allopatry) tends to lead to cladogenesis, causal either to extinction of one emergent gene pool or to speciation: This reference frame is clearly crucial to several genuinely evolutionary patterns of change, as distinct from those constituting mere dynamic equilibrium in the adaptive response. It should be clear from the outset that the same selectional regime operating within the domain of periodicity expressed within t, T and Tc will give rise to quite different evolutionary potentials in each case. A niche parameter ﬂuctuating within the domain of time t will obviously be met by quite different manifestations in the adaptive response, than if this periodicity were only evident in the context of a much larger time frame, such as T or Tc. The ambient state of niche periodicity for a large percentage of genetic variation is probably ⬎t but ⬍T, so that by convention (and due to practicality!), adaptive niche structure is generally best analyzed in its ‘‘static’’ perspective (corresponding to periods ⬍t 씮 ⬍T ). We must, however, also consider dynamic aspects of niche change for periods T 씮 Tc in order to gain deeper insights into evolutionary activity, and this clearly leads us from observational to extrapolatory criteria of analysis. These larger time frames thus form valuable reference points through which to examine major anagenetic change, as distinct from the shorter term behavior of allelomorphic states in a gene pool which expresses dynamic behavior within the context of a preexisting adaptive capacity. Spatial Reference Frames of the Adaptive Response Niche space must also contain signiﬁcant reference frames for evolving adaptive systems, the two primary divisions following the ‘‘micro- versus macrospatial’’ coordinate systems:

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45

s ⫽ real space within the niche of a gene pool ( gene pool niche space) S ⫽ geographic space containing similar, noncontiguous gene pools of a species ( gene reservoir niche space) The coordinates of gene reservoir space are clearly the macrospatial coordinates of the adaptive niche and environment linked to geographic distribution and dispersal, and these coordinates must be crucial in the allopatry–sympatry scenario affecting speciation mechanisms (see Chapter 6).

Population, Gene Pool, Species, and Lineage Niche Using the temporospatial framework proposed above, we can now look at the niche interface in several dimensions. Taking niche space in general, we can consider some useful summations over various temporospatial scenarios: N⬍s ⫽ population niche, the smallest contingent of functional niche space tNs ⫽ gene pool niche, the adaptive niche relative to any single gene pool, over one generation tNS ⫽ gene reservoir niche, the niche occupied by the entire gene reservoir over one generation TcNS ⫽ species niche, the niche occupied by the gene reservoir for the life span of a species ⬎TcNS ⫽ lineage niche, moving into the domain of anagenesis and longer term evolutionary phenomena t

The above categories must also have some bearing on the dichotomy between fundamental and real adaptive niche (that is to say, fundamental niche relates to species niche, real niche to population niche, and so on). We can also extract parametric or sub- or hypoparametric niche space from the above expressions in order to examine short- and long-term evolutionary effects of different adaptational regimes, an approach which in fact will be shown to have far-reaching consequences for evolutionary theory. In the latter context, the lineage niche is clearly the fundamental concept required in discussions of long-term evolutionary mechanisms. This approach will be developed further, as anagenesis and other modes of evolutionary change come to be examined in detail in later chapters.

TEMPORAL PERIODICITY OF THE NICHE INTERFACE Although it is possible to arrive at a categorization of niche space following the above system, it is obvious that much dynamism must be contained within ‘‘static’’ domains (e.g., leading species niche parameters may well be stable in the longer term, but many other parameters within the boundary of a species unit will manifest temporospatial polymorphism). It is evident that some niche parameters are variable in time and others are not, and it is also evident that degree of dynamism is linked to level in the niche space hierarchy. The manner in which niche regimes vary in time and space must also have a large impact on the evolutionary behavior of adaptive systems. In particular, speciation

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THE EVOLUTION OF ADAPTIVE SYSTEMS

mechanisms and the impact of interspeciﬁc evolution on anagenetic change must depend heavily on temporospatial conﬁguration with respect to the larger coordinates (see Chapters 6 and 17), and the boundary between evolutionary scenarios characteristic of dynamic equilibrium in adaptive capacity as against evolution also lies here.

Modes of Periodicity in the Niche Interface Niche periodicity can best be deﬁned in terms of the reference frames designated earlier. It must also be stated at the outset that the periodicity of niche parameters can take either of two forms, with very different effects on the adaptive response: 1. Oscillatory periodicity, or bidirectional variability of some niche parameter within the range ⬎0 씮 1.0, where the adaptive response may be reﬂected in frequency changes in the allelomorphic structure of the gene pool 2. Boolean periodicity, where a niche parameter is simply present or absent over a temporal sequence (or at a given spatial location), and the genetic response can only be based on more erratic ﬂuctuations, perhaps in allelomorphic variation linked to recurrent mutation Static and regularly periodic niche interface structures of period ⬎t are clearly those most likely to enter the organismic level in terms of evolutionary changes in behavior and structure, truly stochastic survivorship factors therefore being identiﬁable as irregularly periodic (or nonperiodic) inﬂuences for which there can be no ongoing adaptive response within the domain of existing adaptive capacity: Consider (for example) dimorphism in the peppered moth Biston betularia (see Kettlewell, 1973)*; a scattered distribution of positive adaptive niche space appropriate to the carbonaria morph exists, namely, polluted environments. Temporal change is clearly also manifested in this, in that subsequent widespread recovery of the wild-type morph has been reported in the aftermath of pollution control. Environmental change has not occurred over so long a time frame that adaptive capacity for reversal has been lost. Dynamic and Static Niche Interface From the above analysis of periodicity in the niche interface, and using the proposed time frames as our standard for the analysis of the structural component of evolution, we may now derive categories of ‘‘temporal dependence’’ for niche periodicity: • Dynamic niche parameters will be deﬁned here as having periodicity of ⬍t 씮 ⬍Tc, and in this situation the adaptive response adjustment can be deemed to fall into the category of dynamic equilibrium for the * More recent studies have seriously questioned some of the original Kettlewell data. The treatment here consequently omits reference to certain aspects of interpretation.

3. DYNAMICS OF THE ADAPTIVE NICHE

47

allelomorphic component of the gene pool (assuming that the latter is affected by adaptive capacity alone). • Static niche parameters express periodicity at ⱖ Tc, where evolutionary patterns involving iterative gene ﬁxation will tend to be manifested, this being associated with the kind of long-term directional change linked to speciation and anagenesis. Clearly then, different niche periodicities will have fundamentally different evolutionary potentials, of which the dichotomy between dynamic adaptive equilibrium and evolution is the most fundamental. Although the great majority of niche parameters are probably dynamic in the very long term, it is nevertheless possible to distinguish essentially static from dynamic in this scenario in the domain of such key modes of change as speciation and anagenesis. Periodicity and the Niche Space Hierarchy How do the above periodicity factors relate to the niche space hierarchy deﬁned in Chapter 2? Shorter periodicities, say, of ⬍t 씮 앑T, are probably of frequent occurrence with respect to much parametric niche space, especially with oscillatory periodicity, whereas longer periodicities (often ⱖTc) more probably typify hypoparametric niche space, owing to the greater long-term stability of broader spatial parameters (which will be much less narrowly deﬁned than the loci of the parametric niche): The aquatic habitat (in general) may have much greater stability as an environment than the presence of any single biotic limiting resource, for a specialized consumer species living in that environment. For Tc and above, we in fact ﬁnd many macroniche parameters of hypoparametric status. Clearly, major body plan design can only be linked to such nonchanging components of the adaptation interface. At the outset then, category of niche space seems likely to be linked to periodicity, and this in turn affects the mode of adaptive response. Microniche versus Macroniche It is highly signiﬁcant that a four-dimensional perspective based on stability versus periodicity of a given set of niche parameters reveals the existence of two broad categories of static versus dynamic type, which can then be used to identify the parameters of micro- versus macroniche: the macroniche is made up of niche parameters static in the temporal dimension, whereas the microniche contains parameters with a purely transient existence (Fig. 12). In this scheme, there is an approximate relationship between macroniche and environmental niche, also between macroniche and the adaptive zone concept of Simpson (see Chapter 17). The categories ‘‘static’’ and ‘‘macro-’’ seem more often to be linked to sub- and hypoparametric niche space, given the very frequent dynamic behavior of differentials at the parametric level expressed in species differences and the link between the higher systematic categories and other levels in the niche space hierarchy.

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FIGURE 12 Relationship between niche periodicity and micro- or macroniche status.

SPATIAL STRUCTURE OF THE NICHE INTERFACE Adaptive capacity contains a range of different phenotypes manifested in the gene pool, some of which obviously have a niche interface varying with space, rather than time. It is therefore now necessary to explore this spatial dimension. Here we are no longer concerned with the spatial dimensions of population versus gene pool, but with the degree to which niche space in general is disjunctly distributed in real space. The Isotopic and Anisotopic Niche Interface Adaptive capacity interdigitates with the spatial structure of the niche interface via the allelomorphic structure of the genotype as follows: • The isotopic niche interface is one that is uniformly distributed on the spatial plane, so that a given gene locus may be expressed in a single phenotype, the ﬁtness of which is constant over gene reservoir niche space. • The anisotopic niche interface is one that is differentially distributed on the spatial plane, so that a gene locus may be expressed in two or more allelomorphic phenotypes that have separate ﬁtness values linked to different loci within gene reservoir niche space. It is evident in examples such as the shell banding and color traits in the terrestrial gastropod mollusc Cepaea studied by Cain and Sheppard (1954) that different morphs of a species may dominate different spatial regions, owing to differentials in the nature of the selective agency determining gene frequencies (visual selection in some areas, temperature effects in others). A similar interpretation has been made with regard to variation in wing marking traits in the nymphaline butterﬂy Maniola jurtina studied by Ford and others (see Brakeﬁeld, 1990, for a review), although in the latter example it is less clear exactly how selective pressures vary from one locality to another. These factors clearly reﬂect the spatial structure of the adaptive niche itself. Similarly, chromosomal races in Drosophila pseudoobscura indicate clinal changes associated with changing environment on a much wider spatial plane (see Dobzhansky, 1970). There are clines in the frequencies of

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3. DYNAMICS OF THE ADAPTIVE NICHE

different chromosome types across the distribution area of this species, and where the environment changes rapidly (over altitude, for example), change may be rapid. Dobzhansky also pointed out that this does not necessarily mean that the same factors apply to a wider geographic pattern. Returning to the concept of adaptive capacity introduced in Chapter 1, we can now conﬁrm that many genotypes within the repertoire of adaptive capacity will actually prove nonadaptive in the context of the ambient anisotropic selection interface.

NICHE PROFILE AS THE COMBINED TEMPOROSPATIAL PERSPECTIVE The signiﬁcance of temporospatial patterns of niche variation must clearly depend ultimately on the longer term aspect of both temporal periodicity and spatial ﬂuctuation manifested in an evolving adaptive system. This composite structure can conveniently be termed niche proﬁle (see below).

Niche Proﬁle and Long-term Dynamics of the Niche Interface Dynamism in the spatial aspect of the adaptive niche was described above in terms of the isotopic–anisotopic dichotomy, and we must now additionally consider how this scheme links to the temporal aspect of static versus dynamic niche parameters for the species niche. Niche proﬁle describes the expression of both temporal and spatial aspects of the niche interface of a species. We may thereby identify two highly signiﬁcant niche proﬁle categories: isotropic (constant with respect to both time and space) and anisotropic (variable in both time and space), as follows:

Static Dynamic

Isotopic

Anisotopic

isotropic (isotopic)

(anisotopic) anisotropic

For example, a gene pool niche could be temporally static, yet spatially disjunct (as with very many polymorphisms). ‘‘Isotropic’’ is thus an abbreviation for ‘‘static–isotopic,’’ and ‘‘anisotopic,’’ for ‘‘static–anisotopic’’ in the context of niche proﬁle. To maintain the adaptive state, the realized adaptive response must clearly also be variable when interacting with anisotropic niche proﬁle, different subsets of adaptive capacity attaining realization at different temporospatial loci, wherever a given niche change presents capacity for complementary adaptational adjustment. Niche proﬁle must therefore act to determine the evolutionary behavior of the adaptive system—given, of course, the additional prerequisite of complementary genetic variation. Isotropic Niche Proﬁle and Adaptive Potential A temporospatially uniform niche proﬁle state obviously links to evolutionary stasis itself. However, by no means is all apparent stasis derived from a

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temporospatially static niche proﬁle (see Chapter 19). And paradoxically, the latter may also link to anagenetic change (since progressive evolution could not occur over lineage time in the absence of a constant niche interface). The above are very broad generalizations, and clearly, much more needs to be done before these relationships can be adequately understood. In particular, it must be that adaptive capacity alone cannot provide the basis for evolutionary advancement with respect to features of the external environment carrying long-term stability, and we must consequently now presume the existence of a greater domain residing in adaptive potential (see Chapter 7). Anisotropic Niche Proﬁle and Adaptive Equilibrium A temporospatially dynamic niche proﬁle must have a signiﬁcant bearing on ‘‘nonlinear’’ patterns of change in the adaptive response, including dynamic equilibrium between the allelomorphic component of the genome and a variable external environment (see Chapter 5). Anisotopic Niche Proﬁle, Polymorphism, and Cladogenesis The effect of a (static) anisotopic niche proﬁle can best be analyzed with respect to balanced polymorphism and also to broader cladogenetic selectional regimes, this scenario clearly favoring diversiﬁcation of the gene reservoir. Of special interest here is the relationship with speciation (see Chapter 6). Niche Proﬁle and the Adaptive Response in General From the preceding analysis, we may now link the conﬁgurations of niche proﬁle listed above with certain broad categories of adaptive response, ranging from stasis, through dynamic equilibrium, to clado- and anagenesis: Isotropic Anisotopic Isotopic Anisotropic

Stasis or anagenesis Gene changes on the spatial plane: balanced polymorphism and cladogenesis Genetic differentiation on the temporal plane: simple dynamic equilibrium in the genetic component of adaptive capacity Genetic differentiation on both spatial and temporal planes: ‘‘complex adaptive equilibrium’’

Given the above range of conﬁgurations in niche proﬁle, it is of course axiomatic that periodicity in niche parameters may or may not lead to complementary change in the adaptive response. There is no reason to suppose that the existence of, for example, an anisotopic niche proﬁle will necessarily lead to speciation, although it is essential to see that the latter is clearly facilitated by the system in question. The above categories of niche proﬁle therefore are descriptions of evolutionary potential alone, and the link between ‘‘potential’’ and ‘‘realization’’ must be explored with reference to the structure of selection as it relates to adaptive capacity, as well as to other as yet unexplored propensities of the adaptive system. One useful overview in this will be to consider the supreme importance of the static versus dynamic niche, given that the temporal dimension is of special signiﬁcance in determining whether an ‘‘expected’’ adaptive response has time to appear and be perpetuated. For example, the reciprocity principle (Chapter 1) is unlikely to be manifested in the structural component of the adaptive response in absence of long-term stability of selectional interactions between gene pools of an adaptive system.

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The link between the adaptive niche space hierarchy (Chapter 2) and niche proﬁle must be looked at with respect to species and lineage niche. Hypoand subparametric niche space are obviously closely linked to longer term evolutionary trends, since many parametric niche resources may be contained as subsets of much larger sub- or hypoparametric domains, so that the latter will often tend to be linked to an isotropic niche proﬁle. Furthermore, both parametric niche space and niche hyperspace in general are of great signiﬁcance for the development of cladogenetic potential, owing to their link with active competition, and these categories must link to a fundamentally anisotopic niche proﬁle. In general then, static niche parameters will tend to be linked to macroevolutionary patterns of change, and an isotopic spatial domain is of special signiﬁcance in the same context.

MAIN POINTS FROM CHAPTER 3 1. It is useful to deﬁne a set of temporal and spatial reference frames for analysis of the dynamic behavior of adaptive systems: t (⫽ life span of an individual) to ⬎Tc (⫽ that of a lineage). These points of reference identify fundamental static/dynamic categories in the niche interface. 2. In the spatial perspective, the adaptive response falls into s (gene pool) and S (gene reservoir) primary categories. Spatial dynamism is in turn deﬁned in terms of the degree of disjunctness of niche parameters in real space (isotopic/ anisotopic niche interface). 3. Niche proﬁle is deﬁned jointly by conﬁgurations of temporal plus spatial reference frames of niche dynamism. The longer term aspect of niche proﬁle can be used to distinguish between adaptive equilibrium and true evolutionary change, and isotropic versus anisotropic categories of niche proﬁles underline this dichotomy. 4. Dynamism is expressed differentially at different levels in the niche space hierarchy. Signiﬁcantly, there are micro- versus macroniche (‘‘dynamic’’ versus isotropic) domains, reﬂecting the relationship between niche proﬁle and adaptive response. The microniche is more often linked to parametric, and the macroniche, to sub- and hypoparametric niche space.

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4

THE SELECTION INTERFACE

THE NATURE OF SELECTION The Darwinian thesis holds that evolutionary change is directed by selection in terms of improved adaptive function, rather than by action of any endogenous ‘‘orthogenetic’’ force. Selection is that mechanism through which differential survivorship is conferred on genotypes as a result of mortality in which a heritable differential between survivors and nonsurvivors is also manifested. Are the supposed properties that have been widely attributed to selection intrinsic to the agencies of selective mortality, or are they a manifestation of some larger domain of interaction within the adaptive system?

Properties of Selection At the outset, it must be clear that selection cannot simply be equated with mortality alone. How, then, does it relate to the adaptive state concept, to equations of the adaptive system, and to measures of ﬁtness for competing genotypes and gene pools? The adaptive state A was deﬁned earlier as being some measure of the probability of survival of a genotype or gene pool in terms of the nature of its survival strategy of a function of adaptive capacity, and accordingly A must have some predictable relationship with the selection coefﬁcient s. Clearly, two genotypes may have A ⫽ 1.0 in isolation from one another, while at the same time, A for both is depressed in the sympatric situation. This scenario clearly indicates the existence of relative adaptive states expressing a differential in

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A, where there is at least partial competition for some limiting resource. That locus in time and space in the adaptive system within which genotypes or gene pools with different adaptive states exist in competition owing to presence of a mutual niche intersect constitutes the selection interface, and the relative adaptive state of such genotypes or gene pools is described by the selection coefﬁcient s (effectively the reciprocal of the coefﬁcient of ﬁtness, W ). Selection can thus be viewed as a property residing in relative adaptive states for genotypes or gene pools, each of which may well carry a survivorship probability of 1.0 in absence of the other. It is thus equivalent to differential survivorship of genotypes, the outcome of which is an increase in the adaptive state of one genotype and a depression for another for the duration of the selection interface. From this standpoint, a monomorphic population clearly has the hypothetical potential to survive with no selection acting on it, solely through the process of adaptation. Selection thus operates only in the niche intersect zone between two or more competing genotypes or gene pools, and outside the intersect zone lies the adaptation interface alone: Biston betularia presents no selection interface unless B. betularia f. carbonaria is also present at the same temporospatial locus. A B. betularia population carrying a frequency of 1.0 for the wild-type allelomorph is thus perpetuated through adaptation (or eliminated through adaptational failure), and selection only comes into play when there is a relative adaptive differential between two allelomorphs present in a sympatric state (in reality, there will of course always be other selectional differentials between individuals and populations, and this scenario is thus a purely hypothetical one).

ARCHITECTURE OF THE SELECTION INTERFACE Selection appears at ﬁrst sight to be a vector quantity, the directionality of which may be supposed to be reﬂected in topology of the adaptive response, and the apparent quantitative properties of selection similarly derive from relative adaptive states when a given gene pool or genotype carries a higher adaptive state relative to a competitor. However, these characteristics cannot truly be regarded as being intrinsic qualities of selection itself, in the context of any agency existing independently of the organism–environment interaction, since polarity (and also directionality) may vary with respect to different conﬁgurations of niche proﬁle. These differentials clearly derive, not exclusively from the selective agency, but from both extrinsic and endogenous properties of adaptive capacity. The natural conclusion would therefore be that the supposed properties of selection lie, not in the selective agent, but in a larger selection interface. Of great importance for evolutionary theory is the fact that the selection interface can be shown to exist in a higher domain than that of individual selection—not only at gene pool and gene reservoir levels, but also in the transspeciﬁc dimension. This observation will be conﬁrmed and emphasized at many junctures in the ensuing analysis.

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The Selection Interface and Adaptive Capacity The selection interface clearly lies in the existence of adaptive capacity for an adaptive response to a changing adaptation interface, being determined not only by the nature of niche proﬁle, but also by the capacity of the organism to manifest some complementary heritable differential within the domain of adaptive capacity (see Chapter 3). The external selection interface thus occurs whenever demanded by the periodicity and spatial distribution of niche, being deﬁned explicitly by the intersect existing between niche proﬁle and adaptive capacity in terms of heritable differentials in the adaptive state.

FIGURE 13 The selection interface as an intersect between niche proﬁle and adaptive capacity.

The selection interface is therefore made up of the loci of adaptational change, wherever adaptive capacity has the facility through heritable variation to respond to dynamic niche structure or to improve on preexisting adaptive strategies. It is now possible to identify supposed attributes of selection, as characteristics of the selection interface as a whole, for example: Mortality derived properties Adaptive capacity derived properties

Density dependence Directionality

Directionality in the Selection Interface There are two conﬁgurations in niche proﬁle that can be shown to be of fundamental signiﬁcance for the evolutionary behavior of adaptive systems: isotropic and anisotopic (see previous chapter), both of which have particular potential to inﬂuence evolutionary directionality when iterated over a lineage time frame then translated into a selection interface. This will clearly not be the case with respect to the anisotropic/isotopic case, which can only relate to adaptive equilibrium, because of links with temporal dynamism. The anisotopic selection interface will be discussed in greater detail in Chapter 5, but it can be illustrated in a preliminary manner as shown in Fig. 14. In contrast, the isotropic selection interface might conversely be supposed to constitute a ‘‘normalizing’’ structure, either in a single stable state, or else around the mean of a variance (Fig. 15). However, owing to the almost universal multiple functionality of organic structures, the ‘‘single stable state’’ situation

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FIGURE 14 A normally distributed variance gravitates toward two discrete components of the total original frequency distribution, manifesting spatial ‘‘disruption’’ of the gene pool in the presence of an anisotopic selection interface (X ⫽ measurement of a quantitative character, Y ⫽ frequency in population).

is probably more accurately described as the resultant of a minimum of two antagonistic selection vectors, in the context of a complex isotropic selection interface: Simpson (1953) discussed an example with shell thickness (as in molluscs), which he reasoned was controlled by the balance between selective forces acting separately in favor of thickness (for protection against predators) and thinness (favoring freedom of locomotion), the result being a ‘‘compromise’’ solution between two extremes, each of which carries some negative corollary.

FIGURE 15 One expression of the ‘‘normalizing’’ (isotropic) selection interface, in which an initially wide variance tends to narrow around an optimum state (axes as in ﬁg. 14).

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The above factors can be viewed as important elements in determination of the architecture of the selection interface, serving to identify the various ‘‘properties of selection’’ as factors residing in particular conﬁgurations, as these relate to long-term tendencies of the adaptive system. Canalizing, directional, centrifugal selection, etc., are thus more usefully seen as properties of the selection interface in its iterative perspective (see below). Selection Proﬁle and Conﬁgurations of the Selection Interface What do different conﬁgurations of the selection interface mean in the context of long-term niche proﬁle? Just as niche proﬁle describes the temporal and spatial dynamic status of the adaptive niche, selection proﬁle similarly describes both the periodicity of the selection interface and its status in the link with the spatial perspective in the genetic component of adaptive capacity over speciation time. In other words, when we speak of ‘‘conﬁgurations of the selection interface,’’ we are simply linking the activity of differential mortality to the pattern of temporospatial variation in the adaptive niche itself: The Cepaea and Maniola exemplars given for the anisotropic niche proﬁle scenario (see p. 48) naturally serve also to identify the behavior of a selection interface, since it is only through the existence of adaptive capacity for polymorphism that modulation of the gene pool with respect to dynamism in the external environment is rendered possible in the sense of ‘active’ adjustment. Selection proﬁle thus describes both temporal periodicity and spatial perspectives of the selection interface over speciation time, thus determining directionality of the adaptive response (adopting the same scheme as that devised for niche proﬁle; see Chapter 3): Selection proﬁle

Properties of the selection interface

Isotropic Anisotopic Isotopic Anisotropic

‘‘Normalizing selection’’: determining permitted range of variation ‘‘Diversifying selection’’: perpetuation of two or more states ‘‘Cyclic selection’’: recurrent allelomorphic variation ‘‘Diversifying plus cyclic selection’’: transient polymorphism

It is furthermore axiomatic that, in certain conﬁgurations of selection proﬁle, changes in the adaptive response may tend to ‘‘shadow’’ selection proﬁle, with a phase difference between selection interface and adaptive response. This is due to the incremental manner in which most gene frequency changes occur, as a function of the mode of operation of the genetic system itself and of the behavior of the equations of the adaptive system. Of special interest is the fact that in an isotropic selection proﬁle (see above), the selection interface will disfavor any deviation from the existing adaptive state, excepting when there is advance toward the major (structural ) attractor (see Chapters 1 and 7). The adaptive response may thus acquire an iterative form of directional orientation with respect to this conﬁguration of selection proﬁle.

The Phenon as Locus of the Selection Interface It should by now be clear that the whole organism cannot be presumed to manifest an holistic selection interface, and that only speciﬁc phenotype struc-

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ture units expressing active allelomorphism can be presumed to exhibit selectional activity at any point in time. This does not mean, of course, that structural units controlled by ‘‘ﬁxed’’ genes and thus lacking a selection interface are ‘‘nonadaptive,’’ but merely implies that they present only an adaptation interface. The selection interface is alone controllant to changes in gene frequency, and thus also to the dynamics of the adaptive response as manifested both in dynamic equilibrium and in evolutionary change. The selection interface may thus lie in a different unit of structure in different individuals of a population, and it may continually change position, so that the gene pool tends to become the focus of selectional activity over n generations (n being some function of the dynamic structure of the external environment). These conclusions clearly reiterate out revised deﬁnition of selection versus adaptation, as well as ratifying the status of the gene pool as the epicenter of the adaptive state (see Chapter 1). The phenon is any structural locus in the phenotype manifesting genetic allelomorphism (or possessing adaptive potential to do so), and having an active selection interface within the time frame of a given generation—whether via one major gene or n additive minor genes. A phenon may be manifested in substructural variation, and when structural, it may concern one or more subordinate parts of some larger structure unit (see Chapter 7). The selection interface refers, not merely to the interface of one phenon at individual level at time t, but to the sum of all phenons presenting an active interface in the gene pool at time t. A ‘‘super-selection interface’’ therefore also lies in the gene pool as an holistic structure deﬁned over n generations and over geographic space, expressed in both temporal and spatial dimensions. And as we shall see at a later point, there is also an interspeciﬁc selection interface operating above phenon level (see Chapter 7). Different phenons may contribute interactively to ﬁtness in either of two ways: multiplicative or additive. In the former situation, two genotypes may affect different temporal phases of development, whereas in the latter, the same component may receive separate increments to ﬁtness from two or more discrete genes. It is of special interest that, where additive genes affect the same phenon, a potential exists for linear, iterative modulation in the adaptive response. Exogenous and Endogenous Components of the Selection Interface Clearly, selection may affect the adaptive state whenever a discontinuity occurs in the adaptive ensemble. This can happen at various developmental loci, thus deﬁning the extrinsic and endogenous selection interface—the extrinsic lying in the behavior–niche function cycle in the interaction between organism and external environment, and the endogenous lying in the development epicycle (or in metabolism). The extrinsic selection interface is perhaps explicit in the deﬁnition of selection itself. The endogenous selection interface is more difﬁcult to understand. For example, a more parsimonious developmental event may be selected over a less parsimonious one; however, the adaptation interface for this change probably lies elsewhere in time and space (probably in the postdevelopmental zone), and it may be widely disseminated as an energetic economy which holds the capacity to facilitate efﬁciency increase in several other mechanisms. The

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extrinsic selection interface can therefore often be traced to a speciﬁc phenon recognizable as an allelomorphic effect in the visible phenotype (as with melanism), but the endogenous may be effectively undetectable in this respect. Three themes will be developed from the above argument at a later stage: 1. The extrinsic component of the selection interface must have some vital relationship with evolutionary rate (Chapter 18). 2. The endogenous selection interface is of particular signiﬁcance with respect to evolutionary forces acting to favor cladogenetic activity (Chapter 6). 3. The endogenous selection interface is also of signiﬁcance in understanding the directional component of the isotropic selection vector (see below) as this affects the evolution of developmental systems (and this may also invoke an important evolutionary corollary with regard to evolutionary rate).

Properties of the Isotropic Selection Interface Having examined the broad anatomy of the selection interface via selection proﬁle, it would now seem pertinent to go on to consider the most evolutionarily signiﬁcant state in this scenario more closely, namely, that of the complex isotropic state (which may well be the basis for most selectional regimes of a long-term ‘‘static’’ kind). Given the existence of multiple functionality, the isotropic selection vector can most easily be understood in terms of a simpliﬁed model which describes a pair of antagonistic selectional forces acting on a single phenotype trait (and it is in this sense that we must apply the term complex to the selection interface). If the selection interface between adaptive capacity and mortality can be described by a vector, then the phenon is its ‘‘point of action.’’ Given capacity for bidirectional change in the phenon, the selection vector is (in a general model, and for any complex isotropic selection interface) the resultant of two component vectors acting with respect to different possible expressions of a given trait. This can be most easily illustrated in an artiﬁcial example, adopting ‘‘X-ness’’ and ‘‘Y-ness’’ in the analogy of a simple orthogonal model. In the idealized scheme, shown in Fig. 16, the resultant vector R of vectors X and Y is given by R ⫽ (X2 ⫹ Y2 ) and the directional component, by tan ␪; ⫽ Y/X. ‘‘X-ness’’ and ‘‘Y-ness’’ are clearly an abstraction only in the above model. However, this artiﬁcial model is nevertheless helpful (a) in order to take qualitative differentials into account and (b) in order to allow clear comparisons to be made between isotropic and anisotopic selection interface structures. For example, the differential between antagonistic selectional forces is often qualitative in the anisotopic selection interface (see Chapter 6), but may be quantitative or colinear in the isotropic case. Most signiﬁcantly, any tendency for movement in the above system (change in X or in Y ) is opposed to a greater or lesser degree by an antagonistic force

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FIGURE 16 Simpliﬁed model of the complex isotropic selection interface. Axes X and Y represent directionally antagonistic vectors expressing potential for directional change in the adaptive response (quantitative aspect reﬂected in X, Y).

favoring change in the opposite direction, the fully balanced state for which will be some expression of ‘‘XY’’*: An interesting and widely investigated case study exists in the shell form of Gryphaea oysters, in which the selective advantage of increased shell coiling was apparently balanced by progressive restrictions on valve opening caused by further extrapolation of this trend. It is believed that increased coiling probably had the advantage of raising the body above the surface of sediment in more unstable substrates, while at the same time leading to difﬁculty in terms of restriction of the feeding mechanism. Evidently, a point is reached at which continued extrapolation of the coiling trend leads to vulnerability (in fact, later forms suffered extinction in many lineages, owing to changes in the external environment; see Chapter 20). The above principle applies well beyond the domain of the biophysical dimension for a single isotropic vector, extending also to encompass the question of mutual dynamic balance and optimality with respect to different parameters of adaptive capacity: An example is seen in the Williams demographic theory of optimum reproduction states (see Williams, 1966). Reproductive effort results in loss of immediate adaptive capacity, but on balance, the net advantage must be greater probability of survival of the lineage. Conse* The isotropic vector does not have to be bipartite. However, this is the most useful ‘‘general’’ model.

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quently, increase in reproductive activity cannot expand beyond that point at which net survivorship capacity begins to be reduced. Another nonstructural example lies in infraspeciﬁc aggression, which will tend to be optimized in ritualistic behavior. Similarly, increase in inclusive ﬁtness cannot exceed a point of negative feedback with respect to inbreeding depression! (See Chapter 1.) The intensity of selection acting on the isotropic selection interface must clearly also relate to permissible frequency distribution in variance of a given phenotype parameter, as a function of contribution to overall ﬁtness. Where this value is high, variance will be low, and vice versa (so that positive variance of low contribution to ﬁtness will tend to be manifested in continuous variation on an intraspeciﬁc basis, and that expressing a very high selective advantage will conversely be reﬂected in tight constrainment of form). The isotropic system may thus tend often to invoke monomorphism—although if the trait in question has a low contribution to ﬁtness, it may alternatively manifest continuous variation about a mean approximating to the XY vector state. We have now extended our view beyond the ﬁtness of one trait relative to another at the same locus, to consideration of W of that locus relative to the entire genotype. It is clearly only when the former tends to constitute a very large proportion of overall ﬁtness that we get a single ‘‘stasigenetic’’ state; otherwise, we witness an expansion of continuous variation. The basis for the complex isotropic selection vector thus lies with the existence of an isotropic selection interface with two antagonistic selectional attractors, as a reﬂection of the axiom of multiple functionality (see Chapters 1 and 7). The ideal adaptive response to the isotropic selection vector must often lie somewhere between two attractors, with bias toward that with the greatest ﬁtness enhancing state—the adaptive response thus being expressed in a single phenotype state. The isotropic selection vector is also an essential tool for an understanding of the manner in which linear directionality is expressed in the adaptive response, as with anagenesis. Principal Components of the Isotropic Selection Interface in the Adaptive Ensemble A general model for the architecture of the complex isotropic selection vector can clearly incorporate dimensions in each functional mechanism within the adaptive ensemble, and the selection interface is thus a fundamentally bipartite structure in terms of principal components in the following: • Logistic dimension: the selection interface as it concerns intrinsic rate of increase in the population • Structural dimension: structural advance toward an adaptive paradigm state as an optimum with respect to n component vectors • Behavioral dimension: for example, as this concerns social interactions within the gene pool in the kinship domain Each dimension within the isotropic selection interface may thus express a fundamentally bipartite structure with antagonistic components acting in two

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FIGURE 17 Complex isotropic selection interface in three domains of the adaptive ensemble.

principal directions. In Fig. 17, the negative corollary of either ‘‘too high’’ or ‘‘too low’’ r in the logistic component of adaptive capacity is a tendency to ‘‘crash’’ N. Consequently the ideal value for r lies between two extremes. Similarly, in the behavioral dimension, we encounter a negative corollary for iterated kin adaptation with inbreeding depression, balanced with that of ‘‘overoutbreeding’’ in loss of inclusive ﬁtness. Again, the resultant constitutes a compromise solution. The above system reﬂects the balance X : Y for certain principal components of the structural attractor, which seem intrinsically likely to express a complex isotropic selection proﬁle. In order that net change may occur in this system, sexual selection, for example, might act to bypass inbreeding depression—if certain visual stimuli also favor ﬁtness, irrespective of kinship.* As stated at an earlier point (p. 57), the signiﬁcance of the isotropic selection interface lies in its relationship with adaptive potential, which propensity must lie in innate properties of the genome to build an adaptive response to some stable parameter of the external environment (see Chapter 7).

SELECTION IN EQUATIONS OF THE ADAPTIVE SYSTEM In Chapter 1, the rudiments of the structural component of adaptation in the Lotka–Volterra equations for competing populations were identiﬁed. How is this equation set related to conventional measures of selection? Clearly, there are two different answers to this question, in consideration of the fundamental dichotomy between density dependent and density independent mortality as these affect selection proﬁle. Only the former category will be affected by population size; however, the importance of density dependent selectional * According to Maynard Smith (1998), many courtship routines do in fact tend to test sensory and locomotor skills, which would in turn probably serve as good indicators of general ﬁtness. The fact that the Y chromosome of males is reduced in size also conﬁrms that factors such as success in mating are not allowed to outweigh general ﬁtness (see Rice, 1999, who investigated the effects on ﬁtness of artiﬁcially enlarged Y chromosomes in Drosophila).

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factors for much evolutionary activity renders it necessary that this relationship be explored further: According to Maynard Smith (1998), density dependent selectional factors may predominate in the perpetuation of genetic variability (this broad statement is not of course intended to exclude such density independent factors as temperature sensitivity differentials in the genotype in the face of a variable microclimate, and so on).

Fitness in the Equations of the Adaptive System The ﬁtness of a genotype, W, is conventionally deﬁned as being given by its reproductive capacity, relative to that of a competitor: For instance, genotype a produces 100 offspring in a given environment, and genotype b, only 90: w for the latter is then 0.9 (taking the most successful genotype as w ⫽ 1.0). The above measure of ﬁtness now requires closer examination, especially in the way it relates to the Lotka–Volterra equations. It seems intuitively obvious that W must be an element embedded in the Lotka–Volterra equations, in terms of density dependent interactions. Correct location of W and s in the equation set of the adaptive system would thus permit integration of the Lotka– Volterra equations with those of population genetics, the latter combining into a larger equation set. Some selectional differentials, of course, clearly result in W values based on factors that are not linked in any way to population density. However, for the density dependent component, there must be an intersect between genetic equations and those of population dynamics—in which latter context, W must be a variable rather than a constant. To investigate the relationship between the Lotka–Volterra equations and those of population genetics more closely, it is useful ﬁrstly to simplify the former. Here, K will be taken to be fully coincident for N1, N2 populations.* In this analysis, interaction can be considered to occur in three stages, during which: 1. The 움 factors in the Lotka–Volterra equations describe the effect of competition affecting changing proportions of N1 and N2 populations in the extrinsic selection interface. 2. The factor rn also manifests components expressed in both the extrinsic and endogenous selection interface (namely, via inputs to rn from fecundity and developmental viability, respectively).† 3. Assuming that fecundity is regarded as being the same for N1 as N2, the Hardy–Weinberg equation (following the effect of competition) * This also anticipates the addition of a qualitatively different ‘‘unshared K’’ factor that will be explored when we later come to examine the anisotopic selection interface. † Fisher’s assertion that the absolute ﬁtness of a genotype lies in r is clearly incorrect. However, this statement is true for a monomorphic or ‘‘static–polymorphic’’ gene pool in a state of stable equilibrium with its natural environment!

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determines genotype frequencies of progeny, and viability then affects the distribution of genotype frequencies in the next generation.

FIGURE 18 Links between equations of population and genetical dynamics. (A–)1–4 ⫽ frequencies of A– at four stages, in a system in which simple dominance is manifested. Note that in the above scenario, selection can be density dependent or independent at extrinsic (premating stage), but only density independent at the endogenous (postmating) selection interface.

The above scheme essentially inserts the Hardy–Weinberg equation into the Lotka–Volterra one, indicating that W (and therefore also s) is a function of r and 움, and also of initial conditions of N and K. W is thus not a simple constant, but a complex variable (which may, however, behave as a constant under certain stable conditions). With different initial conditions, W as an attractor may tend to converge on some particular value as both populations reach equilibrium level. More usefully, W is described directly by the above equation for all values of t, when we adopt the standard of identical initial conditions for N1 and N2 and when we exclude any nonheritable differentials. In this equation set, ﬁtness (W ) is thus more correctly described by;

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W⫽

兰tt⫹1 (dN1/dt) 兰tt⫹1 (dN2/dt)

It is highly signiﬁcant that this link with the Lotka–Volterra equations identiﬁes W as a variable, since differential survivorship based on a competitive element must be partly a function of logistic activity arising from the effect of the limiting resource K on population size N. W will consequently increase as population size ascends toward equilibrium, attaining the status of an apparent constant at the latter point only. Where W is a dynamic variable, the coefﬁcient of selection s must also be dynamic, and neither can logically be determined as a constant when a density dependent element is present. While this may make little or no difference to parameters of mere recurrent or polymorphic variation within the domain of changing gene frequencies, it can nevertheless have considerable impact on the question of longer term evolutionary rates in angenesis (see Chapter 18). From the above analysis then, the equations of population genetics become part of the equation set of the adaptive system, extending the largely logistic role of the Verhulst equation to link with equations expressing dynamics of the structural component of the adaptive response.

MAIN POINTS FROM CHAPTER 4 1. Selection can only be deﬁned in the context of a heritable differential survivorship between different genotypes. 2. The apparent properties of selection have to be understood in the context of the whole selection interface in the adaptive system, rather than being viewed as being intrinsic propensities of the selective agency itself. 3. Intensity, directionality, and degree of density dependence are the most important properties of the selection interface. 4. The selection interface lies in the link between adaptive capacity and niche proﬁle, and different conﬁgurations of selection proﬁle (combining temporal and spatial elements) can be linked to classical ‘‘selection modes.’’ Isotropic and anisotropic selection interface structures are of special interest, particularly in view of the essential dichotomy existing between adaptive equilibrium and evolution. 5. ‘‘Points of action’’ in the selection interface are located in particular phenon units, rather than in the whole organism. 6. The selection interface has both extrinsic and endogenous components, the latter being of fundamental importance to an understanding of the developmental perspective in evolution. 7. The complex isotropic selection vector reﬂects balance between antagonistic selectional forces linked to multiple functionality, and this conﬁguration of the selection proﬁle is of fundamental importance for an understanding of directionality in anagenesis. 8. The complex isotropic selection vector has dimensions in all components of the function ensemble (behavior, structure, metabolism, logistics). Consequently, there are no ‘‘selﬁsh’’ domains that can bypass a state of negative feedback in the context of iterated evolutionary change.

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9. Because ﬁtness is frequently a function of population density, the vital density dependent component of the selection interface can be modeled in terms of a link between the Lotka–Volterra equations and those of population genetics. W and s are, in this context, variables rather than constants. 10. The linked equations of population genetics and of the Lotka–Volterra model must form a key component of the equation set of the adaptive system.

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ADAPTIVE EQUILIBRIUM

A stark dichotomy exists between the population and developmental perspectives in genetics, as perhaps crystallized by Gilbert (1997), in criticism of an earlier pronouncement of Dobzhansky’s: ‘‘A major assumption of the population genetics approach to evolution was that the search for homologous genes is quite futile except in very close relatives. . . . Molecular biology and developmental genetics have shown this assumption to be invalid.’’ The Mendelian perspective, having been largely based on the behavior of substructural genes manifesting ongoing allelomorphism in populations, is clearly fundamentally different from that of the developmental approach, and a realistic understanding of evolutionary events (as distinct from recurrent variation) clearly depends on a ﬁrm understanding of the latter. It is from this standpoint that Stebbins (1988) rejected the view that ‘‘evolution consists of alterations in gene frequencies within and between populations.’’ It must be underlined at this point, that many supposedly ‘‘evolutionary’’ perspectives in population genetics have in reality tended to concern dynamic equilibrium and not actual evolutionary change. There are fundamental differences in the way adaptive systems express adaptive equilibrium as against true evolutionary behavior, and this has clearly been reﬂected in quite different points of interest in population, as against developmental genetics. It is indeed at this point that we encounter a ‘‘split’’ between special theories of evolution, centered on that particular aspect of adaptive systems theory relating to the dichotomy between adaptive capacity and adaptive potential. In resolving this

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dilemma, we need to pay closer attention to the sharp dichotomy existing between the ambient scenario of ﬂuctuating frequencies of substructural allelic states and that concerning the complex evolutionary pathway to multiple gene ﬁxation in the morphogenetic domain. Similarly, we must also pay more attention to the role of selectively positive (and less to the role of neutral) mutation in the adaptive equilibrium model itself. Above all else, we must not give in to the temptation to describe realization of preexisting adaptive capacity as ‘‘evolution,’’ but rather we should pursue a deeper understanding of other mechanisms which manifest greater relevance to the analysis of the longer term evolutionary behavior of adaptive systems. Finally, we must of course, at the same time, take positive steps toward retrieving what is useful from population genetics, and not (as some workers have done) discard the notion that true evolutionary change must pass through transient states that are broadly analogous to frequency ﬂuctuations observed in adaptive equilibrium. Indeed, the allelomorphic structure of the gene pool is the same for all but a few unchangeable domains controlled exclusively by maternal inheritance. In the present chapter, we shall continue to examine the phenomenon of adaptive capacity in the context of a facultative epicycle expressed in adaptive equilibrium, expanding the argument that this mode of activity probably constitutes the major component of the ambient adaptive response in the gene pool. In this context, the Mendelian model serves perfectly well in the analysis of most selectional activity actually observed in natural populations.

ADAPTIVE EQUILIBRIUM AND ALLOMORPHISM IN THE ADAPTIVE RESPONSE It is clear that the adaptive response contains two different modes of dynamic behavior, the most dramatic of these being evolution itself, the other being manifested only in ﬂuctuating gene frequencies within a preexisting repertoire of recombinable allelomorphic genes comprising the genetic component of the adaptive capacity of a gene pool, as this interdigitates with a dynamic selection interface. The latter is the state of adaptive equilibrium referred to above, and this is the fundamental behavior expressed by adaptive systems under the guise of apparent ‘‘ambient stasis’’ (see Chapters 1 and 19): That the viability of some mutants is dependent on environmental factors has been known since the work of Timofeef-Ressovsky (1934), who demonstrated that the Drosophila eversae mutant is inferior to the wild type at 15–16⬚C and 28–30⬚C, but superior at 24–25⬚C.

Allomorphism Organism and environment can be said to exist in a state of mutual adaptive equilibrium when dynamism in the adaptive niche is met by complementary dynamism in the adaptive response through realization of adaptive capacity. This is clearly not a function of mere stochastic changes in population structure, the active as against ‘‘passive’’ logistic element in this implicating the presence of selectional activity.

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In analyzing adaptive equilibrium, it will be convenient to begin by looking at that dynamic selection interface in which selection ﬂuctuates purely on a temporal plane. This approach allows us to analyze adaptive equilibrium in an elementary manner, before going on to look at more complex anisotropic systems which concern dynamism additionally involving the spatial dimension. The simplest scenario through which to understand the inﬂuence of selection proﬁle on adaptive equilibrium is when some genotype in a gene pool has a variable contribution to ﬁtness, as a function of time: Time Polarity of selection

t1 ⫹

t2 ⫺

t3 ⫹

tj ⫺

In the above scenario, a gene allelomorph is positively or negatively selected according to temporal periodicity in the selection interface. This situation clearly corresponds to a simple form of dynamic adaptive equilibrium in the adaptive response: Dempster (1955), also Haldane and Jayakar (1963a,b), found stable polymorphism possible with regular cyclic variation in which an allele is positively selected in alternate generations. Perhaps more generally, there will be a more complex anisotropic relationship between adaptive capacity and selection proﬁle, where genetic variation is expressed in relation to both spatial and temporal dimensions*: Biston betularia f. carbonaria (the melanistic form of the peppered moth) is positively selected in some habitats and within certain time frames, but negatively selected at other places and times (see Kettlewell, 1973), and thus links to an anisotropic selection interface. The same phenomenon has been documented for Cepaea snails. Huxley and Mayr both thought that variation in Cepaea could only be random. However, cryptic coloration is now known to be selected—although ‘‘least conspicuous color’’ varies between habitats—and selection on the basis of temperature regulation is also differentially expressed on a spatial plane. Both positive and negative frequency dependent selection may be involved in this ( Jones et al., 1977). Developing the theme of the inﬂuence of selection proﬁle on patterns of phenotypic variation a little further (see table in Chapter 4), we can predict the adaptive response for each conﬁguration of the selection interface. In this approach, we can identify allomorphism as that selectionally determined component of adaptive equilibrium which encompasses all leading effect genetic and phenoplastic variation (Fig. 19). In general, adaptive equilibrium describes the ambient adaptive response in allomorphism to any manifestation of a temporally and/or spatially dynamic selection proﬁle. In this context, variation expressed purely as a function of the temporal element may be referred to as chronomorphism, so that the generic term allomorphism thus encompasses * Models of a dynamic environment (such as those proposed by Dempster, 1955, and Levene, 1953) have sometimes led to conﬂicting views on the effect of ‘‘coarse grained environments’’ on supposed evolutionary change (see Maynard Smith, 1998). It is essential to see that the spatial ‘‘patches’’ in such environments must not be seen as ﬁxed points, but are themselves dynamic.

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FIGURE 19 Allomorphism and conﬁguration of the selection proﬁle.

both temporal and spatial (‘‘stable’’) polymorphism. Adaptive equilibrium is thus explicitly described by the iterative trend in allomorphism over n generations: Dobzhansky (1970) stated that genetic diversity is maintained primarily not by new mutants, but by the advantage of heterozygosis. It is thus ‘‘kept up by natural selection, and also by environmental ﬂuctuations in space and time that alter the signs and magnitudes of selective advantages and disadvantages.’’ Dobzhansky also held that there are two major kinds of genetic variability in natural populations: that maintained by mutation and controlled by ‘‘normalising selection,’’ and that maintained by ‘‘balancing selection,’’ the latter being stable polymorphism which cannot be explained by recurrent mutation alone. In contrast to the situation seen with allomorphism, many deleterious mutations tend to be maintained in populations because of the low level of selection acting against them, combined with recurrent mutation (as a consequence of which, allomorphism is clearly not synonymous with allelomorphism!). Dobzhansky’s view therefore encompasses adaptive capacity in ambient adaptive equilibrium for many, but not all, ﬂuctuating or recurrent allelomorphs. Only a certain proportion of observed genetic variation is actively poly- or chronomorphic, as is clearly demonstrated by the proven existence of very many near neutral allelomorphs in natural populations. The generic term allomorphism therefore speciﬁcally excludes variation perpetuated by purely stochastic processes in the behavior of adaptive systems.

Temporal Domains in Adaptive Equilibrium In consideration of the overwhelming importance of time frame in determination of patterns of evolutionary change, adaptive equilibrium may now be usefully analyzed as a particular function of temporal wavelength and amplitude in the selection proﬁle. It will be seen that different modes of expression are largely controlled by conditions in these variables.

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The relationship between mode of periodicity in the selection interface and adaptive response identiﬁes three fundamental domains of adaptive equilibrium, and it should be noted that any ‘‘general reference time frame’’ constitutes an artifact that is exclusively relevant to speciﬁc structure units and gene pools. 1. Primary Adaptive Equilibrium In primary adaptive equilibrium (period ⬍ t ⫽ periodicity of environmental parameters within the life span of the individual), we encounter variation corresponding to environmentally controlled variation of the phenotype in the adaptive response, as generally met by metabolic and behavioral adjustment within adaptive capacity. Within time ⬍t, adaptive systems must have the adaptive capacity to tolerate certain levels of misalignment in the external environment, by adjustment not only in the logistic response, but also in phenotype form. This adjustment is clearly beyond the domain of allelomorphism so far as this particular time frame is concerned, but it can nevertheless be realized in terms of a dynamic epigenetic response to externally generated, nongenetic determinant signals (phenotype plasticity). This situation will be examined in greater detail when we go on to investigate extrinsic determination factors affecting development (Chapter 11): The monocotyledon Plantago lanceolata is well known for its ability to display gross phenotypic variation according to habitat, producing short, broad leaves in heavily grazed or trampled ground, and elongate, narrow leaves in ‘‘rough’’ conditions. While some component of this is ‘‘microgenetic,’’ much of it is phenoplasticity. ‘‘Phenoplasticity’’ is thus the mechanism for adjustment within a narrow temporal frame, although primary adaptive equilibrium is also expressed in the plastic relationship between behavior and the external environment: This is reﬂected in learning, when new neurons are created in response to experience; Gilbert (1997) refers to learning as ‘‘an environmentally adaptive component of the nervous system.’’ 2. Secondary Adaptive Equilibrium In secondary adaptive equilibrium, the existing genotypic repertoire of the gene pool is capable of a dynamic response to changing selection regimes in the external environment. Periodicity in the range ⬎t 씮 T thus constitutes the fundamental substrate for genetic allomorphism in the adaptive response as manifested in frequency ﬂuctuations of allelomorphic genes, and this clearly constitutes the main focus for the genetic component of ‘‘adaptive capacity in dynamic equilibrium’’: The polymorphic variation in Cepaea, Biston, and Maniola quite clearly belongs to this category, and similar examples have been very widely documented in population genetics. Dobzhansky (1970) observed that the ﬁtness of some Drosophila mutants can be greater or lesser than the wild type, according to varying external environments. Dobzhansky and Pavlovsky (1958) also found that chromosomal inver-

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sion variants in Drosophila apparently allow temporary ‘‘pseudolinkage’’ between genes adapted to transient environmental factors. Genotype speciﬁc habitat selection must also greatly broaden the conditions for allomorphism when pleiotropism is involved, or when the relevant alleles are closely associated on the chromosome (Hedrick, 1989): Experimental evidence from de Souza et al. (1970) has demonstrated habitat preferences in Drosophila larvae that are linked to polymorphism. Secondary adaptive equilibrium is therefore expressed in ﬂuctuating gene frequencies within the domain of the existing gene pool, and this may encompass behavioral as well as structural traits. 3. Tertiary Adaptive Equilibrium In tertiary adaptive equilibrium, adaptive capacity for recurrence of transiently ‘‘lost’’ genotypes with positive selection regimes of longer periodicity in the range ⬎T 씮 ⬍Tc (periodicity greater than ﬁxation time, less than speciation time) is maintained via recurrent mutation. This criterion, in fact, forms the functional boundary of adaptive capacity: Data on genetic variation in beak size in two species of Darwin’s ﬁnches in the Galapagos Islands (Geospiza magnirostris and G. fortis) show directional change in the adaptive response in terms of unusual changes in the wet–dry season cycle affecting seed production in the birds’ food resource, with return to normal phenotype distributions on reversal of climatic conditions at a later stage. This may be presumed to involve parameters of adaptive capacity implicating recurrent, rather than novel mutation. Adaptive capacity for tertiary adaptive equilibrium thus clearly resides in recurrent mutation, and it is interesting to consider the view of Lande (1975) that quantitative variation in general is maintained through recurrent mutation, rather than selection. This is a somewhat extreme claim, considering the capacity of a periodic selection proﬁle to maintain allomorphism. However, Lande’s hypothesis does serve to indicate the level to which recurrence may contribute to the domain of minor additive (that is, nonallomorphic) variation. The existence of mutator genes which apparently operate in a site speciﬁc manner (Cairns, 1988) strongly supports the view that adaptive capacity is partly linked to recurrent mutation. In summary, Primary adaptive equilibrium ⫽ phenoplasticity and behavioral/ metabolic adjustment Secondary adaptive equilibrium ⫽ ambient genetic allomorphism Tertiary adaptive equilibrium ⫽ recurrent genetic allomorphism Adaptive equilibrium can thus be deﬁned in general as comprising ongoing and recurrent genetic allomorphism plus ‘‘phenoplasticity.’’ It excludes the

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passive logistic response, along with any stochastic element impinging on the system. Its relationship to the adaptive response in general is shown in Fig. 20.

FIGURE 20 Adaptive equilibrium in relation to the total adaptive response.

At a later stage, we shall also consider that a larger domain beyond that of tertiary adaptive equilibrium accounts for much disjunct periodicity in the adaptation interface, much of which has frequently been interpreted in terms of ‘‘linear evolution,’’ and which links to realization of adaptive potential (as distinct from adaptive capacity).

Variation Where does the familiar term variation ﬁt in with our concept of a hierarchy of levels of adaptive equilibrium? Variation lies in the range of phenotypes complementary to the allelomorphic complement of a given gene pool, as expressed by the state of adaptive equilibrium existing between gene pool and environment within any chosen temporospatial reference frame, but it also includes allelomorphic states perpetuated through action of a heterogeny of stochastic factors. ‘‘Variation’’ thus refers to true allomorphism plus the inﬂuence of randomization factors (as well as to rare and frequently transient changes of the evolutionary kind). More traditionally, ‘‘variation’’ has been used in the sense of referring to any randomly chosen group of phenotypes, rather than being deﬁned exclusively in the context of unbiased population sampling. It is thus a heterogeneous descriptive term, with little value in evolutionary analysis. It is important to realize at this stage that not all apparent variation is selectional, since it can arise through stochastic factors alone. It is also signiﬁcant that the special theory sometimes termed ‘‘neo-Darwinism’’ and synthesized by Haldane, Fisher, and Wright in the early part of the twentieth century

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was largely based on observations concerning either nonadaptive or allelomorphic variation perpetuated in a state of adaptive equilibrium. This component of the general theory will become a major topic of discussion in Chapter 13.

STRUCTURAL AND LOGISTIC STRATEGIES OF ADAPTIVE CAPACITY The concept of the ambient selection interface as a fundamentally tripartite and anisotropic structure interacting with the allelomorphic gene pool in the context of adaptive capacity is essential to an understanding of the nature of the adaptive response. Having identiﬁed adaptive equilibrium in both logistic and structural components of the adaptive response, it is now necessary to consider how the architecture of the anisotropic selection interface provides a suitable substrate for maintenance of the adaptive state, bearing in mind the probability that much variance–selection interactivity is likely to center around a selection interface of this kind. It has been useful up until now to consider modulations of logistic and structure capacities as being separate logistic and structural components of the adaptive response. However, these mechanisms clearly play linked roles in adaptation, forming an integrated strategy for maintenance of the adaptive state in the face of a changing external environment. It is now necessary to look more closely at the role played by the logistic component of adaptive capacity in adaptive equilibrium.

Logistic Adaptation and Adaptive Equilibrium How does the strategy of adaptive capacity compensate for the highly dynamic behavior of anisotropic niche proﬁle in view of the inﬂuence of stochastic factors in the adaptive system? With reference to these questions, it is instructive to analyze the adaptive state in terms of the logistic component of the adaptive response. Given that a gene pool may possess some structural deﬁciency in one or more components of the adaptive state (for example, a low developmental viability) or else face predation and interspeciﬁc competition against which there is no defense, it appears axiomatic that one simple means of balancing such a deﬁciency would simply be to increase fecundity. The balancing effect of increasing the intrinsic rate of increase thus explains the usually large discrepancy between fecundity and ‘‘expected rate of increase.’’ Logistic adjustment in r therefore must perform a fundamental function in balancing against deﬁciency in the adaptive state, in terms of counteracting negative viability and also counteracting stochastic mortality factors: Dobzhansky (1970) expressed the view that ‘‘differential fecundity is in principle, as powerful a selective agent as differential survival mortality.’’* * In retrospect, it would now be better to use the term ‘‘substrate’’ rather than ‘‘selective agent’’ in this context.

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The balancing function of logistic adjustment can be better understood by analyzing the adaptive state A by designating the fundamental adaptive state as Af ⫽ survivorship capacity of a gene pool in the absence of any logistic adjustment with respect to ambient mortality factors. Af is then a subset of A (the probability of survival), exclusive of the balancing effect of increased fecundity to offset stochastic mortality factors, the logistic contribution being encompassed by the real adaptive state Ar. Thus, if Af ⫽ survivorship in the absence of logistic adjustment, then fecundity will ideally modulate to 1/Af, which latter is linked to the logistic attractor for r in adaptive systems (since if r is too large, populations will tend to ‘‘crash’’ through ‘‘overshoot,’’ and if too small, N may also converge on zero). The structural and logistic components of the real adaptive state are therefore additive in their interactive effect. The differential between real and fundamental adaptive states illustrates how A always carries some element of reciprocity, Af being inadequate for survivorship in any other than an artiﬁcial environment, not only in terms of abiotic inputs to the adaptive system, but also in relation to the minor adaptive niche. Owing to the discrepancy between fundamental and real adaptive states, some varying fraction of fecundity must relate to compensation for a heterogeny of deﬁciency factors, logistic adjustment balancing against potentially negative effects arising from stochasticity manifested in the dynamics of the external environment, as well as in endogenous nonviability factors. ‘‘r-selected gene pools’’ are thus those that tend toward the domain of logistic adaptation, their adaptive state being strongly inﬂuenced by the logistic component of the adaptive response. In contrast, ‘‘K-selected’’ gene pools tend toward competition on the basis of heritable differentials in the structural domain, thus manifesting an adaptive state that is less reliant on logistic balance (see also Chapter 6). Clearly, the size of the differential between fundamental and real adaptive states must have a crucial bearing on the evolution of adaptive systems: The relationship between fecundity and adaptive capacity is exempliﬁed by such examples as wind-pollinated plants, as also by certain root feeding moths (Hepialidae) which scatter immense numbers of eggs at random—and of course in the very high fecundity values manifested in a great many marine organisms (especially invertebrate species). All of these examples clearly link to the very high levels of stochastic mortality found in certain types of environments.

Structural and Logistic Components of Adaptive Capacity in the Fecundity Offset Strategy What is the actual relationship between the real adaptive state and fecundity? To answer this question, we must continue to accept that a great many sexually reproducing organisms live in unstable environments. In a perfect adaptive system, ␾ (fecundity) would be equal to 2 in order to replace the parent generation. However, assuming that sexual reproduction constitutes an adaptive response to environmental imperfection that can never be completely bypassed, we shall call this optimum replacement ﬁgure ␳, for a more realistic system. Therefore, as the fundamental adaptive state Af 씮 1.0, so ␾ 씮 ␳, and when Af ⬍ 1.0, fecundity must increase.

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A useful index expressing the degree to which mortality is in fact having to be logistically (or ‘‘structurologistically’’) compensated may then be ␳ /␾. In reality, ␳ /␾ is probably generally less than 1.0 (perhaps often very low). Given that fecundity may normally be increased in order to compensate for deﬁciency in structural adaptation in the face of environmental instability (␾ ⬎ ␳), it is now necessary to examine this ‘‘offset’’ ﬁgure in more detail. It can in fact be shown that the fecundity offset value is really a bipartite structure that is not in fact exclusively linked to the logistic component of adaptation, notwithstanding the fact that ‘‘structural overshoot’’ is perhaps less apparent than logistic. The greater the expression of stochastic–dynamic behavior in the selection proﬁle, the more the structural component of the adaptive response will tend to constitute an ‘‘approximate ﬁt’’ only, and the more this will tend to be reﬂected in ﬂuctuating gene frequencies in the domain of adaptive capacity. This fact therefore identiﬁes the existence of a composite offset complement in fecundity where, speciﬁcally in the adaptive equilibrium model, we have also to compensate for loss of superﬂuous ‘‘bad ﬁt’’ genotypes in each generation. Some increase in r is thus needed in order to compensate for loss of genotypes that are sometimes positively selected and sometimes not—this being quite different from the situation where, for example, some element of the fecundity offset simply balances against developmental nonviability that is not subject to any ﬂuctuation with respect to selection. Thus, it may often be a useful strategy to generate a larger population, not only in terms of mortality factors against which no defense exists other than ‘‘safety in numbers,’’ but also in terms of generation of a range of ‘‘potentially useful’’ genotypes. This element should clearly be interpreted as a property of the gene pool which constitutes an emergent corollary of genic selection within the boundary of the larger gene pool (following Williams, 1966). One component of the composite fecundity offset strategy in which fecundity is increased in order to offset stochastic mortality factors is therefore concerned with a dynamic selection interface acting in terms of the structural component of the adaptive ensemble, while another counteracts the effects of mortality factors against which there is no defense other than the logistic. There must also be a varying degree of interplay between structural and logistic components of the adaptive response with respect to the anisotropic selection interface, and this will depend on the nature of stochastic activity present in the adaptive system in question. Adaptive equilibrium is thus expressed by the changing pattern of adaptation described by the adaptive response to selection proﬁle over a given time course, not only in terms of logistic, but also of structural variation within the domain of adaptive capacity. Selective and Nonselective Offsets of Fecundity Following the above analysis, the value of ␾ can be regarded as holding numerical offsets against a heterogeny of mortality factors, including that concerned with maximizing the adaptive strategy of the range of genotypes available within the adaptive capacity interacting with an anisotropic selection proﬁle, and another balancing ‘‘nonadaptable mortality factors against which

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no such structural response exists.’’ As already stated, there must also be some degree of interaction between these two offsets. That fraction of the logistic component of adaptive capacity that is structured to balance against ‘‘nonadaptable’’ (i.e., stochastic) mortality factors is the nonselective offset of fecundity. Similarly, that numerical offset balancing stochastic mortality factors affecting the expression of the structural component of adaptive capacity with respect to genetic allelomorphism in adaptive equilibrium constitutes the selective offset. The logistic component of adaptive capacity is thus expressed in selective and nonselective offsets of fecundity, these being linked, respectively, to ﬂuctuating deterministic and stochastic environmental inﬂuences in the adaptive system which jointly reﬂect the differential between fundamental and real adaptive states. The nonselective offset even acts to counteract intrinsic factors arising from the genome itself (for example, with respect to the mutational load incurred through accumulated deleterious mutations). In particular, the selective offset of fecundity is that adjustment to fecundity such that variation in the external environment can be met through the mechanism of recombination in the allelomorphic component of the genome (see Chapter 13). This relates to parameters for which some adaptive strategy exists, but where the adaptive response is imperfectly adjusted with respect to the irregular periodicity of survivorship factors in the niche interface. The fecundity offset strategy can thus be more explicitly understood as being a structurologistic adaptive response, and its signiﬁcance lies in its relationship with the gene pool selection interface. The genetic element in the

FIGURE 21 Selective and nonselective offsets of fecundity.

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above scenario can also be illustrated with reference to the genotypic output as shown in Fig. 22.

FIGURE 22 Selective and nonselective offsets of fecundity in the architecture of the gene pool.

In the simpliﬁed model of Fig. 22, the selective offset lies in a range of three genotypes of a single gene locus, only one or two of which actually have a probability of encountering positive selectional interaction within a given time frame; the nonselective offset is an additional factor that takes into account the ambient level of stochastic mortality in the adaptive system. The simplest structure for three genotypes at a locus (with no dominance) can only equal 4, and thus the nonselective offset is simply twice the size of the gene pool, with 50% random mortality. In this system, selection acting in a single generation does not favor all genotypes simultaneously (for example, the heterozygote may be positive in one generation, and negative in another). A more realistic system must involve n haplotype frequencies, to which we must also add a variable inﬂuence of stochastic mortality factors, leading to a need for dynamism in the recombination strategy itself (hence with a variable crossing-over strategy also coming under genetic control; see Chapter 13). The above scenario can accordingly be expressed in terms of the equation set for an adaptive system, in terms of a larger number of haplotype frequencies—assuming that recombination frequencies are here only an approximation to ‘‘good ﬁt’’ with environmental ﬂuctuations for all but a few leading effect loci.* * The genetically effective population size (generally denoted Ne, following Wright, 1940) is not equivalent to the N of the Lotka–Volterra equation set, but is that subset of the same which actually contributes in a genetic sense to the succeeding population. In gene pools with a large nonselective offset, ‘‘effective N’’ will clearly be much smaller than in a more deterministically sculptured gene pool.

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The Intersect between Selective and Nonselective Offsets of Fecundity The situation of a failed adaptive strategy within the selective offset clearly identiﬁes an intersect between deterministic and stochastic factors, in that stochastic events also play a part in determining the outcome of interactions for the selective offset. The intersect selective offset/nonselective offset takes the form shown in Fig. 23. Why is stochastic mortality not just the nonselective offset itself? The difference is that ‘‘failed strategy’’ mortality factors are due to potentially adaptable factors that are subject to periodic behavior, whereas the true nonselective offset also incorporates factors against which no adaptive strategy exists. The intersect is thus the expected nonﬁt rate within the selective offset, and the nonselective offset sensu stricto is any additional stochastic mortality excluded from this.

FIGURE 23 Average expected stochastic loss within the selective offset effectively forms part of the nonselective offset.

The relative status of the selective and nonselective offsets is fundamental to the outcome of longer term evolutionary events, since the nonselective offset contains factors which affect the dynamics of the coefﬁcient of selection, and thus also of evolutionary rate (see Chapter 18).

The Fecundity Offset Strategy and an ‘‘Index of Adaptation’’ It has been shown above that the probability of survival of a gene pool must take into account developmental and metabolic viability linked to the structural response (and thus to ‘‘true’’ adaptation), and that it also includes balance against ‘‘nonadaptables,’’ linked to the logistic response. The concept that the adaptive state A is ‘‘some function of the adaptive strategy of a gene pool’’ clearly needs expanding in order to explicitly reﬂect the fundamentally different roles played by the logistic and structural elements of adaptation. The real adaptive state (Ar ⫽ probability of survival of a gene pool) must now be supplemented by some index linked to goodness of ﬁt in the fecundity offset strategy, thus reﬂecting the differential between fundamental and real

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adaptive states. How, then, can Ar be modiﬁed to encompass differentials in adaptive strategy in this domain? We may begin by considering that the size of the fecundity offset is very approximately inversely proportional to ‘‘goodness of ﬁt’’ between a gene pool and its environment, justifying this by observing that if r is moving toward that level at which a high level of unpredictability is invoked, then this may be an adaptive response to a level of stochastic factors in the adaptive system whereby extinction is threatened. Logistic adaptation has been selected over structural, and the fundamental adaptive state has been diminished. In the above approach, we are of course really only comparing adaptive strategies within Ar ⫽ 1.0 states, in terms of the degree to which logistic adaptation is required in order to counteract deﬁciencies in the fundamental adaptive state. However, the probability of survival of a given gene pool may be equal to 1.0, yet that gene pool may not be fully adapted to its environment in the structural sense, in that a ‘‘poor ﬁt’’ adaptation interface is compensated for by logistic adjustment through existence of a large fecundity offset. The adaptive state might then be more fully understood through consideration of the relative roles of deterministic and probabilistic factors in the structure of the fecundity offsets, based on the premise that, in general, the higher adaptive state is that which maximizes the deterministic against the probabilistic component of adaptation. In this context, a useful adaptive index might therefore be more accurately reﬂected in terms of the differential between fundamental and real adaptive states. The degree to which ‘‘blind logistic adaptation’’ is used to counteract unpredictable mortality factors may thus more accurately reﬂect the adaptive state of the gene pool through an appropriately chosen adaptive index Ai, which seeks to compare two dimensions of adaptation, one deﬁned by the structural component, the other, by the logistic. However, this assumption clearly requires closer examination. Major and Minor Attractors and the Adaptive Index To what extent does ␳ /␾ (see p. 76) as an index of structural versus logistic adaptive capacity really reﬂect the probability of longer term survival of a gene pool, and what is the evolutionary signiﬁcance of this index? Is the adaptive state particularly dependent on the structural or on the logistic component of adaptation in the longer term of evolution—and what evidence is there for any preferred predominance of one or other of these two factors? Should it arise that the structural component of adaptive capacity is indeed ‘‘the leading factor,’’ could it then be that an ‘‘all structural’’ strategy constitutes the ideal one for maximization of the adaptive state? Or should the adaptive system in reality oscillate between two attractors as an expression of ‘‘the appropriate balance between structural and logistic elements in the fecundity offset strategy’’ (this situation thus forming the causal factor behind the latter)? To answer the above questions, it is obviously necessary to consider the separate roles of the selective and nonselective offsets of fecundity in the Ai equation, and here it will also be crucial to consider the index ␳ /␾ in terms of the time span held by adaptive capacity itself, as a possible further step toward a more realistic index of the adaptive state of a gene pool. Given that (␾ ⫺ ␳)

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is the total offset value, we should therefore be comparing the long-term adaptive capacity residing in Os /(␾ ⫺ ␳) and Ons /(␾ ⫺ ␳), respectively.* In view of the fact that a purely logistic strategy may intuitively seem to constitute a weaker option than the structural, it would perhaps be surprising that structural adaptation may not necessarily form the attractor for A in the adaptive system. The arguments for and against supremacy of the structural offset factor are as follows: For A high logistic component will lead to low evolutionary rate, in that environmental change is being met by logistic and not structural modiﬁcation, thus implicating a likely long-term disadvantage. Very low evolutionary rate does in fact seem often to link with a hostile environment, suggesting that ‘‘retained structural primitiveness’’ is probably a poor adaptive strategy in the very long term (a view that is seemingly conﬁrmed by the observation that many ‘‘extant primitives’’ are rare and/or of restricted distribution; see Chapter 18). Similarly, relict gene pools probably do not become extinct through mere logistic deﬁciency, but through structural misalignment arising as a corollary of overreliance on compensatory logistic adaptation (Chapter 20). Adaptive capacity for a gene pool or lineage to control and manipulate the environment is primarily a function of the structural component. An all logistic strategy might also allow buildup of negative viability in the gene pool. A logistic offset adjustment serves to balance against loss of (structural) ﬁtness, only so long as a balanced relationship between N and K is maintained. Against Just as it is possible to postulate negative feedback in the logistic strategy, so too the structural adaptive response can be seen to have certain detrimental corollaries. One major problem with iterative structural modiﬁcation lies with ‘‘overspecialization’’ resulting from reciprocity in the adaptive response (see Chapters 1 and 20). Retention of a more generalized structural state through low evolutionary rate may thus actually conserve structural ﬂexibility, so that logistic plasticity seems a necessary component of long-term survivorship. Many lineages have, in fact, clearly manifested long-term survival on the basis of a high logistic component in adaptation, without either becoming ‘‘overspecialized’’ in the structural domain or being ‘‘rare.’’ The hypothesis of ‘‘the structural component manipulating the logistic’’ assumes that the eventual outcome of such a strategy is not environmental catastrophe! The Solution Despite a prediction that the selective offset might seem to be the most likely candidate as a ‘‘leading effect’’ in the fecundity offset strategy, it would appear that an all structural adaptive response may not be sufﬁciently resilient in view of sudden changes in the external environment. And indeed, it seems very likely that no natural adaptive system would be stable enough to allow * Where Os ⫽ selective offset, and Ons ⫽ nonselective offset.

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complete loss of logistic adjustability, especially with respect to the emergence of novel stochastic mortality factors. We must therefore now consider the likelihood that capacity to be able to adopt a selective and/or nonselective offset strategy ‘‘as and when needed’’ must constitute the true optimum in terms of longer term survivorship prospects. However, it is nevertheless clear that this capacity would be easier for a predominantly structural regime to attain than for an exclusively logistic one, in that the selective offset might readily convert to a purely logistic one if the environment becomes more unpredictable, whereas this ﬂexibility clearly does not appertain to the nonselective offset. The correct solution to the above question therefore seems to be ‘‘a middle road’’: enough structural adaptation to allow selection to respond genetically with respect to ﬂuctuating environmental factors, along with the capacity to provide purely logistic adaptability that can compensate for other factors in the dynamics of the environment, while at the same time preserving structural ﬂexibility. Long-term survivorship thus depends on maximization of a structural response strategy, while concurrently keeping the purely logistic option open. The ratio of structural to logistic components of adaptive capacity may thus lie in a state of dynamic equilibrium between two attractors (structural and logistic), either of which can predominate at any given time. However, of these, the structural is probably the ‘‘major’’ attractor, and the logistic, the ‘‘minor’’ (see also Chapter 1). The gene pool thus tends toward the logistic attractor as a function of the level of stochastic mortality factors, but also gravitates toward the structural attractor whenever adaptive capacity allows. Given that adjustment of the nonselective offset is probably an easily realized modulation from a base in the selective offset, the true adaptive index might therefore lie primarily in adaptive capacity for expansion or contraction of the variance of Os /(␾ ⫺ ␳), measured within a time frame not greater than that of the rate of environmental change—in which case, ␴ 2[ Os /(␾ ⫺ ␳)] over lineage time might be the best index of the adaptive state. The values of Ai ⫽ ␴ 2[Os/(␾ ⫺ ␳)] can now be seen to reﬂect an adjustable input which links to both logistic and structural components of the adaptive response, and a high adaptive index so deﬁned thus explicitly describes afﬁnity with the structurologistic attractor. The adaptive state is now more appropriately expressed as an index that has some link to capacity for longer term survivorship, although Ai is not simply a ﬁxed high or low value. The adaptive index is also linked to diversiﬁcation of the adaptive niche via the selective offset of fecundity, as well as to the degree to which adaptive systems tend toward a state of chaos. The main signiﬁcance of the index Ai will be shown at a later point to be linked to its effect on evolutionary rates, in the substrate of evolutionary change (see Chapter 18). The Adaptive Index and the Adaptive Response How do Ai values as deﬁned by the above equation ﬁt with the nature of the adaptive response? Where the selective offset is low, this may clearly often be associated with an unstable niche interface linked to high levels of stochastic mortality, a situation that will be correlated with high levels of ‘‘drifting’’ microgenetic variation. Differentials in the fecundity offset strategy thus have

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a bearing on the way in which niche architecture links to selectional activity in the adaptive system and, through this, also on how adaptive strategy determines evolutionary rate. Almost paradoxically, it can also be shown that higher values of the adaptive index may in fact offer less opportunity for initiation of anagenetic evolution, in that population space may frequently come to be dominated by adaptive equilibrium within the allomorphic genotype (see Chapters 14 and 19). In the adaptive index, we see a reﬂection of the changing balance between major and minor attractors, and thus also of long-term propensity for survivorship (see Chapter 20). Of course, ‘‘long-term’’ does not imply ‘inﬁnite’ (and there can therefore be no ‘‘ultimate index of the adaptive state’’ of a lineage!). Adaptive Equilibrium and the Gene Pool Concept The concept of selective and nonselective fecundity offsets further conﬁrms the role of the gene pool as the ‘‘epicenter of adaptation,’’ in that the optimum adaptive state clearly lies with the survivorship capacity of a range of potentially viable genotypes by virtue of a necessity to maintain ﬂexibility in adaptive capacity against a dynamic niche proﬁle. Here, it is only necessary to see that, for a dynamic selection curve, ﬁtness is higher for a gene pool retaining capacity for recombination, than for any homozygous population. If homozygotes AA and BB are, respectively, the ﬁttest genotypes in alternating generations, then retention of both alleles is clearly essential to longer term survival: This situation can be further investigated from a simple hypothetical example. Let gene A have a greater capacity for reproduction irrespective of its value to ﬁtness in general (for example, by virtue of a sexual selection trait that masks some other deﬁciency in ﬁtness). An anomaly must exist here, since the course of selectional activity must actually depend on the leading allelomorph gene (for which sexual selection may well provide no visual ‘‘marker’’). However, in the context of the selective offset of fecundity, we can see that some ‘‘reproduction winners’’ will also ‘‘hit the leading allelomorph target’’ through recombination, while others that do will carry only the false marker. Clearly, those genotypes which combine both ‘‘false’’ and ‘‘genuine’’ traits are those best suited to survive. This means that selection continues to act in favor of ﬁtness in general, and evolutionary change will therefore not be channeled into any ‘‘selﬁsh’’ domain, other than in the very short term. The gene pool thus constitutes the epicenter of adaptive capacity, and not the gene—despite the fact that this situation arises as a corollary of apparently ‘‘selﬁsh’’ activity in the face of a dynamic environment! The gene pool thus remains an outcome of organic (rather than biotic) adaptation (see Williams, 1966), in that it evolves primarily as a corollary of individual selection, and not through group selection. The foregoing scenario is permitted by the allelomorphic structure of the gene pool in the context of the fecundity offset strategy, which allows coexistence of various recombinatory subsets of the fundamental genotype that would

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not be manifested in a gene pool with ‘‘perfect ﬁt’’ in relation to the external environment (see Chapter 13). Inclusive ﬁtness similarly resides in the gene pool, and not in the gene. The complex isotropic selection interface model (Chapter 4) may indeed manifest forces both favoring and opposing ‘‘selﬁshness,’’ but evolution can only proceed when the balance is against this criterion. The model in question is thus, in fact, a superset of the inclusive ﬁtness model. Finally, the fecundity offset strategy can be seen to clearly conﬁrm the validity of the adaptive capacity concept introduced in Chapter 1 (see also Chapter 3).

MAIN POINTS FROM CHAPTER 5 1. Allomorphism is deﬁned as the genetic component of adaptive capacity, as this relates to the state of dynamic balance between gene pool and external environment. 2. Most selection controlled change in gene pools is directed toward ‘‘adaptive capacity in dynamic equilibrium’’ as monitored via the allomorphic component of the gene pool, rather than being concerned with true evolutionary change. This mechanism is manifested in both genetic and phenoplastic variation. However, the concept of allomorphism excludes stochastic, nonselectional components of variation. 3. Primary to tertiary domains exist for adaptive equilibrium, according to different conﬁgurations of the selection proﬁle. Most genetic allomorphism lies in the secondary domain, but the functional boundary of adaptive capacity lies with tertiary adaptive equilibrium. 4. A fecundity offset strategy is manifested in both structural and logistic inputs to the state of adaptive equilibrium, owing to the gravitation of gene pools toward logistic and structural attractors. This is reﬂected in the existence of selective and nonselective offsets of fecundity. 5. The fundamental adaptive state excludes any input from the logistic component, which latter is included in the real adaptive state. 6. It is useful to deﬁne an index of adaptivity which reﬂects the dynamics of the fecundity offset strategy as this relates to longer term survivorship. However, as selection can only be ‘‘blind to the future,’’ there can be no ‘‘ultimate coefﬁcient of adaptation.’’

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THE CLADOGENETIC SELECTION INTERFACE

It has been useful to simplify discussion of the behavior of adaptive systems by ignoring interactions between competing gene pools. However, the potential for lineages to undergo spatial diversiﬁcation and cladogenesis is self-evident. What happens when adaptive divergence in the gene reservoir on the spatial plane of niche creates large scale hybrid depression, or when gene pools diverge in allopatric populations such that capacity for reproduction is lowered in the event of subsequent sympatry? Either divergence must reach a limit, or else the gene reservoir must ‘‘split’’ in some way. These manifestations of change clearly derive from activity originating within an anisotopic selection interface that constitutes a demand for cladogenesis. This is no longer movement within adaptive equilibrium, but actual evolutionary change involving differentiation of the genome such that there is disjunct divergence in the genotype or phenotype, either via the action of epigenetic homeostatic mechanisms or through the erection of reproductive barriers, as an adaptive response to forces in the anisotopic selection interface. Certain aspects of cladogenesis have been widely investigated in the light of discoveries in the ﬁelds of classical Mendelian and population genetics. However, owing in part to certain limitations inherent to the latter disciplines, the true domain of cladogenesis has not been evident, nor has the full meaning of cladogenesis as a process been adequately understood. The behavior of cladogenetic systems clearly has a general application in evolutionary theory, since many selectional regimes resulting in modulation to gene frequencies or in gene loss are derived from cladogenetic activity of one kind or another. The full extent of this can best be appreciated following the tenets of adaptive systems theory.

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ORIGINS OF THE CLADOGENETIC FORCE Cladogenetic forces arise from spatial dynamism in the selection interface, as a function of the adaptive response to particular conﬁgurations of the anisotopic selection proﬁle (see Chapter 4). The nature of this dynamism is diverse, the result being that more than a single route to cladogenesis is possible. There are, in fact, two principal models of the cladogenetic process, in which the spatial differential lies in s (sympatric) and S (allopatric) domains, respectively (see Chapter 3).

The Cladogenetic Selection Interface Whereas the complex isotropic selection interface implies a single ‘‘compromise solution’’ to antagonistic selectional forces, cladogenesis demands two solutions to a scenario in which separate structural attractors relate to spatially discrete niche space for independent sectors in the gene reservoir, the key mechanism for which is eradication of capacity for generation of the hybrid state. When an anisotopic selection interface invoking hybrid depression is involved, we may also encounter a selectional force acting against a maladaptive hybrid state which carries no complementary niche space in the external environment, along with a greater or lesser component of developmental nonviability. The X and Y axes of the selection vector diagram (Chapter 4) will clearly now constitute independent allelomorphic traits in the fundamental anisotopic selection interface. Here, there can be no resultant vector since X and Y can only be acting at two or more discrete phenon points linked to noncontiguous niche space. This structure may, however, also present an obligate selection vector ([XY]), owing to the allelomorphic structure of the genotype, whenever sympatry occurs. Again, we use a simple orthogonal model as an analogy.

FIGURE 24 The obligate selection vector ([XY]) representing the hybrid state in a cladogenetic selection interface.

The hybrid selection vector thus has a directionality that is determined entirely by the endogenous genetic environment, which can ideally be taken as being halfway between the two parent homozygote states. In quantitative

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terms, the contribution to ﬁtness of the hybrid state is determined as a function of the external selective environment and endogenous factors in viability, plus any element of frequency overshoot involved. Its quantitative value is then the resultant of opposing positive and negative components.

FIGURE 25 Resultant of the obligate (hybrid) selection vector as a function of opposing elements.

In more general terms then, the cladogenetic selection interface is essentially an anisotopic one in which there is • Either a centrifugal selectional force arising from hybrid depression, where the hybrid state is less ﬁt than either homozygote • Or a spatial dimension in gene reservoir niche space; that is to say, the gene reservoir manifests allopatry in which some element of genomic divergence is occurring in noncontiguous gene pools It is also of great signiﬁcance that in either situation, separate gene pools (or subgene pools) may also manifest some qualitative property linked to unshared niche space. In the ﬁrst scenario, cladogenetic forces clearly arise from the ﬁtness difference between homogeneous and split gene pools. In terms of the gene pool selection interface, the difference is W(X ⴙ Y ⴙ 2[XY]) W(X ⴙ Y ) If the value of the above expression is ⬎1.0, then we have a centripetal selectional force favoring homogeneity of the gene pool. If it is ⬍1.0, then there is a cladogenetic selection interface expressing a centrifugal element which favors splitting of the gene pool. In the latter instance, the cladogenetic element clearly arises ultimately in the balance between centrifugal and centripetal cladogenetic forces, the former being that component of the anisotopic selection interface tending to favor differentiation of the genome in terms of hybrid depression

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(and also of the niche intersect), the centripetal cladogenetic force being that component favoring unity through hybrid vigor. In this scenario, both genomes are selectively positive, but the hybrid state decides whether or not both parent states will tend to be perpetuated without modiﬁcation. With the generation of larger scale cladogenetic forces, we also tend to observe an emerging dichotomy between quantitative and qualitative phenotypic differentials. This situation is caused, in particular, by the differential between genetic incompatibilities appearing in the sympatric versus allopatric domains. We have now seen that there are in fact two ways in which ‘‘centrifugal forces’’ can be said to exist in adaptive systems. There are antagonistic centrifugal selectional forces residing in the complex isotropic selection interface and acting jointly on a single phenotype state (see Chapter 5), and there are also combined centripetal/centrifugal forces acting on the gene pool through allomorphism, heterozygote advantage, hybrid depression, etc., in the anisotopic selection interface—the latter tending to favor the presence of more than a single phenotype state in the gene pool, thus giving rise to a cladogenetic selection interface. In the ﬁrst scenario, the solution will gravitate toward a single optimization point for traits with a high contribution to overall ﬁtness (or a continuous distribution around that point, where contribution to W is low), while in the second scenario, gene pool splitting will clearly be favored. The centrifugal force residing in the second model above clearly has a centrum in the hybrid state, frequently incurring the unstable condition of hybrid depression (which latter acts against the balancing effect of hybrid vigor). Here, there are n genes affecting n traits, conforming to an anisotopic selection interface with principal components in the spatial domain, which could be resolved either through splitting of the genome or else via internal homeostatic adjustment. In the allopatric model (gene pools of a gene reservoir diverging in noncontiguous regions of niche space), we also witness the evolution of cladogenetic forces in the complete absence of any capacity for the expression of hybrid depression. Here, the ‘‘obligate XY vector’’ is absent, and the principal components of the X and Y vectors (as they affect speciation) become prezygotic isolating mechanisms diverging in allopatric gene pools. At this stage, we can see that the allopatric model could include two resolutions: one in which full speciation occurs entirely within the allopatric state, and another in which incomplete reproductive isolation leads to pressure for speciation in the neosympatric state (namely, as the allopatric state converges on the sympatric). It also follows that speciation is an unlikely outcome in the state of plesiosympatry (where we would probably witness homeostatic solutions to antagonistic selection pressures rather than genome splitting). Centripetal and Centrifugal Selectional Forces and Cladogenetic Drive The tripartite structure of the sympatric cladogenetic selection interface is due to a combination of unshared niche space and simultaneous existence of a niche intersect factor—that component of the cladogenetic selection interface affected by niche overlap between competing genotypes or gene pools, and forming the exogenous component of the centrifugal cladogenetic force (see

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above). In approaching the problem of the dichotomy between a shared and unshared limiting resource, we also come to confront the problem of the contribution to ﬁtness, both of ‘‘competition space’’ and niche space unique to speciﬁc genotypes or gene pools interacting within the same adaptive system. Under what circumstances does adaptational divergence within the gene pool actually generate cladogenetic selectional forces? Looking at the single allelic locus situation, there has to be some force opposing elimination and favoring perpetuation of the weaker genotype of a positive allelic pair. When a new allelomorph is positively selected, the parent allele may or may not tend toward elimination through ﬁxation of the new allele, depending on whether or not the two allelomorphs contain some degree of independence in terms of unshared niche space. If the niche intersect is ⬍1.0, the old allele may be readily perpetuated, but if it tends to 1.0, it will tend to be eliminated in the absence of any element of hybrid vigor providing a centripetal force. Thus although if there is hybrid depression there will be a centrifugal force, the proportion of unshared niche space present is clearly highly signiﬁcant in deciding whether or not mutual survival is possible. Clearly, centrifugal and centripetal forces arise speciﬁcally in the niche intersect zone, while areas of unshared K also impart some element of directionality to the behavior of cladogenetic systems. In general then, the centripetal component in the cladogenetic selection interface (unshared niche space plus hybrid vigor) favors perpetuation of the hybrid state and unity of the gene pool, and the centrifugal component (niche intersect plus hybrid depression, also divergence in allopatry with respect to prezygotic isolating mechanisms) favors elimination of the hybrid state or speciation (Fig. 26). The above is clearly only one possible scenario for the infraspeciﬁc case (since many alleles only differ in quantitative aspect), but it is clearly more highly probable for gene pools evolving in the allopatric state and rejoining in neosympatry: Dobzhansky (1970) similarly recognized two types of ‘‘balancing selection’’: heterotic balance (⫽ centripetal polymorphism) and diversifying selection (⫽ one component of the centrifugal element), ‘‘Diversifying selection favours different genotypes in different environments.’’ We shall now conclude that the balance between centripetal and centrifugal selectional forces of the above kind constitutes cladogenetic drive, in the degree to which the net centrifugal element favors occlusion of the hybrid state. To what extent can cladogenetic drive also be said to occur in the purely allopatric situation? Here, we must consider the evolution of prezygotic isolation factors as a further component of cladogenetic drive, since this factor also derives from selectional forces tending to partition the lineage gene reservoir and is thus centrifugal in nature. Hence cladogenetic drive has to be deﬁned in terms of forces arising in either the sympatric or allopatric domain. The Extrinsic Component of Cladogenetic Drive in the Niche Interface As we have seen, a tripartite selection interface clearly lies at the root of the sympatric centrifugal force, speciﬁcally in the zone of the niche intersect,

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FIGURE 26 Centrifugal and centripetal elements in the anisotopic selection interface (unshared niche space in hybrid state not shown).

from which premise we can identify two extrinsic properties, both of which form a highly signiﬁcant input to cladogenetic drive: 1. The niche intersect factor itself: the actual extent of niche overlap for two competing genotypes or gene pools, which equals the intersect of set K1 with K2.* A small intersect may mean little probability of generation of the hybrid state. Similarly, the amount of adaptive niche space peculiar to each parent gene pool determines the degree of inﬂuence of any niche overlap on the strength of the centrifugal force, in terms of the probability of being able to bypass the intersect zone by virtue of shifting niche parameters for one or both competitor gene pools. 2. Niche ‘‘intensity’’: the relative ‘‘degree of penetration’’ of the niche for each genotype with respect to the intersect region as a function of the extent to which niche hyperspace is expressed (see Chapter 2). There are, in fact, two main factors to consider here: (a) the efﬁciency of nutrition location (behavioral component; for example, ratio of time spent in parametric as against subparametric niche * Using K as an approximation to niche (since this identiﬁes the essential limiting resource component).

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space) and (b) the energy utilization factor (‘‘metabolic component’’; for example, velocity of ingestion process, efﬁciency of energy conversion or assimilation). The above factors will have an important directionalizing input to cladogenesis, in that the stronger competitor will tend to oust the weaker from the zone of niche overlap in any speciation event. As already stated, the extrinsic element also has a large part to play in the allopatric evolution of differentials between gene pools, and this will be particularly true in the dichotomy between heterokaryosis and simple heterozygosis (see below), whenever hybrid depression in the neosympatric state is involved. Endogenous Cladogenetic Drive and Hybrid Depression Although it has been possible to show the origins of cladogenetic forces as being partially a function of niche interactions, it is also apparent that various endogenous factors must also be active within the framework of the gene pools concerned. Of these, negative developmental viability resulting from hybridization between noncompatible or only partially compatible genomes is clearly a major inﬂuence. While developmental deﬁciency can in general be offset by logistic balance, this is clearly not possible when the negative element is located in the hybrid state, and this incapacity for logistic balance of hybrid depression must in fact constitute the basis for a large contingent of cladogenetic drive. The endogenous component of the centrifugal force is thus that element arising from the degree of genotypic differential between competing genotypes or gene pools and resulting in depression of viability for that component of the genotype expressing heterozygosity or heterokaryosis. The genotypic or gene pool classes may be presumed to have speciﬁc areas of adaptive niche. Looking at this in the context of a simple single allele divergence, the further apart the AA and aa classes are in developmental terms, the more likely the Aa genotype will contain a large negative developmental component in the adaptive state: 씯AA WAA

Aa ⬎

WAa

aa씮 ⬍

Waa

Negative developmental viability thus identiﬁes a major endogenous element in the cladogenetic selection interface in the form of a centrifugal force tending to favor suppression of the hybrid state, and clearly the presence of genetic capacity to evolve dominance is part of the adaptive response to this scenario. The above model must of course be extended to the multigenic case, with respect to gene pools arriving at a neosympatric state. Here, suppression of the hybrid state itself is a question of more profound evolutionary changes than mere acquisition of epigenetic homeostasis in dominance. Heterozygosis and Heterokaryosis in Cladogenetic Drive The hybrid state may clearly be positive or negative in terms of the coefﬁcient of selection, and two different expressions of hybridity exist with respect to the organization of the genome, namely, in heterozygosis and heterokaryosis.

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The former constitutes the differential between homologous chromosomes as expressed by allelomorphism alone, whereas the latter is that differential manifested in more complex misalignment between partially nonhomologous chromosomes (the latter situation more probably originating from allopatric changes occurring in the genome): Dobzhansky (1970) investigated chromosomal sterility with regard to translocation hybrids, reporting deﬁciencies and deleterious duplications in some meiotic products. He also observed that hybrid Drosophila pseudoobscura ⫻ D. persimilis males are generally sterile. Here, meiotic chromosome pairing is variable and only a single division occurs. Only when the X chromosome is paired with parent autosomes do testes develop normally, and the more the autosomes include the other species, the smaller the testes. Thus, all chromosomes carry genes concerned with fertility, and depression of the latter may often form a large component of the endogenous element in the development of cladogenetic drive. The inﬂuence of negative heterokaryosis in cladogenetic drive is again underlined by evidence from isozyme studies showing a likelihood that regulatory genes from one species may be incompatible with structural genes from another (Nei, 1987). Heterozygosity and heterokaryosis also form the collective categories: Hybrid vigor Hybrid depression

Positive heterozygosis/heterokaryosis Negative heterozygosis/heterokaryosis

Negative heterozygosis and heterokaryosis can be distinguished as shown in Fig. 27. Negative heterozygosis concerns the presence of two allelic states of a single gene locus that are homeostatically compatible but selectionally deleterious in combination, whereas negative heterokaryosis concerns nonsense combinations of nonhomologous chromosomes where genetic divergence has evolved in allopatry, and where the chromosomes have been restructured to such an extent that they may be unable to take part in normal meiosis. The latter situation frequently leads to fertility loss, owing to 50% or so of the

FIGURE 27 In negative heterozygosis (left), the heterozygote is less ﬁt than either homozygote. In negative heterokaryosis (right), chromosomes are meiotically unmatched.

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heterokaryotic gametes being entirely deﬁcient in certain genes. Negative heterozygosis and heterokaryosis both form an important part of the postmating isolating mechanism of the speciation process, and frequency overshoot (see below) is also part of hybrid depression, a general scheme for which latter is shown in Fig. 28.

FIGURE 28 Components of hybrid depression.

As indicated above, there may also be positive heterozygosis/heterokaryosis, as, for example, with the centripetal element or with sex determination. The Centripetal Force and Hybrid Vigor As we have seen, the hybrid state for two competing genotypes or gene pools often carries a negative selective state, or else a ﬁtness value lying between that of the two homozygous classes. However, it may alternatively relate to unshared niche space or to metabolic superiority relative to either homozygote or gene pool. This is the centripetal selectional force, tending to maintain rather than suppress the hybrid state and favoring balanced polymorphism in the adaptive response. The centripetal force may also tend to suppress genome splitting, indicating that cladogenesis derives from the degree to which balance between centrifugal and centripetal selectional forces determine the degree of cladogenetic drive: Levene (1953, also Li, 1955) showed that in a gene pool adapted to two different environments, a sufﬁcient condition for stable polymorphism is that the harmonic mean of the viabilities of the heterozygotes be greater than that of the homozygotes. Dobzhansky (1970) stated that many dominant lethal genes have been found to be ‘‘heterotic,’’ showing that hybrid superiority has the capacity to perpetuate even deleterious alleles (as, for example, with malarial resistance in human hemophilia mutants). Dobzhansky also suggested possible ‘‘physiological and ecological sources’’ as the causes of heterozygote advantage, citing experiments on Drosophila pseudo-

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obscura which indicated various differential survivorship factors at play, including rate of development, fecundity, and longevity. Hybrid vigor is thought to be frequently due to overdominance (where the heterozygote is ﬁtter than either homozygote), including ‘‘associative overdominance’’ (where different inbred lines become homozygous for different deleterious alleles). In this situation, a centripetal force can be seen to operate within the domain of endogenous gene homeostatic properties alone. The centripetal force is often simply a function of positive heterozygosis, although inversion heterozygotes probably constitute positive heterokaryosis, in which more complex factors must be involved.

The Cladogenetic Selection Interface in the Equation Set of the Adaptive System An understanding of cladogenetic drive and of the cladogenetic selection interface in general can most readily be modeled in the equations of the adaptive system, in the context of the sympatric gene pool. The Cladogenetic Selection Interface and Partitioning of K The simplest situation with which to understand the nature of the spatial differential in the adaptive response is to examine the situation where the selection proﬁle is anisotopic: Spatial loci Genotype

s1

s2

AA

⫹

⫺

aa

⫺

⫹

This situation clearly constitutes a stable polymorphism in the adaptive response, leading to a higher adaptive state for the gene pool by virtue of ‘‘diversifying selection.’’ Where is this genetic scenario actually located in the modiﬁed Lotka–Volterra equation set? (See chapter 5) Clearly a noncompetitional element must now be introduced. The Lotka–Volterra equations have already been shown to identify the selection coefﬁcient in terms of differentials in r and in heritable elements in the 움 factors. However, not all selectional differentials between genotypes are linked to competition, since some new genotypes may expand the contours of the existing niche, thereby bestowing a positive change which involves no element of competition with the parent genotype. W is therefore not exclusive to the intersect K1:K2, nor to the selection interface so deﬁned, since there may be additional factors in ﬁtness linked to unshared niche space. Indeed, in ‘‘pure’’ polymorphism, two genotypes can only be maintained at constant relative frequencies if both also manifest an unshared K complement, which may be located in the homozygote classes or even in the heterozygote state, as in centripetal polymorphism (see above). Consequently, W is only determined by the modiﬁed Lotka–Volterra equations when no such factor is involved and the genotypes in question are in total competition with respect to niche space. W is thus a composite term, which must also be made to encompass the

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‘‘unshared K’’ factor. To incorporate ‘‘unshared niche space,’’ K must accordingly be split, so that there has to be a K value shared by competing genotypes (K1⫹2) plus a K value unique to each niche (K1 and K2). The equation set of the adaptive system may now be set out in algorithmic fashion for the polymorphism-with-dominance situation, assuming that the polymorphism in question does not constitute the whole niche: a. Some part of N1 is controlled by dN1/dt ⫽ rn1 ⫻ N1t⫺1 ⫻ (K1 ⫺ N1t⫺1)/K1, and some by rn1 ⫻ N1t⫺1 ⫻ (K1⫹2 ⫺ N1t⫺1 ⫺ 움21 ⫻ N2t⫺1)/K1⫹2 b. Similarly, part of N2 is determined by dN2/dt ⫽ rn2 ⫻ N2t⫺1 ⫻ (K1 ⫺ N2t⫺1)/K1, and some by rn2 ⫻ N2t⫺1 ⫻ (K1⫹2 ⫺ N2t⫺1 ⫺ 움12 ⫻ N1t⫺1)/K1⫹2 The above expands the structural component in the equation set of the adaptive system by incorporating additional terms discriminating between shared and unshared K in the Lotka–Volterra equations, thus extending the domain of the selection interface beyond that of direct competition. The revised equation set now identiﬁes a noncompetitive differential between interacting genotypes or gene pools, determining W, not only as a dynamic variable, but also as one that is only partially expressed in the 움 factors. W can therefore be directly determined solely when there is no noncompetitional element in the system in question. The modiﬁed Lotka–Volterra equation set serves to deﬁne a more complete adaptation interface of which the selection interface is a subset, in that the unshared K element allows coexistence of two only partially competitive states manifesting an ongoing selectional differential. ‘‘Unshared K’’ lies in the adaptation interface, while only shared K lies in the selection interface. The model given above is of course a simpliﬁcation, in that the majority of variance–selection interactions obviously involve, not allelic, but haplotype frequencies. However, the actual conclusions drawn above will be valid well beyond the domain of the minimum model. From the above observations then, the behavior of the cladogenetic selection interface must be a function of (a) the 움 factors of the hybrid state and (b) the size of unshared K, relative to shared K for all genotypic states. Cladogenetic Drive in the Equation Set of the Adaptive System To identify the locus of the centripetal and centrifugal forces in terms of density dependent selection in the Lotka–Volterra equations, it is only necessary to look at the simple situation where niche space corresponding to the anisotopic selection interface can be examined in relation to a single allelic pair. Continuing to use K as an approximation to adaptive niche in the equation set of the adaptive system (K ⫽ limiting resource ⫽ that part of the total niche actually entering into the logistic equation), hybrid vigor or depression then arises in the ﬁtness relationships of W values of homozygous and heterozygous phenotypes, as a joint function of niche intersect and the adaptive state of the heterozygote genotype (WAa). In the anisotopic selection interface: K1

K1ⴙ2

K2

AA

Aa

aa

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if WAa ⬎ WAA, Waa (and K1⫹2 is large), then cladogenetic drive results from a centripetal force; if WAa ⬍ WAA, Waa, then the system experiences a centrifugal force. We must now extend this approach to encompass that situation where compound heterozygosis and heterokaryosis exist, and a large cladogenetic force is generated. Following on from the equation set introduced above (where K1⫹2 ⫽ shared K, and Kn ⫽ unshared K ), 움13,23 are additional factors describing the selectional differential between hybrid and parental genotypes or phenotypes. The anisotopic selection interface is described by an equation set in which the adaptive state of monomorphic populations is higher than that of the hybrid population. Thus, in a population where N1 and N2 have high levels of shared K, the genotype corresponding to N3 has the capacity to lower the adaptive state of the combined gene pool. This situation thus models the cladogenetic selection interface when the rn3 and 움13,23 factors reﬂect hybrid depression.

FIGURE 29 Deﬁnition of the selection differential 움13, 23.

The above modiﬁed equation set thus clearly identiﬁes the locus of the centripetal and centrifugal forces in the adaptive system, in expressing the distribution of the K dimension as the ‘‘functional niche’’ in cladogenetic activity, and also in identifying the locus of the centrifugal force in the adaptive state of the hybrid genotype or gene pool. Differential adaptational viabilities of genotypes or gene pools may thus be understood as being implicit in the 움 factors in the Lotka–Volterra equations, so that both extrinsic and endogenous elements are expressed therein, given the presence of an additional complement relating to the hybrid state. In this situation, hybrid depression constitutes the leading factor for the quantitative input to cladogenetic activity in the anisotopic selection interface, while the directional component is expressed in the vector model (see Fig. 25).

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CLADOGENETIC CAPACITY AND POTENTIAL Cladogenetic drive (see above) does not ‘‘cause’’ cladogenesis, but only ‘‘favors’’ it, since actual divergence at any level can only occur if there is adaptive capacity or potential for this to happen. Cladogenetic capacity and potential constitute special subsets of adaptive capacity and potential in general, and as such, they similarly manifest both extrinsic and endogenous components.

The Nature of Cladogenetic Capacity and Potential Cladogenesis is clearly inﬂuenced by a complex of antagonistic centripetal and centrifugal forces promoting cladogenetic drive and by the architecture of the selection proﬁle, and this mechanism can therefore be viewed as an adaptive response in which capacity and potential must exist in order to resolve antagonistic selectional forces arising in the gene reservoir. Cladogenetic capacity is linked to that component of adaptive capacity which relates to resolution of selectional conﬂict in the cladogenetic selection interface. It is a genotype or gene pool interactive function of the sum selection proﬁle ⫹ adaptive capacity in which not only niche structure, but also the developmental viability component of the adaptive state (and thus, the endogenous component of adaptive capacity) play a signiﬁcant role. Cladogenetic capacity is manifested in capacity for homeostatic adjustment within the boundaries of the existing genome. The allelomorphic structure of the genotype must contain signiﬁcant inputs to cladogenetic capacity, since some component of adaptive capacity may balance against hybrid depression via recombination or rearrangement of genetic material on the chromosomes, or through homeostatic adjustment. Cladogenetic potential is likewise linked to an innate adaptive potential for resolution of cladogenetic drive.* It is frequently concerned with the more complex problem of multiple allelic differentials and complex karyotypic dichotomies that have evolved in the allopatric scenario and which cannot be resolved other than by speciation. Cladogenetic capacity and potential are thus deﬁned in terms of adaptive capacity or potential for cladogenetic drive to be resolved, either through gene homeostasis or else via speciation. We have now effectively separated ‘‘factors demanding’’ (cladogenetic drive) from ‘‘factors facilitating’’ cladogenesis, the latter lying with endogenous and extrinsic components of adaptive capacity or potential. In this scenario, the ‘‘centripetal and centrifugal forces’’ already mentioned are seen to be selectional attractors toward which actual propensity for movement may or may not be present. The Extrinsic Component of Cladogenetic Capacity and Potential and ‘‘Free, Adjacent Niche Space’’ Where speciation involves some degree of niche shift in one or both competitor gene pools, a potential to move into free, adjacent niche space must also * A full deﬁnition of the boundary between ‘‘capacity’’ and ‘‘potential’’ will require deeper analysis of the means by which novel major changes are effected in the adaptive ensemble (see Chapter 7).

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form an important component of the extrinsic factors facilitating resolution of cladogenetic drive, and this must play a particularly signiﬁcant role in realization of cladogenetic potential. The hybrid depression element in the centrifugal force cannot, for example, always be satisfactorily resolved in the absence of free niche space. This is a further, extrinsic component of cladogenetic capacity or potential which must also contribute to directionality in the adaptive response. The Endogenous Component in Cladogenetic Capacity and Potential and Developmental Nonviability The developmental component in the cladogenetic selection interface residing in negative heterokaryosis cannot be resolved in lack of genetic capacity or potential for genomic change in that domain. In this, we identify capacity and potential for developmental homeostasis or for reproductive isolation as constituting the principal endogenous components for resolution of the centrifugal force in the cladogenetic selection interface. The presence of potential for the development of species isolating mechanisms is of prime signiﬁcance to the question of endogenous elements in cladogenesis (see below).

REALIZATION OF CLADOGENETIC CAPACITY AND POTENTIAL It is now clear that realized cladogenesis is derived from resolution of cladogenetic drive via cladogenetic capacity and potential. This can be summarized as shown in Fig. 30.

FIGURE 30 The complex of factors leading to cladogenesis: cladogenetic drive to cladogenetic capacity and potential.

It is furthermore necessary to ask, what factors decide how cladogenetic capacity or potential is realized? Although it is obvious that speciation constitutes one possible outcome of the above, it has also emerged that resolution of cladogenetic drive can also occur within the boundary of the gene reservoir. Furthermore, not all apparently species level outcomes actually involve separation of two lineages, since two apparently emergent species may simply gravitate toward racial merging, or else one may simply oust the other from the adaptive

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system. Realization of cladogenetic capacity and potential can occur at several levels, from infraspeciﬁc to divergence of major evolutionary lineages.

Axial and Tangential Components of the Adaptive Response to Cladogenetic Drive A general model can seek to identify all aspects of realization of cladogenetic capacity and potential. However, this model must also relate to different domains of cladogenetic activity in a different manner. Given that several different outcomes of cladogenetic behavior are possible (see above), it must be that the behavior of a particular cladogenetic selection interface depends particularly on the balance existing between centrifugal and centripetal forces. If cladogenetic drive is slight, and the interface is a plesiosympatric one, then a purely infraspeciﬁc resolution may be possible on the basis of genetic homeostasis alone. However, if cladogenetic drive is greater and allopatry is implicated, then cladogenetic potential must determine whether or not two lineages can coexist. This question of balance is universal but can be most clearly illustrated in that situation in which emergent species are involved. Firstly, we must consider the possibility of racial merging. Genomic anastomosis occurs when two emergent gene pools merge into a common gene pool via compound mutual allelic substitution and when homeostatic readjustment in the epigenetic environment involving ‘‘exchange of best alleles of each emergent genome’’ and reorganization of dominance hierarchies occurs. This mechanism could clearly be biased toward one parent gene pool in the context of any racial merging event. The next higher level is clearly that of the complete divergence of two emergent species, a process that can be called binary resolution (speciation), with respect to cladogenetic drive (with a 1:1 survival of emergent species). If, however, a very large difference in cladogenetic potential exists between two emergent gene pools, then one may simply replace the other in the context of species or cladogenetic substitution (the 1:0 element in resolution of cladogenetic potential). Cladogenetic substitution thus occurs when one discrete gene reservoir entirely replaces another in its adaptive niche as a result of selectional differentials with a leading effect in a cladogenetic selection interface. The above scenarios are clearly based on discrepancies in the balance between cladogenetic forces affecting gene pools in different ways, and it is this question of balance that we must now pursue further. In this context, we are now additionally concerned with the question of whether the parent classes are of approximately equivalent adaptive states. Clearly, this may often be approximately true in the context of ambient microevolution, but it is of special interest in the context of the longer term behavior of cladogenetic forces that there may be a larger dichotomy between ‘‘best’’ and ‘‘second best’’ pathways out of cladogenetic conﬂict. Cladogenesis may thus tend at times to manifest two quite unequal potential resolutions, the axial and tangential, depending on the quantity/quality of free niche space available to each (these being greater for the axial, and lesser for the tangential). This dichotomy arises from inherent differentials in cladogenetic capacity and potential. Therefore, although these resultants may actually be approximately equal for ambient speciation events, we must in a general model also consider the existence of a greater domain in

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which considerable potential for divergence may lie in the gap between axial and tangential resultants. The preceding concept can be explained more clearly with reference to the binary resolution model (see above), in consideration of the interactive qualities of two genotypes or incipient gene pools occupying partially intersecting niches. In this model, endogenously generated axial and tangential cladogenetic potentials for realization of cladogenesis are now further facilitated by the dimensions of free, adjacent niche space. Here, resolution of the cladogenetic force will clearly depend, not only on the degree of negative selectional force encountered in the hybrid class and in the size of the ‘‘unshared K’’ component for both homozygote and parent genome classes, but also on the degree to which adaptational change can permit exodus from the niche intersect state via accessible niche space in the external environment. In this, we witness a capacity to reduce or eliminate the intersect itself.

FIGURE 31 A niche intersect which is large in relation to the K1 gene pool, but small in terms of the K2, at the same time indicating that capacity for resolution of the centrifugal force lies partly in existence of free, adjacent niche space (which is again limited for K1 and large for K2).

Successful cladogenetic realization may accordingly depend on the existence of niche space particular to each genotype or gene pool in the niche interaction, and clearly this may lie within the extrinsic component either of adaptive capacity (existing unshared niche space) or of adaptive potential (free, adjacent niche space). The entire niche interaction underlying cladogenetic activity in speciation is thus seen as a function of niche intersect, independent niche space, and free, adjacent niche space [and this appears to have a preferred

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axial (K2) and tangential (K1) resolution in the example shown in Figure 31 above]. Cladogenetic Drive and the Concept of Benign and Hostile Adaptive Niches As we have just seen, spatial relationships of the niche interface may at times give rise to divergent axial and tangential potentials in terms of adaptational strategy. This could simply mean a quantitative differential, but it could also constitute a qualitative one in terms of, for example, a switch from one prey or food plant to another. More signiﬁcantly for certain processes of macroevolutionary change, binary resolution of cladogenetic drive could sometimes mean a fundamental differential in adaptive strategy relating to a dichotomy existing between the benign and hostile adaptive niche. The ‘‘hostile’’ adaptive niche is that in which penetration of competition and selection is low because of a high incidence of stochastic mortality factors. In contrast, the ‘‘benign’’ niche holds a larger contingent of deterministic, selectional interactivity. These we may now choose to link to tangential and axial resolutions of cladogenetic potential. In the axial (⫽ benign) niche, stochastic mortality is low and selectional interactions in population dynamics are high, tending to maximize niche realization through competition where the niche is expanding as a fraction of the total environment—the stronger genome thus tends to take over intersect niche space, forcing the weaker into a more restricted and hostile zone. In the benign niche, the fundamental adaptive state is thus converging on the real, and the structural component of the adaptive response predominates. The tangential (⫽ hostile) niche contains higher levels of stochastic mortality, and thus little selectional interactivity, tending to maximize niche realization within a zone of lower competition complementary to a smaller and/or contracting niche—the ‘‘weaker’’ genome thus tends to retract into relatively less functional niche space. Here, the fundamental adaptive state is diverging more widely from the real, and the logistic component of adaptation predominates, this adaptational scenario being one in which there is ‘‘stochastic override’’ of natural selection as well as of mortality in general. In the hostile niche, competition may be further diminished through an ‘‘impenetrability factor’’ equivalent to a state of sequestration from the action of selection. Given that positive gene mutation constitutes ‘‘the substrate’’ and selection, the ‘‘reagent’’ of evolutionary change, a niche in which there is shelter from predation, competition, weather conditions, etc., is one in which both substrate and reagent may be present, but interaction occurs with a low level of probability only. The benign niche is more open to selectional activity through efﬁcient exploitation of a ‘‘popular’’ limiting resource (shared by many competitors) and is additionally removed from random mortality factors. Such regimes are thus not to be construed as being ‘‘benign’’ in the sense that high levels of mortality are excluded, but only with regard to facilitation of a deterministic organism–environment interaction with respect to the structural component of adaptation—and it should thus be realized that the terms benign and hostile refer solely to penetrability of selection.

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Since the ‘‘benign’’ state is the deterministic choice, and the ‘‘hostile’’ one is that in which logistic adaptation is pitted against stochastic factors, this must also reﬂect greater movement toward the major (structural) attractor in the competitively superior emergent species. This dichotomy may often constitute an improved deﬁnition of the terms axial and tangential, so that the ‘‘size of free, adjacent niche space’’ may frequently constitute a qualitative rather than quantitative attribute, at least with regard to longer term evolutionary events. The differential between axial and tangential resultants in the largest domain of cladogenesis can be summarized in the context of a cascade described by the following parameters: Axial (as benign niche)

Tangential (as hostile niche)

Expanding into ‘‘larger’’ niche volume High Af, reﬂecting deterministic, structural adaptive response Higher Ai in variance of Os /(␾ ⫺ ␳) Tending toward structural attractor

Contracting into ‘‘smaller’’ niche volume Low Af, reﬂecting stochastic, logistic adaptive response Lower adaptive index Tending toward logistic attractor

In this model then, the axial resultant tends to maximize niche realization through competitive superiority, and the tangential, through avoidance of competition and predation via a logistic strategy. It does not, of course, follow that qualitative differentials of the above kind exist in every cladogenetic selection interface, and a qualitative differential may actually only be ‘‘different food plant,’’ etc.; consequently ‘‘axial’’ is not automatically equivalent to ‘‘benign.’’ In fact, the degree to which more deeply seated niche factors penetrate resolution of cladogenetic potential underlies the differential between ambient speciation and larger scale cladogenetic events. The axial and tangential resultants of cladogenetic potential may at times, however, manifest identiﬁable links with the nature of the adaptive response at higher levels, and then broadly contiguous elements of the environment may become compartmentalized via specialization in the context of cladogenesis. In this scenario, we can observe a cladogenetic cascade in that train of mechanisms in the organism–environment interaction tending to give rise to axial and tangential (and potentially, benign versus hostile) resultants in the realization of cladogenetic potential (Fig. 32). The above scenario is of great importance for an understanding of the macroevolutionary activity of adaptive systems, with implications extending well beyond the domain of cladogenesis itself. It is interesting also to consider that the existence of axial and tangential components of the resolved cladogenetic force may constitute support for the view that structural and logistic attractors may have respective ‘‘major–minor’’ status in the evolution of adaptive systems. In this context, the adaptive index Ai (Chapter 5) probably does not contribute directly to the long-term survivorship of a lineage so much as acting to determine the life span of a species, in that the axial choice in binary resolution may, on average, have a greater chance of establishing a stable lineage niche. r- and K-Selection and the Benign–Hostile Adaptive Niche The concept of axial and tangential resultants of the centrifugal selectional force clearly links to the concept of r and K strategies and also to the question

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FIGURE 32 The cladogenetic cascade in its relationship with the benign and hostile adaptive niche.

of evolutionary rate. However, the actual role of the r versus K dichotomy has been the subject of much confusion in the past. The dichotomy ‘‘r- versus Kselection’’ is in fact often used simply to denote high versus low reproductive rates, rather than the differential between constant versus variable environments: Brookﬁeld’s model (1986) uses the Lotka–Volterra equations plus two parameters ( q ⫽ size of regularly repeated nonselective crash in population size and x ⫽ time in generations between crashes). However, there is no change in relative abundance on the basis of this model. In contrast, experiments with Drosophila (Mueller and Ayala, 1981a,b) show that K-selected populations do in fact manifest higher growth rates than r-selected ones under K conditions, and, similarly, r-selected populations do likewise under r-selection. However, not all predictions of the experimental regime were fulﬁlled.

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In the present interpretation, a ‘‘K-selected’’ population implies the presence of a selectable heritable differential between genotypes, even in a variable environment, whereas an r-selected regime does not. Thus, ‘‘r-selected’’ gene pools do not actually need to have higher growth rates than ‘‘K-selected’’ ones, since the fecundity offset strategy (Chapter 5) may be high in the latter (namely, in terms of a large selective offset component). Perhaps the most signiﬁcant factor here is that the K limit (and thus also the selection interface) will have a much lower probability of lying in sub- or hypoparametric niche space in the hostile than in the benign adaptive niche (see Chapter 2); clearly this must have profound implications for evolutionary rate of lineage (see Chapter 18).

THE DOMAINS OF CLADOGENESIS It is evident that the resolution of cladogenetic forces is not conﬁned to speciation, since cladogenetic activity may be expressed, not only in the speciational domain, but also in infraspeciﬁc genomic change and in postspeciational divergence. Cladogenetic forces may in the ﬁrst instance be resolved through homeostatic mechanisms maintaining allomorphism. Second, binary resolution need not be resolved by complete elimination of the niche intersect zone, since the hybrid depression component of the cladogenetic force will cease once two gene pools have erected reproductive barriers (hence two species often show niche overlap). In the latter instance, we must identify gene pool isolation as the leading factor in determination of the functional boundaries between two emergent gene pools of a cladogenetic selection interface. It is also essential to see that resolution of cladogenetic potential does not end with speciation, since much niche modulation will in fact be postspeciational, and structural diversiﬁcation may also follow the speciational event. Another possibility is, of course, that newly emergent species may differ in little else other than niche divergence, and whether or not this situation will be perpetuated will clearly depend on the degree of residual cladogenetic drive and cladogenetic potential: Dobzhansky (1970) described ‘‘sibling species’’ as good biospecies lacking morphological differentiation. The siblings Drosophila pseudoobscura and D. persimilis have ethological differences combined with sterility of males and other viability breakdown factors; each has its own chromosomal polymorphisms.

Minor and Major Cladogenesis—The Phenotypic and Genotypic Domains A simple anisotopic selection interface describes allomorphism perpetuated for one or more gene loci, its form being at least bi- and potentially tripartite in nature with respect to the spatial dimension of the adaptive niche of a gene pool. As we have seen, it is partly with the latter that cladogenetic

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drive lies. The same situation exists in a multiallelic situation, where two incipient gene pools manifest negative hybridism in the neosympatric state. In the ﬁrst example, realization of cladogenetic capacity and potential may constitute nothing more than homeostatic adjustment within the contours of the gene pool itself, but in the latter case, cladogenetic pressure may lead to speciation. The fundamental similarity between these ‘‘minor’’ and ‘‘major’’ expressions of disjunct phenotypic divergence must not be overlooked, however, since both clearly constitute resolution of conﬂicting cladogenetic forces in the gene reservoir. In this scenario, selectional conﬂict involving simple heterozygosis will tend to be realized through evolution of dominance, and more complex heterokaryosis via speciation or cladogenetic substitution (see Chapter 14). It is now clear that cladogenetic activity may occur in three broad domains: 1. That resolved in an intraspeciﬁc mode by evolution of acquired dominance (some proportion of which may be derived from cladogenetic capacity alone). As stated by Givnish and Sytsma (1997), ‘‘Ecological and adaptive divergence can occur without speciation.’’ Here, we view this event occurring as a response to cladogenetic drive. 2. That involving speciation, always involving realization of cladogenetic potential. 3. That involving postspeciational divergence. Speciation to Postspeciational Divergence As we have just seen, minor (⫽ phenotypic) cladogenesis is that mode which incorporates only subspeciational microevolutionary change in the domain of genetic homeostasis. Major (⫽ genotypic) cladogenesis encompasses speciation plus that component of postspeciational divergence which expresses continued activity of the same cladogenetic selection interface which gave rise to the preceding speciation event in the ﬁrst place. Thus, Minor (phenotypic) cladogenesis is the homeostatic occlusion of the hybrid state. Major (genotypic) cladogenesis is speciation, with actual elimination of the hybrid state, plus residual cladogenetic pressure continuing into the postspeciational domain. We can compare and contrast major and minor cladogenesis as shown in Fig. 33. In this context, minor cladogenesis can range from establishment of dominance with respect to a single allelic state, to reorganization of a substantial proportion of the parent genomes (for example, in the context of genomic anastomosis). Allomorphism (see Chapter 5) in which there is evolved dominance clearly derives from a cladogenetic selection interface with respect to the allelic classes, and such a scenario may commonly express adaptive equilibrium. Realization of cladogenetic potential occurs here as an expression of epigenetic homeostasis, so as to occlude the hybrid (heterozygote) state, in manifestation of acquired dominance (as distinct from the usually deleterious scenario of spontaneous

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FIGURE 33 Major cladogenesis (top) removes the entire hybrid zone, whereas minor cladogenesis (bottom) merely removes negative heterozygous states from part of the repertoire of adaptive equilibrium and restores order into ‘‘nonsense heterokaryotypes.’’

dominance). The ‘‘dominance solution’’ is thus diagnosed as constituting a true resolution of cladogenetic selectional conﬂict, and it obviously applies only to the intraspeciﬁc case, where a genetic load in the recessive homozygote class can be homeostatically accommodated. As a broad approximation then, cladogenetic capacity may be largely realized in allomorphism via dominance, and cladogenetic potential links to speciation and an element in postspeciational divergence derived from the original cladogenetic selection interface (Fig. 34). This view will, however, also have to be expanded with closer examination of racial merging and species substitution (see Chapter 13). Adaptive Equilibrium and Minor Cladogenesis Competition is the struggle between genotypes or gene pools to occupy the maximum state of adaptation in a shared niche. A gene pool is always tending to increase its state of adaptation through allomorphism, by spreading

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FIGURE 34 Manifestation of cladogenesis in minor and major modes.

its dependence on limiting niche parameters over a progressively more diverse range of resources. The primary adaptive response in the genetic component of adaptive capacity may thus generally be structured so as to counteract intraspeciﬁc competition in the adaptive system through allomorphism, so lowering total mortality through ‘‘spread of K,’’ thus maximizing the adaptive index via the selective offset of fecundity. Allomorphism will occur in a gene pool containing allelomorphic genotypes which have access to areas of unshared niche resources, when different allelomorphs coincide with mutually independent temporal and/or spatial components of the adaptive niche, and where individual genotype ﬁtnesses are together additive to overall gene pool ﬁtness. Even when the heterozygote simply equals half of homozygote ﬁtness, this may still generate a centrifugal force as a result of ‘‘frequency overshoot,’’ since recombination cannot adjust hybrid genotype frequencies to the selection proﬁle. Centripetal polymorphism constituting allelomorphism perpetuated by the existence of a higher hybrid adaptive state than for either homozygote is, in contrast, intrinsically ‘‘anticladogenetic’’ in nature, but nevertheless may sometimes evolve as a solution to cladogenetic forces through modiﬁcation of ﬁtness in the hybrid state. The overall view of polymorphism (sensu lato) is that it frequently constitutes an adaptive response complementary to resolution of cladogenetic conﬂict arising in the anisotopic selection proﬁle. And even where dominance is not involved, polymorphism still has the capacity to raise the adaptive state of the gene pool through ‘‘spread of K.’’ Chronomorphic regimes also serve to maximize the adaptive state, although not directly within the context of cladogenetic capacity or potential.

Major Cladogenesis—Speciation to Postspeciational Divergence The dichotomy between intraspeciﬁc and transspeciﬁc resolutions of cladogenetic capacity or potential clearly points to a fundamental division within cladogenesis itself, and it has already been shown that this dichotomy must arise from the quite different opportunities for genetic differentiation existing

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in the sympatric versus allopatric situation. The speciational domain clearly requires further elucidation. The Inﬂuence of Neosympatry in Major Cladogenetic Potential Negative developmental viability clearly has a greater probability of arising when gene pools have evolved in geographic isolation for a long period prior to sympatry rejoin, so that factors such as dispersal, migration, and dynamism in the abiotic environment may often be the overriding factor in the development of major cladogenetic drive. With plesiosympatry, the gene pools in question have always formed part of the same gene reservoir, but with neosympatry, gene pools of a formerly sympatric gene reservoir have become allopatric then rejoined in sympatry at a later stage. The latter scenario clearly has a profound effect on the genotypic component of adaptive capacity or potential, since neosympatric systems will tend not to have evolved those homeostatic adjustments tending to support hybrid genotypes in sympatry. Since the incidence of novel mutation within allopatric populations clearly forms a highly signiﬁcant input to selectional conﬂict in the event of neosympatry, the accumulation of nonhybrid compatible differentials in the genotype in the neosympatric state clearly constitutes a fundamental problem for cladogenetic potential, having a profound effect on endogenous cladogenetic forces. Consequently, a large interactive component exists between extrinsic and endogenous elements. Above all else, the dichotomy between plesiosympatry and neosympatry is reﬂected in a parallel differential between simple heterozygosity and complex heterokaryosis in the hybrid state. As we have already seen, this must have a large bearing on the question of whether a major or minor resolution is possible for cladogenetic drive. The capacity for the neosympatric scenario to inﬂuence speciation is now beyond question. Whether or not we also accept the possibility that total species isolation can evolve in allopatric gene pools (see below), it is nevertheless widely argued that much ambient speciation occurs in the neosympatric situation, at least in part because of the endogenous viability component of ﬁtness acting to favor genome splitting in a developmentally negative hybrid genotype state. In this instance, some component of the hybrid problem will additionally be due to nonallelic genes that are incapable of expressing mutual allelism in the hybrid state, namely, where chromosomal rearrangement is implicated (as with inversions and translocations). Cladogenetic forces arising in the anisotopic selection interface will therefore be resolved either through homeostatic adjustment or through speciation, according to cladogenetic capacity and potential in the adaptive system in question, and the presence or absence of a neosympatric scenario must play a signiﬁcant role in determining which strategy is actually invoked. In general, however, polymorphism will tend to arise in the sympatric situation (often to some extent via cladogenetic capacity), and speciation will occur in the neosympatric state, via cladogenetic potential (Fig. 35).

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FIGURE 35 Links between plesiosympatry and neosympatry and minor versus major cladogenesis.

A general summary of the differential between different levels of cladogenesis can now be made: Postspeciational divergence

Minor (phenocladogenesis)

Major (genocladogenesis)

Intraspeciﬁc gene pool origin, evolving in plesiosympatry One to several allelic differences Domain of negative heterozygosis Hybrid viability predominates in resolution Partly via domain of cladogenetic capacity

Interspeciﬁc gene pool origin, Interspeciﬁc competition evolving in neosympatry Multiple allelic differences (No hybrid state) Domain of negative heterokaryosis — Free, adjacent niche space predominates Domain of cladogenetic potential

Further progress into adjacent niche space Involves both cladogenetic and anagenetic potential

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The above will, however, require some modiﬁcation in light of the strictly allopatric model of the speciation process (see below).

MODELS OF THE SPECIATION PROCESS Speciation identiﬁes irreversibility as a further propensity in realized major cladogenetic potential (bearing in mind the manner in which the dominance system of minor cladogenesis may presumably break down in the event of a reversal in the selection interface). How speciation actually occurs is a question that cannot be easily answered in terms of a single universal model, and the solution is consequently pluralist in nature. We have already considered the possibility of speciation occurring in allopatric divergence in prezygotic isolation mechanisms, either intrinsically or as a result of subsequent sympatry rejoin, and these are clearly quite different processes. In particular, speciation in the neosympatric state is clearly an actively evolved process, whereas speciation through evolution of a barrier in prezygotic isolation in the allopatric state is a corollary of activity occurring in such mechanisms as the speciﬁc mate recognition system, as argued by Paterson (1985). Unfortunately, the prospect of a unifying principle emerging from this overview has been much marred by the polarized stance taken by some supporters of both sides of the argument, as has often been the case in the past with many other aspects of evolutionary theory. In this context, it should also be noted that Dobzhansky and Mayr did in fact recognize the signiﬁcance of divergence in prezygotic isolating mechanisms in their speciation theories. Criteria for evaluating the relative signiﬁcance of these two seemingly ‘‘rival’’ hypotheses may also contain hidden difﬁculties; for example, good evidence exists for the predominance of sexual selection in the speciation process (see Chapter 15), but this does not necessarily help discriminate between the two main models that have been proposed!

The Reinforcement and Speciﬁc Mate Recognition Models Following Dobzhansky’s (1937a) theory that species formation is due to development of reproductive isolating mechanisms evolved in response to hybrid depression, Mayr (1942) proposed the biological species concept, which held that ‘‘species are groups of (actually or potentially) interbreeding natural populations that are reproductively isolated from other such groups’’ (also Mayr, 1963: ‘‘Species are not deﬁned by the fertility of individuals but by the reproductive isolation of populations’’). Mayr (1982) later revised the biological species model to incorporate the adaptive niche concept, a move that was attacked by Hengeveld (1988) on the grounds that the latter is typological and undeﬁnable. However, this criticism can surely now be met from the standpoint that the adaptive equilibrium of a species is complementary to a suite of niche parameters that are nonidentical with those of any other species, and which reside in adaptive capacity linked to the architecture of the gene pool (see Chapter 5).

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Dobzhansky also discussed the question of whether speciation occurs through isolation derived from a by-product of the accumulation of genetic differences between races or through active selection for reproductive barriers in the neosympatric state, citing good evidence for the latter theory, particularly in the context of reinforcement of preexisting partial barriers developed in allopatric populations. Where the cladogenetic force is linked to incipient, neosympatric gene pools, resolution has reached maximum expression when gene ﬂow between gene pools approaches zero, and the speciation process has been manifested. The boundary of the gene pool must be determined by isolating factors arising in all dimensions within the selection interface. In particular, hybrid states will tend to be negatively adaptive as a function of the genetic distance between parental genotypes and kin, and sexual selection must both similarly act negatively against remote genotypes, the result being that these and other factors will tend to erect active behavioral barriers against gene ﬂow between dissimilar incipient gene pools. Such mechanisms are obviously of paramount importance in understanding the speciation process. In the Dobzhansky–Mayr model then, prezygotic gene pool isolating mechanisms are presumed to evolve actively in order to eliminate a passively evolved negative hybrid class. Such nonviability does not necessarily lie in the structural domain, since many ‘‘biospecies’’ are known to be capable of producing hybrids (and the adaptive state of the hybrid class is, in any case, by no means limited to morphogenetic nonviability). Species isolating mechanisms (whether behavioral, structural, or metabolic) are viewed here as forming part of the adaptive response to viability deﬁciencies in the hybrid state as it relates to the natural environment. That alternative routes to the speciation mode are also possible is certain, and it is now necessary to consider other perspectives on speciation. Paterson (1985) rejected the Dobzhansky–Mayr synthesis, deﬁning species as the most inclusive population of individual biparental organisms which share a common fertilization strategy, the speciﬁc mate recognition system, which latter evolves in allopatry independently of any need for any input from the postzygotic mechanisms visualized by Dobzhansky and Mayr as forming an integral part of the biological species concept. Paterson also criticized the Dobzhansky–Mayr view of the mechanisms underlying the biological species concept on the grounds that isolation was reputedly regarded by these authors as constituting ‘‘the primary function of traits deﬁning a species.’’ However, as King (1993) points out, isolating mechanisms are regarded as being a product of geographic isolation and not a causal mechanism for production of species. Paterson thus assumed that in the biological species concept, postzygotic reproductive isolating mechanisms are selected for, which is not the case; as stated by King (1993), they are selected against. King also stressed the obvious importance of chromosomal change in promoting speciation as evidence in favor of the usual interpretation of speciation mechanisms implicit in the Dobzhansky– Mayr model. However, evidence for and against the speciﬁc mate recognition hypothesis often tends to be open to more than a single interpretation, and some of the data could be used alternatively to support either view! (See Lambert and Spencer, 1995, for a range of opinions in this area).

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Profound genetic differences exist between certain Australian Rattus species (Baverstock et al., 1986) including chromosomal traits, but laboratory hybrids manifest increased vigor. Would some species hybridize in the wild if they became sympatric, and would the ‘‘more vigorous’’ laboratory hybrids survive in a natural environment? Different answers to such questions could either support or oppose the Paterson model. The dichotomy between the Dobzhansky–Mayr and Paterson hypotheses has clearly become linked to the differential between the relative importance in the speciation process of prezygotic as against postzygotic isolation mechanisms. Maynard Smith (1998) discusses this problem, comparing what he terms the reinforcement hypothesis (genetic divergence in allopatry reducing viability and/or fertility of hybrids, following Dobzhansky–Mayr) with the recognition in allopatry model (prezygotic isolation evolving rapidly in allopatry, independently of hybrid depression factors arising in subsequent neosympatry, following Paterson). In this context, Maynard Smith reviewed evidence from the work of Coyne and Orr (1989), who carried out tests on 118 species pairs of Drosophila, measuring genetic distance on the basis of number of amino acid substitutions plus degree of hybrid inviability or infertility and prezygotic isolation. The ﬁndings of Coyne and Orr were as follows: • Mating discrimination, sterility, and inviability all increase gradually with time, as a function of genetic distance. • For allopatric species pairs, pre- and postzygotic isolation evolve at similar rates. • For sympatric species, prezygotic isolation evolves more rapidly. Maynard Smith concluded that, on the whole, the data in question tend to support the neosympatry–reinforcement hypothesis, more than they do the speciﬁc mate recognition system model. In particular, the recognition in allopatry hypothesis would predict a greater degree of prezygotic isolation mechanisms evolving in allopatric species, whereas this factor is actually more evident in sympatric species pairs. Proponents of the Paterson model tend in contrast to stress the many uncertainties surrounding the observed behavior of hybrid zones between supposedly speciational gene reservoirs, although apparently failing to give due consideration to the prospect of total niche intersect between gene pools. It is instructive at this juncture to compare the speciﬁc mate recognition system option with the fundamental cladogenetic selection interface and to ask whether the former could actually be a direct derivative of the latter, rather than a completely independent option. It could be argued that the speciﬁc mate recognition mode of speciation might be derived from a niche dichotomy which was originally a subset of some larger, preexisting anisotopic selection interface in a eurytopic gene reservoir with a wide distribution. Evidence for this lies in the fact that mate recognition itself is partly based on niche differentials linking to mate search and/or chance encounter activity (as is perhaps evident in cases where laboratory matings succeed and natural ones do not occur). Minor cladogenesis could thus feed into major, as the spatial component gravitates

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toward allopatry for certain gene pools. Where dominance would constitute a solution in the sympatric situation, allelic substitution would tend to evolve in allopatric populations, and this could affect either future propensity for generation of hybrid depression or divergence in the speciﬁc mate recognition system: Koopman (1950) destroyed marked hybrids between D. pseudoobscura and D. persimilis in each generation and was successful in increasing reproductive isolation over n generations. Kessler (1966) repeated this experiment, but chose from observed mating frequencies on the basis of mating choice, obtaining both high and low isolation lineages. Most signiﬁcantly, Dobzhansky (1970) interprets these experiments as working on preexisting mechanisms. Wallace (1954) and Knight et al. (1956) initiated ethological isolation between two strains of Drosophila melanogaster that had previously exhibited no mating discrimination, uncovering a weak yet statistically signiﬁcant preference for homogamic matings over about 30 generations. The interpretation offered here is that the facility for reproductive isolation observed in the above experiments must have been part of adaptive capacity in the ﬁrst place, so that the raw material of species isolation probably lies latent within the boundaries of adaptive capacity. The question of variability in prezygotic species isolating mechanisms thus becomes crucial to an understanding of the relationship between what seem to be two quite different models of the speciation process. It is perhaps signiﬁcant that Paterson did in fact regard courtship related characteristics as being rigidly deﬁned throughout the range of a species—a view that must remain controversial in view of the work cited above. Taking a much wider view then, speciation could be regarded as being that mechanism by means of which reproductive isolation between gene pools is either actively or passively established in the binary resolution of a major cladogenetic selection interface, and we must begin by assuming that a propensity both for hybrid depression and for effective divergence in prezygotic isolation mechanisms might be present to some degree in the adaptive capacity of a gene pool entering a cladogenetic selection interface. Given the existence of some plasticity with respect to prezygotic isolation factors, followed by occurrence of neosympatry associated with a certain degree of negative hybridization, the system would naturally tend to evolve away from the latter and toward the nonhybridizing element in the gene pool. In this way, the dynamics of the anisotopic selection interface may often tend to be inﬂuenced jointly by endogenous and extrinsic forces, according to the existing variance in both pre- and postzygotic mechanisms. In this view, there may then be a complete spectrum of speciational substrates between the ‘‘pure’’ Paterson model on the one hand, and the Dobzhansky–Mayr model on the other. The speciﬁc mate recognition system itself may thus be partly a function of cladogenetic capacity, in that some degree of prezygotic isolation may evolve in contiguous gene pools:

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Certain ‘‘races’’ of insect species are attached to certain food plants, but they are not speciﬁcally distinct from other populations with a slightly different habit. Outcomes of the Paterson model also do not necessarily predict speciation. Where (as has been claimed) the speciﬁc mate recognition model produces new species with no fundamental niche divergence with respect to limiting factors, the likely outcome will be cladogenetic substitution in neosympatry, following the tenets of the competitive exclusion principle. Alternatively, if two species are only separated by the speciﬁc mate recognition system, and if substitution does not occur, there may well be a devolution of species isolation between them, manifested in racial merging. A further possibility may of course be that niche divergence could sometimes constitute a purely postallopatric isolation phenomenon, and then the speciﬁc mate recognition system would be operating quite independently of any link to the reinforcement model. However, where taxonomically ‘‘good’’ species do meet and hybridize in nature, there appears to be no ﬁrm evidence that the speciﬁc mate recognition system has been evolving any faster than negative viability (a conclusion apparently conﬁrmed by the Coyne and Orr data). Consequently, if the speciﬁc mate recognition system does occur independently of the existence of a neosympatric selection interface, then this may be a relatively infrequent event, excepting perhaps where cladogenetic (species) substitution is invoked. A General Model of Speciation Summarizing the above in a general model of speciation, under the S (geographic space) condition, there may be genome splitting, under two possible regimes: 1. Neosympatric state: Genome splitting occurs via reinforcement, as an adaptive response to cladogenetic drive in hybrid depression. 2. Allopatric state: Genome splitting occurs via ‘‘autospeciation’’ (⫽ allopatric speciation sensu stricto, for example, via the speciﬁc mate recognition or equivalent mechanism). Thus, summarizing all possible outcomes, we have the model shown in Fig. 36. It should also be understood at this point that allopatric speciation (sensu novo) encompasses not only the speciﬁc mate recognition model, but also any other components of prezygotic isolation which possess the potential to achieve total species isolation. With respect to the actual question of species deﬁnition, we should take the view of Butlin (1987), ‘‘Species should be deﬁned by the absence of gene ﬂow, whatever the characters responsible for its prevention.’’ In addition, we must not confuse validity of any theoretical species concept (concerning the manner in which species are formed) with taxonomic questions relating to how they are deﬁned in actual practice! Nor should any ‘‘general’’ model of speciation overlook the deep dichotomy between animal and plant systems, with particular regard to the propensity for raising barriers to reproduction through courtship behavior in animals, as well as to the much greater capacity for viable hybridization and speciation via polyploidy found in plants (Stebbins, 1988).

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FIGURE 36 Manifestations of cladogenesis in different conﬁgurations of gene reservoir niche space.

Sympatric Speciation Mayr (1942) dismisses sympatric speciation other than for polyploids, although Maynard Smith (1966a) seriously considered the possibility of genetic potential for this to occur. A large part of the problem surrounding sympatric speciation of course lies in the extent to which ‘‘allopatric’’ also means geographic isolation. Examples such as the Lake Victoria cichlid ﬁshes (and others) show that this question is not easily answered: Evidence for sympatric speciation can be difﬁcult to distinguish from the ‘‘microallopatric’’ model, even in the presence of molecular data, as, for example, concluded by Reinthal and Meyer (1997) with respect to their data on Cichlidae. The behavioral plasticity of many cichlid species allows considerable niche overlap to exist in Nature (Greenwood, 1981). However, it is unclear to what extent this constitutes a postspeciational development. Kondrashov and Mina (1986) deﬁne sympatric speciation in terms of probability of mating dependent on genotype only, with the intention of removing the semantic argument from the question as to what ‘‘sympatric’’ actually means. As Futuyma (1998) points out, allopatry must be deﬁned according to severe reduction in movement of individuals or of their gametes and not by geographic distance. The parapatric model (see King, 1993, for a discussion) considers environmental as against purely geographic divergence. The Maynard Smith model of sympatric speciation (1966a) has ‘‘disruptive selection’’ determined by some loci while reproductive isolation is affected by others, a system which requires ‘‘linkage disequilibrium’’ between selected and isolating loci to operate (see Chapter 13). This would in fact only be possible

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if the cladogenetic selection interface also formed the leading effect phenon cluster—and there may be good reasons to suppose that this is an unlikely scenario, in that a leading effect in the anisotropic (as against anisotopic) selection interface is likely to be the most frequent conﬁguration. White (1968) reassessed the view that sympatric speciation demands the spread of mutations which would be deleterious (namely, those involved with preventing mating, or rendering this fruitless) with particular respect to chromosomal as against ‘‘point’’ mutations. Mechanisms of sympatric speciation have thus been linked to chromosome breakage and reorganization: White and others (see White, 1968) studied 160 segregates of Moraba viatica and M. scurra superspecies of grasshoppers in which semispecies with different karyotypes occupy adjacent territories. Races of the M. viatica group contain chromosomal fusions, inversions, plus a translocation. Signiﬁcant reduction in male fecundity has been found in hybrids collected in nature, presumably having evolved subsequently to the original chromosomal mutations. The allopatric model has been rejected for the M. viatica group, and White proposed stasipatric divergence occurring through ‘‘meiotic drive’’ on the basis of some hypothetical segregational advantage in the egg, so that speciation (or at least raciation) might thus be driven by ‘‘endogenous chromosomal activity).’’ An endogenously driven model of sympatric speciation of the above kind has found little favor, however, appearing unlikely unless there are other advantages in chromosomal rearrangements. White (1968) believes that over 90% of all species differ in chromosome traits and that the latter are causal to speciation. Carson (1982) disagrees with this conclusion, arguing that chromosomal reorganization should be seen as part of the speciation process. It is nevertheless possible that the cladogenetic phenon cluster could become the leading effect in the face of chromosomal change, especially since it seems likely that the latter may usually be linked to leading effect allomorphism of the exclusively spatial kind in the ﬁrst place. That is to say, chromosomal change is positively selected through extrinsic demands of an anisotopic selection interface, with no temporal element being involved, and thus with no need to invoke any ‘‘endogenous ﬁrst cause’’ (see also Chapter 3). Although no great problem exists with acceptance of the view that chromosomal change forms a signiﬁcant component of postzygotic isolation, it does, however, seem unlikely that this can form part of any viable model for sympatric speciation in the absence of other factors discussed by Maynard Smith (see above).

The Postspeciational Selection Interface The initial stages of speciation may frequently be behavioral–metabolic, with little or no anagenetic separation (as with ‘‘sibling species’’), whereas other manifestations of cladogenesis may affect major structural divergence involving longer term changes expressed in the postspeciational domain. A selection

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interface thus clearly also exists between discrete species. There must therefore be two different types of cladogenetic selection interfaces, one tripartite (with a hybrid state), the other bipartite. The latter relates to that component of cladogenetic activity which continues beyond the species isolation event itself (and even beyond subsequent speciational bifurcations) and which thus constitutes true postspeciational cladogenesis. In addition, two species may diverge on the basis of characteristics that formed no part of the original cladogenetic interface, and we should therefore conﬁne the term postspeciational divergence to the converse situation. Finally, there may also be a cladogenetic selection interface between nonsister species (even between remote lineages), when a limiting resource comes to be shared by unrelated organisms. This situation cannot be deemed to form any part of postspeciational divergence (sensu lato) and must be construed as part of species selection (see below). Following the concept of the postspeciational selection interface, we also identify a higher level of divergence, in that not all speciational change is substructural or ‘‘ambient’’ in nature. Ambient versus Renschian Cladogenesis The macroevolutionary aspect of cladogenesis clearly belongs partly in the postspeciational and transspeciational domain, as a corollary of the rare coincidence of qualitative niche shift and iterated neomorphic change in structure. We must therefore now distinguish between ambient and Renschian modes of cladogenesis, the former constituting a purely microevolutionary expression of cladogenetic activity in the context of a predominantly substructural mode of species divergence, the latter being linked to postspeciational divergence plus anagenetic change (see also Chapter 8). Above all else, the diversity of cladogenetic activity underlines the limits of adaptive capacity in general, so that adaptive potential clearly now requires a more detailed analysis. We conclude by asking the question, what is the function of cladogenesis in general in the evolution of adaptive systems? The answer lies at least partially with resolution of antagonistic forces in the anisotopic selection interface. Allomorphism thus lies at the root of all cladogenesis, although only major (genotypic) cladogenesis has a very large effect on the topology of macroevolutionary change. Species Selection We must also consider the interspeciﬁc selection interface in the light of problems that have been raised concerning confusion with ‘‘group selection.’’ Eldredge (1989) has discussed the conceptual difﬁculty in regarding species selection as a direct, ‘‘higher level analogue of natural selection,’’ namely, in that species cannot be regarded as being interactors in the sense that individual organisms are. However, Eldredge nevertheless insists that group level effects do in fact occur: ‘‘It is to be stressed at this juncture that species as wholes do not participate in interspeciﬁc competition.’’ Following the criticism of group selection by Williams (1966), it is quite clear that such factors can only emerge as a corollary of individual level selectional activity. Eldredge supports his claim by proposing that ‘‘spatiotemporal localization qualiﬁes as a heritable and species level emergent character, thus posing a possibly valid example of

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true species selection.’’ For example, if a new species becomes fully sympatric with an old one (as is in fact the case with many real examples), then interspeciﬁc competition may well result in extinction (or pressure for change) of one or both species involved. However, this does not occur as a result of group selection in terms of any trait that was originally selected as having been advantageous to a group entity, but as an emergent corollary of some negative competitional propensity that is manifested at the genic (individual) level. Clearly, the familiar competitive exclusion principle applies to interspeciﬁc competition, and indeed, the niche of one species may simply be a subset of that of another (as distinct from the less probable scenario of expressing exact niche coincidence!). This situation clearly does not constitute a case for group selection in the sense that the latter has been widely understood in the past. Thus, we must accordingly accept species selection in terms of Eldredge’s emergent properties interpretation, in accordance with the effect hypothesis ﬁrst advanced by Vrba (1984). Species selection is thus only to be understood in the context of an interspeciﬁc selection interface which acts essentially as an emergent property of genic selection (see also Chapter 8). In contrast to some recent interpretations, the inﬂuence of species selection is not limited to cladogenetic substitution, but also extends into the domain of the postspeciational selection interface. Contrary to the view of Williams (1992), species selection does in fact also hold special status within the domain of ‘‘clade selection,’’ since it is here that reproductive boundaries begin to act to remove the signiﬁcant inﬂuence of hybrid depression or hybrid vigor from the architecture of the cladogenetic selection interface.

MAIN POINTS FROM CHAPTER 6 1. Cladogenesis derives from spatial dynamism in the selection interface, and can thus be analyzed via the anisotopic selection vector. 2. The cladogenetic selection interface describes selectional forces manifesting cladogenetic drive, as an expression of the balance between antagonistic centripetal and centrifugal elements of an anisotopic selection interface that is linked either to the niche intersect between competing genotypes of a neosympatric gene pool or to divergence in allopatry. 3. Cladogenetic drive contains both extrinsic and endogenous factors. The former lie in the niche intersect, the latter, in hybrid depression. 4. Cladogenetic capacity and cladogenetic potential can be identiﬁed in the innate capability of a gene reservoir for an appropriate adaptive response to a cladogenetic selection interface. Each has endogenous and extrinsic components—homeostatic adjustment is the leading endogenous factor, and free niche space, the predominant extrinsic element. Facility for reproductive isolation clearly constitutes the essential component of cladogenetic potential. 5. The sympatric cladogenetic selection interface can be modeled through introduction of factors representing shared and unshared K in the equation set of the adaptive system. Shared niche space lies in the selection interface, and unshared, in the adaptation interface alone.

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6. Realization of cladogenetic capacity and potential can occur at more than a single level. In the intraspeciﬁc domain, evolved dominance constitutes a ‘‘phenotypic resolution’’ of cladogenetic drive in the same way as speciation through reproductive isolation constitutes a genotypic solution. There are thus two principal domains for resolution of antagonistic cladogenetic forces: minor ( phenotypic) and major ( genotypic) cladogenesis, the latter constituting speciation itself. 7. There are two main models of the speciation process, the neosympatric (‘‘reinforcement’’) and allopatric (‘‘recognition’’) models. The former is better supported by the existing empirical data. A general model encompasses both. 8. Binary resolution of cladogenetic potential in speciation may at times manifest a major ‘‘axial–tangential’’ dichotomy between benign and hostile niche structures, and this can be of considerable signiﬁcance with respect to major lineage bifurcations. 9. Renschian cladogenesis, as manifested in the divergence of higher group lineages, is linked to a postspeciational selection interface (which may be punctuated by further ambient speciational events). Many Renschian cladogenetic events are linked to a divergence between benign and hostile niche regimes. 10. Species selection does not constitute any form of ‘‘group selection,’’ but arises as an emergent corollary of genic selection. In this context, species selection has a highly signiﬁcant role to play in evolution.

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ADAPTIVE POTENTIAL It has already emerged that the concept of adaptive capacity is clearly an inadequate explanation of the adaptive response as manifested beyond the domain of adaptive equilibrium and that the greater domain of evolution demands the existence of a higher sphere residing in adaptive potential.

Evolution and Adaptive Potential Manifestation of adaptive equilibrium in the structural adaptive response via perpetuated allomorphism does not constitute true evolutionary change in the adaptive system, implicating nothing more than a link to niche diversiﬁcation and changing selection polarity in the realization of adaptive capacity, in terms of preexisting and/or recurrent allomorphism. In contrast, evolution is concerned with the much larger question surrounding realization of adaptive potential, in which propensity for patterns of change extending beyond the domain of adaptive capacity must be manifested. We may at this point be tempted to restrict evolution sensu stricto to mechanisms which give rise to breakdown of gene ﬂow between gene pools, and this again would reiterate the functional boundary of adaptive capacity as being that existing between evolutionary and nonevolutionary modes of change in the adaptive response. However, it is essential to point out that some component even of intraspeciﬁc (minor) cladogenesis must surely belong to novel, as against recurrent mutation, so that ‘‘evolutionary’’ does not in fact

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translate simply as ‘‘transspeciﬁc’’ as against ‘‘intraspeciﬁc.’’ As we shall see also in the next chapter, not all iterative mutational change in the genome is necessarily ‘‘one way.’’ The essential deﬁnition of evolution therefore links to the dichotomy between adaptive capacity and potential, although the latter can clearly include microgenetic additions to the repertoire of adaptive capacity itself, as well to cladogenesis and anagenesis. A deeper analysis of adaptive potential is clearly fundamental to any understanding of the general theory of evolution, as well as of the links between several ‘‘special’’ theories that have been proposed in the past. Of special interest, here, is the contribution of Thompson (1917), who was the main architect of one signiﬁcant special theory that has attracted closer attention only in recent years. The adaptive systems approach allows us to look at these problems within the uniﬁed concept of adaptive potential. Limits of Adaptive Capacity Speciational change clearly cannot be wholly derived from adaptive capacity, nor can much postspeciational change belong in that domain. While realization of cladogenetic potential may occur in the substructural domain (for example, via behavioral change), much speciation clearly also involves structural differentiation, and it is in the latter scenario that we encounter the problem of adaptive potential in its widest horizons: Thoday and Boam (1959) selected for low and high sternopleural bristle number in Drosophila melanogaster, with 50% gene exchange between two populations at each generation. The difference in bristle number between the two lineages gradually increased, owing in fact to only two genes on chromosome II. This differential must have been concealed within adaptive capacity in the ﬁrst place, such propensities presumably reaching realization through recombinational changes or recurrent mutation (or a combination of both). Although the concept of adaptive capacity can thus demonstrate a certain degree of propensity for iterative change to the phenotype, this gives no indication of how major anagenetic changes can occur. Large scale evolutionary events must involve fundamental changes to the structure of the preexisting genome, frequently linked to iterative changes in phenotypic structure which facilitate radical modiﬁcations to body plan of a kind that cannot possibly lie within the domain of adaptive capacity. Such changes clearly indicate movement toward some distant goal, apparently thereby manifesting an apparent element of directionalization in evolution: Although artiﬁcial selection can expand variance within a range, a plateau is reached beyond which no further progress can be made, so that change via recombination/recurrent mutation clearly only operates within a certain limited domain. The usual explanation for this is that ‘‘the store of variation is exhausted’’ (that is to say, adaptive capacity has been fully explored ). Mather (1953; and others) stated that several ‘‘selection plateaus’’ of this kind may occur in nature, owing to a

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gradual recombination of tightly linked genes through crossing-over and through novel mutation. These observations serve to illustrate the importance of neomorph mutation in adaptive potential. Thus, although some part of ambient speciational divergence may be accounted for via mutation within genes linked to the adaptive capacity in dynamic equilibrium, major anagenetic change cannot be explained through recombination and chromosomal rearrangement alone. Adaptive potential must therefore concern additional genetic mechanisms plus a propensity for iterative morphogenetic directionality, whenever large scale genetic and structural transformations occur during longer term evolution. In summary, many potentially attainable structural states lie well beyond the limits of adaptive capacity and beyond the bounds of probability of realization through simple allelic recombination and ‘‘ambient–recurrent mutation’’ of existing genes. Since adaptive capacity is the innate ability of the organism to adapt (endogenous component) or of the external environment to be adapted to (extrinsic component), there must similarly be a larger structure expressing the relationship between existing adaptive capacity and possible states containing potential for major topological change in the structural component of adaptation—and clearly it must be this latter domain which constitutes true adaptive potential. Where periodicity of selection proﬁle is much greater than average ambient speciation time, niche parameters linked to the isotropic selection proﬁle may permit iterative change toward a more distant structural state, thus linking to realization of adaptive potential. Where an isotropic selection interface exists, there is therefore a probability that iterated change in the genome could lead to improved levels of adaptation in terms of phenotype changes which lie far beyond the domain of existing adaptive capacity. Adaptive Potential and Prospective Adaptation or Evolutionary Competence It is perhaps axiomatic that adaptive potential must lie partly in a domain deﬁned by preexisting form, and this element has been investigated in terms of prospective adaptation (following Simpson) and evolutionary competence (following Stebbins). Simpson developed the concept introduced by Parr (1926) regarding the ‘‘prospective versus real’’ functions of organisms. In this context, adaptive potential can be viewed as being initially a function of adaptive shift in the behavioral domain (a vital concept that will be taken up at a later stage in the context of the relationship between adaptive shift and architecture of lineage in Chapter 17). In fact, this link between behavioral change and emergence of the structural domain in realization of adaptive potential further conﬁrms behavior as being ‘‘the realization function’’ for adaptation in general (see Chapter 1): Simpson discussed the signiﬁcance of prospective adaptation on the basis of such examples as the observation that vertebrate lungs developed in the aquatic environment, but were evidently an adaptational prerequisite for later evolution in the terrestrial domain, as initially

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mediated by behavioral change. In the same way, it is thought that the evolution of desiccation-resistant spores in aquatic algae may have constituted a vital preadaptation which allowed subsequent invasion of the terrestrial environment by plants (Thomas and Spicer, 1986). One component of the epigenetic dimension to adaptive potential therefore lies with hidden propensities of existing phenotype structure itself, and here we may identify behavioral change as a redirective force in the adaptive ensemble, with eventual corollaries for all levels of function. Prospective adaptation affords a ﬁrst indication of the nature of a directionalization component implicit in adaptive potential, while obviously at the same time offering little more than a superﬁcial view of a much larger structure. This particular mechanism should therefore perhaps be viewed as arising from ‘‘structure potential that is merely waiting for a behavior shift to happen’’ (see also Chapter 17)—although it must be clear that prospective adaptation has a proximal limit, in the same way that adaptive capacity does.

Components of Adaptive Potential As with adaptive capacity, it is presumed that separate endogenous and extrinsic components exist also in the domain of adaptive potential. The reality of this demands an understanding of a more complex array of mechanisms than those described by the concepts of the adaptive niche linked to Mendelian population genetics, including several important conceptual structures that were investigated by Thompson (1917). A fresh interpretation of the Thompsonian approach is explored below, and this aspect of adaptive potential will be further integrated into the general theory at a later stage (see Chapter 15). The Endogenous Component of Adaptive Potential in Morphogenetic Potential Within the endogenous domain of adaptive capacity, the logistic component centers largely on fecundity and behavior, while the structural component is closely linked to the variance of structure as deﬁned by the phenotype spectrum complementary to existing and recurrent allomorphism. Adaptive potential for complex morphogenetic change clearly cannot lie with mere ‘‘prospective adaptation’’ alone, nor in the preexisting complement of allelomorphic genes, but instead must concern a multidimensional relationship between genes, development, the preexisting phenotype, and adjacent morphosystems, linked to complementary adaptive potential existing in the external environment. Genes involved in this scenario will furthermore tend to be those which do not express major allelomorphism in the gene pool within the context of the ambient time frame. The attainable morphosystems of endogenous adaptive potential must be presumed to lie both close to the existing phenotype (the prospective adaptation component) and also in proximity to the architecture of existing developmental coordinates. In this context, we must consider the existence of a morphogenetic potential constituting that set of morphosystems generated by the entire range of possible conﬁgurations of the equation(s) controlling parameters of the growth curve for a given unit of phenotype

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structure. Clearly, adaptive potential must be linked to this morphogenetic landscape in some way. The concept of morphogenetic potential can be usefully explored with reference to one particularly well-known and illuminating example, namely, that of the logarithmic spiral curve as found in the protective shells of many molluscs and other animals: A spiral is described by polar coordinates: O ⫽ the pole, and a straight line starting at the pole and revolving around it is the radius vector. A point P moving along the radius vector under a given velocity then describes the ‘‘equable’’ spiral. A radius OP comprising successive whorls increases in arithmetic progression and will equal a constant quantity a multiplied by the number of whorls (given in effect by the angle of revolution, ␪), so that r ⫽ a␪. To connect this equation with the situation found in mollusc shells, it is necessary to consider a spiral in which the whorls gradually increase in width, owing to the fact that a constant acceleration supplements the velocity of movement of the point P. In this situation, the equation changes from r ⫽ a␪ to r ⫽ a␪. The equable (arithmetic) spiral now becomes the logarithmic or equiangular spiral. Thompson (1917) showed that generation of a logarithmic spiral could be explained in terms of a simple growth curve in terms of growth at a point P resolved into a force F acting along the line OP (see above) and a force T acting perpendicular to OP, with constant magnitude of each force. The resultant of forces F and T (PQ) makes a constant angle with the radius vector, the latter being a fundamental property of the logarithmic spiral. He also showed that the most fundamental intrinsic property of such a curve lies in the property of continual similarity (hence the observed association with organic growth). Above all else, this property of increase by terminal growth without change of form is exclusive to the equiangular or logarithmic curve. It is thus a unique class within that set of forms regarded as gnomonic.* There are several good reasons for choosing the log spiral as an exemplar for the adjacent morphosystems concept: ﬁrst, its status as the simplest gnomonic growth curve. Second, the morphogenetic potential of this curve has been computed (see below). Again, the realized frequency distribution of this particular morphogenetic landscape is also known for living and fossil organisms. Finally, the nonliving nature of the spiral shell might perhaps also hold the highest probability of providing evidence for or against a ‘‘nonadaptationist’’ interpretation of morphogenetic change (see Chapter 15). Before going on to look at this system in greater depth, it will be pertinent to add that a consideration of ‘‘geometric versatility’’ in development (Vermeij, 1974) does not automatically transmit into morphogenetic potential, since capacity for actual expression will depend on such factors as developmental modularity (see Chapter 12): * Following Aristotle, a ﬁgure added to a geometric shape such that magnitudinal change occurs without change of shape (see Thompson, 1917).

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Thomson (1988) following Holder (1983) notes that manifestation of tetrapod limb types has been consistent, both in what is and in what is not produced: ‘‘The simplest and most obvious element of constraint in this system is that where there is a strong axis of organisation, the medial digit will be the hardest to lose.’’ Thus, not all ‘‘geometrically possible’’ conﬁgurations are necessarily developmentally feasible. Wolpert (1971) has also pointed out that a geometrical understanding of form gives no indication of the developmental and biochemical mechanisms behind evolutionary change. Fortunately, however, the log spiral example seems, from actual observation, to lie close to a realistic morphogenetic landscape in terms of developmental potential also. Raup computed a range of molluscan shell morphotypes on the basis of different conﬁgurations of an equation describing the above logarithmic spiral, speciﬁcally in terms of the ratios of two radii originating in the center of the spiral (see Raup and Stanley, 1971, 1978, for a comprehensive treatment). He showed that within the considerable range of form generated by this equation, realized structure was concentrated around an adaptive optimum in which the ratio 1/W (W ⫽ square of ratio of radii) was equal to 2, and D (distance of aperture from apex) was equal to 0.35, thus with a pronounced bias away from biophysically weak designs in which successive shell whorls are not in contact (namely, where intrinsic strength and hydrodynamic stability are both low). Thus, while the entire range of spirals does seem developmentally attainable, only an adaptationally viable subset is actually realized in real organisms. Structure potential, as the endogenous component of adaptive potential, must therefore relate particularly to innate properties of the genome to encompass novel parameters in the structural adaptive response, such as those giving rise to the generating curve in the above example, thereby connecting to morphogenetic states which lie, not only beyond the limits of existing and recurrent allelomorphic systems, but also within the adaptationally positive range: At a more complex level, Simpson (1953) theorized that the ancestral mustelids did not have lutrine prospective functions in a static sense but in a dynamic one, having apparently been capable of being developed in the course of time. The same applies to the potential in early angiosperms for the independent acquisition of water conducting vessels in monocotyledons and dicotyledons (Takhtajan, 1954). Endogenous adaptive potential (structure potential ) may thus be postulated to reside in the adaptationally positive complement of morphogenetic potential lying beyond the boundaries of extant and recurrent gene-developmental systems, yet nevertheless having some relationship to existing structure through probability of realization via iterated genetic mutation. Thus, morphogenetic potential only becomes adaptive potential when we examine that subset of the former that is also adaptationally positive: The same concept is implicit in the ‘‘morphogenetic construction rules’’ of Oster et al. (1988), who deduced those parameters via which the vertebrate limb may and may not alter, in relation to a reaction– diffusion model for determination of form. Shubin and Alberch’s gen-

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eral theory of limb formation (1986) utilized the Oster et al. model to show that a great range of tetrapod limbs can be produced from generative rules of the limb ﬁeld. Goodwin (1984) discussed the ﬁndings of Maden (1982), who studied supernumerary limbs in the amphibian Ambystoma in which digit number varies from one to six, concluding that the limb ﬁeld of a single species is capable of generating a variety of basic skeletal patterns which is greater than that observed in the full range of tetrapod limbs: ‘‘Each organism carries within it the potential of creating a great variety of forms, for each morphogenetic ﬁeld is described by equations with many solutions which deﬁne a set of morphological possibilities.’’ Some of these outcomes are thus developmentally constrained, while others are ‘‘attainable, but adaptationally valueless.’’ As already argued above, our view of morphogenetic potential and its relationship to adaptive potential must be tempered with acceptance of the fact that theoretical range and actual range may be two different things, and that adaptive potential is further restricted to the positive component of the attainable morphogenetic landscape. Most signiﬁcantly for the question of realization of adaptive potential, the range of form generated by the log spiral curve (see above) constitutes a real, rather than hypothetical morphogenetic potential, and the relationship between this and real adaptive potential is also understood. Degrees of Freedom in Endogenous Adaptive Potential The extent to which an attainable morphogenetic potential may also generate a range of adaptationally positive phenotype states leads naturally to the concept of degrees of freedom in adaptive potential. Clearly, some arrays of generated morphotypes may contain a larger contingent of positive states than others, depending on the nature of structure and function in the involved trait: The concept of degrees of freedom in adaptive potential is linked to the question of ‘‘adaptational versatility’’ following Vermeij (1974), who cited an example in the branching patterns of angiosperms which apparently led to a much greater range of possible forms than in gymnosperms. Another exemplar of increased ‘‘adaptive versatility’’ lies with actinopterygian bony ﬁshes, in the freeing of the maxilla from the cheeks in the upper jaw, then in subsequent freeing from the ethmopalatine connection in holosteans—which in turn allowed unprecedented adaptive radiation of feeding types in the acanthopterygians. The Extrinsic Component of Adaptive Potential in Niche Potential Structural evolutionary change must also carry some adaptive advantage, and thus the extrinsic component of adaptive capacity was framed in terms of parameters of the niche interface (see Chapter 2). This niche capacity is largely a dynamic structure for periodic niche parameters. Consequently, the greater domain of adaptive potential must, in contrast, relate to nonperiodic niche parameters manifesting an isotropic selection proﬁle (see Chapter 4). The ex-

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trinsic component of adaptive potential must consequently relate in part to free, adjacent niche space lying near the boundary deﬁned by the constraints of existing adaptive capacity. This need not, however, involve qualitative niche shift. Niche potential can be merely a larger, inaccessible biomass within the domain of the existing adaptive niche—or else, most signiﬁcantly, an improvement in the way the existing niche is exploited via ‘‘niche intensiﬁcation’’ (see Chapter 6). The extrinsic component of adaptive potential may thus relate to free, accessible niche space, or else capacity to expand in the domain of niche hyperspace. Unlike niche capacity, however, the emphasis must clearly lie with the isotropic niche proﬁle. Adaptive potential is now visualized as being the sum of structure (endogenous component) and niche (extrinsic) potentials, in the same way as adaptive capacity is derived from endogenous and extrinsic components—capacity and potential being distinguished by the boundaries of attainable morphosystems within the existing genetic complement for the endogenous component, and frequently also by existing, as against free, adjacent niche space for the extrinsic component. These elements are of course further linked to the isotropic (as against dynamic) selection proﬁle. The quasi-inﬁnite nature of resources such as ‘‘aerial environment’’ also indicates the importance of sub- and hypoparametric niche space in this (see Chapter 2). Evolution can therefore proceed through functional or qualitative change in niche or by niche intensiﬁcation, and this must constitute a fundamental dichotomy (see Renschian cladogenesis, adaptive shift and function shift). Adaptive potential seems likely also to engender a major directionalization function (see below), owing to the intersect between degrees of freedom in structure potential and niche potential.

ADAPTIVE POTENTIAL, BIOPHYSICAL PARADIGM, AND STRUCTURAL ATTRACTOR The adaptive response cannot ‘‘direct itself.’’ What factors, then, do direct long-term iterative evolutionary change? Directionality must lie primarily in the isotropic selection vector (see Chapter 4), but what is the source of this directionalization inﬂuence? The answer can be shown to lie in a dialogue between two major elements: the biophysical paradigm for a given adaptational function, and the endogenous component of adaptive potential. These factors formed part of a heterogeny of mechanisms studied by Thompson (1917), who did not, however, clearly distinguish between different components nor seek to integrate his own theoretical work with the Darwinian synthesis. The most signiﬁcant elements in the Thompsonian special theory are those which plead for an ‘‘internal force’’ directing evolution. What is the true signiﬁcance of this phenomenon?

The Biophysical Paradigm Concept The structure–function paradigm approach of Rudwick (1964) can be linked to analysis of directionality in terms of the iterative selection interface, linked to the directional component of exogenous adaptive potential. Although Rudwick

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considered his adaptational paradigm as a basis on which interpretation of structural states of unknown function could be made, we can more usefully invert Rudwick’s concept by asking which structural state would, in view of the fundamental physical laws, serve a prestated functional demand? This particular approach identiﬁes the biophysical paradigm concept. As we have seen already, the endogenous component of adaptive potential can only be understood in terms of selectively positive changes to structure. Positively selected changes clearly must enhance the adaptive state within the context of the external selection interface, and structure must therefore be capable of incremental progression in some absolute, biophysical sense. In any understanding of the organization of the biophysical paradigm, the ﬁrst principle must therefore be that the topology of major structural change must also agree in its adaptational role with what Thompson termed ‘‘a special subset of the physical laws.’’ The biophysical paradigm is now deﬁnable as being that structure which maximizes functional efﬁciency relating to a speciﬁc demand determined by the external adaptation interface, as constrained by some subset of the fundamental physical laws relating to intrinsic limitations peculiar to organic structure. In this concept, we also witness a fundamental axiom concerning organic adaptive systems, namely, that their behavior is bound by the tenets of Newtonian physical laws. As indeed argued by Pennycuik (1992), ‘‘At the intermediate scales of biology, Newtonian physics still works as well as it ever did’’: The essential parameters of a structure for the function of ﬂight must include factors such as an aerofoil surface capable of providing lift that is suitably powered by an appropriately designed skeletomusculature system, linked in turn to essential propensities of metabolic rate and ventilation of the respiratory system. The biophysical paradigm concept links to adaptive potential in the sense that it is the major determinant factor of directionality in the isotropic selection vector for iterative variation–selection interactions. A given structure needs to fulﬁll some adaptational function in the adaptive system. There is thus a large input from the fundamental physical laws, in the way these relate to biological systems, and the architecture of organic superstructure must take into account various factors which effectively act as ‘‘universal constants’’ in adaptive systems. It must also be made clear, at this juncture, that biophysical limits should not be confused with ‘‘geometric limits’’ (Simpson, 1953): Lull and Gray (1949) showed that D’Arcy Thompson’s morphological transformations often cannot be extrapolated beyond a certain intrinsic limit. The concept of limits may thus be confused. ‘‘Geometric limits’’ are of no concern for the analysis of evolution, whereas those of biophysical systems most certainly are. Simpson correctly reasoned that there are also mechanical limits (for example, upward limit to size change): ‘‘Often when a trend stops, it has reached an inherent or mechanical limit.’’ It is essential to realize also that a close relationship exists between the biophysical paradigm concept and that of extrinsic adaptive potential, in the same way

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as extrinsic adaptive capacity was linked to the adaptive niche at an earlier stage (see Chapter 2). Degrees of Freedom in the Biophysical Paradigm Degrees of freedom exist not only in endogenous adaptive potential, but also in the biophysical paradigm, a fact that is most strongly overt in the extreme convergencies which occur between remotely related lineages with respect to certain organ systems, namely, where the number of degrees of freedom is apparently very small: Convergence between compound eyes of the superposition type in different higher groups is so extreme that it is said to be virtually impossible to tell one phylum from another from isolated histology sections (Nilsson and Osorio, 1998). This demonstrates how tight functional constraints can be, and how precise the evolutionary response to them can be. Alexander (1983) discusses similar narrowly deﬁned structural paradigms in the design of aerofoils and hydrofoils. Some of the most fundamental components of adaptive systems may in fact possess no degrees of freedom whatsoever. Rensch (1959), for example, listed 20 essential requirements of living systems: the necessity of being carbon based and requiring the properties of colloidal proteins, having to evolve within a certain temperature range, etc. Conversely, some biophysical paradigms may be much more loosely deﬁned, including, for example, those that are fractal in nature (following Mandelbrot, 1977), as with many absorptive surfaces in respiratory and digestive systems (see Pennycuik, 1992).*

The Structural Selectional Attractor The attractors of adaptive systems have really only been clearly understood in terms of the logistic domain (e.g., as with that situation where several initial states converge on a single stable one in the context of the Verbulst equation). Structural attractors clearly emerge in a similar manner in the context of selectional interactions linked to logistic mechanisms and structural variation residing in evolving adaptive systems. Accordingly, biophysical paradigms for structure can be likened to both stable and dynamic logistic attractors, the former being more analogous in topology to the Verhulst than to the May equation, while in the same way, adaptive equilibrium can be used to illustrate structural systems which resemble dynamic logistic attractors of the foregoing kind. The overall view is that the stable biophysical paradigm state is a structural selectional attractor emerging from iterated selectional activity in the adaptive system. The biophysical paradigm, in its role as the fundamental structural attractor, clearly determines which changes are adaptationally positive and which are not, whereas the endogenous component of adaptive potential determines which changes are likely to actually occur. Thus it should be clear even at this * Although the contribution of fractal geometry is probably low in terms of most higher group traits, its signiﬁcance may nevertheless be profound in certain other respects (see p. 133).

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stage that ‘‘degrees of freedom in adaptive potential’’ is a meaningless concept in the absence of complementary freedom in the biophysical paradigm. Directionality in this interaction thus lies in the intersect between degrees of freedom in the biophysical paradigm and in the structural component of adaptive potential, the outcome being a selectional attractor which invokes a directionalizing element in the context of the isotropic selection vector. This now identiﬁes the (real) structural attractor of the adaptive system (see Chapter 1) as a multidimensional entity lying in the intersect of the structural component of adaptive potential with the biophysical paradigm.

FIGURE 37 Relationship between degrees of freedom in endogenous adaptive potential and biophysical paradigm and the structural selectional attractor.

In Fig. 37, ‘‘degrees of freedom in biophysical paradigm’’ is equivalent to ‘‘number of ways a function could be carried out,’’ and those in endogenous adaptive potential concern ‘‘the range of selectionally positive morphosystems actually within reach.’’ That part of the biophysical paradigm excluded from the structural attractor thus consists of ‘‘unattainable states,’’ while the excluded domain of adaptive potential amounts to ‘‘potential to actually expand the existing extrinsic niche interface.’’* It is thus now possible to expand Thompson’s ‘‘special subset of the physical laws’’ (see p. 129) by adding ‘‘as deﬁned by constraints imposed by the limits of adaptive potential.’’ The structural attractor thus deﬁnes the directional input and the selection interface, the magnitudinal input to an isotropic selection vector directionalizing the iterative adaptive response (see Chapter 4). The biophysical paradigm clearly determines a fundamental orientation in the architecture of the selection interface during longer term, iterative change * Endogenous adaptive potential and degrees of freedom in the biophysical paradigm are (quite artiﬁcially!) assumed to be of similar magnitude in Fig. 37.

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in evolution, and in this, adaptive potential also has a directionalizing inﬂuence on the structural attractor. With respect to the actual directionality of iterative selection interactions, it is easy to see that ‘‘multiple initial solutions’’ at the locus of a novel adaptive shift (see Chapter 17) will generally tend to become one or a few as the structural adaptive response proceeds. We may now draw together our earlier deﬁnitions of the extrinsic and endogenous factors and deﬁne the totality of adaptive potential as constituting a relationship between the preexisting adaptive state and a higher one reﬂected in the biophysical paradigm for a given function, as constrained by the probability of the existing genome being able to progress toward this ideal by virtue of neomorphic mutational change. To what extent does the concept of the structural selection attractor reﬂect the inﬂuence of so-called orthoselection? In the context of this perplexing question, Williams (1966) has stated that ‘‘selection has no eyes for the future.’’ However, the structural attractor apparently constitutes just such a mechanism. In this, it should nevertheless be noted that Williams’s view that the goal of an individual’s reproduction is to maximize representation of its own germ plasm relative to that of others in the same population is in no way contradicted by the concept of directionality via the structural attractor of the adaptive system, and movement toward a distant adaptive state is simply a complex evolutionary corollary of genic selection arising from intrinsic properties in the greater adaptive system. The Dimensional Spectrum of the Structural Attractor The structural attractor clearly manifests a dimensional spectrum. That is to say, it expresses a range of dimensional conﬁgurations according to absolute size, within a range deﬁned by the endogenous adaptive potential of the genome in question. This happens in certain superstructures, owing to the presence of such inﬂuences as the relationship between area and volume as size changes, and to the interaction between gravity and biophysical mechanisms: Certain surface area to volume ratio constraints affect design, for example, those connected with heat gain or loss and those connected with surface structures such as cilia (see Reiss, 1989). Biomechanical aspects of the dimensional spectrum are of particular interest in the context of the Simpsonian adaptive zone concept (Chapter 17) and also serve as a useful exemplar of the interactive roles of extrinsic and endogenous factors in the determination of selectionally favored pathways of morphogenetic transformation (see Chapter 15). Although the dynamic behavior of biophysical paradigms can perhaps most easily be construed in terms of biomechanical factors, their true domain is universal. The link with metabolism can, for example, be amply illustrated in the relationship between absolute size and metabolic rate: According to Kleiber’s law, many biological variables tend to increase or decrease by body mass raised to the power 1/4 or 3/4, in which the relationship with metabolic rate is of fundamental signiﬁcance. Here, Kleiber’s law is known to hold for 27 orders of magnitude, from the

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subcellular level to the dimensions of a blue whale. Increase in surface area compared to volume as a function of linear measure clearly predicts an inherent incapacity to cope with geometric increase in terms of surface area for dissipation of heat, so that a considerable downward adjustment of metabolic rate is imperative for survival. Change in metabolic rate with size increase is, however, optimized in the Kleiber relationship. According to West et al. (1997), the key to understanding this phenomenon probably lies in the fractal geometry of branching networks forming the transport systems of living organisms, which is now shown to constitute the optimal design for efﬁciency of nutrient transport and maximization of metabolic rate in the face of size increase.

Constraint and Directionalization in Adaptive Potential and the Biophysical Paradigm We must now explore the link between ‘‘constraint’’ and directionalization in the evolution of adaptive systems. At the outset, it must be made clear that more than one view of the effect of constraint has been offered in the past. For example, Maynard Smith et al. (1985) have discussed the role of developmental constraints, with heavier emphasis on the question of possible links with stasis than will be found in the ensuing treatment. That analysis does not distinguish between limits of the biophysical paradigm and those arising in endogenous adaptive potential, nor do these authors separate anagenesis from ‘‘evolutionary trends’’ in general. For these reasons, no detailed comparison between the two very different approaches is offered below. The directionalization function comprises a heterogeny of constraintive mechanisms and their corollaries, each of which tends in one way or another to orientate the iterative adaptive response in anagenesis. Many intrinsic limitations act on the biophysical paradigm, all of them having some effect on the probability that a given functional change will also be reﬂected in structure, and some of these limitations serve also to deﬁne a constrained subset of the maximized physical paradigm state in terms of organismic limits. The structural attractor thus tends to be a somewhat limited subset of the fundamental physical paradigm, owing to the many constraints peculiar to natural adaptive systems, and these factors may also serve to determine the probability that a given adaptive potential will in fact reach realization. Thomson (1988) holds that ‘‘developmental constraints can explain evolutionary trends.’’ However, this should certainly not be taken to infer that anagenetic evolutionary sequences arise simply through ‘‘constrainment’’ alone. What does occur is that degrees of freedom in adaptive potential may tend to directionalize the adaptive response along one of several possible pathways: Thomson (1988) agrees that it will be a general property of any constrained system that, to the extent to which it is alterable, it will be more readily changed in some directions than in others. The degree to which major coordinates both of endogenous adaptive potential and of the extrinsic biophysical paradigm may often be highly directionalized is most clearly demonstrated by the frequency, not only of evolutionary

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convergence, but (in particular) of parallel evolution, the continuation of an anagenetic sequence beyond one or more cladogenetic nodes owing to manifestation of the directionalization function. Simpson (1953) correctly rejects simplistic genetic reasons for parallel evolution, since convergence between remote lineages is common. Parallelism offers proof of the maxim that many major coordinates in the structural attractor have one to a few degrees of freedom, most probably arising from the inﬂuence of constrainment within the biophysical paradigm. The above factors clearly form a basis for directionality in evolutionary change, and this relationship between adaptive potential and biophysical systems also forms a rationale for an explanation of the early concept of so-called orthogenesis or ‘‘programmed evolution.’’ The complex of constraints acting to directionalize the adaptive response may be listed as follows. a. Constraints Due to Accumulated Adaptive Shifts A majority of superstructural traits in higher organisms have undergone one to several qualitative adaptive shifts, in which a structure originally designed for one purpose has come to take on a new one. This naturally imposes design limitations on the newly acquired function, depending on the degree of difference between old and new biophysical paradigms: The trajectory of the recurrent pharyngeal nerve in higher vertebrates as compared to its original trajectory in the ﬁshlike ancestors of terrestrial vertebrates (and particularly in its diversional pathway in long-necked mammals such as the giraffe) is a well-known exemplar of suboptimal design (see Ridley, 1993, for a discussion). b. Constraints Due to Multiple Functionality The multiple functionality principle states that most modular components of phenotype form tend to manifest more than a single adaptation interface. Very many biophysical systems fulﬁll more than a single function as a result of incomplete adaptive shifts (see above); therefore, each functional component of a compound superstructure may sacriﬁce efﬁciency to a greater or lesser extent, in that an advance for one function may constitute a negative step in terms of another function concurrently residing in the same structure. Consequently, the ideal state of adaptation for a given sequence of structural change may be less efﬁcient in biophysical terms, than if the structure in question had no other function: A leg may both walk and grasp prey. The biophysical paradigm for a structure capable of fulﬁlling both functions will tend to be more tightly constrained (in terms of either walking or grasping) than one performing either function independently of the other. Similarly, Niklas (1988) concluded that the geometry of plant design very frequently tends to manifest a considerable level of suboptimality owing to division of labor. The inﬂuence of multiple functionality has already been implicated in the architecture of the fundamentally complex structure of the isotropic selection interface (Chapter 4).

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c. Constraints Due to the Nature of Biological Kinematic Systems There tend to be only a few kinematic links and few planes of action in many biophysical systems, leading to a narrow channeling of adaptive solutions to a functional problem. This is often linked to the ‘‘prospective adaptation’’ situation, where a structure is evolved from a preexisting structure of quite different function (see a and b above): Flight in vertebrates is accomplished by modiﬁcation of a walking limb. The earliest ﬂying appendages would have been of suboptimum design (as evident from the rarity of any transitional forms in the living fauna). This element of constraint is a natural corollary of the interactive nature of degrees of freedom residing in both the biophysical paradigm and endogenous adaptive potential. d. Fabricational Constraint Owing to the limitations of continuous development (as distinct from a ‘‘parts-assembly’’ mode of construction), certain physical structures may have a very low probability of realization in biophysical structure systems, for example, where an assembly strategy is needed to maximize mechanical efﬁciency (this may, however, be partially negated in the very long term, in the context of duplication–cooption; see Chapter 12): The vertebrate eye is constructed back to front in terms of the positioning of light receptor cells in relation to nerve supply. It could have been designed more efﬁciently given a more direct mode of assembly. Here again, phyletic history forms a signiﬁcant input to the situation at hand. Many other less obvious constraints appertain to development, and these will be examined in detail at a later point (see developmental chapters). e. Constraints Arising from the Nature of Anagenetic Change As with the question of continuous development, biophysical paradigms can only be reached through the intermediary of a progressive sequence of suboptimum forms, often through a process of simpliﬁcation from an initially more complex state or, alternatively, through complexiﬁcation (sometimes the latter, followed by the former). This means that for most complex superstructures, there will only be incremental progress toward paradigm form, and there will thus be a large temporal element deﬁning the degree to which adaptive potential has actually been realized with respect to any given niche interface. More signiﬁcantly, it also means that there has to be a fully functional state at each point along the anagenetic sequence (as with the continuous development scenario already mentioned above). f. ‘‘Constraints Imposed by Selection’’ Maynard Smith et al. (1985) distinguished developmental from selectional constraints (although Arthur, 1997, modiﬁes this to make certain apparent ‘‘selectional’’ constraints ‘‘developmental’’).

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A low intensity of natural selection in the selection interface may mean that some attainable minor functional reﬁnements are never actually realized in certain lineages, owing to their very low contribution to ﬁtness. This situation may also occur for larger manifestations of potential anagenetic change also, if the leading effect lies elsewhere in the phenotype, and the latter scenario can in fact be shown to be of quite profound signiﬁcance in this context (see Chapters 18 and 19). There is also a deﬁnite link to pleiotropism in the context of selectional constraints, in that evolutionary rate may be affected by negative side effects of otherwise positive gene mutations.* The biophysical paradigm is thus not ‘‘the ideal physical paradigm,’’ but some subset of this as constrained by various interrelated organic factors, inextricably constrained by endogenous adaptive potential for any other than the smallest paradigm distance. The most signiﬁcant deductions to be made here are that (1) a great many adaptations are likely to be closely channeled, rather than divergent, when we consider separate lineages adapted to similar niche parameters, and (2) the same anagenetic sequence evolving in parallel in different lineages may do so at quite different evolutionary rates. This means in turn that parallel evolution will often tend to predominate in phylogeny and that divergent, monophyletic solutions will be uncommon for many response mechanisms: The propensity for parallelism in evolution is exempliﬁed by examples where the fossil record is more than unusually complete, as with Sheldon’s work (1987) on trilobites, where changes in the mean number of pygidial ribs clearly occurred independently in several lineages. The same phenomenon is almost universally implicit in cladistic analyses, both of paleontological and of neontological data (see Chapter 21); even the formerly widely held assumption that the coelom is monophyletic has been challenged (see Nielsen, 1995). The above conclusions are of fundamental signiﬁcance in the interpretation of morphological data in a phylogenetic perspective (see Chapter 21), as well as for an understanding of how structure is organized, controlled, and modiﬁed in development during periods of major evolutionary change in natural adaptive systems. Adaptive potential thus determines that constrainment of the fundamental structural attractor as determined by endogenous limits, and is in turn directionalized by the extrinsic biophysical paradigm. The biophysical paradigm– endogenous adaptive potential interaction can also be shown to be the true basis for an understanding of ‘‘structuralism’’ in evolution, in the same way as it explains the early concept of ‘‘orthogenesis’’ (see Chapter 15). It should also be stressed at this juncture that ‘‘constrainment’’ must be understood in terms of a directionalization function (particularly in the sense of ‘‘directing parallelism’’), and neither as a factor preventing evolution from occurring nor as a causality for ‘‘nonadaptive evolution.’’ * This category of ‘‘selectional constraint’’ is linked to the genetic component of adaptive potential, and it will be discussed separately in the context of development.

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Paradigm Distance and Directionality Clearly, some biophysical paradigm states will lie close to existing structure, while others will be topologically and developmentally more distant from the ‘‘preadaptive state.’’ Paradigm distance, the morphotopological distance between preadaptive state and biophysical paradigm form, is an expression of the degree of impediment to realization of adaptive potential resulting from the gap existing between endogenous and extrinsic elements. Paradigm distance tends to 0 and directionality in the selection vector is unidimensional when structure complementary to some freshly discovered niche parameter lies within the reach of existing adaptive capacity, and its value is deemed as being ⬎0 when one or more structure units are required to change in such a way that appropriate modiﬁcations lie beyond the reach of existing or recurrent allelomorphic systems, thus requiring iterative, directionalized mutational change in realization of adaptive potential. A large paradigm distance is therefore equivalent to ‘‘remote adaptive potential’’ in the sense of there being only a rudimentary intersect between the morphogenetic landscape and the biophysical paradigm: Flight appendages in insects, birds, and mammals must have presented a very great paradigm distance from any rudiments which preceded them in fully terrestrial forms. Not only was adaptive capacity equal to 0 for this transition, but adaptive potential must have been very low. Even such remote biophysical paradigms as the examples given above must, however, have carried some probability of realization in adaptive potential, which clearly contains a dimension far beyond that expressed in ‘‘prospective adaptation.’’ Nevertheless, ‘‘paradigm distance’’ must certainly constitute one of the most signiﬁcant true constraints on actual evolutionary change. Likewise, choice between n adaptive solutions to a functional problem must tend to involve preferential shifts toward states of low, rather than high paradigm distance, and this clearly constitutes an important input to the directionalization function also.

Dynamics of the Biophysical Paradigm The biophysical paradigm (and thus also the structural attractor) cannot be considered to be a static structure, toward which adaptational change progresses in linear fashion. Directionality must tend to be driven into progressively narrower channels as adaptive potential is realized and ‘‘multiple possible solutions become just one or a few’’: With early ﬂight adaptations, gliding appendages formed by simple transformations of climbing or grasping limbs clearly presented a high adaptive potential for further modiﬁcation; the earliest changes must also have determined what subsequent ones would be the most favored. In such scenarios we may also witness divergence, as lineages with a common ancestor directed by Renschian cladogenesis (see previous chapter) explore separate realizations of adaptive potential. Not all anagenetic change is mani-

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fested in parallelism and convergence, and in this, the question of degrees of freedom in the structural attractor clearly becomes of special signiﬁcance. Dynamic Factors in Adaptational Reciprocity The reciprocal nature of the adaptive response must inﬂuence the form of the biophysical paradigm, in particular for parametric niche-adapted traits. The nature of the limiting resource of a gene pool clearly determines functional needs, and adaptational change may in turn create a demand for some reciprocal adaptive response in the resource gene pool. Examples of positive reciprocal responses (as in the moth haustellum length and ﬂower depth in insect pollinated plants already mentioned) show the high degree to which reciprocal factors may at times deﬁne and alter preexisting adaptive paradigm states. Dynamic Factors in the Dimensional Spectrum It is a further fundamental attribute of the biophysical paradigm that it is often profoundly affected by factors correlated by absolute size (see above). The nature of the biophysical paradigm is determined by dimensional parameters in the adaptive system itself and is thus a fundamentally dynamic structure, owing not only to the reciprocity principle, but also to allometric laws (and especially to gravity inﬂuenced parameters, as a principal component in the latter, see Thompson, 1917; Huxley, 1932). One fundamental law of allometry holds that volume tends to increase as the square of increase in surface area, and the corollary of this is that mass increases in a similar way. The outcome is that many biophysical paradigms must also change according to increase in absolute size, and also that there may be ﬁnite limitations imposed on the latter. Consequently, the true principal components of the biophysical paradigm contain the equation for allometric modulation with respect to any particular structure in relation to speciﬁc function and absolute size, as determined by parameters of the adaptive niche: Thompson (1917) noted that a ﬁsh, in doubling its length, multiplies its weight eight times, and it all but doubles its weight in growing from 4 to 5 inches long. Other well-known examples include the changing length:breadth ratio of supporting vertebrate limbs and the limits on insect body size according to the diffusion properties of oxygen in the tracheal system. Similar relationships exist with scaling and ﬂight; for example, body mass carries many design implications for wing structure (see Pennycuik, 1992). Thompson also pointed out that a common effect of scale is that some forces act in proportion to surface area, while others (above all, gravity) do so in proportion to body mass. According to the same argument, and following Herbert Spencer, Thompson also showed that structural paradigms for biological function invoke Galileo’s principle of similitude: ‘‘If we build two bridges geometrically similar, the larger is the weaker of the two.’’ In addition to the direct implications of size change, there are numerous complex corollaries of even quite simple dynamic paradigms: The scaling of body mass and metabolic rate (see pp. 132–133) also carries an indirect impact on such factors as biodiversity: large species

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with higher energy efﬁciency can eat lower quality food, and this in turn affects niche structure. Longevity, age at maturity, and population density are also affected by this relationship (West et al., 1997). The above observations clearly conﬁrm the concept and signiﬁcance of a dynamic structural paradigm, notwithstanding the fact that certain exceptions exist: Some structures do not follow the principle of similitude: the vertebrate eye, for example, does not vary in proportion with surface area or mass of a body. Dynamic Factors Linked to Incremental Change The incremental change hypothesis expresses the view that positively selected mutations in evolution correspond to small morphogenetic changes only. Owing to the existence of large paradigm distance and to constraints imposed by preexisting structural architecture on adaptive potential, it must be assumed that complex macroevolutionary anagenetic sequences are generally built stage by stage, in an incremental manner, this being linked to the above observation that the biophysical paradigm itself expresses dynamism during the trajectory of evolutionary change. This not only contributes to the directionalization element (see above), but also carries a corollary for the changing architecture of the structural attractor. This maxim will be investigated in greater depth in later chapters.

THE STRUCTURE AND FUNCTION INTEGRAL AS LOCI OF ADAPTIVE POTENTIAL To fully understand the changing architecture of the adaptive response with respect to realization of adaptive potential, it is necessary to look further into the way in which complex structure is organized. It is evident that organismic structure cannot advance as a unity toward some complex new biophysical state (‘‘preadaptive state to distant paradigm state in a single step’’), but must change incrementally and in iterative fashion, one component at a time. The ‘‘components’’ in question are units of structure capable of responding more or less autonomously to a selection interface, in response to demands in the external environment. These units are phenons (Chapter 4), the phenotypic unit corresponding to a unit of genetic change, and certain phenons must also contain the potential to be integrated incrementally in longer term evolution, thus forming larger units of structure. The theory of biophysical paradigms thus clearly necessitates recognition of higher structure units and integrals which operate above the level of the phenon, and this is a natural corollary of the fact that adaptive potential and the structural attractor are both dynamic entities.

The Structure Unit and Integral While the phenon is ‘‘a gene–phenotype unit having an active selection interface,’’ a structure unit constitutes a larger unit of discrete superstructure, the

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lowest holistic unit above tissue level, irrespective of the existence of an active selection interface. Following the maxim outlined above, phenons of a common selection interface may be progressively integrated as structure units, and a structure unit is thus effectively an assemblage of genetically ‘‘ﬁxed’’ phenons linked to an isotropic adaptation interface. Although many structure units have a fully autonomous function, others clearly operate in concert with other units belonging to a greater whole. A structure integral is a set of structure units expressing physical integration as part of a single holistic system linked to a common adaptive paradigm, illustrating the way in which smaller structure units are organized into larger superstructures: The insect wing is a good example of a complex integrated structure containing many structure units. Such structures cannot possibly have evolved ‘‘in a single step,’’ and must have involved iterative superimposition of a large number of structure units, each of which lies above the domain of a single phenon.

The Function Integral A function integral is a set of structure units expressing some degree of functional homogeneity, regardless of level of actual structural integration, and for which no other functional links exist. This concept reﬂects the fact that there is an adaptational (and thus potentially selectional ) modularity acting on different structures, which can act quite independently of the boundaries of purely developmental modularity (see Chapters 9–16). The structure units of a single structure integral may thus belong to one or more function integrals, either alternatively or else simultaneously in time, thus expressing the multiplicity of function criterion discussed earlier in this chapter. Those structure units belonging to a function integral are thus correlated according to the tenets of a common adaptation interface: Tinbergen (1959) pointed out that 25 characters of kittiwake gulls can be grouped into just a few adapted systems (cliff nesting behavior, pelagic feeding, etc.). As we have seen, the insect wing plus muscles and central nervous system can similarly be taken to form a single function integral; however, not all aspects of the wing belong to a single function integral. Wing color pattern, for example, belongs to a separate function integral which also incorporates components of behavior (for example, wing color pattern and behavior linked to choice of concealment position in cryptically patterned species). Similarly, the nervous system’s function is not restricted to control of ﬂight. Thompson (1917) likewise drew reference to the fact that, although we consider muscle and bone as being independent entities, ‘‘They come into being together, and they act and react together. . . . There can be no change in the one that is not correlated with changes in the other’’. Whereas Thompson was concerned with the problem of ‘‘single character evolution,’’ Simpson (1953) observed that it is common for

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‘‘blocks of characters’’ to be involved in the rise of higher categories, and that this need not always be a simultaneous mechanism. Hypsodonty in horses is linked to size increase, even although each trait evolved independently of the other. All of the above examples clearly point to the existence of highly organized function integrals in the superstructure of higher organisms. It is important at this stage to realize that the boundaries of structure and function integrals are drawn, not by developmental modularity, but by the present and past architecture of the selection interface. At a later stage, we shall see how structure can be modiﬁed during evolution in order that developmental modularity can be tailored to selectional modularity (see Chapters 9–12). Multiple Functionality and the Structure Integral As we have already seen, a given structure unit may also belong to more than a single function integral. Curio (1973) has argued that when the same character is employed in more than one context it should only be regarded as an adaptation in that context in which it makes the greatest contribution to ﬁtness. However, no reason has been offered to suppose that such balance is not itself subject to further dynamic change. In general, it may be assumed that many structure integrals belong to more than a single function integral, and that the adaptational balance between n functions expressed in them may also be subject to change. Additionally, new functions may be added to supplement or even to supplant the preexisting repertoire of adaptive capacity.

The Structure Integral and the Transspeciﬁc Selection Interface The allomorphic component of adaptive capacity is differentially distributed over n phenon units which relate in turn to differentials in niche dynamism, and the selection interface contains n phenons of n structure or function integrals at any one point in time. How then do individual structure units relate to ﬁtness? Each phenon (and structure unit) must carry an individual contribution to the adaptive state. Most signiﬁcantly, an active selection interface will be manifested in some structure units and not in others, and then only in the phenon itself. Essential superstructures will exhibit little or no variation, in contrast to the phenotype traits of an anisotropic selection proﬁle relating to the allomorphic component of the genome. The selection interface appears thus to be limited to loci expressing several relative adaptive states at the phenon level, while the adaptation interface is manifested by the whole organism–environment interaction. This is, however, an intraspeciﬁc rule only, applying where the heritable adaptive differential is most noticeable in the presence of allelomorphism. In addition, a common selection interface also exists between competing species (see previous chapter), and this may clearly be based on holistic units of superstructure, since the heritable differential between species exists partly with respect to ﬁxed genetic states. Thus, many structure integrals which seem invariable within a species may nevertheless manifest a transspeciﬁc selection interface of some kind.

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The Leading Effect Phenon It is of considerable signiﬁcance for the evolutionary behavior of the adaptive system that certain phenons may act to ‘‘carry’’ the rest of the genome in the context of the selection interface. There are thus leading effect and sequiform phenons within any chosen time frame. A leading effect phenon holds the highest contribution to ﬁtness within the selection interface, thereby tending to ‘‘direct the adaptive response.’’ A sequiform phenon is one which holds a lower contribution to the adaptive state than the leading effect, consequently tending to be ‘‘directed’’ by the latter. This observation can be shown to be of great signiﬁcance for the longer term evolutionary behavior of adaptive systems in terms of the probability of a given increment being made in the integration of phenon to structure unit, and structure unit to structure integral (see Chapters 14 and 18): Wright (1982a) rejected the notion of ranking genes in order of importance, because of changing selectional balance in adaptive topography. However, this ignores the existence of a leading effect in terms of major genes which manifest allomorphic variation carrying a large contribution to the active selection interface (see Chapter 13). Many genes of allomorphic status do in fact exhibit high modularity in Nature, certain loci of high contribution to ﬁtness in this sense acting to ‘‘direct’’ gene frequency change in general. The concept of leading effect and sequiform phenons can perhaps most easily be demonstrated in the context of vestigiation. The contribution to ﬁtness may not equal 0 for a functionally redundant state equivalent to a single structure unit, since there may be some residual morphogenetic role of that structure. In the latter case, the adaptation interface is broken for a single structure unit, but not for the entire organismic state. Some ‘‘weak’’ structure units are thus perpetuated by the overall adaptive state of the entire phenotype.

MAIN POINTS FROM CHAPTER 7 1. Realization of adaptive potential (as against capacity) deﬁnes the essential differential between adaptive equilibrium and evolution itself. 2. ‘‘Prospective adaptation’’ is linked to realization of adaptive potential through behavioral change alone. However, this component of adaptive potential has a proximal limit in the absence of structural change. 3. As with adaptive capacity, adaptive potential manifests both extrinsic and endogenous domains. The extrinsic domain lies in free, adjacent niche space, and in optimization of the existing adaptation interface in terms of gravitation toward a biophysical paradigm complementary to some exogenous function. The latter must, in turn, link to an endogenous domain in the selectionally positive component of morphogenetic potential residing in the developmental system. 4. The trajectory of anagenetic evolution is qualitatively different from that of adaptive equilibrium and microevolution, in terms of gravitation toward

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a more or less ‘‘distant’’ structural selectional attractor contained in the intersect between degrees of freedom in the biophysical paradigm for adaptive function and endogenous adaptive potential. 5. The structural attractor is not a ‘‘ﬁxed’’ entity, but manifests dynamism in the dimensional spectrum, as a particular function of lability in absolute size. 6. A complex of directionalization factors can be identiﬁed in the structural attractor, as a mechanismic corollary of the activity of various endogenous developmental (and other biotic) ‘‘constraints.’’ 7. Although actual change within the time frame of a generation can occur only in the phenon of the active selection interface, adaptive capacity and potential must be regarded as being distributed among n iteratively assembled structure units and structure integrals. Structure integrals are in turn coordinated in terms of a superior domain in the context of a function integral reﬂecting adaptational (and potentially also selectional) modularity. 8. Multiple functionality explains both the degree of complexity and the apparent suboptimality manifested by many structure integrals of higher organisms.

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EVOLUTIONARY MODE

EVOLUTIONARY MODE AND THE ITERATIVE ADAPTIVE RESPONSE The term evolutionary mode describes the topology of iterative phenotypic change in the adaptive response to the long-term selection proﬁle. What range of modes of evolutionary change are manifested through realization of adaptive potential, and how are these related to the behavior of adaptive systems? Speciation (Chapter 6) is clearly one mode, but not all evolutionary activity can be analyzed in the context of a cladogenetic selection interface. A deeper understanding of the nature and diversity of evolutionary modes in general is clearly an essential component of any global theory. In the context of the analysis of adaptive systems, these questions clearly relate to all aspects of the topology of realized adaptive potential.

Allelogenesis and Evolutionary Mode in Amphigenesis, Cladogenesis, and Anagenesis Positive neomorph (namely, nonrecurrent) mutation, which we shall now term allelogenesis, must clearly form the true root of all evolutionary change. Thus, although we have deﬁned evolutionary mode in terms of topology of realized iterative change in the phenotype, not all evolution actually leads to ‘‘modal’’ behavior in that sense. Although the genic mutational mechanism is in all probability fundamentally homogeneous for all evolutionary modes, much allelogenesis will express no form of iterative topology, mutational activity thus often simply constituting ‘‘evolution in the absence of any evolutionary mode being expressed,’’ as, for example, in addition to the existing complement of allomorphs.

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Evolutionary mode can be understood only in terms of the topology of iterative phenotypic change resulting from repeated allelogenesis according to the dynamics of the selectional attractor, in the context of the long-term selection proﬁle. There also has to be a time scale over which evolutionary topology is observed, and this could very usefully be not less than that of ambient speciation time for the lineage in question, thus linking back to our earlier deﬁnition of Tc in Chapter 3 (for which, of course, there can be no ‘‘general’’ value, only an average that is speciﬁc to the lineage over a given time course). Earlier authors deﬁned several distinct evolutionary modes. Notably, Huxley (1958) recognized cladogenesis, anagenesis, and stasigenesis, and Rensch (1959) held a similar viewpoint. Cladogenesis has already been explicitly deﬁned in terms of disjunct diversiﬁcation linked to a bipartite selectional attractor in an anisotopic selection interface (see Chapter 6). In contrast, anagenesis manifests a linear topology with respect to an isotropic selection proﬁle and a unipartite selectional attractor, generally for greater than ambient speciation time, so that anagenetic increments may often tend to be transspeciﬁc modulations toward a distant paradigm state. Not all evolution can, however, be usefully categorized in terms of clado- and anagenesis. Where there is a cyclic topology in the form of evolutionary reversal with respect to periodicity in the selection interface and adaptive response that is expressed over a much longer time frame, we may then encounter an additional evolutionary mode which can be termed amphigenesis. In this mode, incremental evolutionary steps tend to be species traits lying just beyond the domain of adaptive capacity. Rising slightly above the domain of tertiary adaptive equilibrium (see Chapter 5),

FIGURE 38 The topology of evolutionary mode (some component of allelogenesis does not, of course, enter any topological channel, and much may be presumed simply to join the repertoire of allomorphism in adaptive equilibrium).

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amphigenesis can be seen as being truly evolution through its links with realization of adaptive potential and despite both bidirectionality in terms of topology and apparent similarity to adaptive equilibrium. Possible links between this evolutionary mode and the speciation process will also need further examination (see below). Given the variable expression of both linearity and directionality in evolutionary mode, it is once more underlined that the deﬁning characteristic of evolution lies with the boundary between adaptive capacity and potential. Any change in adaptation is therefore equivalent to evolution, provided only that transgression of adaptive capacity is indeed manifested. Thus, when an apparently new phenotype arises through recombination of preexisting alleles alone, this does not constitute evolution, unless we are looking at the time delay between a neomorph mutation and its attainment of an adaptive peak (a new allelomorph may take some considerable time to reach its adaptive zenith in terms of recombination with other allelomorphs). However, the ‘‘peak-climbing’’ process is seen as transgressing adaptive capacity into adaptive potential, only when we are not observing a recurrent state in the ongoing adaptive equilibrium existing between variation and a ﬂuctuating external environment: It is not entirely clear, for example, whether or not observed examples of ‘‘acquired dominance’’ such as that of Biston betularia f. carbonaria are due to truly neomorphic or recurrent allomorphic variation.

Simpsonian Phyletic Evolution Simpson (1953) recognized phyletic evolution as an evolutionary mode, a term regarded by Wright (1949, 1982b) as being linked to anagenesis sensu Rensch. Simpson included ‘‘short range adaptation to occasional or nonrecurrent environmental changes’’ and ‘‘evolutionary trends’’ of a heterogeneous kind in his concept of phyletic evolution, and despite its obvious heterogeneity, he viewed phyletic evolution as the alternative mode to speciation on the grounds that anagenesis occurs within the framework of a nonbranching lineage. This view has found little support from other workers, however, and the concept of phyletic evolution can be shown to have only restricted application to reality (see Chapter 17). Linear anagenetic change must not be equated with phyletic evolution, since the latter may contain not only novel anagenetic factors, but also amphigenetic patterns and diverse postspeciational allomorphic elements. Continued linear evolution beyond the boundaries of a speciation event may obviously derive from a wide heterogeny of genetic and selectional systems, some of which did and some of which did not form part of the cladogenetic selection interface that gave rise to the original speciation. Similarly, anagenesis cannot be supposed to occur solely within the conﬁnes of a lineage that has not undergone speciation at some point! ‘‘Phyletic evolution’’ as noncladogenetic change in a lineage is clearly a heterogeny.

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The Microevolution/Macroevolution Dichotomy It is important to realize that neither evolutionary mode nor status within the microevolution/macroevolution dichotomy is concerned with differentials in mechanism or process, only in pattern (see also Carroll, 1997). The distinction between micro- and macroevolution was ﬁrst made by Goldschmidt (1940). Macroevolution (sensu Goldschmidt) was supposed to occur through chromosomal rather than genetic mutation, irrespective of the action of selection. This view was not generally accepted by other workers, particularly once the origins and function of chromosome mutations had become better known, and the terms microevolution and macroevolution have also subsequently come to be applied somewhat loosely by many authors. Attempts have also been made to deﬁne macroevolution on the basis of changes occurring between rather than within a species, often on the assumption that macroevolutionary mechanisms are slow accumulations of changes occurring at the ‘‘micro’’ level (see Brooks and McLennan, 1991, for an overview). The developmental perspective on genetics obviously does not support such a view, and other difﬁculties with this simpliﬁcation will be discussed at a later point (see Chapters 17 and 18). At this point, it is possible to usefully redeﬁne microevolution and macroevolution on the basis of reversibility versus nonreversibility with respect to endogenous adaptive potential. To fully understand the differential between micro- and macroevolution, it is necessary in the ﬁrst instance to consider the scenario presented by the isotropic niche proﬁle. In this situation, very longterm stability in key parameters of the adaptive niche may permit complex structural change to evolve, given the existence of an attainable distant biophysical paradigm plus the presence of complementary endogenous adaptive potential. This situation may lead to a macroevolutionary event, in that circumstance where degree of movement toward the structural attractor is great enough to invoke irreversibility due to loss of endogenous adaptive potential, as a corollary of increase in developmental complexity. Micro- versus macroevolutionary patterns are therefore determined by the nature of activity within the adaptive system with special reference to the long-term selection proﬁle, macroevolution thus generally also tending to encompass some component of gene pool splitting in addition to anagenesis, as a corollary of the time factor itself. With the foregoing revised deﬁnition of macroevolution, irreversibility in anagenesis can be interpreted as invocation of the ‘‘developmental ratchet,’’ whereas for cladogenesis, it is simply equivalent to speciation. It is also important to see that the microevolution/macroevolution dichotomy as deﬁned above has no direct relationship to evolutionary mode, since these constitute potentially independent criteria (see below). A further problem lies in the fundamental similarity between different modes of linear structural change, certain of which have a subtle interrelationship (and one of which does not in fact constitute evolution at all). Here, it is useful to consider a time scale which may tend often to center around ambient speciation time of a lineage as a convenient yardstick for comparing tertiary dynamic equilibrium and amphigenesis. We may now attempt to list different manifestations of linear evolutionary topology (inclusive of the micro/macro dichotomy) thus:

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Tertiary adaptive equilibrium

Evolution: amphigenesis

Micro- or macroanagenesis

Reversible through adaptive capacity. Mutations have arisen and entered adaptive capacity as allomorphs perpetuated in dynamic equilibrium, thus being fully reversible in the face of a changing selection proﬁle.

Only reversible through adaptive potential. Mutations involved are generally both neomorphic and (other than transiently) nonallelomorphic. This clearly constitutes ‘‘microevolutionary anagenesis in reverse mode.’’

Linked to proximate biophysical paradigm and dynamic selection proﬁle, tending to be expressed in quantitative change. Commonly only manifested in substructural traits.

Linked to a more distant biophysical paradigm and greater periodicity in the selection proﬁle. May be expressed in qualitative change. Generally manifested in structural traits. Often transspeciﬁc in expression.

Microanagenesis is fully competent with respect to reversibility, but this does not occur, owing to the presence of an isotropic selection proﬁle within the minimum time span of speciation. Macroanagenesis is not reversal-competent, owing to the degree of developmental complexity extending beyond threshold for same. Remote biophysical paradigm. Very long periodicity in the selection proﬁle eventually invokes a ‘‘developmental ratchet’’ mechanism in macroanagenesis.

Generally expressed in infraspeciﬁc mode.

Generally manifested at higher taxonomic levels.

Most ‘‘nonlinear’’ allelogenesis may be usefully categorized as constituting microevolution, although as we have seen above, anagenesis can also come under the latter category. In much the same way as genomic anastomosis is a microevolutionary resolution of the same cladogenetic regime which gives rise to speciation, some component of anagenesis is microevolutionary, since with limited paradigm distance, reversibility is (at least in theory) possible, even when no actual reversal in selection proﬁle demands it. In this, we can also see that the only dichotomy between microanagenesis and amphigenesis lies in actual reversal of the selection proﬁle and adaptive response, with respect to amphigenetic mode. Microevolution (as amphigenesis) differs from tertiary adaptive equilibrium only in that loss of adaptive capacity for reversal has been invoked in the context of speciational divergence, and in the correlated occurrence of longer periodicity of the selection proﬁle. Tertiary adaptive equilibrium itself (as reversible change in continuous variation within adaptive capacity) is clearly equivalent to classic ‘‘directional selection,’’ but unlike anagenesis and amphigenesis, here there is only change in variance within the existing repertoire of continuous variation. At the other end of the spectrum, in macroevolution, the genetic system has simply changed beyond any potential for reversal. The above relationships can perhaps best be illustrated from a hypothetical (and unrealistic!) example: Tertiary adaptive equilibrium: Flying appendage is facultatively evolved within existing spectrum of adaptive capacity, hence is both genotypically and phenotypically reversible in the time span of a few generations.

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Amphigenesis: Flying appendage completely reverts to walking function with respect to reversal in selection proﬁle over ambient speciation time. Microanagenesis: Flying appendage is capable of reverting, but no selectional demand actually exists for this to happen. Macroanagenesis: Flying appendage becomes completely nonfunctional on reversal of an adaptive shift, owing to irreversibility in adaptive potential. In reality, of course, progression from rudimentary gliding to an advanced ﬂight mechanism rather obviously constitutes a macroanagenetic trajectory, since this change could only occur via iterative incremental change toward a superstructural state deﬁned by a rigidly constrained biophysical paradigm, and since the selection proﬁle in this scenario can only be isotropic. Where a subsequent reversal in the external selective environment does occur, this will mean either extinction or vestigiation. Not all real examples, however, manifest a clear categorization in terms of micro/macro status: In the above context, the classic work on ‘‘orthogenesis’’ in Gryphaea oysters may refer, not to microevolution (as claimed by Carter, 1951, on the grounds that ‘‘microevolution consists in gradual change of the mean form of a population’’), but to true macroevolutionary change. It is apparent that many Gryphaea lineages were unable to revert structurally in the face of a reversal in external environmental conditions (see also Chapter 20). The Link between Minor/Major Cladogenesis and the Microevolution/ Macroevolution Dichotomy Returning to our earlier categorization of cladogenesis as minor versus major (Chapter 6), it is further necessary to point out that there need be no precise correspondence between micro- and minor or macro- and major categories of cladogenesis. Macrocladogenesis clearly contains all components of both minor and major cladogenesis that have transcended a certain threshold of reversibility, and microcladogenesis similarly contains those that have not. However, it is nevertheless clear that there will often tend to be some rough approximation between micro and minor and between macro and major. Both evolutionary mode and the micro/macro dichotomy are thus functions of the interaction between selection proﬁle and adaptive potential, in which the value of Tc forms a highly signiﬁcant controllant inﬂuence.

ANALYZING EVOLUTIONARY MODE We have now outlined the primary topological deﬁnitions of the terms cladogenesis, amphigenesis, and anagenesis, placing these evolutionary modes in perspective with the architecture of the selection interface, also clarifying the microevolution/macroevolution dichotomy as a function of reversibility in the

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context of adaptive capacity or potential. There now follows an account of each mode in turn.

The Role of Allelogenesis Although allelogenesis includes noniterative, transient allelomorphic states leading both to gene ﬁxation and to expansion of allomorphism, we must now add that it should be taken to exclude the addition of neutral microgenetic alleles, the frequencies of which come to be determined purely as a function of nonselectional (stochastic) forces, a situation that has been aptly termed ‘‘genetic drift’’ in the past. As already indicated above, allelogenesis is concerned with the addition of new allomorphic genes, not only to the repertoire of adaptive equilibrium, but also to all modes of true evolutionary change.

Amphigenesis Amphigenesis is a fundamental evolutionary mode that has previously been overlooked. As stated above, its differentiation from ‘‘reversible directional selection’’ lies with the distinction between adaptive capacity and potential, and with a differential in temporal periodicity of the selection proﬁle that is very often linked to a duration greater than or equal to the ambient speciation time for a given lineage. Amphigenesis is thus essentially a superset of adaptive equilibrium, as we transpose from adaptive capacity to adaptive potential and microevolution. Similarly, amphigenesis is distinguished from microanagenesis only through links with actual reversal in response to a dynamic selection proﬁle: Ovipositor length in parasitic wasps cannot constitute ‘‘linearly progressive evolutionary change,’’ since increase–decrease trends are universally distributed in the taxonomy of these insects, being often expressed even in species-to-species differentials. This parameter can obviously change in either direction, according to such extrinsic selectional demands as (for example) degree of concealment of the parasite’s host. This pattern of change seems unlikely to be explained as movement within adaptive capacity, and thus probably constitutes amphigenesis. Similarly, the distribution of the anal cremaster in the pupa of ditrysian Lepidoptera is in all probability a trait that has ‘‘come and gone’’ in many different lineages, according to a highly labile adaptational requirement that is met by a simple structural adjustment (Brock, in prep.). Sheldon (1987), in his detailed study of well preserved lineages of trilobites, observed deﬁnite examples of evolutionary reversal, which he remarked had probably gone unnoticed owing to a reliance on the validity of Dollo’s law. This probably also constitutes amphigenesis, given the time frame over which these trends were in operation, plus the usual taxonomic value of the characters involved. Chromosome number is a further example of an amphigenetic character (see Chapter 13).

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Most observed ‘‘microevolutionary’’ change in organisms is in fact either genetic drift or adaptive equilibrium expressed in allomorphism, leading neither to speciation nor to anagenetic change, only rarely constituting true microevolution, when the presence of neomorph mutation is explicitly proved. Likewise, amphigenesis (rather than linear anagenesis) is probably a very common input to speciation patterns in many evolutionary lineages (see Chapter 21). Considering the likely correlation between amphigenesis and generation of species diversity, this evolutionary mode may be linked more to spatial (than to purely temporal) dynamism. This is why amphigenetic change can tend to be approximately coincident with speciation time, while at the same time being expressed by different parameters of superstructure than those affected by an intrinsically more isotropic anagenetic selection interface. Amphigenesis and the Disjunct Selection Interface Amphigenesis may often be expressed in that situation in which a structural state is entirely lost in the phenotype because of a disjunct discontinuity in the selection interface, then reappears, either through recurrent mutation or else via a neomorphic change in which the recurrent phenotype state is determined by analogous rather than homologous genetic material. Our deﬁnition of amphigenesis therefore does not require that a recurrent phenotypic state equates with an atavistic genotypic one, since the same outcome may result from a different genotypic background: This can easily be understood from an analogy in mimicry, where the similar color patterning of model and mimic are obviously generated from different gene systems. In the same way, there is no reason why some evolutionary reversals within a single lineage should invariably occur by true atavistic mutation.

Anagenesis Wright (1982b) used the term orthogenesis for anagenesis. Rensch (1959) discussed many early accounts of ‘‘directed evolution’’ in the context of his own concept of anagenesis, which latter was, however, tied to a misleading and poorly deﬁned notion of ‘‘progressive evolution.’’ Confusion between anagenesis and the Simpsonian heterogeny of ‘‘phyletic evolution’’ has already been discussed above. Similarly, the term trend has also given rise to much confusion. Some workers use the latter term only for parallel anagenesis, while Simpson (1953) stated that his own usage was ‘‘neutral . . . without implication to causes.’’ Gould (1990) has claimed that ‘‘trends’’ have always been discussed as ‘‘lineage anagenesis.’’ However, evolutionary biologists from Darwin to Huxley have in fact long presumed that anagenetic change must pass through multiple speciation events. Gould also argues that ‘‘anagenesis is almost always the product of accumulated cladogenesis ﬁltered through a higher level process of species sorting’’ (see Chapter 20). Clearly, we must now dismiss the term ‘‘trend’’ as a heterogeny that is descriptive and nothing more. Similarly, such concepts as ‘‘phyletic evolution’’ and ‘‘species sorting’’ do not form any rationale for an interpretation of anagenesis.

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We have already redeﬁned anagenesis in terms of an iterative adaptive response in some component of phenotype form to the isotropic selection proﬁle, involving realization of adaptive potential and manifesting linear structural progression toward a static structural attractor. As we have already seen above, this mode of evolution also includes both micro- and macroevolutionary elements, according to whether or not irreversibility is possible. In contrast to the situation with amphigenesis, the principal coordinates of the structural attractor for an anagenetic sequence are constant at least over ambient speciation time of a lineage, and often far beyond (i.e., excluding allometric inﬂuences in the dimensional spectrum and the effect of adaptational reciprocity). Although anagenesis may at times initially constitute a response to a changing external environment, it may tend to proceed in the context of a niche proﬁle that is static, at least for certain major coordinates of the biophysical paradigm. This link between anagenesis and static niche proﬁle may seem intuitively unlikely. However, this will be shown to be a correct interpretation for a signiﬁcant element of anagenetic evolution (although this hypothesis will nevertheless have to come under closer scrutiny at a later juncture in Chapters 17 and 19). Redundancy of the isotropic selection proﬁle for anagenesis during the later stages of a complex anagenetic sequence results in developmental–homeostatic barriers to structural reversal, giving rise to vestigiation (or even extinction), and this phenomenon again underlines the reality of the dichotomy existing between micro- and macroanagenesis. Anagenesis and the Adaptive Niche The total niche will contain components linked to modes of adaptive response as diverse as primary allomorphism and anagenesis, there being no sense in which anagenetically structured components of the phenotype constitute ‘‘nonadaptive’’ aspects of the organism–niche interface by virtue of the absence of an active selection interface during periods of anagenetic stasis (as has sometimes been imagined). The correct interpretation here is that the selection interface is largely concentrated on adaptive equilibrium for most ambient activity in the adaptive system, whereas essential niche-linked structural parameters exist in a state of evolutionary stasis maintained by a ﬁxed contribution to the adaptive state for long periods of time, namely, through the medium of the adaptation interface alone. The anagenetic component of the total niche is simply the spatial summation of a cluster of isotropic niche parameters (the macroniche), the most stable of which are identiﬁable particularly (although not exclusively) in sub- and hypoparametric niche space (see Chapter 2).

Major Cladogenesis and Anagenesis Is all anagenesis ultimately derived from a major cladogenetic selection interface? Speciation occurs as a partial realization of cladogenetic potential. How does iterated cladogenetic activity affect subsequent evolution following the actual genome split itself? And what happens when a cladogenetic event is also coincident with a major anagenetic shift?

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Cladogenesis is composed of several levels of selectional activity, from minor (phenotypic) through speciation (genotypic), continuing into the domain of the transspeciﬁc selection interface. The reason for rapid structural divergence of species may often lie, not in the act of speciation itself, so much as in postspeciational divergence. There will clearly have been a release from the centripetal component of cladogenetic potential once reproductive isolation has been implicated, and this may in fact facilitate such activity. Postspeciational cladogenesis (see Chapter 6) is identiﬁed as an evolutionary mechanism involving mutual repulsion between isolated gene pools following a speciation event, in which the two gene pools involved continue to compete for shared niche space until the centrifugal cladogenetic force is fully resolved. This results from a tendency for progressive elimination of the gene pool niche intersect following the evolution of gene pool isolating mechanisms—a mechanism that is also partly signiﬁed by ‘‘character displacement’’ for gene pools with only a partial distributional overlap (see below). The speciation process itself need contain only that complement of potential for behavioral or structural modulation lying within the domain of gene pool isolating mechanisms, up until gene pool isolation is effectively equal to 1.0, although the degree of divergence between emergent gene reservoirs will obviously depend on events that have occurred in independently evolving, allopatric gene pools. In this context, ‘‘microspeciation’’ is, in fact, the true speciation mechanism per se, and much postspeciational divergence will probably tend to reside in postspeciational cladogenesis. This is the result of postspeciational centrifugal selection forces affecting the continued morphodifferentiation of species through extension of the inﬂuence of cladogenetic forces beyond the narrower conﬁnes of primary species isolating mechanisms. Postspeciational divergence is also the mechanism responsible for (rather than being strictly synonymous with) ‘‘character displacement’’: Lack (1947) found that seed eating geospizine ﬁnches in the Galapagos occurring on the same island were more divergent in beak length than when they occurred alone, and that species with very similar beaks rarely occurred together. Brown and Wilson (1956) stated, ‘‘When two species overlap geographically, differences between them are accentuated—the effect in question being weakened or lost outside this zone.’’ Dobzhansky (1970) stated that habitat, temporal, and ethological mechanisms in particular were involved in ‘‘character displacement’’ of this kind. Character displacement between species is clearly one aspect of postspeciational cladogenesis, and this also belongs in the postspeciational component of the phyletic evolution heterogeny of Simpson. The intensity of the postspeciational cladogenetic force must clearly be proportional to the degree of distributional sympatry in gene reservoir space; hence, character displacement is simply the expected steep end of the postspeciational cladogenetic gradient manifested in evolutionary change to gene pools of a gene reservoir that are only locally contiguous in distribution, so far as species emerging from a common cladoge-

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netic bifurcation point are concerned. This does not, of course, exclude competition from more distantly related species having an effect on evolutionary rate and direction in the postspeciational domain (see Chapter 18). Given that some ‘‘cladists’’ have chosen to reject the concept of postspeciational divergence, it is essential to see that the phenomenon of character displacement quite clearly proves the reality of this mechanism, in the context of restricted overlap between ranges of species. Where complete neosympatry exists (as must surely be a frequent scenario), postspeciational divergence must logically be at least as great as that expressed when there is only a partial intersect. Renschian Cladogenesis and the Domain of Anagenesis The above analysis contains several points which clearly require deeper investigation. Under certain conditions, a speciational event may lead to the origin of a new lineage manifesting a new anagenetic sequence. This mechanism is clearly not ‘‘ambient speciation,’’ which latter must contain much amphigenetic activity. The cladogenetic event that gave rise to the class Aves, for example, is clearly of a qualitatively different nature to that separating closely related species of phylloscopine warblers! ‘‘Macrocladogenesis’’ (where two new higher groups diverge at a speciation node) occurs whenever a cladogenetic event explores divergent paths, one of which is linked to a novel anagenetic sequence, complementing a new lineage niche. Renschian cladogenesis (see Chapter 6) is thus expressed by an iterated adaptive response to a coincident cladoanagenetic selection interface. In Renschian cladogenesis, a new anagenetic lineage is initiated; in ambient speciation, new gene pools are deﬁned within the context of the preexisting lineage: Ambient speciation

Renschian cladogenesis

Iterative dimension is not constantly directional in terms of the selectional attractor. Niche proﬁle is not isotropic for any leading effect.

Iterative dimension is directional in terms of niche proﬁle and the structural attractor. Niche proﬁle is isotropic for some leading effect phenon or structure unit or integral.

Renschian cladogenesis is therefore ‘‘cladoanagenesis,’’ its origin involving functional change and qualitative niche shift. It is also transspeciational in ultimate directionality, in that an emergent lineage may subsequently be punctuated by further, ambient speciation events. The corollary of this is that any anagenetic sequence that is linked to the Renschian bifurcation will in no way be impeded by subsequent cladogenesis. Cladogenesis and anagenesis may alternatively be manifested as potentially independent mechanisms, since there is no reason why anagenesis cannot be initiated by factors which did not form part of the preceding cladogenetic selection interface. Thus, postspeciational cladogenesis only includes that component of anagenetic activity that is ‘‘residual’’ in terms of a partially resolved, preexisting Renschian cladogenetic event. However, we must at a later stage go on to consider how much anagenetic change can occur before speciation is actually invoked by that process (see Chapter 17).

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ANAGENESIS AND EVOLUTIONARY PROGRESS Rensch (1959) proposed usage of the term anagenesis for ‘‘development towards higher phylogenetical levels’’ and cladogenesis for lineage splitting. Huxley (1942) developed similar ideas to Rensch, deﬁning progress as an unrestricted type of improvement permitting further improvement. Rensch’s view of anagenesis included the notion that ‘‘a general improvement is met with in all major animal phyla and in numerous animal classes so far as we may judge by their phylogeny,’’ a viewpoint that has since been widely contested (see, for example, Williams, 1966). This insistence of an equation between anagenesis and general evolutionary progress was probably in large part responsible for a decline in interest in this evolutionary mode in many quarters.

Dimensions of Evolutionary Progress Huxley (1942) and Rensch (1947) listed those characteristics which they regarded as constituting progressive evolution. Their views were, however, later dismissed by Simpson (1949), although Dobzhansky (1970) chose to disagree with this refutation: Rensch’s features of anagenesis were given as increased complexity, rationalization of structure or function (including simpliﬁcation or centralization), increased plasticity of structure and function, ‘‘improvement permitting further improvement,’’ and increased independence of environment and command over environmental factors. Rensch further concluded that the most essential phenomena of anagenesis were increased complexity and rationalization of form and function of organs and structures. Not all measures of evolutionary progress have been linked to anagenesis. Thoday (1953, 1958) proposed time as the measure of progress. However, some of the least evolved living things then become ‘‘the most advanced,’’ despite the observation that many long-term ‘‘survivors’’ are in fact of very restricted distribution and probably approaching extinction! Similarly, diversity of species in a lineage is no measure of progress, as many ‘‘explosive radiations’’ have been short lived in geological terms. The question of evolutionary progress has also been raised in relation to the proﬁle of additive genetic variance in populations, as with Fisher’s fundamental theorem of natural selection, which held that the rate of increase in ﬁtness of any organism at any time is equal to its additive genetic variance at that time. Fisher’s theorem is, however, a misunderstanding of ﬁtness. For example, a gene pool may enjoy high survivorship in a stable, channeled environment or in a highly chaotic one, by virtue of having little in the way of additive genetic variance in the former, or a mainly logistic adaptive strategy in the latter (see also Maynard Smith, 1998, for a discussion). The question as to whether long-term evolutionary change can manifest any characteristics which may be described as ‘‘progressive evolution’’ must now be critically reexamined, and here it is necessary in the ﬁrst instance to

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distinguish progress in the adaptive state from anagenetic progress toward the structural attractor. Progress must clearly be investigated with reference to two quite different dimensions. The state of adaptation for a given subject gene pool seeks to maintain stasis (probability of survival 씮 1.0) in relation to changing selection proﬁles in the adaptive system. Over time, the fundamental adaptive state of a lineage may tend to increase by virtue of such diverse criteria as expansion of the total number of gene pools and expansion of the allomorphic domain in response to the periodic behavior of the selection interface. However, the real adaptive state of a gene pool perpetually tends to 1.0, in the absence of extinction. The fundamental adaptive state (see Chapter 5) thus follows a path of dynamic equilibrium, since variation in the external environment is continually acting to depress adaptivity and thus, also, to deﬂect the lineage gene pool toward a logistic strategy. Even if we consider that the index Ai gives an indication of the degree of gravitation toward the structural attractor, this no doubt also follows a pathway of dynamic equilibrium at the level of lineage, at least in the longer term. Evolution thus constitutes organic change in the adaptive response in terms of maintenance (rather than ‘‘raising’’) of the real adaptive state. However, evolutionary topology simultaneously describes the integral of structural adaptational change over lineage time. This integral is ‘‘summed,’’ not within the state of adaptation (which, as we have just seen, perpetually tends to 1.0), but only in the dimension of structure as this relates to the biophysical paradigm state. The later situation can thus only be understood within the context of anagenesis, and in relation to the structural selectional attractor (see previous chapter). Adaptational progress thus appears to relate to ﬂuctuation between fundamental and real adaptive states, and not to the structural element of evolution as manifested in anagenetic change, but the latter can nevertheless objectively be termed ‘‘progressive’’ in relation to the biophysical paradigm state. Only on the anagenetic plane do we ﬁnd (in this modiﬁed context) true progressive evolution, since the state of adaptation cannot proceed beyond 1.0. This situation can be visualized by viewing evolutionary progress on two planes (Fig. 39). To what extent can ‘‘structural progress’’ in the above scenario be linked in turn to improvement in the actual adaptive state? Knoll (1984) states that no mass extinction of vascular plants occurred at the K–T boundary. However, taxon replacement was clearly associated with improvement of vascular architecture and mechanisms of fertilization, and angiosperms thus ousted other groups. The above example seems to show that the anagenetic state does ultimately affect the probability of longer term survival. However, many other lineages (for example, Echinodemata and Coelenterata) have survived in the very long term with similar logistic adaptive strategies to those of lower plants! Consequently, although it is possible to ﬁnd examples where structural progress has apparently led to a sustained increase in the adaptive state, these two planes appear not to be inextricably linked in the very long term.

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FIGURE 39 The adaptive index (Ai) is seen following a pathway of adaptive equilibrium, whereas anagenesis (Ya) progresses toward an adaptive optimum (X axis ⫽ lineage time; Y axis ⫽ adaptive state).

We must now go on to reconsider the view expressed by Williams (1966), ‘‘Selection will maintain adaptation by occasionally substituting one adaptive character for another, but this will not result in any of the kinds of cumulative progress that have been envisioned.’’ This statement is entirely true in terms of the adaptive state of a lineage, but it does not apply to the phyletic trajectory toward a functionally reﬁned state in the structural attractor as manifested in anagenesis. A further problem is, of course, that we also have to distinguish between functional and adaptational progress: A ﬂint axe is functionally primitive compared to a powered chain saw, but it could prove adaptationally superior if the high technology method encounters nonsustainability over a longer time frame. Because selection (and adaptation in general) is ‘‘blind to the future,’’ many functional advances will constitute adaptational blunders in the longer term. Gryphaea coiling is an example of this (see also Chapter 20). Behavioral Evolution and Evolutionary Progress From the above analysis, progress in evolution appears to be a predominantly structural phenomenon. However, the ultimate goal is stabilization of the strategy of maximizing deterministic survival factors over purely stochastic inﬂuences in the adaptive system, and the mechanism for this may in fact tend ultimately to shift toward the behavioral domain, as the axial drive of longterm evolution reaches fruition. This function may be seen as an extension of behavioral control beyond the time t dimension (life span of an individual), as rendered possible by ﬂow of information from generation to generation, initially through the medium of parental care and learning and ultimately

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through cultural evolution. This clearly constitutes the true axis of evolutionary progress, in the very long term: The selection interface for perpetuation of genes concerned with social interactivity follows a modiﬁed paradigm deﬁned by Hamilton (1964a,b), according to an increase in probability of survival arising from an effect of the behavioral interaction in question, this being linked to degree of genetical relatedness between ‘‘helper’’ and ‘‘recipient’’ individuals. This is inclusive ﬁtness, as deﬁned by number of offspring produced by a ‘‘helper’’ genotype AA minus offspring produced by the carrier owing to help received, plus additional offspring produced by relatives as a result of help from AA, weighted by degree of relatedness between AA and recipients. In the tripartite model of the selection interface (Chapter 4), the leading factor may fall progressively more to kinship adaptation via the medium of inclusive ﬁtness. However, this does not change the concept of the gene pool as forming the ‘‘epicenter of adaptation.’’ This confusion arises only from the (perfectly valid) approach of adopting a ‘‘genocentric’’ view of the manner in which inclusive ﬁtness operates (see Dawkins, 1976). However, choice of a convenient reference frame should not be misconstrued as a negation of the way in which higher levels of complexity evolve in the gene pool, as an emergent evolutionary corollary of fundamental genic selection. Behavior is thus ultimately dominant over structure as the leading realization function in orientation of the adaptive ensemble (see Chapter 1), in the quest for maximization of the adaptive state, and the selectional attractor similarly comes to encompass that domain. Advanced behavioral systems clearly possess the capacity or potential for direct manipulation of the environment—and ultimately also of the structural component of adaptation itself. In this context, genetic engineering becomes part of human adaptive capacity and potential. Capacity for information processing could thus be a better measure of progress (although only if this is additionally linked to cognizance of shortterm gain as against long-term loss!). Complexity and Evolutionary Progress The behavioral paradigm clearly requires a certain level of preexisting structural complexity before an optimum ﬁtness strategy can be further invoked. Evolution thus must initially follow a path of increasing biophysical efﬁciency, and this in turn may or may not contain a corollary for an increase in behavioral plasticity also. In the release of complex behavior patterns, we may ultimately also observe a mechanism tending to release the adaptive state from its pathway of dynamic equilibrium. The criterion of complexity extends far beyond that of structural advancement and behavioral ﬂexibility, to additionally encompass aspects of the holistic activity of entire biotas: Odum (1971) stated that increasingly complex and diverse systems have achieved control over the atmosphere. In this view, there is in fact some form of general progress in the evolution of adaptive systems

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that is manifested by whole biotas, rather than by discrete phyletic lineages. This must be viewed in the context of the potential of global adaptive systems to proceed toward the evolution of higher levels of complexity within which consciousness emerges. In this manner, it can also be seen that adaptive systems themselves manifest progress in terms of the level of complexity emerging during very long-term evolution.

MAIN POINTS FROM CHAPTER 8 1. Allelogenesis, as positive neomorph mutation (exclusive of mutations perpetuated in a state of genetic drift by stochastic factors alone), is the raw material of all evolutionary change. 2. Evolutionary mode is manifested in topology of the phenotypic adaptive response following iterative allelogenesis over lineage time. Three fundamental modes exist: cladogenesis, anagenesis, and amphigenesis. 3. The microevolution/macroevolution dichotomy should ideally be based on the presence or absence of reversibility within adaptive potential. Only speciation and anagenesis (in part) constitute true macroevolution. 4. Amphigenesis constitutes evolutionary reversal within the domain of adaptive potential. It is thus equivalent to ‘‘anagenesis which not only retains adaptive potential for reversal, but where the latter actually occurs.’’ This evolutionary mode may frequently form a large element in species differentiation. 5. Anagenesis arises from an iterative train of evolutionary changes gravitating toward major coordinates of a distant structural attractor, in the context of an isotropic niche proﬁle. It may be linked to postspeciational divergence or else function entirely independently of any cladogenetic selection interface. 6. Evolutionary progress can be deﬁned in relation to the trajectory of an anagenetic sequence, but not necessarily in the adaptive state of a lineage. However, progress is also an emergent property in the evolutionary behavior of entire adaptive systems.

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Having investigated those factors which determine the architecture of the structural attractor and the modes of evolution associated with different conﬁgurations of selection proﬁle, it is now necessary to consider how these factors relate to development. There is clearly a need at this juncture to understand the biophysical paradigm concept, not only in relation to the ﬁnal phenotype state at the adaptation interface, but also in consideration of aspects of function which operate during development. In this approach, we should also hope to be able to identify the developmental coordinates of adaptive potential, as a prelude to a deeper investigation of the manner in which genetic systems control and modify structure paradigms. Adaptive potential cannot be envisaged as being realized by virtue of one step gene mutation or from mere recombination of preexisting alleles, but must involve factors appertaining to iterative neomorphic mutational activity of genes affecting the major coordinates of development. The genetic dimension in adaptive potential thus clearly lies with the developmental, rather than Mendelian model, in that the latter can have only limited relevance beyond realization of adaptive capacity. As stated by Maynard Smith (1972), the failure of neo-Darwinism lay mainly in the lack of a developmental component to the genetics program. It is in the latter that we must now seek a deeper understanding of the true signiﬁcance of the Thompsonian ‘‘internal’’ input to the general theory of evolution.

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DEVELOPMENTAL DYNAMICS OF THE BIOPHYSICAL PARADIGM We have so far considered evolution of the phenotype, yet the ﬁnal adaptive state of structure cannot be divorced from the mechanisms of development. Thus, there must be other biophysical paradigms operating at precursor levels. The structural selectional attractor cannot therefore constitute a single entity relating to the ﬁnal phenotype state, but must tend to vary in some manner with respect to different phases of development. The biophysical paradigm is thus a dynamic entity, not only during anagenesis, but also throughout development. The ensuing discussion will be particularly concerned with the morphogenetic dimension in development, since major evolutionary changes are deﬁned and measured in that context, in terms of progress toward paradigm form in biophysical design. In this context, the largest functional ‘‘anagenetic targets’’ must be four-dimensional loci described by the coordinates of growth and morphogenesis.

Adaptational and Fabricational Paradigms of Development That the biophysical paradigm is dynamic within the trajectory of development for any chosen structure integral is clear from the fact that different developmental activities evidently perform different functions at different developmental stages: The thoracic tracheae of the insect wing manifest independent functions at different developmental stages, having a respiratory role in the embryo combined with a morphogenetic one connected to the trajectory of developing wing veins, ultimately providing mechanical support of the wing membrane in the adult phase. What principal biophysical paradigms does a structure pass through during the course of a complex developmental trajectory of the kind just described? To answer this question, we may begin by comparing and contrasting two different goals of development, one linked to the structural coordinates of direct adaptational mechanisms of the free-living phenotype, the other concerning the mechanisms through which phenotype form is actually assembled. These functions thus appear to be respectively linked to adaptational versus fabricational paradigms, a dichotomy which will be shown to identify a sharp divergence in the morphogenetic patterns around which development is organized. Thus, not all function is adaptation in the sense of direct interaction with the external environment, in that those fabricational mechanisms lying deeper in the trajectory of development clearly have an indirect adaptational role to play, thus relating to a quite different biophysical paradigm. The adaptational paradigm is the biophysical paradigm state that we have already examined in some detail (Chapter 7), and which relates to direct manifestation of adaptation in the organism–environment interaction, whereas the fabricational paradigm is that which is concerned with ‘‘how to construct something in an energy efﬁcient manner.’’

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The overall biophysical paradigm thus changes during development, owing in particular to the existence of a fabricational function at certain stages. There are therefore phases when the coordinates around which development is organized are predominantly external (linked to the adaptation interface) or internal (linked to fabricational function), and these differentials have profound implications. Clearly, a fundamental distinction also exists between structural paradigms lying in earlier parts of the developmental function cycle and those existing at later stages, since the former are more likely to be linked to the fabricational than to the adaptational paradigm. Structural paradigms for early development thus may manifest a completely different relationship to the function integral components of ﬁnal phenotype form. In general then, the developmental trajectory tends to begin within the framework of a predominantly fabricational paradigm, then gravitate progressively toward an adaptational one as we approach the phenotype state. Locus of the Selection Interface in Development While the adaptation interface lies at the end of a function cycle in behavior, the selection interface can lie at any point in a behavioral or developmental function cycle. Selection acts not only on ‘‘ﬁnal traits,’’ but also on the fabricational viability of precursor morphogenetic states of earlier development. The endogenous selection interface is that which demands the fabricational paradigm. At a later stage, we shall also see that a further, indirect adaptation interface also exists in development, in the restricted sense of the embryogenetic paradigm (see below).

PRINCIPAL STRUCTURAL PARADIGMS OF DEVELOPMENT We may consider that early development is dominated by cytogenesis as the zygote divides and cells multiply, at ﬁrst seemingly with little evidence of determination, then with the ﬁxing of a few major coordinates such as the anterior–posterior and dorsoventral body axes, as cytogenesis gives way to a histogenetic phase. As cleavage ends and gastrulation commences, we begin to see the emergence of those morphogenetic coordinates that are characteristic of higher group lineage, then of progressively narrower systematic divisions. Many observed evolutionary changes are reﬂected within these mid-level developmental coordinates, so that a ﬁrst approach must be to examine the nature of the morphogenetic paradigms around which development evolves in the immediate wake of early cytohistogenesis.

Ontogeny, Phenogeny, and Embryogeny Given that qualitatively different biophysical paradigms clearly do exist for fabricational versus adaptational states (see above), it follows that the developmental process itself must be subdivisible into several interacting yet quasiautonomous systems.

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The highest coordinates of morphogenesis must in fact be organized around biophysical paradigms deﬁning developmental processes corresponding to three principal paradigms based on quasi-autonomous functions linked to adaptational and fabricational structural paradigms, and also to the external versus internal adaptation interface. The three principal processes of development are here named as follows*: 1. Phenogeny is that developmental paradigm which is linked to an active adaptation interface with the external environment. 2. Ontogeny is that paradigm which is concerned with purely endogenous fabricational function. 3. Embryogeny is the endogenous adaptational paradigm, linked to parent metabolism rather than to the external environment. The above scheme can be visualized as shown in Fig. 40, using part of the development trajectory for the insect wing as an exemplar.

FIGURE 40 Embryogeny, ontogeny, and phenogeny in relation to a single developmental trajectory (the thoracic tracheal system of an insect).

No developmental paradigm can of course be presumed to be a single static entity, but rather the phenogenetic, fabricational, and embryogenetic paradigms must constitute dynamic structures. In the same way, the three structural paradigms must also interdigitate with one another during the course of development. Each fabricational sequence thus forms part of a continuum which gradually merges with a phenogenetic sequence, the latter ending at the adaptation interface in the ﬁnal phenotype state. Separate function chains in the developmental trajectory may thus express qualitatively different manifestations of evolutionary activity, and certain developmental trajectories may manifest considerable mutual autonomy. For example, the embryogenetic paradigm may include certain elements that are completely independent of the phenotype state. * In the nomenclature used here, I have striven to avoid proliferation of new terminology, while at the same time being aware that certain terms have been used either in different contexts or even synonymously in the past.

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The above observations can be shown to have profound implications for the concepts of adaptive capacity and potential, and it is also evident that the structural attractor has separate domains in pheno- and ontoanagenesis. Origins of the Phenogenetic Sequence The nature and origins of phenogeny as a dynamic structure can be understood through consideration of a simple developmental sequence expressing only growth by repeated binary cell division. Change in absolute size may come to link to a sequence of temporal changes in the adaptive niche as the organism–environment relationship complexiﬁes, and this in turn may favor change in the structural adaptive response. Even in the absence of any real qualitative change in niche, the adaptive paradigm will thus tend to manifest an endogenous differential expressed in the dimensional spectrum (see Chapter 7) as a result of a varying gravitational inﬂuence as growth proceeds. The adaptive response to selection pressure linked to dynamic niche parameters may thus tend to be expressed in differential growth, thereby describing a simple phenogenetic sequence, rather than a single ﬁnal state. Altered adaptational paradigms linked to changing niche structure may thus come to be expressed in the adaptive response as a phenogenetic sequence. In this scheme, some cell lineages may express simple linear growth while others manifest an ‘‘allometric’’ (log–linear) pattern, and the values of constants and variables in the equations of growth may diverge between different cell lineages, the outcome being the evolution of a progressively more complex phenogeny. Of particular interest from the viewpoint of adaptive potential is the likelihood that one focus for ﬂexibility in developmental coordinates clearly lies with those axes of growth linked to allometric differentials in the phenogenetic sequence, a circumstance which seems likely to be a fundamental attribute of most higher organisms (see Chapter 16). The phenotype of higher organisms is frequently described by a sequence of connected states, rather than by a single postembryonic form: The larval body vestiture of butterﬂies and moths has a phenotypic adaptive function through several instars which often differs considerably from one instar to the next. Such state-to-state changes are not of exclusively fabricational function, but reﬂect differences in the external adaptation interface at different stages of postembryonic development, which are probably at least partly linked to size differentials.

Phenogeny thus describes the trajectory of development of the phenotype in terms of structure linked to adaptational activity in a changing external environment and is frequently described by a phenogenetic sequence. Caenophenogeny The more niche change during development tends to lie with qualitative differentials, the more the phenogenetic sequence will tend to express discontinuity over the course of a developmental trajectory, as the adaptive response meets a demand for structural specialization. Very many phenogenetic sequences thus consist of nonlinear patterns of change. In this, we must distinguish between simple and complex ‘‘caenophenogenetic’’ developmental trajectories. The biophysical paradigm for a given developmental phase can thus be either ‘‘axial’’ or ‘‘tangential’’ to the primary phenogenetic sequence:

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• Axial refers to quantitative change, for example, linked to an environmental cline correlated with simple growth relationships in the relevant adaptive response. • Tangential refers to qualitative change, where the adaptive niche is qualitatively different from one phenogenetic phase to next; differentials do not then form a simple linear progression with respect to the coordinates of morphogenesis.

FIGURE 41 Caenophenogeny: P1, P2, P3 ⫽ three phenogenetic states carrying adaptational specializations in terms of qualitative temporal differentiation in the adaptive niche (N1–N3).

In this way, the phenogenetic sequence either shows an axial progression between closely related adaptational paradigms, or else it manifests qualitative changes when the adaptation interface links to highly tangential adaptative states. Caenophenogeny can therefore be deﬁned as that manifestation of phenogeny in which a qualitatively different adaptation interface affects independent components of morphogenesis via the adaptive response, and this will usually reﬂect a sequence of qualitatively different niche regimes. Haeckelian ‘‘caenogenesis’’ is thus a special case of phenogeny: The above trend can be seen in its most extreme manifestation in the metamorphosis of holometabolous insects, which incurs two phases of embryogeny (namely, where there is a second quiescent phase linked to larval metabolism). This clearly constitutes complex caenophenogeny. Dynamism in the spatial and temporal planes is, of course, a fundamental characteristic of the adaptation interface. The ‘‘horizontal perspective’’ is derived from distribution of ‘‘spread K’’ over gene reservoir niche space via the allomorphic structure of the gene pool, while the ‘‘vertical perspective’’ of phenogeny lies with niche parameters which change over a time course (the distribution of K over time t). The Origins of Ontogeny and Embryogeny The emergence of a multicellular organism resembling the cytogenetic stage has been supposed to have occurred from a ciliated unicell which formed

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an aggregate not unlike the early embryos of the ﬁrst metazoan phyla (see Gilbert, 1997). Wolpert (1990a) states that the evolution of development required little that was not in the original eukaryotic cell, and that the origin of embryonic structures probably lies with Haeckel’s gastrea theory. A colonial protozoan gave rise to a two-layered structure, the inner layer entering through invagination (many higher animals manifest an early gastrea stage resembling this hypothetical ancestor). From the gastrea body plan, retention of nonciliated cells created adaptive potential for evolution of a multiplicity of specialized cell types, so that an early stage in which migration of cells to a protected interior occurred was a crucial development in the advance toward a more advanced form of multicellular organization. Greater stability of the blastula suggests that this is that stage at which the fundamental body structure is established (Anderson, 1973). The early gastrealike organism possessed a multicellularity which in turn must have constituted the substrate on which not only phenogeny but also ontogeny and embryogeny must subsequently have been superimposed as an adaptational corollary of increasing complexity. Following origins of the gastrea, the embryo must then have appeared in the form of a quiescent stage, which in turn would have favored the evolution of fabricational and other endogenously functioning specializations. Two mechanismic corollaries follow on from quiescence: (1) ontogenetic traits are permitted to evolve in response to selection for fabricational parsimony, while (2) truly embryogenetic traits such as mechanisms for communication with the external environment (for example, oxygen exchange) would be demanded in the context of a progressively prolonged quiescent stage. The appearance of specialized embryogenetic and ontogenetic traits may then have facilitated the capacity to evolve an even longer period of quiescence, which in turn required supplementation of stored food resources, while at the same time increasing the opportunity for further complex differentiation of tissues. Embryogeny and ontogeny must therefore have evolved in concert from the earliest stage in the evolution of complex multicellular organisms. The Intersect Ontogeny–Phenogeny Ontogeny sensu stricto was deﬁned above as being that sequence of precursor states in the developmental function cycle which precedes a fully active adaptation interface with the external environment, also describing a fabricational sequence in morphogenesis. From the preceding analysis, the phenotype itself must be deﬁned by a phenogenetic sequence of structural change or single ﬁnal state having a direct interface with the adaptive niche. Exclusively ontogenetic states are therefore neither phenotypic, nor are they part of phenogeny. However, during much of development, a given structure unit clearly may simultaneously express both fabricational and adaptational function. It is thus evident that the three developmental paradigms (phenogeny, embryogeny, and ontogeny) do not display total autonomy. The greatest levels of ‘‘vertical’’ modularity may perhaps be found in the early divisions between endo-, ecto-, and mesoderm (for example, many endoderm derived structures have a truly embryogenetic role

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to play, whereas mesodermal features tend more toward the phenogenetic paradigm); likewise, ontogeny may often tend to constitute the dominant force in early development: Predominantly fabricational paradigms can be seen in operation, for example, with gastrulation in the Drosophila embryo. Anterior and posterior rudiments of the developing gut do not join up until stage 14 (following Hartenstein’s nomenclature, 1993), although these rudiments are evident by stage 5 (stages 1–4 ⫽ cleavage). This can only relate to the ontogenetic paradigm. The possibility that some pivotal point exists at which the predominant morphogenetic paradigm changes from ontogenetic to phenogenetic may perhaps be approached from the observation that diverse vertebrate classes share a common phylotypic stage which appears after organogenesis has begun. This phenomenon is linked to the ‘‘developmental hourglass’’ metaphor of Raff (1996), which describes that situation whereby propensity for mutational change of developmental parameters is high ‘‘above’’ and low ‘‘below’’ the phylotypic stage—a circumstance which, according to Duboule (1994), might have some correlation with the domain of the Hox genes (see Chapter 11). From the viewpoint of the present analysis, Raff’s model seems likely to relate in some way to the transition between fabricational and adaptational paradigms during development. However, despite the broad pattern of ‘‘phenogeny succeeds ontogeny,’’ it is clearly not possible to deﬁne any absolute spatial or temporal dividing line between these two developmental paradigms, since many structures have a joint fabricational and adaptational role to play at the same time horizon, and since some parts of the embryo may be forming organs while others are still in the process of gastrulation (as indeed is the case, e.g., with the chick embryo). Fabricational Parsimony in Ontogeny Wolpert (1990a) considered that the selection forces acting on development were to some extent unclear, yet apparently suggestive of economy of energy usage; if the same thing can be done in two ways and one is more energy efﬁcient, perhaps selection will act on this. In the present view, the basis for endogenously acting selection pressure in development is presumed to lie with fabricational parsimony, with respect to the ontogenetic rather than phenogenetic paradigm. Much ontogenetic activity presumably expresses a dual function: fabricational (how to make something) and fabricational parsimony (the most economical way of fabricating a structure in terms of energetic economy), given the relative absence of constraints normally imposed by the adaptational paradigm. ‘‘Pure’’ ontogeny thus describes that component which completely excludes coordinates linked to the active adaptation interface and which is thus concerned with fabricational parsimony, often with a broadly modularinteractive function for several different morphogenetic trajectories. The further we recede from ﬁnal phenotype form in the developmental sequence, the more the paradigm for ontogeny may tend to converge on a state deﬁned by fabricational parsimony, this evidently frequently overriding the modularity expressed by discrete structure and function units of the ﬁnal phenotype.

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Only where the adaptation interface is completely redundant (i.e., in the sense of former adaptational coordinates becoming encapsulated into the quiescent phase of development) can selection favor developmentally parsimonious change in the fabricational sequence of ontogeny. A ‘‘lost terminal state’’ may then either tend to ‘‘recapitulate’’ an earlier phenotype, or else more probably, it may represent some modiﬁcation of the latter which has come to serve as a fabricational precursor to the ﬁnal phenotype state, while at the same time introducing some metabolic saving by virtue of being a simpliﬁcation of the original phenotype state from which it was derived. The ontogenetic sequence must not therefore be presumed to automatically manifest the phenomenon of recapitulation, although it may sometimes converge on that state under certain circumstances (see Chapter 16). Earlier ontogeny is thus characterized as being that component for which biophysical paradigms tend toward fabricational parsimony, rather than being concerned with the exogenous adaptation interface. It is further seen as an energy rationalization function superimposed on development, the function for which probably lies in economic distribution of energy throughout development—and thus also through metabolism in general. The domain of fabricational parsimony clearly has an intersect with all ontogeny, although earlier development clearly offers the greatest opportunity for its manifestation. The structure–function interface for ‘‘pure’’ ontogeny is truly internal, and any selectional activity will also link to an endogenous paradigm. It is a major part of the deﬁnition of pure ontogeny that fabricational parsimony will, furthermore, tend to include structures derived from cell lineages that are not functionally linked in the ﬁnal phenotype and that also may not have originally been developmentally linked. This phenomenon will be investigated more fully in the context of fundamental developmental mechanisms (see next chapter). Fabricational parsimony acts continually to modify precursor states, potentially leading to an expansion of free morphospace for continued evolution, while also invoking some degree of rigidity against further change. That paradox will clearly need considerably more attention in the analysis of adaptive potential. Embryogeny and the Endogenous Adaptation Interface We have already observed the existence of separate exogenous and endogenous adaptational paradigms. This criterion explicitly deﬁnes embryogeny sensu stricto, at the same time distinguishing the extrinsic from the endogenous adaptation interface. The latter lies with the embryo in its links with parent metabolism and direct exchange with the external environment, while the former lies in the external environment itself. As predicted by the intersect between phenogeny and ontogeny, all three developmental paradigms are not discrete but interlocking, in that a given structure may jointly manifest ontogenetic and embryogenetic functions, etc. (Fig. 42): The interaction between ontogeny and embryogeny is exempliﬁed by the development of the wing in some holometabolous insects. The course of the adult wing veins, following the paths of thoracic tracheae

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FIGURE 42 The intersect between the three developmental paradigms (X ⫽ ontophenogeny, Y ⫽ ontoembryogeny).

of more primitive insect groups, has come to be partly determined independently of the developing tracheae, which latter continue to function in respiration, during that phase in which specialized changes to adult wing veins are beginning to appear from separate rudiments. In those orders where tracheation is reduced, the tracheae may not actually penetrate the wing sac until after the wing veins have formed (see Comstock, 1918, also Snodgrass, 1935). Thus embryogeny and ontogeny are more closely coupled in hemimetabolous than in advanced insect lineages (nevertheless expressing some degree of interaction in both). The embryo itself is thus essentially that phase of development during which energy exchange is linked to parent metabolism, and is therefore to be regarded as constituting the functional basis for an endogenous environment interface.

General Architecture of Development The principal structure paradigms of development have now been identiﬁed as phenogeny, embryogeny, and ontogeny. The broad relationship between these three processes during the course of a generalized developmental trajectory can be most conveniently illustrated following the tenets of the following simpliﬁed model.* In the purely schematic system used in Fig. 43, the following conventions have been adopted: * Reiss (1989) gives three common growth curves for animal development: the Bertalanffy equation, dW/dt ⫽ AWm ⫺ BW; the Gompertz equation, dW/dt ⫽ AW(loge W ); and the logistic equation, dW/dt ⫽ AW ⫺ BW 2. The simple log–linear model used here is merely a convenient reference frame for discussion of partitioning within the developmental landscape, rather than being intended as a realistic model of growth or morphogenesis.

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X axis ⫽ time course of development Y axis ⫽ accumulative growth in embryogeny ⫹ ontogeny ⫹ phenogeny (highly schematized as following a simple linear trend) Ye ⫽ accumulative morphogenesis partitioned to embryogeny Ye⫹o ⫽ morphogenesis partitioned to embryogeny plus ontogeny Following the above conventions, the proportion of growth apportioned to the three developmental paradigms for morphogenesis is indicated by partitions within the total growth curve. The schematic model serves to address, in a very general way, the usual level of complexity found in the developmental systems of higher animals.

FIGURE 43 Generalized model of animal development, showing the three principal paradigms of structure (X ⫽ developmental time, Y ⫽ all growth, Ye ⫽ growth in embryogeny, Ye⫹o ⫽ growth in embryogeny ⫹ ontogeny).

Ignoring the artiﬁciality of the above model, the signiﬁcant features are as follows: • Early development is dominated by ontogeny and embryogeny. • Embryogeny tends to end more or less abruptly at, or immediately after, the eclosion line, that point in time at which the embryo becomes a free-living organism. • Ontogeny may tend to continue into the free-living juvenile stage for some time, but it terminates before the ﬁnal sexually mature phenotype state is reached.

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• A large component of pre-eclosional development has a combined (embryogeny ⫹ ontogeny ⫹ phenogeny) paradigm, with ontogeny and phenogeny dominating the mid range. • Phenogeny is the dominant force in postembryonic development. • Following the end of phenogeny, the ‘‘static’’ adult stage is reached: An exemplar exhibiting all of the above features can be found with the development of a hemimetabolous insect in which pre-eclosional ontogenetic development of wing is followed by continued fabricational development during the posteclosional stage, and where there is also an embryogenetic function of wing tracheae at the pre-eclosion stage. Posteclosional phenogeny is also evident in the larval stage of many holometabolous insects. The above system cannot of course serve as a ‘‘universal’’ model for all developmental systems. There is a particularly stark contrast between animal and plant development, which latter is said by Stebbins (1988) to possess only about one-ﬁftieth of the degree of complexity of that found in higher animals, as well as exhibiting a very different temporal pattern for cell and tissue differentiation in the embryonic meristem. The Principle of Morphogenetic Accommodation A framework for the analysis of adaptive potential must link to the coordinates of biophysical paradigms existing in the temporospatial matrix of development. From the above observations, two principles emerge regarding the distribution of the coordinates of complex morphogenesis, the second of which constitutes a corollary of the ﬁrst. The modularity principle states that there must be n epicenters of morphogenetic activity that are at least partially but probably never totally developmentally autonomous. Even the developmental loci of adaptive versus fabricational biophysical paradigms may lack complete autonomy, but must to some extent constitute a continuum passing from fabricational to adaptational paradigm, rather than simply ‘‘lying end-to-end’’ in the developmental trajectory: Thompson (1917), referring to the developmental process in general, stated that ‘‘the form of the entire structure under investigation should be found to vary in a more or less uniform manner, after the fashion of an approximately homogenous and isotropic body.’’ However, the divisions between phenogeny, ontogeny, and embryogeny must nevertheless have some inﬂuence on the modularity hierarchy expressed in the developmental program (see also Chapters 10 and 11). The accommodation principle states that the principal coordinates of developmental topology for a given phenotype structure integral lie in a more or less extended time frame within development, thus spanning different biophysical paradigms, separately linked to the external adaptation interface and to fabricational parsimony. Brieﬂy, there can be no ‘‘ﬁnal adaptive state,’’ in lack of morphogenetic continuity with some precursor fabricational state existing at an earlier developmental horizon. The same view is expressed in the continuity principle of Horder (1983).

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The principle of morphogenetic accommodation can also be shown to have a larger dimension with respect to parameters of mutational change (see Chapter 12), and adaptive potential must in turn be linked to both modularity and accommodation, with special reference to degrees of freedom residing in adaptive potential itself. In the latter, we see evidence of that category of socalled evolutionary constraints which in reality manifest a directionalization function over anagenetic change (see ensuing chapters).

MAIN POINTS FROM CHAPTER 9 1. Adaptive potential can only be fully understood in the context of development. The coordinates of adaptive potential must accordingly be viewed as being four-dimensional in nature. 2. The structural biophysical paradigm changes during the course of development, owing to the existence of separate extrinsic and endogenous adaptive paradigms plus an additional fabricational paradigm. 3. Three principal structural paradigms of development can now be recognized: ontogeny (endogenous fabricational paradigm), phenogeny (extrinsic adaptive paradigm), and embryogeny (endogenous adaptive paradigm). 4. Owing to the existence of the endogenous fabricational paradigm in ontogeny sensu stricto, not all biophysical paradigms manifest a direct adaptation interface during development. However, all are linked to either an extrinsic or an endogenous selection interface. 5. The fabricational paradigm of true ontogenetic development is probably chieﬂy concerned with fabricational parsimony. 6. A generalized ‘‘root model’’ of animal development can be designed to reﬂect the three structural paradigms of development. This much simpliﬁed model provides a convenient basis for analysis of the role of development in evolution. 7. Owing to the functional diversity of developmental paradigms, separate domains of pheno- and ontoanagenesis must also be presumed to exist. 8. Development may express both modularity and morphogenetic accommodation in terms of the geometric coordinates of a given superstructure, and degrees of freedom in adaptive potential are much inﬂuenced by these factors. Modularity is concerned with the degree of autonomy expressed by a given phenotypic structure unit during different phases of development, whereas morphogenetic accommodation reﬂects the manner in which phenogenetic, embryogenetic, and ontogenetic paradigms interlock within the developmental trajectory of a given phenotype structure integral.

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ADAPTIVE CAPACITY AND POTENTIAL IN THE MECHANISMS OF DEVELOPMENT

We now have a broad understanding of adaptive capacity and potential and of the principal structural paradigms of development, and it is already evident that the apparent mystery surrounding the structural component of adaptive potential is due to complications with the dichotomy existing between Mendelian and developmental schools of genetics. Attention therefore needs now to be diverted to analysis of the fundamental mechanisms of development itself. As we saw in the previous chapter, there has to be a topological continuum between the fabricational and adaptational paradigms of development. This is not necessarily a geometric continuum in superstructure, since it may also concern substructural factors such as the manner in which cells are aggregated into tissues. It is this latter translational aspect of development which forms the main subject matter of the present chapter. The developmental model must now be followed from gene transcription, through a hierarchy of translation levels. Here, we must endeavor to understand the nature of the controllant factors affecting morphogenesis and the primary mechanisms underlying changing developmental architecture. How do these mechanisms allow structure to be channeled into a multiplicity of trajectories relating to different biophysical paradigms in a manner manifesting a greater or lesser degree of modularity? Adaptive potential cannot be understood, nor the outcome of its realization predicted in the absence of an answer to this question. Any general model must also seek to incorporate the common factors of quite diverse systems operating in different lineages.

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COORDINATES OF ADAPTIVE CAPACITY AND POTENTIAL IN DEVELOPMENT The framework of adaptive capacity and potential must derive from roots in the modular-interactive array of mechanisms of developmental translation as they ascend from determination to morphogenesis. This analysis must therefore begin with a broad overview of those coordinates around which superstructure is progressively built, on the assumption that potential for change must somehow reside within these same parameters.

Translation Levels of Development Translation, beginning with primary translation in protein synthesis, refers to any stage in the course of genetic activity beyond gene transcription itself. At the primary translation level, a protein is ordered from the genetic code held in a DNA sequence, while subsequent events beyond this stage concern epigenetic interactivity* manifesting determination, differentiation, and morphogenesis as the outcomes of repeated sequences of translational events. Lower translation levels are thus expressed in determination and differentiation, these being the ﬁrst links in a cycle of epigenetic interactivity, while higher translation levels can be identiﬁed in growth and morphogenesis. The geometric coordinates of morphogenesis condense thus from precursor states residing in a nested sequence of complex interacting translational mechanisms. Some part of the developmental structural paradigm is therefore translative, so that at each point, geometric and translative coordinates may coexist. Determination, differentiation, and growth clearly form that set of developmental mechanisms which constitutes the essential ‘‘building blocks’’ of morphogenesis, and all translation levels involved can be supposed to contain some component of adaptive potential, in the sense that the developmental program may (at least in theory) be subjected to mutational change in a positive direction at any stage. The coordinates of development are both translative and accommodative (see previous chapter). In ‘‘pure’’ ontogeny, there may frequently be amalgamation of ultimately functionally independent cell lineages, and in this scenario, adaptive potential must be ‘‘ﬂexible’’ with respect to some coordinates and ‘‘rigid’’ for others, as a function (in part) of translation level, and also modularity in relation to accommodation. Lower Translation Levels—Determination and Differentiation The primary translational activity of genes above protein synthesis itself lies in determination, which is structured around a program of repressor and activator functions in gene regulation. Repressors may act to limit cell commitment by blocking unwanted genetic activity, while activators are selective ‘‘on’’ switches acting on other, more ‘‘downstream’’ genes with speciﬁc functions for each required cell type.† In a general model, the time delay between determi* The term ‘‘epigenetic’’ was originally used to describe supposedly nongenetic inﬂuences on development (see Hall, 1992, for an overview). Here, it is applied to the properties of higher translation levels of diverse determination factors—in the sense of determinative signals passing between cells and tissues, ‘‘above’’ the level of primary genetic translation. † Determination has also been distinguished from speciﬁcation (Slack, 1983). This nomenclature essentially separates ‘‘capacity for differentiation in the correct environment’’ from ‘‘capacity for autonomous differentiation.’’

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nation and the earliest detectable evidence of cell commitment can vary over a wide range: The totipotence of egg cells is often lost during the ﬁrst few cell divisions. Drosophila labeling experiments carried out by Chan and Gehring (1971) demonstrated that the blastoderm cells (not nuclei) are already determined in terms of anteroposterior developmental destinies and that events of detailed pattern formation have occurred by the third larval instar, indicating a stepwise sequence of determination apparently involving a binary switch mechanism operating at an epigenetic level. Cell determination can be brought about in many ways: extrinsic signals such as gravity (identifying ‘‘top from bottom’’), external ionic molecules, unequal cell divisions, uneven molecular gradients, contact with other specialized cells, and so on. In general, cell-endogenous determination factors can be deemed to be of proximal type, extrinsic ones, remote acting. Some of these signals function as simple Boolean switch mechanisms, whereas others (especially those of remote acting type) initiate graded responses affording positional information. Given that some component of remote acting regulation may arise through nongenetic signals, determination itself is thus not to be seen exclusively as a direct genetic function (see next chapter). To adopt a uniform system of nomenclature for ‘‘proximal as against remote acting’’ determination factors, the following convention is proposed here, and will be used throughout: • ‘‘cis- and trans-acting’’ (in lowercase) will be used to refer to the intracellular aspect of gene regulation (i.e., in the customary usage of these terms). • ‘‘CIS- and TRANS-acting’’ (in uppercase) will be used to denote proximal and remote acting functionality, in the intercellular domain. For example, any determination factor acting through cell-to-cell contact is CIS-acting, and a TRANS-acting factor is one that travels from cell to cell without the need for actual physical contact. The overall view of determination and commitment in relation to activity of genetic controllant factors can be illustrated as in Fig. 44. Differentiation The state of commitment is a function of the sum of the activator or repressor activity of determination (any state ⬍ totipotence)—it is effectively a state of differentiation. Differentiation itself describes the outcome of progressive determination and can thus be regarded as being ‘‘accumulative’’ in the sense of being iterated with respect to higher translation level activity. Competence is the developmental capacity of a cell (or of any higher morphogenetic locus) to respond to an inductive signal (Waddington, 1957) and thus to undergo subsequent differentiation, growth, or morphogenesis (Fig. 45). Determination is thus the ﬁrst step toward morphogenesis, and differentiation constitutes the ﬁnal state of iterated determination at the cell-tissue level. Determination is manifested at the level of the cell and initiated through a

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FIGURE 44 Parameters of control over determination and commitment.

combination of cell-autonomous (cis-/trans-) plus external (CIS-/TRANSacting) molecular and physical stimuli. Even at this stage, it is possible to hypothesize that the coordinates of adaptive capacity and potential must in some sense be fundamentally linked to those of determination and differentiation. While the lower translation levels obviously relate more to earlier development, they nevertheless also form those precursor stages through which any apparent ‘terminal addition’ at phenotype level must pass. Consequently, the degrees of freedom residing in endogenous adaptive potential must depend in part on the architecture of determination and differentiation. Higher Translation Levels—Growth to Morphogenesis The geometric coordinates of phenotype form arise from loci of determination–differentiation as translation transcends the cellular level to differential tissue growth in morphogenesis, and the largest structural coordinates of development thus emerge from higher level translational activity. Morphogenesis can therefore only be understood from analysis of a sequence of precursor translational events occurring between gene transcription and the organization

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FIGURE 45 Iterated determination leading to differentiation.

of structure. The complete sequence of such events is therefore transcription 씮 primary translation 씮 determination 씮 differentiation 씮 growth and morphogenesis. This is not a single train of events, but rather, it is a set of nested sequences, elements of which progressively ascend a trajectory of mechanisms involving complex interactivity. Not only is there an ascending hierarchy of translation levels, but also the sequence determination 씮 differentiation can be followed at different temporospatial levels in the same organism. Intermediate translation levels include the establishment of loci and coordinates of determination, while the highest translation levels clearly lie in the differential mitotic activities surrounding ordered growth patterns following on from the creation of coordinates systems. Growth itself can be cellular or mitotic. As mitotic activity, it may be organized around simple coordinates derived from programmed binary cell division (thus excluding allometric or other complex models). In morphogenesis, we observe a more complex programming of growth, such that varied responses to transformational coordinates systems give rise to complex form. To this observation, we should also add that the ‘‘morphogenetic substrate’’ itself consists of two quite distinct modes of supracellular organization: Thomson (1988) points out that there are two basic patterns at the tissue level that are of fundamental importance in morphogenesis, epithelium and mesenchyme. The former is a single cell layer on a

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basement membrane, the latter, multidimensional. Epithelia can be folded and distorted in various ways, whereas mesenchyme forms organ rudiments through migration, condensation, cell division, change of cell shape, also via effects arising in the extracellular matrix, and through differential cell death. It is at the level of morphogenesis alone that we ﬁnd those major coordinates systems corresponding to the geometry of adaptational paradigms, although this may of course link to complex emergent properties arising from such simpler control systems ordering lower translational events. The nature of gene control over the above mechanisms is now quite extensively understood for some (but by no means for all) components. Major Loci of Translation—Compartments to Morphogenetic Fields The larger coordinates systems of development deﬁne closely circumscribed temporospatial zones of developmental space-time in a sequential hierarchy, within which determination, differentiation, growth, and morphogenesis take place, the spatial loci of translation. TRANS-acting factors tend to describe the largest of these loci (frequently acting in analog mode), and these include the morphogenetic compartments that have been particularly well studied in Drosophila. Following the establishment of the largest TRANS-determined boundaries, a nested sequence of narrower (often digitally coded ) coordinates is then deﬁned. From these events, we obtain a hierarchy of loci of growth and morphogenesis. There may be compound morphogenetic ﬁelds (such as the vertebrate limb ﬁeld), which constitute complex loci of translation in which latent loci of determination, differentiation, growth, and morphogenesis are nested within some larger locus of determination. What form do the ‘‘major coordinates’’ alluded to above actually take? A locus of translation may be particular to a speciﬁc determination, differentiation, growth, or morphogenetic event, or else it may harbor an array of different functions (as in a complex morphogenetic ﬁeld). The coordinate parameters for development are thus found within a hierarchy of loci of translation comprising: Loci of determination Loci of differentiation Loci of growth Morphogenetic ﬁelds Loci of morphogenesis A locus of determination is that zone in developmental space-time at which a totipotent cell or cell clone is determined in terms of its subsequent developmental fate. As we have seen above, loci of determination are of particular signiﬁcance in deﬁning major coordinates in positional information, and a locus of differentiation evolves as iterated determination comes to that point at which the fully functional state of a specialized cell type is reached. A locus of growth is the locus described by regular, binary mitotic activity in developmental space-time, for any cell or cell clone (excluding allometric or other complex models). A locus of morphogenesis is a growth locus in which mitosis undergoes complex organized patterns of growth (or cell movement

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of preexisting cellular units). Any such locus may be descended from a single cell or else constitute a polyclonal assemblage. A morphogenetic ﬁeld is a compound morphogenetic locus in which integrated determinative–differentiative activity is coordinated. It involves a group of cells whose position and fate are determined with respect to the same boundaries (following Weiss, 1939), despite showing little or no differentiation at an early stage. All translational loci should be viewed as dynamic structures, having a fourth dimension in developmental space-time. Morphogenetic compartments

FIGURE 46 Hierarchy of loci of determination and morphogenesis.

are also larger ﬁeldlike loci determined through the action of morphogens and other top-level regulatory genes. Included are the parasegments and other known compartments of Drosophila:

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‘‘Compartmental boundaries are lines separating regions of tissue whose cells have progeny which do not cross the boundary’’ (Kauffman, 1993; see also Garcio-Bellido et al., 1973). A compartmental boundary separates domains of cells which have taken alternative developmental commitments. Fields and morphogenetic compartments constitute major loci for determination of patterns of growth, differentiation, and morphogenesis, the translative domains of which change as development proceeds, and often form the initial step in the move to compartmentalize structural units as quasi-autonomous entities. Most signiﬁcantly, the hierarchy of nested major 씮 minor coordinates from morphogenetic ﬁelds downward describes the essential paradigm of how developmental gene activity is organized, and the sequence of TRANS- 씮 CISacting determination in this has considerable implications for adaptive potential (see below, also Chapters 11 and 12).

Adaptive Potential in TRANS-acting Determination Factors As we have already seen, the effect of iterative determination is the generation of complex coordinates systems around which translation and morphogenesis are constructed. What kind of coordinates systems lie within this asecending sequence of translation levels? Clearly, these must in some way progress from translative to geometric structures in an accommodative manner. Adaptive potential may appear to be restricted to coordinates of the highest translation level, but it must be that translational resources for this propensity really lie throughout a hierarchic sequence of determinative events. We may thus follow ontogeny through to phenogeny with respect to a given structure, but not necessarily via geometric coordinates, in that other, lower translational mechanisms may also be involved. It seems intrinsically likely that truly phenogenetic paradigms must lie in the domain of the coordinates of morphogenesis itself, and that morphogenetic accommodation with respect to such parameters probably lies particularly in the intersect of phenogeny with ontogeny. In the same way, the most labile structural paradigms of all should perhaps be found in the loci of lower translation levels, in the domain of ontogeny. In what way are adaptive capacity and potential linked to particular proximate and remote acting factors of determination? This situation cannot be understood without ﬁrst examining the foregoing loci of translative activity more closely. Some component of determination must be cell-autonomous; however, the greater component of morphogenesis is determined via signals passing from cell to cell and from tissue to tissue. Thus, while determination and differentiation may perhaps be partially understood in terms of cell-endogenous linear mitotic programs, the true basis for complex morphogenesis clearly must lie with higher coordinates systems of the kind based on CIS-/TRANS-acting mechanisms. Early development is partly typiﬁed by distribution of TRANS-acting morphogenetic factors which travel widely in a syncytium or in a cytohistogenetic

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medium, deﬁning morphogenetic coordinates which in turn underlie the lower translation levels of determination 씮 differentiation. Morphogen gradients deﬁne positional information (see below), and these form an important class of molecular determinants arising remote to the locus of determinative activity. Some gradient models of this kind indicate quite simple coordinates systems, while others are considerably more complex in nature: Wolpert (1969, 1971) proposed that cells have access to an underlying coordinates system, and thus know their position in relation to a developmental ﬁeld. The cell ﬁrst assesses its positional information, interprets this according to its cell type, then forms a speciﬁc part of the overall pattern. Genes thus interpret signals which specify a cell’s position within a ﬁeld, and the specifying signals act like coordinates of position, carrying no other information. Evidence for this theory came originally from the antennapedia mutant in Drosophila, which causes distal antennal cells to become distal leg cells, while Bicoid was the ﬁrst morphogen producing gene to be discovered in Drosophila (see next chapter). Sander (1960) ﬁrst discovered evidence for the presence of anterior and posterior morphogens in bug eggs, on the basis of data gained from ligation experiments. Polar, Cartesian, and spherical coordinates systems have been proposed for such determination factors. In the above view, complex differential growth can be understood in the context of systems of coordinates and positional information laid down by primary determinants of the morphogen kind. However, this is not the only model that has been proposed: Maynard Smith and Szathmary (1995) discussed the interactions taking place between cells in a morphogenetic ﬁeld in two possible models: (a) positional information, a gradient within which scalar quantities (or qualities) specify position in the ﬁeld, and (b) ‘‘prepattern and competence,’’ where a standing wave of values of some scalar quantity is directly responsible for organization of differentiation for repeated patterns. TRANS-acting systems of the above kind apparently create the major coordinates of development, and the programmed order built around them could, whatever its mechanistic strategy, form a signiﬁcant component of adaptive potential (see also Chapter 15). However, Horder (1983) criticizes the validity of the view that TRANS-acting genes (of the homoeotic kind, for example) control pattern, stating that the available data suggest that the latter is built up gradually by multiple sequential interactions between differentiated structures, so that the CIS-acting mechanism of induction may often be a central mechanism, at least with regard to the domain of phenogeny (see below). This viewpoint will be given careful consideration in the present analysis. Complex Coordinates Systems and the Turing Model More complex coordinates systems of the ‘‘prepattern’’ kind may be a function of simpler models, as argued by Kauffman (1993). The Turing model has two chemicals with activator–repressor relationships:

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Substance X autocatalyzes formation of itself and catalyzes formation of Y; Y inhibits formation of X and of Y itself. X is the activator, Y, the inhibitor. Both X and Y can diffuse in the tissue—but Y does so more rapidly than X. The whole system can reach a steady state (⫽ no pattern formation). However, if equilibrium is disturbed (namely, through ﬂow of energy and matter invoking a dissipative system), then patterns may then be generated (see Kauffman, 1993). Such reaction–diffusion models have been applied to many systems, and some aspects of how shape may be controlled in relation to coordinates of morphogenesis may well be based on the Turing model. Of particular interest is the fact that dissipative systems are said to be capable of generating patterns of morphogenetic order on the basis of reaction–diffusion activity alone: Meinhardt and Klingler (1987) utilized models based on reaction– diffusion mechanisms to predict the generation of pigmentation and relief patterns on mollusc shells belonging to a number of different genera and species. In their model, an autocatalytic reaction is antagonized by an inhibitory substance, and more complex patterns occur with more than one inhibitory substance, or with superimposition of two patterning processes. Computer simulations based on this model reproduce ﬁne details of natural patterns. Shell patterns in the gastropod Bankivia fasciata can also be predicted from the Turing model, although explanations based on neural activities could also ﬁt this data! (see Meinhardt, 1982; Murray 1989, etc.). Murray (1981) devised a model for generation of lepidopteran wing patterns on the basis of a biochemically plausible mechanism based on a diffusion morphogen that activates a gene in a threshold manner, to generate a stable heterogeneous pattern. However, diffusion ﬁelds suggested in this model are very much larger than any known examples. Likewise, Maynard Smith and Szathmary (1995) state that the Turing model’s main weakness lies in lack of direct evidence for the molecular mechanisms involved. Molecular systems for determination of morphogenetic coordinates are of the highest signiﬁcance for an understanding of adaptive potential, since they link coordinates of determination with the higher translational activity of the gene on the one hand, and with the functional coordinates of potential for adaptational change on the other. In this, we witness a further, translative dimension in morphogenetic accommodation.

Adaptive Potential in CIS-acting Determination Factors Later development in higher organisms is often heavily dominated by CISacting morphogenetic factors, passing from one cell to the next or between adjacent tissues, including both chemical and physical agencies. In such systems, we may at times observe further evidence of apparent ‘‘self-organizational’’

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factors. According to Horder (1983), induction probably plays a very much larger role in more ‘‘downstream’’ morphogenetic activity, than do TRANSacting determination factors. Induction Many morphogenetic events have been traced to determinative factors derived from cell–cell or tissue–tissue contact, a process known as induction.* Induction arises from tissue-to-tissue molecular stimuli acting at higher translation levels, as differentiation proceeds to growth and morphogenesis. Inductors are thus often molecular determinants acting as ‘‘proximal morphogens,’’ the molecular CIS factor of tertiary translation generating morphogenesis within higher coordinates deﬁned by earlier (often TRANS-acting) mechanisms: The manner in which lens formation in the vertebrate eye is brought about through inductive action of the optic cup on the overlying ectoderm has been known since the work of Spemann (1901). The same phenomenon is also known with the balancer organ in salamanders (for example, Triturus), and here experiments have been carried out with trans-species implants which show that the inductive stimulus is still present in forms (Ambystoma) which have lost the organ itself (see Sang, 1984; also see Gilbert, 1997, for a broad review of revisionary work since Spemann). Paracrine or growth and differentiation factors have been identiﬁed as those proteins responsible for short distance induction in the formation of numerous organs. The same molecules are widely involved throughout the animal kingdom and appear to form just four families ( ﬁbroblast growth factor, hedgehog, wingless, and TGF-웁; see Gilbert, 1997). Also involved are the cell adhesion molecules responsible for the speciﬁc aggregation properties of mobile cells. Newtonian Morphogenetic Factors Brenner (1981) postulated that hierarchic systems of gene control over development may involve shared substrates, also that the way in which genetic space maps onto organismic space may involve further unknowns. Among these latter is the question of mechanical interactions between cells and tissues. Mechanical induction is due to determination factors arising from physical forces between adjacent differentiating tissues, as distinct from the direct action of products of gene transcription–translation. This factor is indicative of the diversity of inﬂuences affecting morphogenesis which could have some input to adaptive potential. Newtonian morphogenetic factors are those determination factors arising from interaction of physical forces resulting from growth and morphogenetic movement, and constituting the physical ‘‘CIS factor’’ of tertiary translation in morphogenesis. It is evident that much kinetic activity is expressed during early development, as at the gastrulation stage, for example, and wherever cell motility and adhesion properties play a prominent role in morphogenesis. Similar mechanical elements in determination must also exist during later development, particu* Holtzer (1968) distinguished two modes of induction, instructive and permissive.

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larly in the way in which quasi-autonomous units of developing superstructure interact. From this observation comes the question as to whether certain tissue movements are due to intrinsic determination factors or to mechanical forces imposed from elsewhere. While thermodynamic models linked to differential adhesive properties of cells may explain cytohistogenetic kineses (see Gilbert, 1997, for a review), it seems likely that direct mechanical stresses must also be involved in some areas of morphogenetic activity. Mechanical forces potentially affecting development at the highest translation level must arise naturally from growth functions and morphogenetic movement in individual developmental trajectories. Such forces have both quantity (growth rate and period) and directionality (according to the nature of the coordinates of loci of commitment, differentiation, and differential mitosis), and they may therefore be regarded as constituting ‘‘Newtonian developmental vectors’’ in terms of their inﬂuence on the course of development. There will thus be certain sites in the temporospatial matrix of development at which morphogenetic vectors interact as physical forces: Thompson (1917) referred to the way in which developing vertebrate tooth buds coalescence, creating mechanical pressures which play a large part in determining the ﬁnal arrangement and conformation. ‘‘Mechanical induction’’ has been investigated by Oster et al. (1980) using a computer model which simulates the viscoelastic properties of the cell wall contained in microﬁlaments, and this model can be used to simulate the behavior of epithelial cells with respect to forces transmitted from cell to cell. The biophysical properties of such tissues could apparently alone account for gastrulation movements and for the ventral furrow of the Drosophila embryo, even in the lack of positional coordinates. Another form of mechanical induction is seen in the development of the wing in Drosophila and other insects, where expansion is brought about by the internal pressure of the body ﬂuid, and mechanical stresses have likewise been identiﬁed in the coordination of chondrogenesis with osteogenesis in vertebrates. As stated by Sang (1984), ‘‘It is salutary to remember that cells have intrinsic properties affecting their shape and motility, not readily predictable from their active genes.’’ It is only necessary to extrapolate slightly from the Oster model to permit incorporation of more widely active mechanical vectors arising from growth and morphogenesis (especially in terms of quasi-autonomous but physically interacting morphogenetic trajectories), and thus to see that force vector ﬁelds might sometimes play a signiﬁcant role in epigenetic interactions at certain stages of development. A signiﬁcant consequence of the Newtonian morphogenetic factor is that morphogenetic forces may interact with one another during the unfolding of a complex developmental trajectory, and clearly, complex determination systems must cope with interactivity of this kind (see next chapter). Morphogenetic vectors express quantity in terms of growth functions and also directionality, which latter may be, in turn, modiﬁed and redeﬁned. Where

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such vectors act as major determinant forces in complex superstructural systems, this domain may hold a large inﬂuence over the behavior of some developmental events. In this model, we may envisage the endogenously generated determination vectors of a given morphogenetic trajectory interacting with ‘‘passive lability’’ characteristics of a second trajectory, the two manifesting some degree of intrinsic modularity combined with a certain level of interactivity in that domain in which Newtonian morphogenetic factors come into play. In this situation, the outcome is the product of two antagonistic forces. From this, it can be seen that the same degree of morphogenetic force can be attained by different balances between endogenous and exogenous factors affecting a given cell lineage, and that the resultant value may be expressed in isomorphic zones described by a graph connecting equivalent values for different combinations of Newtonian determination factors arising endogenously versus extrinsically to a given morphogenetic parameter. A large morphogenetic force may therefore be due to endogenous factors in the developmental trajectory of a structure, or else it may be due to the impinging inﬂuence of some other cell lineage, as a function of passive lability in the ﬁrst trajectory. In terms of adaptive potential, it seems most probable that the inﬂuence of Newtonian determination factors in general will tend to dominate the fabricational rather than the adaptational paradigm for evolutionary change, being thus sequestered from the latter as a function of ‘‘vertical’’ modular inhibition (see below). Most probably then, mechanical determination factors will tend to be particularly active during earlier ontogeny, when fabricational parsimony tends to predominate the structure paradigm. This is an important conclusion in terms of the degree to which ‘‘self-organization and spontaneous order’’ can be said to inﬂuence patterns of evolutionary change with regard to the ﬁnal phenotype, as against the early ontogenetic stage of development (see Chapter 15). While it has been concluded that CIS-active determination factors in general lie close to the loci of adaptive potential, it seems likely that mechanical induction may tend usually to be excluded from this.

ADAPTIVE CAPACITY AND POTENTIAL IN THE CONTEXT OF DEVELOPMENTAL MODULARITY Why are the temporospatial loci of lability with respect to adaptive potential tightly constrained in certain domains within the developmental program? We cannot begin to see what the parameters of adaptive capacity and potential actually are, until development has been understood in terms of the relationship between the loci of translation and known ‘‘architectural’’ models of development.

Architectural Models of Development and Morphogenetic Lability As we have seen, morphogenesis is essentially a dialogue between growth functions and complex organizational mechanisms. It can be affected by either cell or tissue movements, differential cell growth, or differential mitosis, and

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will frequently occur through a combination of several of these factors. Morphogenesis is thus growth organized around a complex hierarchy of developmental coordinates, and as we have seen above, an element of modularity in terms of the degree of mutual autonomy manifested by different morphogenetic trajectories also enters this equation. It has already emerged that some part of this modularity must be linked to the dichotomy between adaptational and fabricational paradigms, and this latter element must also be encapsulated within the principle of morphogenetic accommodation. Not all aspects of developmental modularity can be presumed to link to lability in adaptive potential. Thus, while Gerhart and Kirschner (1997) have argued that morphogenetic compartments are important for potential evolutionary change as a function of their developmental independence, it has to be assumed that modularity in general is closely linked to the more complex strategies of translation—and it is also apparent from comparative morphology alone that the phenotype is not altered ‘‘per compartment,’’ so much as through the medium of more integrated, holistic units of the structure unit and integral kind described earlier (Chapter 7). Clearly, this situation can be understood from the fact that developmental and selectional modularity cannot be one and the same thing from the viewpoint of adaptive potential. In fact, the integration of many developmental modules must occur predominantly through the activity of CIS-acting factors, so that any subsequent gravitation toward complex neomorphic transformation must accordingly be more closely linked to factors of this kind than to those elements actually conferring compartment identity at an early developmental stage. The strategy through which morphogenesis is organized around the loci of determination, differentiation, and growth has thus been presumed to follow a path described by the balance between modularity and interactivity, as this particularly relates to emergent holistic units of the phenotype. However, this pattern also has to be capable of large scale reorganization, if complex domains within adaptive potential are to be realized—and it is clear that many of the restrictions imposed on realization of adaptive potential must be due to the way in which modularity is organized around fabricational paradigms of ontogeny. Mosaic and Regulative Development, Modularity, and Adaptive Potential Given that developmental modularity may be very different from that residing in latent adaptive potential, it is clearly important to arrive at some understanding of the architecture of translational modularity in a ‘‘typical’’ developmental system. In what way are patterns of differential growth in morphogenesis generally organized around developmental coordinates systems? Although it is possible to identify the various translational mechanisms underlying growth and morphogenesis and to understand their broad relationships to positional information and other coordinates laid down by determination, it is much more difﬁcult to see how these processes are organized and integrated in the context of a supposedly ‘‘generalized’’ developmental trajectory leading to the ﬁnal phenotype form.

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In the past, morphogenesis was thought to be organized in two fundamentally different ways, according to the degree to which autonomous and conditional speciﬁcation are involved. In model 1 (the mosaic or lineage model), cell speciﬁcation is predominantly autonomous to cell lineage and morphogenesis evolves as a linear program tending to manifest high levels of modularity. In model 2 (the regulative or assembly model), cells retain a wide ranging developmental potential and a greater degree of cell-to-cell interactivity is involved in determination, so that a nonlinear assembly of parts is facilitated on the basis of controlled interactivity between only quasi-autonomous modular trajectories. In mosaic development, particular cells give rise to particular structures, while the regulative strategy is in contrast more ﬂexible, in that cell fates can be altered without derailing development. Some component of morphogenesis has thus been viewed as the result of programmed cell division or cell death from a smaller number of precursor cells, and some as being due to movement and reorganization of larger, preexisting bodies of cells for which endogenous determination factors are less signiﬁcant. This apparent dichotomy has also been presumed to apply to the ways in which development is organized in different phyletic lineages: The above differential could be presumed to be present, for example, in the dichotomy between epithelial and mesenchymal cells, since the two main ways of communication (diffusible substances versus cell contact) and the different mechanisms of morphogenesis (cell division, cell death, movement–segregation–aggregation, shape change, etc.) are to some extent differentially expressed in these two cell types. All cell divisions have been followed from egg to adult in the nematode Caenorhabditis elegans, the body of which comprises only around 1000 cells. The embryo is still spheroid when about half the ﬁnal number of mitoses has already taken place, and attainment of the elongated adult form occurs predominantly through cell differentiation, further mitosis tending to be mainly growth rather than morphogenesis. In C. elegans, morphogenesis was at ﬁrst thought to be predominantly an autonomous linear, algorithmic program of cell division coupled with cell death, with relatively little input from interactive effects between cells, as perhaps suggested by the fact that the entire cell lineage can be written down as a branching tree. In contrast to the nematode scenario, insect bodies are to a much greater extent, ‘‘assembled from pieces,’’ especially during later development: Drosophila nuclei at ﬁrst divide in a syncytium, and cell membranes do not appear until after the thirteenth nuclear division. The ﬁrst plane of cleavage is random, but nuclei do not mix randomly as they divide, since there are roughly male and female ‘‘territories.’’ Unlike C. elegans, later developmental events are clearly not decided strictly on the basis of cell lineage. Drosophila in fact shows a sequential hierarchy of parasegments and morphogenetic compartments around which differ-

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entiation and morphogenesis is organized, the ground plan of which is laid down at gastrula stage—furthermore, the compartments are evidently polyclonal in origin. Marked cells at the blastoderm stage of Drosophila show wing plus leg anterior or posterior compartments, while the same experiment carried out at the gastrula stage shows descendant cells conﬁned to either wing or leg. At a later stage, the wing divides into two compartments. Kauffman (1983 and elsewhere) found that the process of compartment subdivision continues until end–middle and even–odd sectors have been deﬁned. However, many structures display a more ‘‘fabricational’’ process of assembly: the muscles take cues from nervous tissue, and (as in the majority of higher organisms that have been studied) cell–cell and tissue–tissue induction mechanisms play a much higher proﬁle in morphogenesis than they appear to do in nematode worms. Mesoderm compartments, for example, have been studied in relation to muscle formation. Each muscle is initiated by a speciﬁc founder cell, but this is joined by elements from a pool of mesodermal cells which then acquire the identity of the founder. Nerves are thought to play a role in induction here also. Lawrence (1992), reviewing the situation with Drosophila, concluded that there is clearly evidence that no ‘‘linear program’’ is involved. Caenorhabditis, in contrast, seemed clearly to follow the mosaic model. However, more recent work has shown that this is an oversimpliﬁcation. Cell interactions do in fact play a role in development in C. elegans, and gut development (for example) is dependent on induction (see Wolpert et al., 1998, for a review). Considerable doubt must therefore be placed on the apparently sharp dichotomy existing between mosaic and regulative patterns of development. Determination certainly tends to occur earlier in mosaic embryos than in regulative ones, but there are no totally mosaic embryos—and the presence of an apparently invariate cell lineage does not mean that fate cannot subsequently be changed. Just as several competing models of genetic control over development exist, probably all having some validity within certain proscribed domains, theories of morphogenesis may also best be seen in a diversity of mechanisms operating at different levels. Clearly, the regulative model may be an advanced development of higher organisms, as has already been suggested with respect to ontogeny (see Chapter 9), and it may in that context have a relationship with developmental paradigms derived from the endogenous selection interface, namely, in fabricational parsimony. In vertebrates, regulative–inductive mechanisms also play an even larger role than they do in the insect developmental system. There is thus clearly a varying degree to which cell lineage versus cell or clone position are of signiﬁcance in different higher groups and at different times during development in a single species, and in our general model we must therefore take both systems into account. If any ‘‘general rule’’ does exist, it may perhaps be that lower metazoans with a simple body plan and smaller total number of cells and of cell types tend more toward the apparently linear–algorithmic (mosaic) strategy, whereas more complex organisms show progressively more advanced expressions of

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the parts-assembly/regulative interactivity model. Complexity thus seems to have generated a much greater demand on the rationalization of development: According to Thomson (1988), in regulative systems, complexity grows out of itself, and this is possibly the only way that a truly complex organism can be created. Two models of organization have thus been proposed: the mosaic or lineage model, which is essentially based on a linear algorithm for differential mitotic activity in morphogenesis, and the regulative or assembly model, based on fabrication of superstructure following a nonlinear assembly of separately formed rudiments in which induction may play a leading role. However, these modes of development are apparently not as different as was at ﬁrst thought. The apparent divergencies between lower and higher organisms which have actually been conﬁrmed may seem to suggest certain restrictions in the way adaptive potential is linked to the hierarchy of coordinates around which development is structured, and this is clearly also related in turn to the dichotomy between fabricational and adaptational biophysical paradigms, namely, in ontogeny as against phenogeny. In view of the above, it is possible to propose a broad relationship between developmental modularity and degrees of freedom in adaptive potential. This does not of course identify ‘‘lower’’ organisms as having low adaptive potential, but merely reﬂects the differential distribution of propensity for evolutionary change in different morphogenetic domains within any given lineage—from which it is possible perhaps to predict, for example, that more complex metamorphoses form a more probable modiﬁcation of simpler ‘‘mosaiclike’’ developmental systems than they do of complex regulative ones. We can summarize some of the foregoing aspects of development in relation to lability within adaptive potential as follows: Determination

Predominant paradigm Modularity Lability to change

Remote (TRANS) Fabricational Proximal (CIS) Adaptational

Low High

High Low

The above clearly ﬁts the broad observation that the most dramatic changes in structure are often those seen in earlier development. Against this, we must, however, balance the fact that remotely related higher group lineages may share common ontogenetic states, even where the phenogenetic phase has diverged very widely indeed, implying that considerable stability may be enforced on certain stages of early development (see comments on the phylotypic stage, Chapter 9). Above all else, the regulative model of development demonstrates a very large inﬂuence on the evolutionary ‘‘rigidity’’ of many TRANSdetermined ontogenetic coordinates, while at the same time suggesting that this apparent lack of lability in adaptive potential can more readily be bypassed in a strictly mosaic developmental system.

Loci of Adaptive Capacity and Potential and Architecture of the Morphogenetic Trajectory Although smaller modules deﬁned by loci of translation can be deﬁned within certain temporospatial boundaries, these generally also collectively form trajec-

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tories of development common to unit structures in the ﬁnal phenotype, in that the loci of determination, differentiation, growth, and morphogenesis must be connected in translational and temporal sequence over the course of development. The train of such events for a given structure unit constitutes a morphogenetic trajectory, describing the complete fabricational sequence for development of a single structural unit from embryo to phenotype. A morphogenetic trajectory is described by the train of developmental events from the ﬁrst locus of determination through all descendant loci of differentiation, growth, and morphogenesis for all cell lineages leading to formation of a given structure unit or integral, as a four-dimensional structure traversing the whole of development. Each morphogenetic trajectory is bounded, either by a cell lineage or (quite frequently) by the convergence of two or more cell lineages to form a functionally integrated whole. Either way, it can be determined as having certain root parameters (namely, the parent cell or cells of the lineage). Following the establishment of the root parameters of a morphogenetic trajectory, it will also tend to have a geometry built around a set of morphogenetic coordinates. The characteristics of a given trajectory can therefore be described in terms of the loci and coordinates of translation. Each morphogenetic trajectory must also pass through fabricational and adaptational paradigms, and here again we encounter the axiom that the developmental pathway concerned must be accommodative. Owing to the fact that different developmental phases of a single structure unit or integral have different temporospatial loci during development, and particularly because of the inﬂuence of the assembly model in morphogenesis, it follows that some structural units will be derived from convergent trajectories and some from divergent: The pharyngeal muscles of the nematode C. elegans are derived from elements originating from two discrete cell lineages, both of which also contribute to other structures quite independently. The Drosophila wing disc shows examples of divergent trajectories for scutum, scutellum, wing, and parts of the adult thorax, and thus for discrete subunits of a structure integral. ‘‘Pure’’ ontogeny clearly links to the assembly model of morphogenesis, involving much manifestation of convergence–divergence in morphogenetic trajectories. Convergence tends to be expressed most noticeably in ontogeny: In the Drosophila embryo, the endoderm invaginates dorsally and at the anterior end during gastrulation, two separate gut primordia eventually joining in the middle, thus following the convergence strategy. Since it is logically impossible that this could in any way represent a ‘‘recapitulation’’ of any conceivable ancestral form, it must be concluded that this ‘‘parts assembly’’ of the gut is a derived condition reﬂecting a fabricational paradigm. In contrast, later development rarely involves such dramatic events. The differential distribution of convergence and divergence during the course of a morphogenetic trajectory clearly reﬂects both temporal and spatial modu-

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larity in the changing topology of lability in adaptive potential during development (see below). Modularity in the Morphogenetic Trajectory Determination clearly lies at the root of the framework within which adaptive capacity and potential must reside. However, as we have seen, adaptive capacity and potential have a higher probability of residing in some zones of a morphogenetic trajectory than in others, a fact which can be linked to the question of developmental modularity. Raff (1996) deﬁnes modularity in terms of units with a discrete genetic organization. These units may be parts of larger entities, they have speciﬁc locations and varying degrees of connectivity to other modules, and they undergo temporospatial transformations: Huxley (1932) diagnosed the presence of a constant partition of growth intensity between different regions of the developing organism, implying constant difference in rates of growth between certain modules. Raff (1994) argued that plasticity is much restricted by global inductive activity (lack of modularity) at the neurula stage. Most morphogenetic trajectories express a greater or lesser degree of modularity (as reﬂected, for example, in the spatial convergence or divergence of cell lineages), and the latter propensity must in turn derive from developmental activity in the sequential progression from TRANS- to CIS-acting determination with respect to larger loci of translation, plus a correlated inﬂuence from the dichotomy between adaptational and fabricational paradigms. This hierarchically nested structure in the morphogenetic trajectory has been appropriately termed a ‘‘level-interactive modular array’’ (Dyke, 1988). As we have already seen, spatial modularity tends to be particularly low during ontogeny, in the sense that many different phenotype structures may be derived from a common primordium, rather than from separate precursors: Gilbert (1997) cites the neural crest derived structures of vertebrates (precursors of jaw, middle ear, etc.) as an example of spatial modularity. It can be seen that in some morphogenetic trajectories, different levels of autonomy may be displayed at different time horizons in the same trajectory, so that there is a temporal as well as a spatial dimension in modularity: Changes to mollusc embryos may produce new larval types, yet result in normal adults. This temporal expression of modularity is also manifested in a quite different manner in existence of the pharyngula stage shared by many vertebrate groups (Raff et al., 1991) and by the gastrula in many higher groups, namely, in view of the great changes occurring in later development in different lineages. The principle of morphogenetic accommodation underlies the existence of an intersect zone between ontogeny and phenogeny, and the lability element in adaptive potential must clearly lie here, where both temporal and spatial modularity are increasing most rapidly.

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Developmental Modularity and Adaptive Capacity Allomorphism has already been discussed as an essential component of ‘‘adaptive capacity in dynamic equilibrium’’ (Chapter 4), and this mechanism clearly contains a vital element of developmental modularity. In fact, allelomorphism in general clearly links to epigenetic events in which a bifurcation in some developmental trajectory occurs at a given stage. However, a large proportion of sustainable allomorphic variation tends to lie in the substructural rather than in the morphogenetic domain. Developmental Modularity and Adaptive Potential As we have already seen, two qualitatively different pathways of morphogenetic change may occur in realization of adaptive potential, in that phenogenetic coordinates will follow an adaptational paradigm, and ontogenetic coordinates, a fabricational one. The coordinates systems of development as deﬁned through determination have a simple relationship to adaptive capacity via allomorphism, but a much more complex one with respect to adaptive potential, in terms of a latent propensity for movement toward a more or less distant biophysical paradigm via an iterative sequence of morphogenetic changes. Owing to the inﬂuence of temporospatial modularity, this transition must frequently be accommodative with respect to onto- and phenogenetic structural paradigms, at least in the intersect zone. Most signiﬁcantly, earlier mutational change is likely to have downstream knock-on effects in development (see Arthur, 1997), and the extent to which such changes can be positively selected will clearly depend particularly on the degree of modularity expressed in the temporal dimension. Adaptive potential will thus tend to be differentially distributed in developmental space-time, as a corollary of the temporospatial distribution of developmental modularity. What exactly is the nature of the ‘‘constraints’’ imposed on adaptive potential due to developmental modularity, and how are these factors ultimately bypassed? Genetic factors which determine truly ontogenetic loci such as the morphogenetic compartments of Drosophila must clearly comprise ‘‘essential’’ coordinates with a very long phylogenetic history, and which may thus possess greater resistance to evolutionary change than do many ‘‘minor’’ downstream parameters. Many of the important evolutionary changes in Drosophila do in fact occur further downstream than the known genetic cascade of development (Powell, 1997), and this is an expected corollary of both temporal and spatial modularity built around large scale coordinates laid down in earlier development. Some developmental modules thus clearly manifest lability, and others, resistance to mutational change—and this must in turn link to degrees of freedom in adaptive potential. While both early and late coordinates of determination may form potential targets of mutational change affecting morphogenesis, rigidity must tend to reside more in certain ‘‘major’’ ontogenetic parameters. The reason for this is that TRANS-determined coordinates seem usually to deﬁne mosaic morphogenetic objects that are only later assembled as components of a holistic phenotype structure unit (parasegments, wing compartments, etc.). The subsequent assembly of a compound phenotype structure integral

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thus seems most likely to be coordinated within CIS-determined translational loci. This situation is presumably due to the fact that TRANS-determined coordinates are linked to a fabricational rather than adaptive paradigm. And as we have already seen, certain major ontogenetic parameters are often effectively ‘‘frozen’’ with respect to mutational effects which actually penetrate the phenotype state. The question of lability to large Newtonian determination factor effects suggests another likely source of negative spatial modularity in development, this probably also manifesting a greater effect in ontogeny than phenogeny. In general, an emergence of increasing developmental lability at or around the ontophenogenetic intersect zone (i.e., in the transition between low and higher levels of modularity) thus seems most likely to coincide with the intersect zone between TRANS- and CIS-acting determination factors, and it is reasonable to suggest that realization of adaptive potential is most likely to be concentrated at or beyond this domain. To what extent do the foregoing postulates agree with actual observations on the developmental systems of real organisms? Early ontogeny does indeed appear to be very tightly constrained in general. However, there are nevertheless certain notable exceptions to this rule: Dramatic change does sometimes occur during early development in species with complex metamorphosis. For example, recent work on Heliocidaris urchins conﬁrms the view that early development can be radically altered. In H. erythrogramma (see Raff, 1996), even gastrulation undergoes profound changes. The latter could perhaps be permissible if very low selectional differentials appertain to the reshufﬂing of certain early ontogenetic features, which could in fact be the case if self-organization has a higher proﬁle in ontogeny sensu stricto than it does in phenogeny (see Chapter 15). There is clearly a fundamental modular interactivity expressed in the spatial dimension at certain levels in development, identifying rigidity where adaptive potential with respect to the exogenous environment must be effectively occluded. This is especially true at those horizons at which development is organized largely around the fabricational paradigm; however, this does not always exclude radical reorganization of certain ontogenetic coordinates. Despite exceptions of the kind described by Raff, certain modes of determination (as well as certain zones within a developmental trajectory) clearly do contain a negative corollary for realization of adaptive potential. The question of modular inhibition intrinsic to certain aspects of development can be seen to be linked to that phenomenon known as ‘‘the developmental ratchet,’’ and this seems often to be a peculiarly ontogenetic effect arising from high levels of interactivity between major prepatterns for separate modules emerging only in later development. Consequently, the dichotomy between adaptive and fabricational paradigms is at least partially linked to differential lability in terms of degrees of freedom in adaptive potential. However, as we have just seen, this does not mean that change is not permitted in ontogeny, only that this is generally conﬁned to ontogenetic level by virtue of temporal modularity (see

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earlier remarks on the phylotypic stage in vertebrates and on Raff’s ‘‘hourglass’’ model, pp. 168–191): Wolpert (1990b) also noted that enormous variations occur in early development which might provide raw material for innovation. However, the question of modularity and the differential between fabricational and adaptational paradigms may often preclude this so far as parameters actually penetrating phenogeny are concerned. In general then, lability to mutational change will tend to be distributed in the developmental trajectory according to capacity for morphogenetic accommodation between a small number of quasi-autonomous modules of determinative activity. So far as the problem of morphogenetic accommodation traversing the coordinates of both the adaptational and fabricational paradigms of a given developmental trajectory is concerned, it is perhaps apparent that the most probable focus of accommodation may be unlikely to penetrate below the intersect zone for phenogeny and ontogeny that is linked to the transitional zone between TRANS- and CIS-acting determination factors. Here we must consider the large measure of stability that is clearly imposed at and around the phylotypic stage as constituting one likely source of conﬁrmatory evidence. Having examined the question of developmental constraints, it is now necessary to go on to brieﬂy examine certain other aspects of modularity that are actually conducive to morphogenetic change. The autonomy of certain morphogenetic trajectories, as evidence of temporal modularity freeing adaptive potential, is nowhere more noticeable than in the division between the germ line and somatic line. And this has obvious connotations for heterochrony, while at the same time drawing attention to the relative absence of such a high degree of dissociation for many other modules of development: In Drosophila, the somatic and germ lineages diverge while the embryo is still in the syncytial stage, at the ninth cycle of cell division. In many other lineages, this element of modularity has been seized upon as a basis for paedomorphosis (see Chapter 16). In contrast to the strong dissociation between germ line and somatic line, those coordinates of determination holding the highest level TRANS-acting determination factors with effects over many units of phenotype structure seem conversely to manifest the greatest level of evolutionary conservatism known in the genetic systems of eukaryote organisms (for example, those under the control of the Hox genes, see next two chapters). In summary, the most ‘‘adjacent’’ morphosystems of a given phenotype state are determined by the degree of modularity expressed by its morphogenetic trajectory. Adaptive potential is thus most ﬂuid in such modes as heterochronous change, where the accommodation requirement is at its lowest level. In this context, both adaptive capacity and adaptive potential may in fact display a linked modularity at certain stages of development, and this must also have important consequences for evolution (see Chapter 16). More remote neomorphic systems may also have the potential to arise through a propensity for some degree of modular interactivity between trajectories linked to different morphogenetic objects via modiﬁcations to a variety

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of translational mechanisms, assuming only that the problem of morphogenetic accommodation can be solved. As will be seen at a later point, this is often made possible by gene duplication (see Chapter 12). Much evidence has been accumulated to support our earlier proposition that realization of adaptive potential with respect to adult phenotype traits seems most likely to occur in the transition zone between proximal- and remoteacting determination factors, no earlier in the morphogenetic trajectory than that point at which the largest intersect between ontogeny and phenogeny exists, and certainly later than the phylotypic stage. Directionalization and ‘‘Constraint’’ in Developmental Modularity We have seen that, owing to a fundamental capacity for reciprocity in determinative activity, both within and between morphogenetic trajectories, the coordinates of adaptive potential must be at least partly accommodative for both the adaptational and fabricational biophysical paradigms. Raff (1996) has also discussed the question of ‘‘vertical’’ (temporal) developmental constraints, which concepts clearly must be connected with morphogenetic accommodation. Raff also noted that exceptions to apparent ‘‘constrainment rules’’ are widespread in that domain, an observation which might in turn be linked to lability in the fabricational paradigm. Raff additionally emphasized the point that ‘‘horizontal’’ (spatial) constraints may be more prevalent, as a function of degree of modular interactivity at any point in time. However, the various ‘‘constraints’’ discussed in this chapter do not constitute impediments to evolution so much as factors affecting directionalization of anagenetic change (see also Chapter 15). The question of constraints in general has already been reexamined in the light of factors tending to directionalize the adaptive response (Chapter 7), and it is perhaps pertinent at this juncture to point out that the sum total of all so-called constraints that have so far been examined cannot be presumed to affect such fundamental evolutionary mechanisms as probability of speciation in any way. Many traits involved in species isolation are in fact substructural in nature, or else comprise a repertoire of simple allelic substitutional differentials or amphigenetic states: For example, the parasitic wasp family Ichneumonidae has an immense species diversity, yet a typical species-rich genus in this family exhibits very little in the way of morphogenetic differential between species. It follows that the narrow channeling of degrees of freedom in adaptive potential and in the biophysical paradigm which occur because of factors arising from developmental modularity only serve to directionalize anagenesis, and in no way do they constitute any form of constraint on the actual occurrence of evolutionary change, whether cladogenetic or anagenetic. In fact, a large part of this ‘‘constraint’’ must be interpreted as promoting directionalization, rather than imposing any real impediment to evolution.

MAIN POINTS FROM CHAPTER 10 1. The coordinates of adaptive capacity and potential do not lie in geometric dimensions of the ﬁnal phenotype, but in those of development. These

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parameters must also be understood in terms of different levels of genetic translation. 2. The translation mechanism can be viewed in terms of a nested hierarchy of proximal-plus remote-acting determination factors, from primary translation of the genetic code through epigenetic interactivity to morphogenesis. 3. Remote-acting determination factors tend to manifest plasticity in the sole context of the true ontogenetic paradigm, so that the exogenous component of adaptive potential tends to lie more in the domain of CIS-acting factors. Mechanical induction factors seem likely to express the same mode of constrainment as do TRANS-acting determination factors, owing to their usual links with the fabricational paradigm. 4. The architecture of a generalized morphogenetic trajectory illustrates the differential distribution of modularity during development. The mosaic strategy demonstrates greater modular autonomy, the regulative, greater modular interactivity—plus a more wide-ranging lability in adaptive potential. 5. Modularity can be understood in terms of developmental units which manifest a discrete genetic organization. These units are frequently parts of larger entities, they have speciﬁc spatial locations, and they manifest varying degrees of interactivity with other modules; they may also undergo temporospatial transformations. 6. Adaptive capacity and potential are clearly constrained by developmental modularity, which latter can best be understood in the context of architectural models of development. The assembly model demonstrates low modularity, even during postontogenetic development—whereas the lineage model manifests high modularity throughout. 7. Adaptive capacity often lies with ‘‘poised bifurcations’’ in a morphogenetic trajectory. 8. The extrinsic domain in adaptive potential must lie at, and ‘‘downstream’’ of, the ontogeny–phenogeny intersect zone, indicating a probable focus at or beyond the TRANS 씮 CIS boundary, subsequent to the phylotypic stage. 9. The degree of modularity is especially important for modes of morphogenetic transformation involving developmental dissociation between different morphogenetic trajectories. However, selectional and developmental modularity need not be the same thing in terms of adaptive potential. 10. The link between developmental modularity and ‘‘constraint’’ affects only directionalization of anagenesis, and presents no real impediment to evolutionary change in the longer term.

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The notion of lability in realization of adaptive potential is a meaningless concept in the lack of any understanding of the gene control system which determines the coordinates of morphogenesis, and the roots of adaptive capacity and potential must also lie ultimately in the genetic domain. Genetic activity is, of course, responsible for control of determination and thus also of translation in general, and the morphogenetically active component of the genome must be structured around a hierarchy of coordinates of determination deﬁned by the interactivity of genes. Allelomorphism, as the basis for alternative pathways through development, must also be fundamental to the realization of both adaptive capacity and potential. Although it is obviously important to consider how the selection interface acts with respect to mutational change within the allelomorphic component of the genome, an understanding of how this mechanism actually affects evolutionary change depends in turn on a knowledge of the strategy of genetic interactivity throughout development, and it is from this latter point that we must continue our analysis. We now know a considerable amount concerning the manner in which TRANS-acting determination factors lay down the earliest and largest coordinates of morphogenetic activity, and something of the way that CIS-acting factors control differentiation and morphogenesis. Adaptive capacity and potential therefore have to be interpreted in the context of genetic control systems underlying these mechanisms.

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GENES, GENE FUNCTION, AND ADAPTIVE POTENTIAL Evolution has seized on imperfections in what must originally have been a simple replication system, and indeed, many extant gene complexes appear to behave as such, either through actual lack of allelomorphism or else through the existence of epigenetic homeostatic mechanisms that prevent disturbance to some equilibrium state in the phenotype output. The problems of gene functionality and interactivity lead naturally to the question of what actually constitutes a ‘‘unit gene,’’ and the answer to this question has become more complex, now that a deeper understanding of the molecular structure of actual genes has been attained. Lewin (1997) deﬁnes the gene as a cistron unit, the segment of DNA actually involved in producing a polypeptide chain, including regions preceding and following the coding region itself, along with intervening regions (introns) between coding segments (exons). From our present state of knowledge, the gene unit is not exactly equivalent to the latent DNA sequence, but to what is actually spliced from this in the stages leading to transcription–translation, in which sense, some Mendelian ‘‘tightly linked’’ genes may therefore in fact be splicing morphs of the same fundamental gene when reexamined at a molecular level (see below). In actual practice, a gene has often been deﬁned in terms of a ‘‘leading effect,’’ which may or may not actually be the target of (positive) selection. The boundaries of a gene may thus frequently depend on recognition of phenotype effect, rather than on intrinsic properties in the link to the selection interface, and molecular analysis may often not be particularly concerned with selectional attributes. It is clearly only in the context of population genetics that such propensities have been given special prominence, and it is thus clear that both approaches can learn much from the other in this respect.

Redundant DNA, the Gene Concept, and Molecular Evolution As already indicated above, our contemporary view of form and function of the gene is radically different from that put forward before the developmental role of genes became better understood, although it is also necessary at the outset to distinguish functional genes from ‘‘nongenetic’’ DNA. Sometimes, molecular geneticists have termed certain discrete DNA sequences ‘‘genes’’ whether or not there is evidence of any translational outcome of transcriptional activity. Indeed, real data on epigenetic homeostatic systems even show that translation at certain loci may lead to no functional outcome in terms of gene product activity. Certain DNA sequences should therefore not be regarded as functional genes, and most signiﬁcantly, nor should mutational activity in redundant DNA be regarded as ‘‘molecular evolution,’’ in the same sense that the origin of a ﬂying appendage constitutes structural evolution. From the viewpoint of morphogenetic changes affecting the phenotype, it is thus clearly of fundamental importance to see whether a given mutation has any function above the transcriptional level. From this, we may deﬁne what is actually meant by ‘‘gene,’’ and so avoid confusing ‘‘neutral mutation’’ with ‘‘nonadaptive evolution,’’ as has often been done in the past. In the scheme below, the term translational is used in the sense of implying not only some change in gene product, but also some change in the adaptive

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state, which in turn establishes a deﬁnite functional change. Thus, some DNA may be ‘‘nongenetic,’’ and some mutations in transcriptionally functional genes may be ‘‘inactive.’’ The term gene should therefore only be applied to DNA that is both transcribed and translated, where the translative product also plays some functional role in metabolism or development. In this approach, we should accordingly hope to avoid an overly ‘‘genocentric’’ view of evolution: It should also be said that some authors claim that the neutral allozyme differentials observed in natural populations are actually maintained by ‘‘balancing selection.’’ A major theoretical problem with data of this kind is of course that, for logistical reasons alone, there can only be a few leading effect allelomorphs in adaptive capacity at any time, while, according to Nei (1987), the genome of higher organisms contains 4000–50,000 structural loci. Lewontin and Hubby (1966) used electrophoresis to detect gene substitutions ‘‘at source,’’ looking at 24 loci for enzymes or proteins in Drosophila pseudoobscura. About 40% were ‘‘polymorphic’’ and around 12.3% were heterozygous. Drosophila may have 10,000 gene pairs, with an estimated 3000 being ‘‘polymorphic’’ and 1150 heterozygous. Dobzhansky (1970) agreed with the present assertion that most variants are probably selectively neutral, in which case we should now add that they constitute neither true polymorphism nor ‘‘evolution.’’ This view is surely amply conﬁrmed by our present knowledge concerning redundant DNA (see Kimura, 1983). In summary, while we must move forward from the simplistic view of genetic evolution presented by the classic Mendelian model, we must also guard against false hypothesis in the molecular model. The key to this new understanding can only come from an holistic view of the developmental role of functional genes in the light of the evolutionary behavior of the greater adaptive system.

The Translational Hierarchy in Gene Function Transcription is that mechanism through which mRNA is copied from DNA through the action of RNA polymerase, and translation is that activity through which a nucleotide sequence on mRNA is subsequently translated into an amino acid sequence at the ribosomes. The latter constitutes primary translation, above which level we have secondary translation (for example, regulatory action leading to determination) and also tertiary translation in epigenetic interactivity concerned with organization of morphogenesis via differentiation and growth. Primary and secondary domains may conveniently be termed infratranslational levels and tertiary, supratranslational, thus usefully distinguishing between substructural and morphogenetic levels of gene activity and interactivity. Genes can thus be classiﬁed according to position in the determinative hierarchy, in terms of their ﬁnal translation level. Infratranslational genes have some role in synthesis of metabolic products or in differentiation of cells, but express

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no effect above those levels, whereas supratranslational genes clearly include those which control growth and morphogenesis. The products of genes in the latter category may either have a direct role (manifesting an autonomous effect at higher translation level) or else act as regulators of other genes (see below). Such genes are clearly of great signiﬁcance in understanding those control systems of development which contain the key to realization of adaptive potential.

Structural and Regulatory Genes in the Supergene Unit A structural gene is one which codes for a protein with a role in metabolism, cell growth, etc. A regulatory gene controls activity at some other locus via a protein product having either a repressor or activator role to play with respect to the activity of other genes, which latter may be other regulators or else structural genes. Such genes clearly manifest a higher translational effect in their homeostatic relationship with other genes. In the present context, it will be found more useful to consider an aggregate of structural and regulatory genes linked to a common function as constituting a supergene, given that it seems ﬁrmly established that smaller DNA units within such structures are generally recognized as ‘‘unit genes.’’ It is further instructive to consider that the lower and higher translational categories discussed above should also apply to the supergene unit as a whole. The highest supratranslational genes will thus be those operating as supergenes affecting complex morphogenesis.

FIGURE 47 The supergene as an autonomous complex of mutually interacting regulatory and structural genes.

Gene Regulation and Adaptive Potential Theories of gene regulation have been greatly inﬂuenced by the Jacob and Monod (1961) operon model formulated in the study of prokaryote genetics. The simplest system has a regulatory gene interacting with an operator site adjacent to a structural gene, and having afﬁnity for the operator site modiﬁed by an inducer or repressor product. Control systems may be positive or negative, acting as ‘‘on/off switches,’’ thus falling into the categories activator versus repressor. This system is well known in prokaryotic organisms but is less understood in higher organisms. As Lawrence (1992) warns, in the attempt to

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derive more complex models suited to the situation in eukaryotes, we must remember the maxim that equations with more than three terms can be made to ﬁt any data! A number of regulatory genes have, however, now been identiﬁed in Drosophila in connection with the determination and differentiation of parasegments and compartments, and activator–repressor activity has also been conﬁrmed in many other cases: The loci nanos, hunchback, and bicoid play an interactive role in determination of anteroposterior polarity at an early stage, whereas the ANT-C and BX-C gene complexes are involved in developmental activity within parasegments, compartments, and speciﬁc zones of differentiation within morphogenetic compartments. Within this complex of supratranslational regulatory genes, some members have an activator and some a repressor role; for example, nanos is an important posterior polarity gene, the function of which is to disable hunchback activity in the posterior region, acting thus as a repressor of the latter. Regulation can be at the transcriptional or else at the post-transcriptional level (as with selective message translation), and the broad pattern now emerging from molecular level analysis of regulator gene activity conﬁrms the view that activation–repression forms the fundamental pattern of activity of supratranslational genes in general. The changing hierarchy of parasegments and compartments in Drosophila identiﬁes a descending hierarchy of temporal relationships of regulatory genes within which speciﬁc loci play a variety of roles, probably in combination with ordered activity of structural genes (see Fig. 48, p. 206). Bearing in mind the close link between genes controlling morphogens (and thus also higher level coordinates of morphogenesis), adaptive potential must clearly be especially linked to supratranslational regulatory genes which generally exist in a state of ﬁxation. In the same way, much adaptive capacity seems likely to be contained in allelomorphism of structural (and particularly infratranslational) supergene complexes.

EPIGENETIC INTERACTIVITY, MORPHOGENESIS, AND ADAPTIVE POTENTIAL To understand the function of supratranslational genes in morphogenesis it is necessary to consider this question in terms of interactivity in the epigenetic environment, taking into account the architecture of the regulatory hierarchy, and also the domain of gene expression.

Adaptive Potential and Communication in the Epigenetic Environment Bearing in mind the mechanisms of intercellular communication, it is clear that much signiﬁcant epigenetic interactivity in the ‘‘upstream’’ sector of the regulatory hierarchy implies transmission via TRANS-/CIS-acting mechanisms. The previous chapter examined the role of CIS- and TRANS-acting factors linked to determination and differentiation, and it was observed that these factors have also been traced to genes affecting morphogenesis. That such

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factors are translational properties of genes also is thus to be expected. Many regulator genes clearly act as switches during development, affecting the temporospatial positioning of loci and coordinates of morphogenesis and triggering differentiation and growth in cell lineages. A further aspect of gene activity must therefore clearly be to receive, transmit, and act on information (for example, many structural genes provide synthetic functions for cell metabolism in response to the activity of regulatory genes, frequently via the intermediary of intercellular communication): MacLean (1989) summarized the broad outline of gene regulation thus: ‘‘It is usually in response to external stimuli, that genes in a cell alter expression. Nucleus and cytoplasm are constantly exchanging information—signals may be received on the cell surface, then be relayed to the nucleus, genes thus being turned on/off accordingly. Hormones enter the cell and may interact directly with genes. Some regulation is also done in response to purely endogenous nuclear events such as: lapsed time, amount of protein synthesised, mitotic counts, etc.’’ The sonic hedgehog locus in Drosophila is an example of a gene with an inductive (CIS-acting) role, whereas bicoid, nanos, and others have been linked to TRANS-acting factors. Regulatory genes may thus be proximal or remote in activity, in relation to their targets, some regulators having an intracellular communication link with the regulated locus while others communicate with external cells and tissues. Many higher level regulators seem to be TRANS-acting, others CISacting, and the predicted temporal hierarchy may often be ‘‘higher morphogenetic coordinates ⫽ TRANS-active 씮 lower coordinates ⫽ CIS-active.’’ There is thus a dichotomy between proximal and remote determination of the intercellular kind versus ‘‘autodifferentiation,’’ and this ‘‘higher/lower’’ status of regulatory genes should also be brought into focus with the ‘‘ﬂexibility’’ aspect of adaptive potential. The developmental model of genetic interactivity thus incorporates an intercellular communication system, both for sending information and for receiving signals from other loci. The quasi-autonomous translational loci of development intercommunicate thus in their links to coordinates systems and positional information, and the transmission function in regulator gene activity is clearly also that mechanism linking transcription to translation as we move from the ‘‘primary genetic’’ to the ‘‘epigenetic’’ domain. The largest coordinates of morphogenesis are therefore linked to the transmission function of TRANS-acting morphogenetic signals, although realization of adaptive potential seems unlikely to constitute mutational change in the expression of regulator genes controllant to such coordinates (given the relative rigidity of the larger translational loci and their links to true ontogeny, as discussed in the previous chapter). Apart from the possibility that some supratranslational genes with a transmissional function may constitute one possible ‘‘target of adaptive potential,’’ it seems more likely that both endogenously activated and CIS-acting systems must form signiﬁcant substrates for much realization of adaptive potential through mutational change. In categorizing genes according to regulatory activity, we have also taken into account the intracellular differential relating to the cis/trans dichotomy in the functional activity of regulator genes (where cis ⫽ regulative effect on same DNA molecule, and trans ⫽ effect on a

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different molecule), and this latter dichotomy has even greater implications for the question of physical organization of the genome (see Chapter 13). The diverse mechanisms involved in transmission and communication in development cannot, however, be divorced from the supposition of any one category of translational locus constituting a ‘‘center of adaptive potential,’’ and this question also links to the accommodation principle, which states that there must be orchestrated change in the coordinates of development, with respect to any complex modiﬁcation at the level of phenotype. Once again, we are forced to presume that this most usually occurs in that domain in which TRANS-acting determination factors interdigitate with the highest level CISactive factors (see previous chapter). In the present context, these factors are under the control of supratranslational genes of the regulatory kind. The Hierarchic Structure of Epigenetic Interactivity Epigenetic interactivity may be expressed at different translation levels, from the chemical messenger function of morphogen activity to Newtonian determination factors. The phrase ‘‘epigenetic interactivity’’ thus encompasses many diverse mechanisms of supratranslational gene activity. It is now necessary to ask what kind of control systems facilitate higher translation level interactivity, particularly within the morphogenetic domain. It is particularly useful at this point to examine the genetic strategy for deﬁnition of an outline morphogenetic trajectory in Drosophila, the fundamental strategy of which can be seen to express a hierarchy of regulator genes operating in an integrated function. This mechanism involves several tiers of regulation, as would be expected considering the likely presence of a hierarchically ordered strategy of activator/repressor activity for control over any other than the simplest developmental trajectory. Using a fragment only of the information available on Drosophila (and greatly simplifying this in the interests of clarity!), we can look at some aspects of the determination hierarchy in the context of the preceding discussion. Figure 48 summarizes the broader ﬁndings of work on early ontogeny in Drosophila, following on from the discovery of some 150 genes associated with this phase of development, by Nusslein-Volhard and Wieschaus (1980). The highest ‘‘upstream’’ gene products in the Drosophila cascade are clearly TRANS-acting morphogens produced by a number of maternal genes. The next major coordinates to be laid down are also formed in a syncytium, within which medium many protein products simply diffuse to neighboring nuclei. These early loci of determination tend to be transient structures, being presumably linked to fabricational paradigms of ontogeny. Cellularization and deﬁnition of parasegmental boundaries occurs concurrently with the appearance of the pair-rule genes, following which the morphogenetic compartments come to be deﬁned by segment polarity genes, which latter include a true selector gene (engrailed ) that continues to confer identity well into later development. The principal source of selector gene activity then follows with activation of the homeotic genes, most of which belong to the Hox clusters BX-C (bithorax) or ANT-C (antennapedia).* * The term ‘‘Hox genes’’ was originally used for vertebrate homologs of ANT-C and HOM-C. It is now used in a generic sense for all genes belonging to these complexes, in all phyla (although gene names with ‘‘Hox’’ in them are restricted to the Vertebrata). In general, Hox genes act as selector switches activating downstream genes involved in segmental development.

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FIGURE 48 Outline hierarchic structure for cascade of regulatory genes affecting morphogenesis in Drosophila showing relationships between strategies of determination and developmental paradigms (examples of genes involved are indicated in parentheses).

In the homeotic selector genes, we encounter that point in the ongoing coordination of development at which the permanent identity of holistic functional body parts is initiated. The activity of certain members of the BX-C cluster (the bithorax complex, which directs pattern formation in parasegments 5–14) has been shown to be involved with speciﬁcation of segment identity

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and individualization of parasegments, determining which body parts particular cells will ultimately produce. These genes clearly must be active in a speciﬁc compartment (or set of compartments), being responsible for pattern generation in a cell autonomous manner: There are three homeobox containing genes in the BX-C: Ubx (Ultrabithorax), responsible for direction of pattern in parasegments 5–15; also abd-A (abdominal-A) and Abd-B (Abdominal-B ), the activity of the aforementioned genes being controlled by the preceding gap and pair-rule genes. Widely studied mutations of the homeotic genes include bithorax and posterobithorax, with anterior and posterior compartmental activity, respectively. Interactive effects are also known to occur between the three homeobox genes of the BX-C; abd-A combines with Ubx in contributing to parasegment 7–9 patterns, and Abd-B modiﬁes the combined effects of Ubx and abd-A in parasegments 10–14, so that the approximately linear hierarchy shown in Fig. 48 actually masks combinatorial properties. Mutants of Ubx made by mitotic recombination are cell autonomous, but they function according to a preexisting coordinates system according to position in the compartment, the ground plan for which latter is laid down at gastrulation from founding cells of maternal origin. Ubx, abd-A, and Abd-B are clearly higher translational regulatory genes. As stated by Lawrence (1992), the functional strategies of the Drosophila cascade give the combinatorial code some properties of a hierarchy. The system outlined above is thus an approximately linear hierarchic control system in which each gene set has some role in activation of the next in temporal sequence. Of particular interest here is the implied link to that cascade of genetic interactivity termed epistasis (in the purely developmental deﬁnition of the term; see below). Of special interest, here, is the observation that merging of earlier ontogenetic and later phenogenetic paradigms appears to occur at approximately that point when the homeotic genes are activated (namely, where TRANS-activity gives way to predominantly CIS-activity), whereas the ﬁner details of phenotype form must be determined by more ‘‘downstream’’ factors involving growth programs indigenous to cells and inductionlike interactivity between cells and tissues. In this, it is evident that those developmental coordinates laid down by far-reaching determination factors of morphogen status do not in fact deﬁne ‘‘malleable phenotype traits,’’ but instead specify more transient precursor states belonging to lower translational domains of the true ontogenetic paradigm.

Adaptive Potential and the Spatial Aspect of Gene Function It is not possible to analyze the apparent linearity of the regulatory hierarchy until certain nonlinear elements in the activity of genetic systems have been examined. From our knowledge of the temporospatial domain of gene expression, the latter element is by no means insigniﬁcant.

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The diverse functions expressed by gene activity may be categorized in several ways. However, there are two main dichotomies of special interest in the context of the present analysis, one lying in the functional–homeostatic role discussed above, the other being that concerned with the degree to which a given gene is specialized in the sense of having a greater or lesser functional speciﬁcity in relation to the distribution of activity within developmental spacetime. Some genes perform the same function in a wide range of cell types, whereas others have a highly speciﬁc function to play in only a single cell type, or even in some cells of a given type but not others. We can examine the temporospatial distribution of gene action by considering the on and off switching of gene activity at different points in time and space using a simpliﬁed model with two spatial dimensions (see Fig. 49). Monotropic genes are those having a single temporospatial locus of activation. They are the cell or tissue speciﬁc genes, exhibiting site speciﬁc activity in developmental space-time. At the other end of the spectrum, eurytropic genes are those genes performing an identical function at many different spatial loci (and sometimes in almost all cells) owing to universality both of transcription and of translation. Many of the latter will be infratranslational genes, but there may of course be others (as with those genes involved in control over mitosis) that are supratranslational. Somewhere between the two extremes of the monotropic and eurytropic categories lie the allotropic genes: those loci that are expressed a small number of temporospatial loci.

FIGURE 49 A gene is switched on or off at two different spatial and temporal loci; 0 ⫽ off, 1 ⫽ on; X,Y ⫽ 2-space; Z ⫽ t ⫽ temporal axis.

The most highly specialized supergenes will clearly tend to be monotropic, and many ‘‘general purpose’’ genes will be eurytropic. The allotropic gene set will be of special interest in the context of ‘‘epistatic linearity’’ (see above), and thus also of modularity in the supratranslational domain (an observation that must also have connotations for adaptive potential, that is, given the disparity which may exist between selectional and developmental modularity; see Chapters 7, 10, and 12). In general, • Monotropic genes will be completely speciﬁc to a single function: Among those loci with an apparent monotropic role are some of the highest level regulators of the Drosophila cascade, including certain

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homeobox-containing genes. These consist of a conserved 180 base pair region (the homeobox) which encodes a conserved amino acid motif, the Homeodomain. Protein products of these genes function as transcriptional regulators. Certain selector genes responsible for determination within morphogenetic compartments in Drosophila are examples. Lawrence (1992) described the ‘‘idealized selector gene’’ as one which is active in a compartment (or speciﬁc set of compartments) and is responsible in cell autonomous fashion for the pattern formed. • Eurytropic infratranslational genes will be those involved in synthesis of cell products common to a wide range of cell and tissue types. These particularly affect basic metabolism: For example, the housekeeping genes involved in essential cellular activities, as with the gene for cytochrome c, are eurytropic infratranslational genes. • Allotropic infratranslational genes will have a synthetic function in more than a single developmental zone, and often also in the adult phenotype (as indeed will be the case with very many infratranslational genes): The globin gene family is an example of an allotropic infratranslational gene. • Eurytropic supratranslational genes will be regulator genes having a similar role to play in growth and morphogenesis in different tissues and superstructures: This may include at least some of the paracrine factors involved in induction. The same proteins have been found linked to growth and differentiation in quite diverse organs and tissues, even in different phyletic lineages. This includes the ﬁbroblast growth factor family and other known genes (see Gilbert, 1997). • Allotropic supratranslational genes will be genes controlling morphogenetic programs for more than a single localized superstructure: The Kru¨ppel and fushi tarazu loci in Drosophila have a main role in early development in deﬁning zones and parasegment boundaries, but they are later expressed in certain neurons. The hedgehog gene also manifests allotropic expression, and certain cell adhesion molecules seem not to be organ speciﬁc in their activity. The concepts of mono-, eury-, and allotropic gene expression clearly link to the structure unit or integral organization of the ﬁnal phenotype (see Chapter 7), in that particular structure integrals and their associated morphogenetic trajectories may have site speciﬁc genes in their developmental program, while at the same time there will be other genes that are also involved in other morphogenetic trajectories. Mono- and allotropic supratranslational genes

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should be those of particular interest with respect to anagenesis, in terms of the architecture of adaptive potential, since eurytropic genes probably express too wide an effect in this context to bypass the problem of negative pleiotropic effects. Continuing with the question of allotropy, the same morphogenetically active gene clearly may have different temporospatial loci of activity (as, for example, shown by several members of the BX-C complex), and this question also raises the problem of how realization of adaptive potential can materialize in the face of such a convoluted developmental strategy! In addition to the latter question, certain other aspects of gene expression and genetic interactivity linked to questions concerning the mechanisms of pleiotropy and epistasis will also have to be analyzed in relation to this problem. The overall picture now emerging is clearly one of a nested set of regulatory genes operating in a temporal hierarchic sequence within the boundaries of the ‘‘level-interactive modular array’’ of the morphogenetic trajectory structure (see previous chapter). Although this does express some qualities of a vertical hierarchy, gene expression is by no means limited to a linearly organized strategy. Analyzing Allotropic Gene Expression As already indicated above, a single gene may have more than a single role to play in development. It is now necessary to superimpose a further layer of complexity onto the allotropy scenario, namely, that surrounding the question of differential splicing at a single gene locus. Given the propensity of genes for splicing, it is obviously possible that ‘‘the same gene acting at different temporospatial loci’’ might actually be a different transcriptional unit derived from the same molecular locus. A given gene unit cannot be presumed always to correspond to a single transcriptional strategy, since the same locus may be spliced in different ways at different times during the course of development. Genes may have introns and exons (for example, the 웁 globin gene has three exons and two introns), and a sequence treated as an exon in one mode may be an intron in another: The mRNA precursor for the cell adhesion molecule N-CAM can be spliced into over a hundred forms on the basis of differential assembly of exons (see Gilbert, 1997). In this way, one gene may create a family of related proteins. Returning to the earlier diagram (Fig. 49), it will now be found useful to replace the digit 1 (⫽ on switch) with a symbol identifying a gene forming a point of interest (A, B, etc). It is then possible to denote a different splicing morph (or allotrope) of gene A by A⫹. This allows us to compare and contrast two different manifestations of allotropy, which we shall term 움 and 웁 modes (Fig. 50). The dichotomy between a gene which operates in the same fashion at different temporospatial loci during development and one which is derived from the same DNA molecule but which changes function in some way thus distinguishes 움-allotropy from 웁-allotropy.

␥-Allotropy and Classical Pleiotropy The term pleiotropy has been widely used in the past in order to describe the one gene 씮 n traits model of development, especially as this relates to

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FIGURE 50 움-allotropy (left: same gene, different temporospatial site of expression) and 웁-allotropy (right: same locus, different splicing morph of gene, and same or different site of expression; A⫹ ⫽ modiﬁed A gene).

widely differing effects of a single locus. How is this related to the developmental model? To answer this question, we must begin by comparing and contrasting classic pleiotropy with allotropic gene expression: Allotropy as ‘‘false’’ pleiotropy

‘‘True’’ pleiotropy

Output is slightly different at broadly similar morphospatial loci.

Output is very different at separate morphospatial loci.

Is the mechanismic link between ‘‘true pleiotropy’’ and allotropy one of kind or of degree? One possible interpretation of true pleiotropy could be that it is simply a higher level manifestation of allotropy, in which there is ‘‘translational saltation,’’ for example, where the same gene interacts with different products of other genes (whether or not it is actually transcribed differently at different sites). Utilizing the model described above, we can now represent one aspect of classic pleiotropism as 웂-allotropism, using the convention A⬍, B⬍, etc. We have now adopted capital letters to represent speciﬁc gene loci as ‘‘on’’ in the context of 움-allotropism, also A⫹, etc., to signify 웁-allotropy, and ﬁnally A⬍, etc., for 웂-allotropism. In this way, it is possible to portray, in a simpliﬁed manner, how genetic activity can be mapped onto developmental space-time.

FIGURE 51 Three different ways in which allotropic gene activity relates to the temporospatial matrix of development (A ⬍ ⫽ 웂-allotropism).

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The 웂-allotropy situation describes a reagent–substrate scenario in that, in addition to a change in the ‘‘reagent’’ (differential transcription), allotropic gene expression may ascend to greater expression when the ‘‘substrate’’ is also different (thus invoking differential higher level translation), the substrate in question being the epigenetic environment with which the reagent gene interacts. This could happen, for example, when the same gene product links to a separate regulatory product of other genes at different temporospatial sites in development: Gilbert (1997) discusses co-option of the engrailed gene in Drosophila, which is used for segmentation in the embryo, and again to specify neuron development; it is used also in the larva, to create an anteroposterior axis in the imaginal discs. This appears to be 웂-allotropism. The eye cells in Drosophila are thought to respond to the same positional cues as those in the leg disc. Again, the ‘‘reagent’’ appears to be the same, but the ‘‘substrate’’ is presumably different, and the same regulatory gene has more than one target site of regulation. Looking at the same question in the transspeciﬁc perspective, the ‘‘substrate’’ for the Ultrabithorax gene is apparently different in Precis butterﬂies and Drosophila (see Gilbert, 1997; f. Warren et al., 1994). We must of course also consider that variation in the reagent–substrate complex may imply some differential in the reagent itself, as, for example, when activity relates to a gradient effect: With the products Bicoid, Hunchback, and Caudal, allotropy may also represent a variation in ‘‘reagent,’’ and this applies also to the Homeodomain family of regulatory proteins. Drieuer and NussleinVolhard (1988) have shown that at least three qualitatively different responses exist to different concentrations of the Bicoid morphogen. Variation in reagent thus implies no necessary change at the transcription level. In the above analysis, it seems safer to assume that much ‘‘false pleiotropy’’ amounts to expression of 웂-allotropism arising from a differential in ‘‘substrate,’’ in contrast to that situation where at most a transcriptional differential in the ‘‘reagent’’ (as with differential splicing) underlies multiple gene activity. This level of allotropic gene expression also seems intrinsically likely to carry the very highest adaptive potential for neomorphic change. As we shall see in the ensuing discussion, however, our revised concept of allotropy does not fully ‘‘solve the pleiotropy question’’ (to which we will return again in the context of mutation in the next chapter), nor does it constitute a complete understanding of allotropism itself. Evidently, the ﬁrst maxim regarding epigenetic interactivity must be that determination factors arising in one trajectory may affect developmental events in others, a phenomenon we have already encountered in induction, as also with Newtonian determination factors, etc. The term pleiotropy can be seen now to be linked, in its broadest sense, to the multiple activity model of gene activity, based on clear evidence from contemporary molecular genetics that the nonmutative form of a gene often has many different loci of action.

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Translational Allotropism and Adaptive Potential Implicit in the concept of allotropy is the notion of multiple switching of a given gene locus, or of variation in concentration of gene product over a distance gradient. However, pleiotropylike effects can also result from a single gene activation event as a direct function of epigenetic interactivity. The former is transcriptional allotropism (arising from differentials in gene product, or in multiple switching), the latter, translational allotropy (apparent allotropism resulting from the translational effects of a single transcriptional event in a which a nonvaried product is also implicated). A translational allotropic effect can occur as, for example, the result of convergence of two morphogenetic trajectories acting as quasi-autonomous modules, when a higher translational event in one module is ‘‘co-opted’’ as an input to another, adjacent trajectory (as, for example, with mechanical induction). Where ‘‘convergent co-option’’ occurs there will be an apparently allotropic effect that will only be identiﬁable in the phenotype when the gene involved is mutant, or when architecture of the entire control sequence is fully known:

FIGURE 52 Translational allotropism in ‘‘convergent co-option.’’ Input 2A in the lower morphogenetic trajectory becomes an input to the upper trajectory, as a result of mechanical induction or of chemical induction in which the inducer is homogeneous.

Thomson (1988) discusses the observation that changes in skeletal cartilage have reciprocal effects in placement of muscles, and the latter likewise on placement of nerve axons. Apparent ‘‘pleiotropic’’ effects of Drosophila BX-C genes include the Kru¨ppel mutant which is one of several known genes having early roles concerned with deﬁnition of zones and parasegment boundaries. The Kr mutation affects deletion of entire segments of thorax and anterior abdomen, and is also expressed in parts of neurons, trachea, and gut at a much later stage in development (in this particular example, it may not always be entirely clear at which point allotropic effects

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are due to multiple transcriptional activity of the gene in question or to reciprocal translative effects of a single transcriptional event). Interpreting classical pleiotropy from the perspective of developmental translation levels, there must then be two principal domains of broadly ‘‘pleiotropic’’ activity: ‘‘pleiotranscriptional’’ and ‘‘pleiotranslational.’’ The pleiotranscriptional domain is that in which a gene inﬂuences several structurally unconnected effects at different temporospatial loci in developmental space-time (as here interpreted in terms of 움- and 웁-transcriptional allotropy). The pleiotranslational domain exists whenever a higher translational gene factor affects a single change, which is then translated as a morphogenetic event that in turn affects several different temporospatial sites of development as a result of reciprocal, higher level translation activity (as with induction, morphogenetic movement, etc.). Theoretically then, there can be no determination factor acting at a higher translation level without some potential arising for morphogenetic interactivity to occur beyond the locus of the ﬁrst observed effect. This reciprocation effect is not a ‘‘developmental pathology,’’ but rather, it should be seen as part of the predictable behavior of the interactive–allotropic structure of genetic systems. From the observed interactivity of many morphogenetic trajectories (and perhaps especially those in the ontogenetic domain), translational allotropy may at times constitute an important component of the epigenetic landscape, just as transcriptional allotropy seems certain to be a general property of much genetic activity. The question of translational allotropism clearly raises many questions concerning realization of adaptive potential (see next chapter).

The Epistatic System and the Architecture of Adaptive Potential The term epistasis is used in quite a different sense by population geneticists from those working on development. In the former usage, ‘‘epistasis’’ relates to the interactivity of genes in relation to ﬁtness, whether or not the genes in question control the same phenotypic parameter. In the developmental view, epistasis describes the approximately linear–hierarchic pattern of interactivity between regulatory genes jointly controllant to the same phenotype trait. It is widely recognized that there is a temporal order wherein different classes of genes are transcribed, and that the products of one gene often regulate the expression of another. We have already witnessed this with the outline developmental program for Drosophila (see above). The developmental hierarchy expressed by a sequential cascade of genetic activity with respect to a single structure unit thus links to the biochemical deﬁnition of epistasis. However, since the ﬁtness interactivity studies by population geneticists may involve loci also having an epistatic relationship in the developmental sense, these two interpretations are not in fact invariably mutually exclusive, although they may nevertheless carry quite different implications with respect to the behavior of the selection interface. Although developmental epistasis was originally discovered as a dominance hierarchy among gene mutations, it has become evident that this mechanism really reﬂects the typical architecture of interactivity between ‘‘ﬁxed’’ genes

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affecting a common morphogenetic trajectory. The term epistasis thus describes the regulatory–hierarchic architecture within the supergene unit, irrespective of any consideration of propensity for allelomorphism in any member of the gene set concerned. As with classical pleiotropy, epistasis must therefore be explored in the revised context of normal phenotype development. Given the complexity of such morphogenetic trajectories as that for Drosophila (see Fig. 48), it is quite clear, of course, that the notion of simple linear epistasis is an oversimpliﬁcation. Nevertheless, this approximation remains the best available ‘‘working model’’ so far as the present objectives are concerned, although from a more realistic viewpoint, it will of course have become clear that any view of the architecture of the epistatic cascade must consider allotropism, particularly in the convergent co-option, translational model. In any reinterpretation of epistasis, certain axioms must be accepted at the outset. Obviously epistasis cannot be properly understood unless we entirely abandon the one gene–one character model of gene activity and ignore the allelomorphic view of gene organization, neither of which contains any special relevance to the question of gene interactivity during normal morphogenesis for a majority of complex structural traits. In addition, any supposed all-genes interactivity model must also be rejected, since epistatic systems can only be presumed to function in an adaptational context when combined with an evolved homeostatic strategy that is closely linked to the modular structure of development. Epistasis is thus that hierarchic architecture through which deterministic interactivity between genes is organized and maintained, and the term should be conﬁned to that domain (thus rejecting the ‘‘ﬁtness epistasis’’ application of the term used by population geneticists). The unit genes of a higher translational supergene complex controllant to morphogenesis of a complex developmental parameter together form an epistatic system that is generally composed of a ‘‘ﬁxed’’ (that is, essentially nonallelomorphic) interactive hierarchy of regulatory and structural genes, ‘‘superior’’ members of which have an epistatic relationship to ‘‘inferior’’ members. A typical epistatic system may be viewed as a hierarchic system governing a trajectory of determination, differentiation, and morphogenetic factors, following the temporal–functional hierarchy indigenous to developmental systems in general. A knowledge of the nature of the epistatic system must serve to illuminate the dichotomies ‘‘rigid/ﬂexible,’’ ‘‘major/minor,’’ ‘‘quantitative/qualitative’’ with respect to the coordinates of adaptive capacity and potential, and these criteria can in fact be shown to constitute different facets of the same problem. In particular, the hierarchic level of activity of a given regulatory gene must be linked to the probability of its being involved in realization of adaptive potential, especially since the highest level members may frequently be associated with rigid ontogenetic traits (see Chapters 10 and 12). Synparametric and Alloparametric Epistatic Systems The basis for a genetic determination system for a chosen structure unit can lie with either of two models: 1. In the alloparametric model, n determination factors affect n qualitatively different parameters of a given structure unit (a ⫽ size, b ⫽ color).

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2. In the synparametric model, n determination factors affect a single parameter (a ⫽ ‘‘circular,’’ b ⫽ ‘‘square’’). The relationship between members of gene sets of both kinds will often prove to be of the epistatic kind, although the synparametric set seems most likely to manifest a ‘‘convex’’ hierarchy of this kind. Both systems may of course operate simultaneously for complex morphogenetic trajectories, and both are of interest in evolutionary analysis. However, the synparametric strategy is of special signiﬁcance when we come to analyze the higher level interactive functions of epigenetic determination mechanisms, in that this form clearly manifests the most constrained kind of epistatic behavior. Synparametric epistatic systems thus seem likely to be of considerable importance with reference to adaptive potential, for example, with special reference to allometric modulation of shape (see Chapter 16). This class of supergenes thus clearly places a particular demand on the architecture of gene homeostatic systems. Alloparametric gene clusters are also considered to be epistatic, by virtue of the probable input from pleiotranslational interactivity between gene units (see above). Convex and Flat Epigenetic Interactivity and the Parastatic Supergene There appear to be two possible types of synparametric gene systems, manifesting different levels of epistasis. A synparametric system can be convex (approximately linearly hierarchical, with a nested sequence of regulator and structural genes controllant over n qualitative effects) or else ﬂat (as with a group of genes interacting in a weaker hierarchy in the ‘‘upstream– downstream’’ proﬁle, and having a purely additive effect). Convex synparametric systems tend to express qualitative differentials and tend to evolve ﬁxation in the context of a clear dominance hierarchy, since they can be presumed to typify the kind of gene system associated with highly complex, ‘‘essential’’ features of phenotype form. Flat synparametric systems tend to express only quantitative variation in a parameter affected by n recessive alleles, and may often manifest allelomorphism in the minor gene mode. These could perhaps be termed parastatic supergenes (and are the same thing as polygenic systems). The causality of ﬂat systems manifesting continuous variation may lie either in near neutral differentials between genotypes or in expression of adaptive capacity linked to some continuously distributed variable in the external environment, whereas more convex structures are likely to have been constructed iteratively through realization of adaptive potential over a very long period of time. Two or more synparametric gene loci are thus only said to have a high level epistatic relationship when they are adaptationally positive, and have a ‘‘convex’’ hierarchic interrelationship. Probably all higher morphogenetic supergene complexes are of this kind, while parastatic systems tend to be linked to more labile patterns of interactivity. Although our molecular understanding of ‘‘ﬂat’’ polygenetic systems is not as good as that for some ‘‘convex’’ systems, it is necessary to attempt to compare these systems on the basis of an earlier knowledge of the behavior of multifactorial gene systems.

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Epistasis and the Supergene Concept It is a fundamental axiom of developmental genetics that the unit genes of a single epistatic cascade should be regarded as belonging to a single supergene, whether or not they are physically approximated on the chromosome. As with the traditional usage of ‘‘epistasis,’’ the concept of what constitutes a supergene has also been confused, and clearly for similar reasons. Certain so-called supergenes, such as, for example, that of the butterﬂy Papilio memnon, involve gene alleles controllant to developmentally independent phenotype traits (wing color, presence of an alar tail, etc.), and this has also been described as ‘‘epistasis’’ with respect to a ‘‘supergene.’’ While the memnon traits do in fact belong to the same function integral (see Chapter 7), they clearly do not form part of the same epistatic system in the developmental sense. Consequently, the memnon gene cluster is neither epistatic, nor does it constitute a true supergene. In the present work, we have observed that some epistatic systems are synparametric, and others alloparametric (see above). However, the memnon example clearly comes into neither category, since it does not involve n genes actually affecting the same developmental object. We also have to observe a true epistatic relationship in determining if an alloparametric gene set is to be considered to be a true supergene, and this is clearly not the case with memnon (as with many other examples of ‘‘epistasis’’ sensu lato). At a later stage, we shall reexamine the memnon ‘‘supergene’’ in the entirely different context of recombination and chromosome structure (see Chapter 13).

Boolean Functions and Flat versus Convex Epistatic Systems As we have seen, an epistatic system is to a greater or lesser degree hierarchic–homeostatic in nature and deterministic in activity, at the same time maintaining a capacity for interaction with a changing internal environment. Boolean functions and networks can be utilized to model certain of these properties (Kauffman, 1993, and elsewhere), and they are at least partly analogous to real epistatic systems in describing the fundamental architecture of the regulatory backbone of those supergenes controlling cell division and morphogenesis. Kauffman (1993) admits that this ‘‘binary idealization’’ is to some extent false (the real system has a greater allotropic basis, and an active gene may exhibit graded activity), but he also argued that the Boolean network model does nevertheless form a valuable approximation to reality. Lewis (1978) likewise explained the genetic control of homeotic genes as a pattern of serial coding of switches in an on or off position. In the present treatment, we must also discriminate between Kauffman’s interests in spontaneous order between randomly interacting circuits and utilization of a modiﬁed model as an approximation to a mechanism of ‘‘ﬁxed’’ control pathways of epistatic systems. In the epistatic array model introduced below (which is loosely based on the Kauffman approach), the number of input epistatic functions is denoted Ki, while the number of output (phenotype) states is given by Kp. The usage of Boolean values to represent input and output states is as follows:

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Boolean value

Input function (gene)

Output (phenotype)

1 0

‘‘On’’ ‘‘Off’’ or negative allelic state

Viable output state Nonviable output state

A ﬂat (‘‘parastatic’’) system may be expressed by a multifactorial model in which the number of phenotypes is ideally Kp ⫽ (Ki ⫺ 1), and where differentials are quantitative in nature—with an essential temporal sequence (L 씮 R) from top regulator to a set of additive ‘‘multiple factors.’’ In Fig. 53 (the epistatic array), each row constitutes a possible epistatic function.

FIGURE 53 Epistatic array for a ‘‘ﬂat’’ parastatic system: phenotypes ( p1–p3) represent different combinations of ‘‘on/off’’ states of input genes (i2, i3) manifesting a simple additive relationship, with i1 having an epistatic regulatory function over i2 and i3.

A loosely epistatic system of the kind illustrated in Fig. 53 could be interpreted in either of two ways. First, it could express the fact that a range of similar phenotypes have much the same selectional value. Alternatively, there could be quite different ﬁtness values for each phenotype, either awaiting some adaptive response in the form of substitutional adjustment to the organization of a genotype in the adaptively negative situation, or else manifesting allomorphism in the positive (this differential being reﬂected in the output row in terms of 1 versus 0 values, as explained above). Epistatic arrays can more usefully describe epistatic relationships in terms of quasi-linear regulatory hierarchies in the context of ‘‘convex’’ systems with a more qualitative relationship between genes and phenotypic output. This situation can be most easily understood by adopting the simpliﬁcation of regarding a 0 input as being equivalent to a negative mutation corresponding to an ‘‘off’’ switch that is causal to misalignment. Consider the following simple analogy: The operational sequence used to make a hole in a piece of wood might be as follows: (i1) ‘‘measure coordinates,’’ (i2) mark center point, (i3) drill the hole. This sequence clearly cannot be varied, either by removing one or more inputs or by changing the temporal sequence,

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without occurrence of some misalignment. An ‘‘epistatic array’’ for the above fabricational sequence is shown in Fig. 54.

FIGURE 54 Epistatic array for fabricational sequence (see text), reading from left to right. Each 0 entry represents a missing operation, so that only the 1,1,1 input constitutes the ‘‘correct’’ operational procedure.

In Fig. 54, inputs (i1, i2, and i3) are analogous to genes controllant to a single morphogenetic trait in terms of a temporal interactive hierarchy. Mutation within the system (signiﬁed by 0 inputs) can then be regarded as being affected by changes to the regulatory system, such that alternative phenotypes only ﬁnd expression through mutation (the ‘‘wild’’ type thus being the 1,1,1 state). The above is broadly analogous to a ‘‘convex’’ epistatic system, with a single viable phenotype state among Ki2 possible outputs. This is a constrained system, in that the correct output (o1) speciﬁcally requires inputs i1–i3 not only to be ‘‘on,’’ but also to be activated in the correct sequence (i1 씮 i2 씮 i3), which is the true interactional hierarchy. All other outputs are nonviable, and differ inter se in a more qualitative than quantitative manner. The relationship between Ki and Kp in ﬂat versus convex epistatic systems (ideally with Kp ⫽ Ki ⫺ 1 in former, and Kp ⫽ 1 in latter, ignoring temporal shifts) is a function of the level of additivity in the system, with ‘‘ﬂat’’ and ‘‘convex’’ being opposite ends of a spectrum. Linear epistatic hierarchies of the convex kind have been found in real genetic systems: A linear interactivity cascade has been found to control vulval development in Caenorhabditis elegans, such functions having been discovered through study of an epistatic relationship between gene mutations (see Gerhart and Kirschner, 1997, for a summary; also Wolpert et al., 1998). Similarly, the relationship between regulatory genes controlling the developmental sequence for Drosophila (Fig. 55) is essentially an epistatic structure (see Fig. 48). As stated at the outset, the above model is a simpliﬁcation. However, the epistatic array approach nevertheless serves to illustrate certain fundamental aspects of interactivity between regulatory genes with a morphogenetic func-

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FIGURE 55 Broad epistatic relationship for Drosophila genes.

tion. Most signiﬁcantly, the Boolean model begins to reﬂect the architecture of an epistatic system when (as proposed here) the actual temporal activation sequence for all inclusive gene loci is made explicit. Bearing in mind the incompleteness of the switch model and the problems of nonlinearity already discussed, we must clearly guard against acceptance of Boolean functions as a complete explanation of how epistatic systems work. In the examples used, we may assume ideally that the 1/0 score in an epistatic function could be an ‘‘on–off’’ condition for activator/repressor regulatory genes controllant to each ‘‘operation’’ in sequence, and analysis on this basis does serve to illustrate certain broad features concerning the manner in which many gene–homeostatic hierarchies appear to operate. The signiﬁcance of epistatic functions lies, not in providing an instant reinterpretation of Mendelian genetics in terms of explicit biochemical and developmental pathways, but in offering a useful rationale for analysis of mutational activity leading to major evolutionary change in realization of adaptive potential. Important questions here relate particularly to the role of canalization of development and also to the dichotomy existing between ‘‘bottom-up’’ versus ‘‘top-down’’ mutational regimes for the generation of morphogenetic transformations (see next chapter), and these themes will be expanded on when we come to consider how more complex homeostatic systems have evolved in the face of iterative mutational change. The value of the epistatic array model thus lies in illustration of certain fundamental properties of regulatory control systems as they relate to the architecture of adaptive capacity and potential. Most signiﬁcantly, this model perhaps also serves as the nearest equivalent to the Mendelian model we have for the developmental perspective of genetic activity and interactivity.

The Panstatic System, Adaptive Capacity, and Adaptive Potential Integrated activity at the epigenetic level implies a high level of homeostatic control over determination factors affecting a given structure integral, and this mechanism is exempliﬁed by regulatory genes in epistatic systems. How are the Boolean functions of synparametric determination factors linked to other determination systems, given the interactive modular array architecture of morphogenesis? An epistatic system may determine a single parameter within a structure unit, and this system is ‘‘endogenously homeostatic’’ (i.e., modular) in the sense of integration of n morphogenetic factors interacting to control a single phenotype parameter, such as, for example, the shape of the insect occipital foramen. However, in addition, other determination factors must link to other parameters of head structure (differentiation of the eye, for example), and these may, in one sense or another, also manifest some degree of interaction with

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adjacent morphogenetic trajectories at certain points during development. A complex structure integral may have many such parameters, each determined by an epistatic system, and these will manifest some element, both of mutual autonomy and of interactivity in the context of the regulative model of development (see Chapter 9). A set of quasi-autonomous epistatic systems may therefore belong to a larger epigenetic structure: in Fig. 56, genes are represented by A, B, C, . . . , and the epistatic relationship ⬎e between genes can then be ﬁgured A ⬎e B ⬎e C ⬎e . . . as a simple temporal hierarchy. It is also useful here to denote 움-allotropes, etc., in the proposed manner (see above) as A ⫹, B⫹, . . ., so that two epistatic systems partially bonded by transcriptional allotropism can thus be represented as follows: 兵A ⬎e B ⬎e C . . . 兵D ⬎e A⫹ ⬎e E . . . This link between quasi-autonomous modules acting as epistatic systems deﬁnes a panstatic system equivalent to n modules that are linked by a level of interactivity that will be less than that encountered between member genes of any of its constituent epistatic systems (that is to say, it is essentially a ‘‘loose alloparametric system’’ in which different modules manifest a considerable degree of mutual autonomy). A generalized (and much simpliﬁed) panstatic system may have the form shown in Fig. 56.

FIGURE 56 Schematized view of a generalized panstatic system, with earlier development showing ‘‘co-option’’ of the A gene at two temporospatial loci of transcription. There is also translational ‘‘cooption’’ of the D gene in later development (DT ). Earlier acting genes (at the top of the cascade) are presumed to deﬁne larger ontogenetic morphogenetic coordinates.

Panstatic systems thus express the intersect between n quasi-autonomous epistatic systems, and they may also reﬂect wide-ranging homologies in the

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genotypic strategies of adaptive systems in general. There are, for example, certain ‘‘conserved’’ supratranslational regulator genes at the upstream end of the panstatic system which affect developmental activity in several metamerically related units of structure, even in very remotely related genotypes (cf. Drosophila homeotic genes): Both ﬂy and vertebrate limbs appear to be formed through a similar developmental pathway; sonic hedgehog mutations cause similar ‘‘mirror image’’ deformations of wing and foot in the chick as in Drosophila (see Gilbert, 1997, after Ingham, 1994). Slack et al. (1993) call the basic body plan of bilateral phyla ‘‘the zootype,’’ a concept based on the conserved function of homologous genes of the Hox cluster which determine the anterior–posterior axes of these phyla. At a higher level in the developmental hierarchy then, a panstatic system contains n epistatic systems affecting the same structure integral, and this complex may reach its widest domain as we approach earlier developmental stages. In general terms, a panstatic system may tend to be largest during early development and smaller at later stages, since the extent of TRANS-acting interactivity generally seems to diminish from the ontogenetic to the phenogenetic phase. In higher organisms, there must then be n epistatic systems expressing some degree of mutual modularity according to the diversity of biophysical paradigms operating within separate morphogenetic trajectories, this autonomy tending to break down as we approach early development: The BX-C (bithorax complex) of Drosophila, for example, reﬂects modular interactivity in the panstatic system with respect to the major coordinates of positional information, whereas intracompartmental regulators must unleash a cascade of more narrowly functioning epistatic genes involved in morphogenesis of speciﬁc phenotype structures. In summary, a complex morphogenetic trajectory must incorporate n epistatic systems in sequence, these tending to be linked, particularly at earlier temporal horizons. The proﬁle of a single morphogenetic trajectory passing through embryogenetic or ontogenetic loci toward the phenogenetic state must consequently be controlled by a set of linked yet at the same time quasiautonomous systems acting to circumscribe each locus of translation in succession. Mutational events in such gene systems are obviously of special interest for investigation of the mechanisms whereby realization of adaptive potential leads to anagenesis, and the degree of mutual autonomy expressed by different components of panstatic systems must have special relevance to the facilitation of such modes of morphogenetic transformation as allometric modulation and heterochrony (see Chapter 16). Implicit in the above scenario is the certainty that the hierarchy in homeostasis within and between panstatic and epistatic systems is connected with ‘‘rigidity/ﬂexibility’’ in the coordinates of adaptive potential. In general, modular inhibition is likely to be greatest at earlier horizons, and especially at the phylotypic stage (see Chapter 9), so that realization of adaptive potential would then most probably occur in the domain of mid-level regulators downward.

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Allelomorphism and Adaptive Capacity in the Panstatic System Allelomorphism is clearly concerned with bifurcations in the genetic control of development, correlated with the presence of asymmetry in the chromosomal organization of genetic material. Thomson (1988) considered that switch genes could be either effects of a single allelic substitution (as perhaps in Drosophila eye color, for example) or else the crossing of a threshold in which addition of one further polygenic allele following accumulation of large numbers of genetic differences collectively affecting the trait in question creates a switch effect. Most evolved allelomorphisms seem likely to be of the former type (see Chapter 13), whereas certain categories of quantitative continuous variation seem more likely to belong in the later category. So far as the architecture of the epistatic system is concerned, allelomorphism has to be envisaged as an alternative state existing at one or more input loci, such that the outcome with respect to a given phenotype trait is not buffered out in the context of interactivity with other inputs.

NONGENETIC DETERMINATION FACTORS One central dogma that has been proposed in developmental genetics is that determination and differentiation are ordered through differential RNA transcription, this constituting a general strategy in description of the way in which genes control development. The activity of epistatic systems must not, however, be assumed to be universally homeostatic for all phenotype structure units, in the sense of constraining development toward the goal of achieving a single output phenotype with respect to an exclusively genotypic input. On the contrary, one function of adaptive capacity must be that gene-developmental systems receive inputs, not only from genetic sources, but also from other factors arising in both internal and external environments, through the intermediary of a variety of metabolic functions. Epistatic systems must therefore be open to the inﬂuence of nongenetic factors, including extrinsic ones arising in the external environment and interacting with the genetic system. Many ‘‘nongenetic’’ determination factors (whether of internal or extrinsic origin to the organism) are endogenous metabolic products or exogenous environmental stimuli that affect determination by impinging on epigenetic interactivity after the manner of TRANS-acting determination factors. Consequently, panstatic systems often have the capacity to incorporate penetrance of nongenetic determination factors of quite diverse origins (Fig. 57). Nongenetic determination factors thus link to internal communications systems, some originating in the external environment yet nevertheless still functioning through the intermediary of endogenous determination factors, and the ambient state of many epistatic systems may be that of dialogue with inﬂuences of this kind. Here, we encounter a second category of TRANS-acting determination factors, arising extrinsically to the genetic system itself, which shows that the so-called epigenetic environment incorporates both higher translational gene products and other exogenous signals having an analogous function in development:

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FIGURE 57 Two nongenetic determination factor inputs (NGDF1, NGDF2) of internal and external origin, respectively, affect two separate parameters (shape and size).

The classical heritability equations show that environmental factors have a variable (and sometimes large) effect on development, for example, in the inﬂuence of nongenetic determination factors in the blurring of discontinuities in continuous distributions of polygene controlled parameters. This observation clearly carries both adaptational and probabilistic interpretations.

The Role of Nongenetic Determination Factors in Adaptive Capacity and Potential Hormones can function as nongenetic determination factors (often in interaction with external stimuli or via feedback from metabolic activities generally): Steroids (for example, estrogen, ecdysone) are examples of nonproteins which regulate gene activity, especially linking nongenetic determination with phenogenetic activity. Ecdysone in insects is known to control gene switching (Ashburner, 1971) and affects cell motility and migration. Karim et al. (1993) have shown that early genes in the ecdysone cascade activate more than 100 later ones.

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The medium of developmental control for parameters of morphogenesis inﬂuenced by nongenetic determination factors originating in the external environment must lie predominantly with genetic epistatic systems, which in turn express evolved differential labilities to nongenetic factors of either extrinsic or endogenous origin. Panstatic systems thus contain labilities, both to internal metabolic and to external (including nonbiotic) stimuli. Control over development is thus not limited to direct genetic activity. However, it is better to say that determination systems may evolve a capacity to interact with nongenetic determination factors at certain levels, since ‘‘lability’’ is itself genetically determined. In this role, hormones are particularly concerned with coordination of developmental events, and this is clearly linked to their much greater capacity for distance activity and speciﬁc targeting propensities compared to the greatest functional domain of a morphogen, as well as to the link between endocrine systems and external environmental conditions. Closely linked to the question of level of lability to nongenetic determination factors is the phenocopy phenomenon, whereby the effect of many gene mutations can be mimicked by exposure to diverse nongenetic stimuli (see below). Nongenetic Determination Factors and Random Interactivity As with environmentally determined traits in general, it is evident that most determinative activities of a phenocopy (where the effect of a gene mutation can be mimicked by a nongenetic determination factor) are probably identical to those of genetic determination, only one or a few points in a morphogenetic trajectory being labile to such inﬂuences. This could be due to the fact that regulator sites that are prone to the inﬂuence of such stimuli are also those that are especially labile to the effects of mutation in many loci in different sectors of the genome. In terms of gene function, therefore, nongenetic determination factors in general must equate with regulatory gene switches expressing relatively speciﬁc translational effects on morphogenesis (for example, controlling quantity or timing of product synthesis). Such factors can affect all translation levels, and they may often simply comprise an ‘‘on 씮 off’’ switch transition that is facilitated by some manner of metabolic disruption. Determination is also an iterative process, so that nongenetic determination factors really only need intervene at a single point in the determination cycle. The real differences between genetic and nongenetic determination factors are then as follows: • Stimuli for genetic determination factors arise directly through gene action (whether at primary transcription or higher translation levels), and are therefore fully intrinsic to genetic systems. They are thus essentially the direct protein products of gene translation. • Stimuli for nongenetic determination factors are extrinsic to developmental systems, arising either as internal products of metabolic activity or in the external environment; they are not simply ﬁrst level protein products of primary translation. Each category of nongenetic determination factor thus plays a role in the control of development, through the intermediary of interaction with translational

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communications systems acting in the determination cycle. To what extent is randomization of epigenetic interactivity involved in this? The nongenetic determination phenomenon in general (and the phenocopy mechanism in particular) may seem perhaps to diagnose a fundamentally random interactivity/nonspeciﬁcity strategy for genes in the epigenetic environment, while at the same time, the frequently negative aspect in the inﬂuence of unfamiliar nongenetic determination factors conﬁrms the existence of a fundamentally deterministic strategy in epistatic systems. Nongenetic determination factors cannot therefore be taken as evidence that developmental activity in general is open to diverse determination stimuli, other than by virtue of actively evolved labilities, or to lack of evolved stability (as in the case of ‘‘shock’’ factors in the phenocopy mechanism). The activity of nongenetic determination factors thus conﬁrms the linear– allotropic model of epistatic systems, while at the same time in no way implying that ‘‘all-genes interactivity’’ is the norm. These conclusions must obviously be of signiﬁcance for an understanding of adaptive potential in evolution. Phenotype Plasticity and Primary Adaptive Equilibrium Where environmental plasticity lies in the domain ⱕt (i.e., within the life span of an individual), adaptive plasticity cannot be attained through frequency changes in allelomorphic genes. However, this scenario also indicates a demand for an adaptive response (heritable or otherwise) of some ﬂexibility, thereby linking to the question of the role of nongenetic determination systems in adaptation and evolution. Clearly, developmental systems are often structured so as to respond to hormonal and exogenous determinative inﬂuences, particularly through the expression of simple scalar transformations, and this must in turn have origins in a selection interface appertaining to adaptive equilibrium (see Chapter 5). The dialogue between certain nongenetic determination factors and developmental viability is thus an important inﬂuence on the adaptive capacity of a gene pool, with special reference to the evolved state of primary adaptive equilibrium, and environmentally ideal conditions are also necessary for optimum success in development, as observed with many phenoplastic nongenetic determination factors that are linked to such fundamental environmental variables as temperature and nutrition. The logistic component of the adaptive response and phenotype plasticity will thus tend to predominate as solutions to highly variable aspects of the external environment. There is thus a physiological, behavioral, or phenotype adjustment (or logistic adjustment in genotype frequencies) in the intrageneration time frame: This is clearly evident in the known adaptive signiﬁcance of phenotype plasticity in many plant species (as with Plantago), and in animals in such parameters as adult body size relative to larval nutrition in many parasitic wasps. Environmentally determined parameters may thus express continuous distributions of closely topologically related adjacent morphosystems as a component of adaptive capacity in the form of phenotype plasticity. This will be shown to have important connotations for adaptive potential also, when we come to consider the topology of changing epistatic systems, in that, for exam-

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ple, modularity manifested in epigenetic determination mechanisms may create that substrate which facilitates that movement between ‘‘adjacent morphosystems’’ seen in allometric transformation and heterochrony (Chapter 16). In consideration of the relationship between nongenetic determination and the nature of the selection interface, it is furthermore essential to see that this mode of determination does not in fact constitute a true ‘‘nonheritable differential,’’ since, as we have seen, nongenetic determination is in reality permitted only by the evolved homeostatic structure of epistatic systems, and consequently ultimately forms a functional and heritable component of adaptive capacity. This underlines the artiﬁciality of the ‘‘chicken-and-egg’’ question often linked to nongenetic determination in the context of Lamarckian evolution: Bradshaw (1965) stated that ‘‘in order to ﬁt the concept of plasticity into our framework of evolutionary principles, we need to know the amount of genetic variability for plasticity that is available in natural populations, its genetic control, and the ease with which it can be selected. . . . At some stage in the evolution of a plastic response randomness in direction and extent must be replaced by ﬁxation.’’

TOWARD A GENERAL MODEL OF DEVELOPMENT The panstatic system described above (inclusive of nongenetic determination factors, both endogenous and extrinsic) constitutes a useful general framework for an understanding of genetic and other determinative activity as it affects development. With regard to the endogenous nongenetic component, we are concerned especially with the action of distance morphogens arising in the endocrine system, usually following the completion of gastrulation–neurulation. This apparently complete framework does not, however, describe the whole developmental program, which must also incorporate instructions linked to the way growth and morphogenesis are organized: Wolpert (1990b) has outlined a scheme which involves a sequence of interlinked ‘‘position’’/‘‘go’’/‘‘stop’’/‘‘stay’’ instructions for programmed morphogenetic activity (also elaborated and illustrated by Arthur, 1997). Our present understanding of genetic control over development does not allow a fully comprehensive exposition of this system as yet, although it is at least now evident that the ‘‘stop’’ instruction is linked to a gradient mechanism, rather than to a cell count (Lawrence, 1992). The Boolean network for the regulatory switch strategy in an epistatic system clearly cannot seek to describe the signaling mechanism of the developmental program, nor does it reﬂect the feedback control loops which must form an integral part of any such system. Only a combined model incorporating the Boolean network and panstatic system models in the context of a genetic control strategy linked to the Wolpert developmental program model has the capacity to provide a more complete picture. This model also needs to include

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those propensities of cell surface molecules which affect adhesion qualities (regarded by Arthur, 1997, as an important link between the one-dimensional genetic code and three-dimensional coordinates of the whole organism), and we also have to incorporate properties of the cellular cytoskeleton (i.e., where signals cause a cell to change shape or to move, the cytoskeleton is at least partly involved; see Arthur, 1997) along with those mechanisms which manifest control over cell motility and migration. Additionally, the true role of Newtonian determination factors (especially at the tissue level and above) is but little known at present, yet this must constitute an important part of any complete model of development. Despite the incompleteness of our picture of genetic control over development, the existing fragments are nevertheless sufﬁcient for an understanding of how adaptive potential links, both to the framework of development and to the evolutionary process. However, we must frame further discussion in the context of known effects of gene mutational activity on morphogenetic coordinates, rather than on any actual knowledge of how all levels of coordinates systems of the adaptive paradigm are modiﬁed. In fact, factors linked to parameters of the fabricational paradigm are presently better understood than the latter, and some aspects of the discussion must inevitably involve speculation as to the validity of analogies between known ‘‘upstream’’ factors and other, lesser known systems operating ‘‘downstream’’ from the earlier gene-developmental cascade, also bearing in mind two conclusions of this and the previous chapter: (1) given the considerable degree of temporal modularity that exists between early ontogeny and phenogeny, adaptive potential will tend to be realized at or beyond that point at which TRANS- gives way to CISacting determination, and (2) this will mainly concern mid-level regulators of supratranslational status in epistatic supergenes. In Drosophila at least, this seems to be subsequent to that juncture at which the Hox genes are activated. These cannot, however, be presumed to constitute general ‘‘laws,’’ given the wide disparity between different developmental systems, comparing one lineage with another, and given evidence for rare events when more deeply rooted zones of developmental change must have been invoked.

MAIN POINTS FROM CHAPTER 11 1. A true gene unit exists only where nucleic acid translation leads to some function manifested in metabolism or development. 2. It is useful to distinguish between infra- and supratranslational genes, affecting substructural and morphogenetic functional domains, respectively. 3. The supergene constitutes the fundamental genetic unit. A typical supergene contains an integrated set of regulatory and structural genes controllant to a single structure unit or integral (or substructural parameter) of the phenotype. 4. Adaptive capacity is especially linked to infratranslational genes expressing allelomorphism, whereas adaptive potential lies particularly with regulatory supergenes of the supratranslational kind. 5. Interactivity in the epigenetic environment occurs via a signaling system linked to intercellular determination factors of the CIS- and TRANS-acting

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kind. Positional information constitutes an important element in the TRANS domain, and is believed to be interpreted by more ‘‘downstream’’ genes lying closer to the CIS mode. 6. The allotropic structure of much of the genome is of considerable signiﬁcance for adaptive potential, owing to links between the domain of gene expression and developmental modularity (which latter need not be the same thing as selectional modularity). This is especially true with respect to ‘‘concerted evolution’’ arising through translational allotropism. 7. The genetic basis for adaptive capacity and potential is contained in the linear–hierarchic architecture of epistatic systems, generally in allelomorphic/ substructural and in ‘‘ﬁxed’’/morphogenetic supergenes for adaptive capacity versus potential, respectively. 8. The interactivity of supergenes within a single epistatic system can be approximated by a modiﬁed Boolean network system. 9. In the wider view of control over morphogenesis, the panstatic system contains n linked yet quasi-autonomous epistatic systems. 10. The Hox genes are supratranslational regulators lying at the apices of panstatic systems, acting as selector switches over downstream genes involved in segmental development. 11. The genetic domain of adaptive potential probably tends to lie with ‘‘mid-level’’ supratranslational regulators in the epistatic hierarchy, where these relate to the TRANS/CIS intersect zone in the developmental system. It is thus divorced from maternal (and the earliest zygotic) morphogen producing genes, being located in supratranslational loci just beyond the homeotic level to well ‘‘downstream’’ of that domain. 12. Nongenetic determination factors must be seen as forming an integral part of the panstatic system. These constitute signals arising externally to the genetic system (including those exogenous to the organism itself ), but nevertheless interacting with epistatic systems at higher translation levels. 13. Nongenetic determination factors are of special importance for primary adaptive capacity, and they also create the modularity substrate for ultimate realization of adaptive potential.

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MUTATION AND REALIZATION OF ADAPTIVE POTENTIAL

It is evident that the architecture of a genetic system may change entirely within the context of adaptive capacity, via recombination of preexisting allelomorphic genes alone. Accordingly, novel gene mutation in the context of allelogenesis (see Chapter 8) must be the ultimate basis for realization of adaptive potential. Given that mutation is clearly essential for true evolutionary change in adaptive systems, to what extent does this imply the presence of an element of randomization impinging on gene-developmental systems? The genetic systems of morphogenesis are not static structures, but must express complex dynamics as a result of mutational change. The effects of mutation tell us much about the way epistatic systems (and supergenes in general) must buffer epigenetic interactivity against the inﬂuence of the negative effects of randomization. Yet conversely, adaptationally positive changes arising from the latter must also come to be incorporated into the gene pool.

MUTATION AND THE EPIGENETIC ENVIRONMENT We could begin this analysis by looking at the nature of mutation of a unit gene in isolation from other events. However, it is ultimately more instructive to look at the reciprocal effects of gene mutation with respect to the wider epigenetic environment,* and this must be the principal target of discussion. * We are continuing to use the term ‘‘epigenetic’’ in the sense of signals passing between cells and tissues ‘‘above’’ the level of primary transcription or translation.

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The Nature of Gene Mutation Mu¨ller (1932) proposed a classiﬁcation of mutations which has only just come into more general usage, since recent conﬁrmation (and some reinterpretation) of certain aspects of his system through molecular analysis (see Sang, 1984, for a reappraisal). Mu¨ller’s amorph (no effect at phenotype level) and hypomorph (reduced output) mutations are now believed to represent structural damage to synthetic genes, while his hypermorph mutants have been linked to mechanisms such as gene ampliﬁcation, which has been shown to occur through unequal crossing-over (Schimke et al., 1977). Much of the Mu¨ller classiﬁcation is perhaps mostly relevant to infratranslational (synthetic) genes. However, of special interest in the present context are his neomorph mutations (those expressing some output in the phenotype that was absent in ancestral adaptive capacity), now interpreted as being particularly due to changes in regulatory function. It is now also believed that many neomorphs apparently involve regulation of numbers of genes. It is possible to see, at this stage, that some apparent neomorph mutations could in reality constitute recurrent allelic states. From this standpoint, it will be useful for the general discussion of apparently neomorph mutations to adopt the term apomorph (⫽ a state that is new in relation to the extent gene reservoir but could be recurrent within a larger time frame). Following on from our identiﬁcation of regulatory genes as the source of morphogenetic change, it is valuable to examine the different ways in which genes of this kind may undergo mutational change. Arthur (1997) outlines the overall architecture of gene mutation in developmentally active supratranslational loci, the important features being altered chromosomal location, altered base sequence, number and identity of cis controlling elements, temporospatial expression pattern, and also (very signiﬁcantly) gene duplication (see below). Continuing to follow Arthur’s argument, the two main features of mutation in a developmental gene are interactional architecture (changes to incoming or outgoing signals) and temporospatial expression plus degree of mobility and durability of gene product. Interactions are probably often altered in groups, and various effects of temporospatial changes include many end points that can be reached in several different ways. Arthur also gives a simpliﬁed visual representation of the cascade of effects of change in the temporospatial expression of a single gene mutation, of which the following is a summary: Spatial changes Temporal changes (Original) Size change Shape change Spatial shift Repetition

(Original): Diminished: Extended: Shifted: Intermittent:

⫹ ⫹ ⫹ ⫺ ⫹

⫹ ⫺ ⫹ ⫹ ⫺

⫺ ⫺ ⫹ ⫹ ⫹

How does the above system interdigitate with the way in which major coordinates of ontogeny are known to be laid down during early development?

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Wolpert (1983) states that positional signal and positional values are apparently conserved during evolution (as is evident, for example, from transspeciﬁc grafting experiments between chick and mouse) and that consequently, it must be interpretation that changes. The manner in which gene mutation is translated into ‘‘interpretation of the positional information system’’ is, however, as yet unclear, and Arthur’s gene changes could, for example, lie either in positional information itself or (following the Wolpert argument) in the way such static coordinates are interpreted: French (1983) has suggested that the gap genes known in Drosophila could have had the effect of shifting the interpretation of positional information (f, Garcio-Bellido, 1977), although it is generally admitted that there are difﬁculties with this hypothesis. Clearly, mutations must alter instructions in the developmental program for morphogenesis. How does this lead to realization of adaptive potential, other than in the limited role of quantitative change to preexisting parameters? Thomson (1988) has pointed out that relatively simple changes in external conditions surrounding mesenchyme migration or epithelial folding could have a major effect on morphogenesis, as will changes in rates of cell division within, or in recruitment to, mesenchymal blastemata. Following Thomson’s observations, it would appear now that these mechanisms seem perhaps likely to be invoked only once certain major coordinates have already been deﬁned during earlier ontogeny (see the comments of Horder concerning the probably greater importance of inductionlike mechanisms in determination of phenotype form in Chapter 10, also the Wolpert hypothesis). Ambros and Horvitz (1984) investigated genes with a morphogenetic function in C. elegans, ﬁnding that certain morphogenetic mutations tend to be ‘‘heterochronic,’’ affecting the timing of cell division. The way in which gene mutations affect realization of adaptive potential in expansion of the morphogenetic landscape can, at least in part, be described by examples such as the above. However, as we shall see, for a more complete picture to emerge, it will be necessary to go on to consider mutation in the wider context of the entire epigenetic environment.

Mutation, Translation Level, and Pleiotropism It is instructive to look at certain of the broader features of modes of mutation. Useful links can thus be made between the main functional types of genes, the probable nature of mutations linked to them, and the principal mutational phenotype changes associated with particular evolutionary activity in the context of realization of adaptive potential. In this endeavor, we shall be particularly concerned with the activity of nonmonotropic genes, owing to a probable link between allotropic gene expression and realization of complex adaptive potential, namely, in the context of classic pleiotropism:

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Genotype in which mutation occurs

Phenotype effect

Eurytropic–infratranslational

This category of genes should produce mutations with universal effects on the phenotype: Hypermorphic change to metabolic product of housekeeping genes giving rise to allozymes, for example

Allotropic–infratranslational

Here, we might expect to ﬁnd mutations of a more site speciﬁc kind: Change to secretory product of a specialized cell type

Positively selected infratranslational mutations in general may often behave as hypo- or hypermorphs (following Mu¨ller) in allelomorphic systems (for example, color changes and minor substructural effects), so that this particular classiﬁcation system perhaps relates best to the activity of synthetic genes which frequently enter adaptive equilibrium, rather than necessarily forming increments of anagenetic evolutionary change. Many infratranslational genes are, of course, those which continue to function in the adult phenotype. The pleiotropic effects of infratranslational genes probably also tend to be restricted to that domain. Clearly, supratranslational genes are those involved in large scale morphogenetic activity, and it is this category that was the principal focus of Arthur’s analysis (see above). How are supratranslational genes affected by mutation? Genotype in which mutation occurs

Phenotype effect

Eurytropic–supratranslational

Some mutations linked to control of growth may belong in this category: Here, the predictions of Arthur’s system may perhaps be fulﬁlled as (e.g.) with respect to change in absolute size.

Allotropic–supratranslational

As with infratranslational genes, mutations in this category will be more site speciﬁc, also tending to express pleiotropic effects: Mutations of Kruppel have effects in the median segments, ventral ganglia, tracheae, gut, and Malphigian tubules.

Although mutation clearly constitutes the means through which adaptive potential can be realized, this may often create problems of negative feedback arising from partial randomization of epigenetic interactivity. The stochastic nature of mutation is manifested most signiﬁcantly in the allotropic and epistatic planes, owing to the fundamental architecture of genetic and epigenetic regulation systems, namely, as pleiotropy, which has different evolutionary connotations at different translation levels: According to Gerhart and Kirschner (1997), those proteins implicated in pleiotropic activity may be those that have been optimized for multiple interactivity in the ﬁrst place.

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The outcomes of mutational activity are predictably different for infra- versus supratranslational domains, as also for monotropic versus eurytropic and allotropic supergenes. Quantitative endogenous change may predominate in substructural gene products, whereas more dramatic manifestations of pleiotropy may tend to be expressed in the morphogenetic domain. It is axiomatic that purely negative pleiotropic effects are more likely to occur with novel qualitative as against quantitative changes, and with large rather than with small scale phenotypic effects. Epigenetic homeostatic systems seem likely to be structured to allow some degree of plasticity within the domain of quantitative variation, and multifactorial genetic systems are likewise contoured around ‘‘adjacent morphosystems.’’ The eurytropic/allotropic basis of much genetic activity at all translation levels underlines the universality of mutational pleiotropism, and the main point of interest for realization of adaptive potential must lie here in a fundamental capacity of pleiotropy for expansion of morphogenetic potential (see Chapter 7), an event that will clearly be of speciﬁc concern with respect to the supratranslational domain. Neomorphic change may then also constitute neotropism (see below), thus entering the qualitative dimension in mutational change to morphogenetic systems. The initial (lower translation level) effects of major mutations are perhaps self-evident. However, it is much more difﬁcult to understand reciprocal effects later in the course of a developmental trajectory, as they come to affect other developmental trajectories—and in terms of morphogenetic effects at a diversity of loci of differentiation, growth, and morphogenesis. In general, however, the external effects of endogenous modulations in a morphogenetic trajectory may relate to a diversity of functions of the induction–competence kind in translational allotropism (see previous chapter). Endoclonal changes may thus possess the capacity to induce exoclonal ones, especially in adjacent developmental trajectories. Evidence from known mutations suggests that pleiotropic activity may indeed at times demonstrate the capacity to transgress the functional boundaries between modular developmental trajectories, so that reciprocal effects may pass between different structure units, and even between phenoand ontogenetic modules. The accumulation of iterative negative pleiotropic effects (especially in mutations affecting morphogenesis) must be concerned particularly with the endogenous selection interface, namely, in developmental viability, so that external pleiotropic inﬂuences must often tend to impinge on the normal development of a given structure unit. Consequently, homeostatic adjustment must be an ongoing process, even for a ‘‘static’’ component of structure.

Pleiotropy, Protropism, and Neotropism We have so far discussed a relationship between allotropic gene expression and pleiotropy, without having actually deﬁned the latter term. Pleiotropy is seen here as the heterogeneous corollary of several mechanisms, and of special interest at this juncture is the related domain of neotropism. Looking at classic pleiotropism from the standpoint of allotropic gene expression, it is possible to interpret the array of effects arising from a single

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gene mutation as follows (see Fig. 58). First, it will be useful to restrict the term pleiotropy to the purely negative effects of mutation. Pleiotropism can now be seen to arise from two possible sources in mutation: (a) from preexisting allotropic gene expression or else (b) as an actual extension to the original allotropic domain; this latter phenomenon is linked to neotropism (see below). ‘‘Latent’’ or 움-pleiotropism thus arises from preexisting genetic allotropism. If a gene is allotropic, a mutation will naturally tend also to express multiple effects in the phenotype, and these may be interpreted as ‘‘pleiotropy’’ especially in the 웁 and 웂 domains of allotropism. 웁-Pleiotropism occurs where negative effects arise in the neotropic domain, as an extension of the original domain of allotropism. The ‘‘substrate’’ of a regulatory gene may thus expand following a neotropic path: Carroll et al. (1995) believe that the homeotic genes of winged insects originally concerned only segment identity or neural patterning, only later playing a part in wing formation (see also Gilbert, 1997). Where positive effects arise from any mode of mutation, these can be termed protropes if originating within the domain of preexisting 움-allotropism, or neotropes, when arising in the context of a new trajectory. True pleiotropes are then the deleterious effects of the same mutations. Within 움- and 웁-pleiotropy, we may also choose to discriminate between ‘‘true’’ and ‘‘false’’ pleiotropisms, the ﬁrst generally arising from multiple transcription (effectively ‘‘pleiotranscriptional’’) and the second originating in translational allotropism (‘‘pleiotranslational’’). These domains have also been termed direct versus relational pleiotropism, respectively (see Futuyma, 1998). Neotropism must also be compared and contrasted with the concept of neomorphism. The latter is clearly not in fact restricted to neotropic gene expression,

FIGURE 58 Domains of protropic, neotropic, and pleiotropic gene expression.

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since any novel mutation can be a neomorph. Therefore, a leading effect neomorph state could be either protropic or neotropic in origin. The two domains of pleiotropism (움, 웁), via protropism and neotropism, can be shown to have particular relationships to patterns of change in evolution, in that any positively selected mutation may obviously also carry n pleiotropic effects (see pleiophorism below). Mutation, the Selection Interface, and Pleiotropism As we have seen above, it is evident that the different effects of a single gene mutation cannot be assumed to all carry the same selectional value. Some may be deleterious and others may carry some selective advantage. Clearly the status of protrope or neotrope as against ‘‘pleiotrope’’ is dependent on the selection interface for the array of effects of a given mutation. Mutation can alter the selection interface of a set of allotropes (or create a new domain of allotropic activity), such that a new selectional differential between different members of the mutational array so created is established. The leading effect phenon is in this context, simply that protrope or neotrope carrying the highest selective advantage. There is thus a selectional hierarchy between different multiple effects of a single gene mutation, and some proportion of mutational effects carry a positive selection interface, either in the domain of preexisting epistatic systems or due to actual expansion of allotropism. However, we must also beware of a quite different category of ‘‘leading effect,’’ in that there are two possible pleiotrope hierarchies for any given mutation expressing a multiplicity of effects: 1. The phenotypic hierarchy: The leading effect here is simply that with the greatest degree of phenotype expression (and quite probably that most likely to most readily be observed in experimental studies). This hierarchy is based on purely quantitative considerations in terms of the visible phenon. 2. The selectional hierarchy: The leading effect is now that with the greatest positive interface with selection based on relative adaptive values, thus expressing a qualitative perspective (which may well be very difﬁcult to identify in actual practice!). The selectional pleiotrope hierarchy is clearly the focus of evolutionary interest and was, of course, that chosen in the preceding revision of terminology. The effect with the greatest positive selection interface is thus seen as the true leading effect of a mutation, with respect to realization of adaptive potential. Pleiotropic Balance and the Pleiophore Principle What happens to pleiotropic states linked to mutations carrying positive protropic or neotropic effects? Given that large scale pleiotropic effects may arise, what overall effect can be supposed to lead to the situation whereby a range of accessible ‘‘adjacent’’ morphosystems may reach realization in the phenotype? It is of fundamental importance to see that the net effect of a given mutation depends on the sum of all positive and negative effects, including not only the leading effect, but also the total depression in ﬁtness arising from all negative

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pleiotropes of the mutation in question. Only on this basis can we attempt to understand how a mutational effect may pass from membership of one epistatic system to that of another (or why a majority are in fact excluded from any such ‘‘cross over’’ behavior). In the most simpliﬁed scheme, a gene mutation has two effects, one positive and one negative. The leading effect will be deﬁned here by that factor manifesting the greatest input to overall selective value, thus deﬁning the principle of pleiotropic balance, which states that no mutation can be positively selected unless the net ﬁtness of the array of multiple effects is greater than that of the nonmutated genotype. The origin of neotropic systems, in particular, must therefore lie with selectional balance between positive effects and negative pleiotropes. Many potentially useful mutations may thus be rendered ‘‘negative on balance’’ if there are many negative pleiotropes, and there must be a W product that describes selection acting on two competing alleles, in terms both of their leading effects and also of their pleiotropic effects. This is, of course, the W value which may be observed in Nature, which should thus be understood as being potentially a composite entity. This is of great signiﬁcance in the context of truly neomorphic anagenesis. The above scenario can be illustrated as shown below. Interpretation of the diagram depends entirely on selectional balance. If A and B are leading effects (protropes or neotropes), then C may be a pleiotrope. However, if C is the leading effect, then genes A and B have an interactive function for trait C and phenotype states A and B could then be pleiotropic effects of those genes. An epistatic system may thus originate (or change), partly through multiple mutational effects.

FIGURE 59 Pleiotropic balance: gene mutation A affects phenotype trait A, while mutation B alters phenotype trait B. Both A and B also affect trait C (see text for discussion).

It is thus not possible to consider mutational effects on the phenotype as being entirely limited to speciﬁc temporospatial sites, excepting perhaps for

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the most closely constrained major genes. Furthermore, we cannot consider any developmental parameter as being entirely immune to negative inﬂuences, owing to the wide domain of pleiotropic activity. Most pleiotropes probably outweigh the beneﬁt of any protropes or neotropes with which they are associated, in the context of pleiotropic balance, so that the mutation in question is consequently selected out. However, whenever there is positive pleiotropic balance in the context of an isotropic selection interface, the neotrope or protrope may then ‘‘carry’’ certain negative components as pleiophores: Arthur (1997) similarly argues that in general, earlier acting genes have more major effects, but an early acting gene may be selected if it has net increase in ﬁtness, thus allowing time for later modiﬁcation of deleterious effects. The hypertrophic mandible of some ditrysian lepidopteran pupae is one possible example of a pleiophoric effect (see Chapter 21). Pleiotropy in Adaptive Equilibrium ‘‘Pleiotropism in adaptive equilibrium’’ is one possible outcome of gene mutation, and this could clearly lead to ‘‘perpetuated pleiotropism.’’ So far as morphogenetic transformation is concerned, pleiophoric states probably generally manifest a state that is not linked to dynamism in the selection interface, and here we can suspect that we are looking at a situation that contains some element of endemic transience in the longer term. However, pleiotropism in the infratranslational domain can probably be perpetuated if selectional balance changes on a periodic basis. Where pleiotropy is perpetuated in adaptive equilibrium, the question of which effect is protropic and which pleiotropic will be linked to expression of dynamism in the selection interface. In this context then, true pleiotropy may actually enter the equation of adaptive capacity: The wing patterns of Maniola butterﬂies have been presumed to be pleiotropes of genes with other effects, in view of observed differences in developmental rates and other parameters (see Brakeﬁeld, 1990). Similarly, pleiotropes for Capaea shell banding genes have also been identiﬁed. Berven and Gill (1983) investigated ‘‘antagonistic pleiotropy’’ in Rana sylvatica, in which length of the larval period and body size are positively correlated in certain habitats, but negatively in mountain areas. Consequently, pleiotropy can be seen to be linked to regional polymorphism in such circumstances. Here, the question of what constitutes true pleiotropy is linked to an adaptational differential evolved in the geographic spatial plane. The above examples show that pleiotropic activity could well give rise to dynamic pleiophorism, especially in phenotype effects of relatively little contribution to ﬁtness. In this situation, there may also be real confusion over what constitutes a protrope as against pleiotrope, in that the leading effect in the pleiotrope hierarchy is itself changing in the context of an anisotropic selection interface.

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This situation also leads to the question of larger levels of pleiophorism appearing during the course of longer term, iterative evolutionary change. As we shall see, problems of this kind probably cannot be resolved endogenously, but are likely to require the additional facility of gene duplication and divergence (see below).

Mutation, Pleiotropism, and Realization of Adaptive Potential As we have already seen, the inﬂuence of mutation on morphogenetic evolution must clearly lie especially with the behavior of regulatory genes held in complex epistatic systems: Conﬁrmatory evidence for a signiﬁcant role of mutation in regulatory genes in evolution comes from the relatively small differences between proteins in lineages which must be regarded as ‘‘remote’’ in terms of anatomical differentiation. Kauffman (1993) likewise states that the discrepancy between diversity in gene or protein structure and anatomy suggests that regulatory gene changes are the more likely cause of structural change. Similarly, Wilson (1975) concluded that adaptive evolution occurs mainly by mutational changes in regulatory genes, on the grounds that the rate of morphological evolution in vertebrates is not correlated with the rate of molecular evolution. According to Raff (1996), differences in morphogenesis may lie in a few selector key genes, in spatial differences in the expression of shared genes, in different patterns of processing of transcripts, or most likely to some combination of these. It is thus axiomatic that cause–effect in gene expression is not a simple linear function of degree of molecular mutation. The effect of, for example, a base substitution in a given gene will depend largely on its position in the epistatic hierarchy in terms of function, and on complex epigenetic factors involving allotropic interactivity with other loci. Similarly, the existence of redundant DNA shows that many mutations have no effect whatsoever on phenotype form. Allotropic–supratranslational genes of regulatory status should thus hold the key to the largest and most signiﬁcant changes at the morphogenetic level, since these also hold the key to neotropic change. From the above analysis, we begin to see how the category of gene can be associated with mode of phenotype change, and thus with the coordinates of adaptive potential. As a general rule perhaps, endogenous changes to preexisting epistatic systems seem likely to have the potential only to bring about less radical changes at the structure level, compared to those involving evolution of novel epistatic systems, since involvement of fresh morphospace targets must open up adaptive potential for radical change. There are thus two levels of neomorphism with respect to a given epistatic system: change from within (via protropic effects) and change from without, the latter constituting the input from neotropism. Therefore, although neomorph change can certainly occur through iterative change involving endogenous reorganization of genetic material within an existing epistatic system, larger scale modulation in the morphogenetic domain

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probably relies ultimately on some element of penetration of exotic genetic signals. For iterative change within an existing anagenetic trend, many quantitative changes may well arise within the developmental module concerned, but qualitative neomorph effects are more likely to originate in gene sets partially controllant to some other phenotype trait. This latter strategy cannot be construed in simple terms of endogenously generated mutation, any more than in terms of genomic reshufﬂing via recombination. Much qualitative neomorphy in morphogenesis may thus become manifest owing to the rare occurrence of neotropic mutation. By looking speciﬁcally at synparametric factors affecting a single structure unit, it is now possible to examine more closely the two possible origins for changes in determinative activity with respect to the parameters in question (see previous chapter): (1) the effects of (presumably ‘‘mid-level’’) regulatory genes expressed exclusively endogenously within that gene set controlling development of the structure unit in question; (2) neotropic effects of extrinsic genes impinging on the same structure unit as a result of modiﬁcation to determination factors originally controllant to other structure units. The latter could occur, for example, via the ‘‘translational co-option’’ scenario described earlier, presumably emerging as lower level regulators gravitating toward higher status via ‘‘bottom-up’’ restructuring in the context of a new emergent epistatic system. Questions relating to epigenetic homeostatic activity thus link closely to the dichotomy concerning endogenous versus modular interactivity at higher translation levels. According to the above interpretation, there is a causal link between classical pleiotropy and the origin of new morphogenetic gene systems. It should therefore not be assumed that ‘‘homeostatic control over pleiotropy’’ is equivalent to excluding all inﬂuence of multiple mutation effects; rather, any positive inﬂuence may be captured, while potentially negative effects are carried as pleiophores and/or selectively sequestered, new epistatic systems coming into being in this manner. Such adjustments should also be viewed as a mechanism by means of which the fundamentally interactive strategy of gene activity is continually diverted from a tendency toward a quasi-stochastic state, toward a deterministic scheme. Genetic homeostasis is, in this sense, predominantly a constraining inﬂuence on the pleiotropic activity of genes, serving not only to control penetrance of negative determinative inﬂuences, but also to coordinate the positive developmental activity of protropic and neotropic effects. Returning to the earlier panstatic system model (previous chapter), we can now illustrate neotropic change following the foregoing principles (Fig. 60). In the diagram below, a partial randomization of epigenetic interactivity constitutes the source of neotropism in the ‘‘target morphozone’’ at ‘‘parameter X,’’ as an expansive allotropic effect establishes a new positive selection interface. The evolving epistatic system thus ‘‘borrows’’ from other, preestablished developmental modules, but also has the adaptive potential to evolve functional divergence and independent modularity through gene duplication (see below). Here, we must consider developmental homeostasis as constituting the ordering mechanism over interacting higher translation effects of diverse evolutionary origins. This mechanism allows for a limited ‘‘all-genes interaction’’

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FIGURE 60 Neotropism in the panstatic system: a new morphogenetic parameter (X ) is affected by neotropes (D and I ) from the two developmental trajectories shape and size.

within certain decanalized zones of the epigenotype (see below), where pleiotropy achieves wide expression. The differential between endogenous and exogenous generation of neomorphic states discussed above clearly also constitutes a deeper view of microversus macroevolution (see Chapter 8), in that the irreversibility factor is more likely to be linked to complex qualitative than to simple quantitative neomorphism.

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Gene Duplication and Realization of Adaptive Potential In Chapter 7, we saw that organic superstructure tends to be organized in a series of structure and functional integrals according to the architecture of the selection interface. In this situation, many viable anagenetic advances must encounter a developmental modularity that is quite different from that lying latent in adaptive potential. This implies in turn that there must be some means through which developmental modularity can change in response to such demands. It is at this point that we encounter the strategy of gene duplication and co-option. Gene duplication is a highly signiﬁcant element in mutational change. Although frequently associated with increased product synthesis at the infratranslational level, it is also known to be of profound signiﬁcance in relation to changing domains of developmental modularity at supratranslational level. The signiﬁcance of gene duplication was ﬁrst recognized by Haldane (1932) and Mu¨ller (1935). Ohno (1970) put forward the hypothesis that duplication is in fact the only means by which new genes evolve, a view that is now universally accepted; new genes arise when one duplicate evolves modiﬁcations absent in the original gene. At the level of allomorphism, heterozygous advantage may set up selection for gene duplication. If two versions of a protein are advantageous, then duplication allows both to be produced in the absence of a possibly disadvantageous heterozygote. Quite apart from total duplications, many domain duplications are also known, especially for structural genes. The basis for gene duplication is now well understood, and it can be facilitated through the medium of unequal crossing-over during cell division. Gene duplication is now known to be a vital element in the restructuring of genetic systems, and this mechanism must be an essential event for the evolution of new epistatic systems in the context of realization of adaptive potential. The principles of mutational change are the same whether duplication is involved or not. However, the most radical changes are likely to demand duplication, especially where a new target in morphospace is also invoked through neotropism. As will be shown, infratranslational gene duplication is often linked to quantitative increase of some synthetic product (namely, without functional differentiation between duplicates). However, it seems certain that supratranslational duplication is particularly correlated with neotropism and pleiotropic balance, and thus with divergence in function between parent genes manifesting a morphogenetic function. Gene Duplication in the Infratranslational Domain It is now known that the structure of the genome differs quite radically from the Mendelian concept. In particular, many synthetic genes consist of series of tandem repeats, and many gene clusters are understood to have evolved by duplication and modiﬁcation. According to Nei (1987), studies in fact indicate that most genes do not exist as single copies, but as clusters.* * Not all repetitive DNA has a functional value, especially middle- and high-repetitive DNA (the role of the latter is uncertain at present; see Maynard Smith, 1998).

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Tandem repeats provide increased capacity for gene production (as with ribosomal genes), while modiﬁcations between members of tandem sets clearly allow an output of varied protein products (as in the globin genes). There is, additionally, evidence for concerted evolution of mutations occurring within gene families, suggesting that this can be an actively evolved strategy, thus allowing iterative change to occur within well-deﬁned channels: Two species of Xenopus show similar rates of parallel change in ribosomal RNA genes, but in the nontranscribed spacer region (NTS) the pattern is different between but not within species. The conclusion is that the above genes did not evolve independently, but in concert. From their similarity, the human 움1 and 웁2 globin genes appear to have split recently, but it is now believed that they did so at least before the origin of mammals. The 움 and 웁 globin genes are on different chromosomes in humans. In Xenopus, however, they are on the same chromosome, except in one species, in which they are duplicated. The mammalian arrangement could have evolved in a similar manner. Similarity of these two genes is, in fact, due to concerted evolution. In examples such as the globin genes, sequences must have been copied horizontally from one gene to the others. This can occur through unequal crossingover or else by gene conversion, these two mechanisms constituting ‘‘molecular drive’’ (following Dover, 1982), with selection acting to favor homogenization of gene families. This is a common scenario for genes within a family, and concerted evolution only takes place between genes with sequence similarity of this kind. Tandem duplications can occur at the same or at different rates in members of a gene family, comparing infraspeciﬁc with transspeciﬁc evolution. It is of particular signiﬁcance, then, that new genes generally evolve following gene duplication of one kind or another. The simple hypermorph functions often associated with duplication tend to constitute intramodular change, often in genes functioning in the adult phenotypic phase, and this seems often to be the rationale which tends to be followed with infratranslational genes. The above strategy therefore constitutes gene duplication linked particularly to intramodular change concerning duplication in the primary role of facilitating hypermorphic gene function, also in allowing differentiation of genes within a cluster, so that some divergence of function may also be attained. Neomorphism in the morphogenetic domain cannot, however, be understood on the same basis (see below). Pleiotropic Balance, Gene Duplication, and Co-option in the Supratranslational Domain It has long been known that synthetic genes frequently manifest duplication and divergence. Of even greater interest from the viewpoint of realization of adaptive potential in anagenetic change at the morphogenetic level is the fact that top level regulatory genes are also known to duplicate and diversify (see end of present chapter and Chapter 16): Some authorities (such as Slack et al., 1993) hold that differences between the phyla arose from differences in the way Hox genes are

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regulated. Interestingly, vertebrates seem to have ﬁve or six copies of Distal-less, which may have originated by duplication of the single copy found in Amphioxus (Price, 1993; Boncinelli, 1994). The homoeotic gene complex (HOM-C) of Drosophila occurs as a single unit on one chromosome, whereas in mammals, the HOM-C genes exist as four gene sets (Boncinelli et al., 1988). These genes control similar parameters of axis formation in widely different lineages, but they have also diversiﬁed in terms of smaller morphogenetic coordinates. The Hox genes have thus manifested duplication both within a cluster and of clusters. Powell (1997) discusses the role of duplication in knirps (kni) and knirps-related (knrl ) genes in Drosophila. Two mutants (Resurrector, Godzilla) suppress otherwise lethal mutants of kni, by allowing knrl to take its place. A gene can easily be recruited into a new function by a single mutation. Duplications in kni/knrl diverged in time of expression, not protein function. As stated by Raff (1996), duplication and divergence are linked to the fact that genetic and developmental co-option is the origin of truly new features in evolution; for example, vertebrate jaws originated as co-option of gill arches. Raff also suggests that the role of the hedgehog gene in development of vertebrate limb and ﬂy appendages could be due to independent co-option of the genes in question (i.e., if there is no true phyletic connection). Raff states that co-option of genes can occur by two general mechanisms: (1) changes in cis-regulatory domains of gene promoters or enhancers, allowing expression in different cell types or at different times; (2) a more pervasive mechanism involving change in the transcriptional machinery of particular cell types, leading to homeotic transformations. In insects, co-option of conserved genes has predominated, whereas in vertebrates, duplication–divergence has played a lead role. The above examples are diagnostic of ‘‘gene duplication as a response to intermodular disarray,’’ in that the selection interface favoring duplication in higher translation level supergenes may often be fundamentally different from that seen in many infratranslational genes. It is at these higher levels that gene duplication and co-option become linked to pleiotropy, neotropism, and expansion of the expressed morphogenetic landscape, hence linking also to realization of adaptive potential. This question will be explored further in the present chapter in the context of genetic regimes for neotropic mutation, and again in the context of impediments to evolutionary change in Chapter 14.

Genic Substitution, Occlusion, and Atavism In classic Mendelian genetics, the ascent of a new gene allele could be visualized in terms of simple genic substitution, where the frequency of a mutant allele becomes 1.0. However, in the developmental model, it has become evident that the phenotype effect of an unaltered locus within a convex epistatic system could simply be suppressed through addition of a further ‘‘upstream’’ gene to

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the epistatic set, with no actual change to the original locus itself (as with gene duplication–divergence; see above). This mechanism constitutes not gene ﬁxation, but genic occlusion. Genic occlusion can be shown in the epistatic array model (see Chapter 11) as diagramed in Fig. 61.

FIGURE 61 Addition of a new member (i3) in an epistatic system has not required substitution at loci i1 or i2. Their expression will simply be altered in phenotype (1,1,1), in which the original phenotypic output (1,1) has been occluded by input i3.

Since epistatic systems may often be altered by the addition of new regulators in the context of genic occlusion, a lost phenotype can sometimes be regained by removing added regulators (depending of course on the degree of subsequent molecular change). This is atavism, a genetic mutation (or group of linked mutations) causal to recovery of one or more traits which may have passed into a state of phyletic occlusion, namely, where there has been iterative genic occlusion. Even a quite simple structural unit may be made up of n phenons (see Chapter 4) that have been integrated through past phyletic occlusion, and evolutionary changes may carry a very large element of occlusional change, as actual evidence from atavism of major essential features suggests: One example lies with the partial transformation of the second pharyngeal arch into a copy of the ﬁrst in mouse embryos (see Chapter 16), and another is seen in the partially atavistic recovery of abdominal limbs in the ﬂeshy ‘‘prolegs’’ of lepidopterous larvae (see Chapter 21). It has also been shown that the larval stage of an interspeciﬁc hybrid between two sea urchin species with widely different metamorphosis patterns resembles a starﬁsh juvenile more than it does either parent species (Raff et al., 1999). At this juncture, it is instructive to return to and expand the earlier treatment of amphigenesis (see Chapter 8), which clearly does not have to involve atavism in the genetic sense. When lost traits are regained, this may be through genes producing convergent or parallel structures - so that amphigenetic change may thus be manifested in either ‘‘true’’ or ‘‘false’’ atavism. Simpson thought that evolution was reversible to that point at which genetic systems remain unchanged. Raff and others (see Raff, 1996) concluded that true atavistic reversal probably happens over 0.5–6 My, but not in frames

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of over 10 my, unless the gene in question is maintained by active selection. Nevertheless, genes no longer expressed in one pathway may be used in another, so that there is in fact a mechanism that could permit much longer periods of atavistic recovery. Reactivation of a complete complex morphogenetic pathway must be much less probable, since the chance of retrieving several interacting genes is much lower than if only one gene is involved, although Raff (1996) has pointed to one apparent exception to the above ruling: Some axolotls have undergone atavistic reversal with respect to neoteny, showing that downstream genes for the switch mechanism have remained functional, thus allowing fairly complex reversal to occur over periods of 0.5–1 My. However, good evidence also exists to conﬁrm that the probability of more dramatic modes of atavism is low, as witnessed, for example, in the recent refutation of earlier experiments which appeared to stretch credulity on the question of complex atavistic reversal seemingly spanning great phyletic distances: Hampe’s (1960) experiments with chick embryos involving apparent reversal in ﬁbular length were repeated by Mu¨ller (1986) and found to be misleading. Similarly, experiments claiming to show regain of teeth in chick embryos have also been severely questioned on the grounds that cross contamination may have been involved (see Raff, 1996, for a review of these experiments). While atavism affords good genetic evidence in support of the phyletic occlusion concept, we must, of course, also guard against ‘‘false atavisms’’ such as those generated by certain homeotic mutations: Any ancestor of Drosophila lacking differentiation of tagmata in segmentation of the kind witnessed in bithorax type mutations must have been very remote indeed, probably antedating the existence of at least some of the genes causing such ‘‘false reversion.’’ The winged ‘‘metathorax’’ is of course a duplicated mesothorax and not an atavism! The combination of neotropism and gene duplication identiﬁes phyletic occlusion as the mode of change operating for most morphogenetic evolution. This will be shown to be an essential element in anagenesis, as also in ‘‘pseudoextinction’’ (see Chapters 17 and 20).

CANALIZATION AND ADAPTIVE POTENTIAL Some form of homeostatic defense against pleiotropism is to be expected in developmental systems, and the mechanism in question has been framed in terms of developmental canalization. The canalization mechanism was proposed by Waddington (1957 and elsewhere) as a higher level homeostatic control which acts to promote a uniform response with respect to certain major coordinates of development in the face of a varied genetic background. How

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does this mechanism connect with the problem of selectional balance during periods of radical evolutionary change?

Epigenetic Noise To understand what function canalization performs, we ﬁrst have to understand why pleiotropism (also pro- and neotropism) occurs in the ﬁrst place. As we have seen already, adaptive potential may be realized as a result of endogenous modiﬁcation to an epistatic system acting to control morphogenesis, and there may also be periods of iterated neotropic change during which accumulating negative pleiotrope effects constitute a growing developmental hazard. The likelihood of a progressive and widespread randomization of epigenetic interactivity in the higher translational domain seems likely in this scenario, given the allotropic nature of many supratranslational genes. We shall adopt the term epigenetic noise to describe any random extension of the fundamental temporospatial domain of a determination factor arising either directly or indirectly from mutation or via environmental changes affecting the phenoplastic domain. Epigenetic noise is thus essentially that complex of quasi-random misalignments of epigenetic interactions arising from the higher translational aspect of genetic mutation, and which gives rise to pleiotropism in the phenotype through partial breakdown of developmental modularity. Epigenetic noise should not be viewed as truly random, but is perhaps due to a tendency toward disruption in the Boolean functions controllant to epistatic systems, as a result of ‘‘pleio-penetrance’’ of extrinsic determinative forces. Above all else, negative pleiotropism arising through epigenetic noise constitutes the greatest impediment to mutational change. Epigenetic Noise and Evolutionary Neomorphism Most mutation probably represents a drift toward randomization of epigenetic interactions that is generally counteracted by selection. In fact, pleiotropy can be deﬁned as being that component of epigenetic noise that is deleterious to the phenotype. However, there must also be a pathway toward viable new morphogenetic horizons in mutational change. Translational pleiotropy does two things: it has the capacity to impede progress in the face of the emergence of epigenetic noise, while at the same time it can provide raw material for morphogenetic innovation. The multiple effect outcome of mutation thus ultimately allows morphogenetic potential to expand as a possible pathway toward realization of adaptive potential, while being simultaneously responsible for the generation of negative feedback in the epigenetic environment. Epigenetic noise is thus not to be construed as a purely negative inﬂuence, since the origins of protropic and neotropic states must lie here also. At the same time, however, the overall effect of ongoing neomorphic mutation seems likely to converge on negative pleiotropism.* * Lerner (1954) considered this to be a response to perpetuated heterozygosity in the face of hybrid vigor; however, the developmental interpretation seems a more likely explanation than one that is probably mainly linked to the substructural domain.

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Canalization as the Adaptive Response to Epigenetic Noise As we have just seen, mutation has the capacity to affect all categories of genetic material, and there must therefore be differential sequestration of the essential factors of morphogenesis against most ambient mutational activity affecting the developmental program. Clearly there must be some mechanism which acts to control recurrent randomization inﬂuences, in the form of a homeostatic response acting as a defense against negative pleiotropism, and the ﬁrst line of defense against such forces must be that of a strategy of developmental homeostasis tending to favor uniformity of phenotype output against a backdrop of continual change. The mechanism in question is that of canalization. Canalization can be regarded as being the sum of homeostatic developmental forces tending to reduce epigenetic noise arising from background pleiotropy: Thomson (1988) described a canalized developmental pathway as one that has the capacity for self-correction in the accommodation of genetic or developmental perturbation. Waddington suggested that canalization might arise through ‘‘stabilizing selection’’ (following Schmalhausen, 1949), although this has most usually been understood as leading to actual loss of variability (see Moyo, 1983). Lerner (1954) was especially interested in the link between canalization and the predominance of hybrid vigor. The question of ‘‘canalizing or stabilizing selection’’ clearly needs to be examined from the developmental angle, rather than merely in the context of adaptive equilibrium, and the latter question will be explored in more detail below. Sequestration and Canalization It is instructive to compare and contrast the canalization mechanism with that of genetic sequestration. Certain mechanisms have been discovered which seem to afford means of control over the actual frequency with which mutation occurs, thus providing constancy in a quite different context from that offered by canalization: Schroedinger predicted that genes must suffer much damage through thermal collision with solvent molecules. Most of this damage is rapidly repaired, only a small fraction remaining as mutation, and there is evidence that this ‘‘inefﬁciency’’ is deliberate. Conversely, Dobzhansky (1970) observed that it was known that some strains of Drosophila melanogaster have higher mutation rates than others, and that this is due to mutability enhancer genes in different linkage groups. In the context of mutation enhancement, transposable elements are known to be important in producing gene novelties, creating new mutations and chromosomal rearrangements, and many authors believe also that transposable elements play an important role in speciation (see Li, 1997). Control over frequency of mutation can therefore work in either direction, and this has signiﬁcant corollaries for realization of adaptive potential.

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Clearly, sequestration must not be confused with canalization. Sequestration is homeostasis against the occurrence of mutation (or of transcription). It thus prevents mutation in active DNA (or transcription or translation in mutational DNA), permitting a ‘‘ﬁxed,’’ nonallelic status for certain essential gene loci. Sequestration is therefore concerned with differential mutability of the gene at the molecular level, preventing mutation at ‘‘sensitive’’ gene sites, facilitating repair to damaged DNA, and preventing transcription when mutations have taken effect. It is thus a mechanism operating at the lowest (transcriptional or pretranscriptional) levels, and (as with canalization) sequestration may at times present a signiﬁcant restraining force, both on the expansion of variation and on realization of adaptive potential. Canalization can now be contrasted with sequestration as constituting an epigenetic homeostatic mechanism operating against expression of higher translational gene effects, its most signiﬁcant function being to prevent negative pleiotropic effects arising from positively selected mutational change from impinging on stabilized epistatic systems. Canalization should thus be seen as an actively controlled homeostatic state of epigenetic interaction, rather than a force impeding the actual incidence of mutation, an adaptive response to repeated randomization events which tend to generate epigenetic noise. Canalization is thus the process by which those homeostatic mechanisms which serve to monitor epigenetic interactivity are built and maintained, ensuring minimum penetration of pleiotropy and manifesting a constraining inﬂuence on the gene sets of many epistatic systems. In this sense, canalization is essentially the higher translation level or ‘‘epigenetic’’ equivalent of sequestration. The behavior of epistatic systems may thus manifest much resistance to translational pleiotropy, and adaptive potential must accordingly be realized only within certain ‘‘permissible domains’’: Stearns and Kawecki (1995) tested canalization in Drosophila, comparing apparently essential with ‘‘trivial’’ traits. They found that the former were indeed more canalized than the latter. Most signiﬁcantly, they also concluded that canalization is against genetic rather than environmental perturbation. The work of Maynard Smith and Sondhi (1960) on the ocelliless Drosophila mutation also demonstrates canalization. The normal phenotype can be ‘‘restored’’ in a homozygous ocelliless culture by selecting ﬂies with partial expression of the normal state. This is said to be possible through ‘‘modiﬁer’’ action; or alternatively, it could perhaps be explained by gene ampliﬁcation at a single locus. Either way, one possible route to canalization of development is the tendency of certain key loci to duplication or ampliﬁcation. It is also pertinent to add that this experiment does not (as has been claimed) ‘‘create’’ canalization. It identiﬁes its preexistence in the adaptive capacity of the natural gene pool. There appear to be several recurrent mutations which can restore the lost phenotype, and these do not have to arise at the same gene loci as other sites giving rise to the same outcome. The hypothesis presented here as an explanation of changing domains of canalization is that gene mutation with a strategic regulatory role in the strategy

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of canalization can have either of two possible primary functional corollaries at the epigenetic level, so far as the homeostatic domain is concerned. Certain key regulatory genes must speciﬁcally serve the homeostatic function of controlling pleiotropic impingement on a given epistatic system, from extrinsic sources. The effects of a given mutation in a strategic regulatory gene manifesting a function in canalization would then be to derandomize epigenetic interactions. One dichotomy within certain regulatory gene mutations may therefore be between those which tend to randomize and those which tend to derandomize epigenetic interactions, the homeostatic balance in this being the means through which epistatic systems possess the capacity ultimately to evolve positively selected novel morphosystems. This function is clearly of prime importance for realization of adaptive potential in anagenetic evolution, in that it identiﬁes a class of mutations the function of which must be to selectively reinforce or diminish the modularity of certain developmental coordinates: Selection for increased canalization has also been shown to occur, as with the Bar eye mutants in Drosophila (Waddington and Robertson, 1966). The inﬂuence of temperature on expression in terms of facet number was reduced from 50 to ⬍15 in only six generations. Again, this may of course have been due to recurrent rather than truly neomorphic mutation. Given the important role of gene duplication in control over positive and negative forces in the regulatory hierarchy, it may of course be that mutational events of that kind are also involved in modulation of the domain of canalization. Canalization in the Boolean Function Model Canalization can be interpreted in terms of a superimposed domain of constrainment in the Boolean function of an epistatic system, the Boolean system for this function being one in which ‘‘many possible input conﬁgurations lead to the same outcome,’’ presumably operating on the basis of some homeostatic ‘‘error detection mechanism.’’ Using the lactose operon as an exemplar, Kauffman (1993) proposed the existence of canalizing functions, where at least one of the regulating variables alone sufﬁces to cause activation of the regulated locus. In this manner, the number of functional outcomes in the system is thus reduced. An example is the ‘‘or’’ function:

FIGURE 62 An example of an ‘‘or’’ function: X is activated when i1 is on or when i2 is on (or when both are on), hence X is not easily displaced.

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An apparent example in higher eukaryotes exists (for example) with expression of the engrailed gene in Drosophila, which occurs when cells contain high concentrations either of Even-skipped or of Fushi tarazu proteins. Similarly, two independent systems involving lin-3 and lin-12 genes are now known to pattern early development of the vulva in the nematode C. elegans. A free (that is to say, totally noncanalized) Boolean function would then be expressed by a model in which the number of phenotypes (P ) equals K2 (where K ⫽ number of actual input variables manifesting states 0 and 1) in the presence of allelomorphism at each of the K loci. Hence, an index of the level of canalization activity in a constrained epistatic system is given by (K2 ⫺ P )/ (K2 ⫺ 1). A less abstract view of a mechanism actually affecting high-level control of the kind involved in canalization comes from investigation of the heat-shock protein Hsp90 which is known to protect against expression of developmental changes, thus acting as a capacitor that could permit genetic variation to build up harmlessly (Rutherford and Lindquist, 1998). Thus, canalization need not be construed solely in terms of ‘‘duplicate control systems.’’ Canalization, Developmental Modularity, and Lability to Realization of Adaptive Potential It is clearly of great signiﬁcance that canalization must form part of that constraining inﬂuence deﬁning the number of degrees of freedom in adaptive potential (see Chapter 7), a situation which can in turn be linked to the question of developmental modularity.* The positive aspect of canalization naturally lies with prevention of pleiotropism in the context of ambient gene pool structure and background mutation, but the corollary of this is that restrictions on developmental modularity may come to block potentially positive avenues of morphogenetic change! The strategy of canalization must serve to deﬁne both ‘‘lateral’’ and ‘‘vertical’’ modularity in the morphogenetic trajectory, in preventing negative feedback in the vertical plane and in suppressing expansion of allotropism in the lateral. In this way, the modularity of a developmental trajectory is both sculptured and maintained. Canalization is thus also causal to certain threshold limits for iterative mutation in epistatic systems through its effects on modularity, no doubt having some correlated effect on the directionalization function (see Chapter 7).

Decanalization, Epigenetic Noise, and Changes in Developmental Modularity Since canalization is linked to modularity and must therefore suppress both negative and positive elements in epigenetic noise, it follows that evolution cannot occur unless there is also some form of ‘‘decanalization.’’ Decanalization * In this context, Raff (1996) argues that canalization may be linked to regulative development (see p. 189), and in this we can see that such factors as duplication of regulative inﬂuences acting on a given determinative pathway could indeed lead to stabilization of certain major morphogenetic parameters.

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is that process of partial randomization of regulatory genetic interaction arising through a tendency of epistatic systems toward the unconstrained state, owing to the inﬂuence of mutation promoting epigenetic noise, most probably through the ‘‘passive’’ proliferation of ‘‘off’’ switches. Epigenetic noise thus tends to passively deconstruct canalization, and canalized systems may thus tend toward a state of decanalization in the absence of selection pressure actively promoting the canalized state. Epigenetic noise may thus penetrate canalized systems through passive accumulation of 0 functions (and perhaps also by some expansion in the domain of activator activity), in the absence of an active selection interface tending to favor homeostatic stabilization of certain morphogenetic parameters. A ‘‘freeing’’ of the Boolean network deﬁning a canalized epistatic system could thus form the basis for decanalization. As the number of inputs deﬁning the same output decreases, so too the number of alternative outputs must tend to increase, and some inputs may now be affected by impinging pleiotropy arising from external domains. This indicates, in turn, that the ‘‘fundamental state’’ of epistatic Boolean networks (in the absence of active homeostatic control) is perhaps one tending toward random interactivity. Adaptive potential cannot, however, be ‘‘freed’’ by artiﬁcially removing canalization. What emerges in this situation is disorder with particular respect to translative pleiotropy, and this is precisely the situation seen in the context of the pleiotropic balance model. The effect of iterated decanalization must therefore be partial decay in the degree of modularity, generally leading to negative selection forces but sometimes to neomorphism. This aspect of changing modularity is linked in turn to the question as to what kind of epigenetic landscape best favors emergence of evolutionary novelty (see Chapter 14). Decanalization and Mosaic versus Regulative Development Since some temporospatial domains in development can be either predominantly mosaic or regulative in nature (see Chapter 10), it follows that decanalization may tend to be linked to intramodular change in some developmental modules and to intermodular activity in others. In the latter situation, we also observe the all-important link to duplication and co-option. Decanalization and the Phenocopy Mechanism Good evidence exists to suggest that decanalization acts to release morphogenetic potential to a more widely expressed state in the phenotype. The phenocopy mechanism (see previous chapter) describes that situation where the effect of a mutant gene is ‘‘imitated’’ by some nongenetic determination factor. This phenomenon has been linked to ‘‘shock’’ elements in environmental determination factors, as seen in the dialogue between gene expression and various inducers of that kind: Temperature sensitivity has been shown in homeotic mutants of Drosophila. For example, proboscipedia transforms labial palpus into arista at 18⬚C, but into leg at 28⬚C. Other alleles of pb are not temperature sensitive. Several phenocopy-inducing factors have been demonstrated for the Drosophila bithorax trait, including ether induction, which has

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been shown to demonstrate increased penetrance in successive generations (Ho et al., 1983). This mutation causes the metathorax to develop as mesothorax. These ﬁndings also appear to conﬁrm the ‘‘binary epigenetic code’’ model favored by Kauffman (1973 and elsewhere). In the creeper fowl mutant, the primary effect can be induced as a phenocopy by growing limb rudiments in nutrient deﬁcient medium, and also by various chemical inducers injected into the egg. This and the previous example evidently belong in the category of remote inducers. Responses to phenocopy agents of the above kind may often prove to be linked to decanalization, in that they tend to penetrate canalized structures in Boolean networks at positions that are particularly labile to such inﬂuences. The phenocopy mechanism seems in fact to underline the analytical value of the Boolean network model of canalization, also expressing the presumed link between decanalization and epigenetic noise (through the probable inﬂuence of analogous ‘‘off’’ switches in at least some ‘‘phenocopies’’). A deeper analysis of the phenocopy mechanism shows that it links to two quite different aspects of the epigenetic landscape. Phenotypic plasticity must be actively structured around ‘‘gaps in canalization,’’ where the permitted inﬂuence of a range of exogenous determination factors interdigitates with primary adaptive equilibrium. Other phenocopy agents may be more remote inﬂuences that have not been canalized against, owing to the fact that they have not been encountered previously in the epigenetic environment (similarly, the genetic determinants that the latter agents ‘‘copy’’ will tend also be highly deleterious ‘‘macromutations’’). The probable mechanisms underlying the phenocopy mechanism suggest that one effect of decanalization must be that of opening up developmental pathways to diverse genetic or nongenetic determination factor inﬂuences, probably via a proliferation of ‘‘off’’ switches. Decanalization of epigenetic interactions may thus occur when some key determination factor has been disrupted, and it is clear also that canalization has to control nongenetic determination factors as well as genetic inﬂuences. In general, however, the latter will have been organized around ‘‘ambient’’ environmental factors, and not around remote shock treatments (as indeed conﬁrmed by the phenocopy mechanism). The phenocopy mechanism is now seen as being linked to the phenomenon of nongenetic determination in general, and such factors are obviously of considerable value in providing evidence of the nature of mechanisms of epigenetic interactivity. First, they illustrate interaction between genetic and nongenetic determination factors. Second, they appear to conﬁrm the reality of canalization in outcomes of diverse input systems to epistatic systems, in that the phenocopy mechanism apparently exploits the ‘‘weak links’’ in a canalized system. Natural exogenous determinants are really ambient environmental inﬂuences, and epistatic systems have evolved to respond to these factors in a speciﬁc manner, this interpretation being based on the observation that shock stimuli are generally nonadaptive and frequently lethal, whereas nongenetic determination factors tend to be adaptive in nature. ‘‘True’’ phenocopies should therefore be interpreted as remote nongenetic determination factors of the exogenous kind, arising from shock stimuli having

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the capacity to break homeostatic controls which act to suppress certain selectively negative developmental pathways, whereas true nongenetic determination factors (as against ‘‘remote phenocopy inducers’’) really belong to the panstatic system: The chromosome ‘‘puffs’’ indicative of the onset of gene activity in the polytene nuclei of many insect larvae can be induced by ammonia, anaeobiosis, inhibitors of electron transport, and uncouplers of oxidative phosphorylation, with puff size being proportional to temperature and duration of exposure. Embryos, speciﬁc tissues, and cell lines respond in the same way to these stimuli. This situation suggests a cell response to extreme conditions. However, such systems may also contain a capacity to become linked to primary adaptive equilibrium. The above observations all seem to conﬁrm the view that most complex epigenetic determination systems are protected by canalization, in that only a few alternative pathways seem to be manifested when their structure is disrupted by a heterogeny of extraneous inﬂuences. The effect of decanalization is therefore to allow greater manifestation of latent morphogenetic potential: At least one aspect of decanalization can be understood in terms of the ‘‘capacitor’’ functioning of heat-shock proteins (see p. 252) in that under conditions disruptive to the functions of these products, ‘‘stored’’ variation could be released into the epigenetic environment, potentially to ﬁnd viable expression at the phenotype level. Genetic Assimilation and the Epigenetic Landscape The concept of the speciﬁc lability of certain components of development to nongenetic determination factors leads naturally to the question of genetic assimilation, that situation where an environmentally determined trait subsequently comes under genetic control (in effect, a ‘‘genocopy’’ of a phenotype state formerly linked to nongenetic determination factors alone). Genetic assimilation is linked to the phenocopy mechanism in the sense that the latter also has links with ambient nongenetic determination factors originating in the external environment, and could perhaps be seen as an indication of how canalization and decanalization may work together in sculpturing lability to diverse determination factors in the epigenetic landscape, wherever differential penetrance of either genetic or nongenetic determination factors is selectionally advantageous to adaptive capacity: Evidence in support of the hypothesis that traits under the control of externally induced nongenetic determination may sometimes pass to genetic control has been widely discussed with reference to the rump calluses of the ostrich (see Waddington, 1942, and Schmalhausen, 1949; also see Maynard Smith, 1966b). Matsuda (1982) considered that the neoteny of talitrid amphipods and salamanders in changing environments could be due to genetic assimilation, and it may also be of considerable signiﬁcance for the validity of the supposed relationship between environmentally inﬂuenced determination and genetic assimilation that the structural

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changes observed in species proliferation of Cichlidae in the Great Lakes in Africa have also been shown to manifest certain links with phenotype plasticity (Meyer et al., 1990; see also Reinthal and Meyer, 1997). The view that the phenocopy phenomenon and genetic assimilation are linked through a related mechanism in changing canalization strategies receives experimental support from experiments with Drosophila: Waddington (1952) produced crossveinless Drosophila phenotypes by subjecting a wild-type population culture to heat shock, as a phenocopy of a known genetic mutation carrying this characteristic. He continued this treatment for several generations, selecting only those individuals showing the mutant trait. In this way, he was able to obtain a genetic strain which expressed the same characteristic on the basis of numerous ‘‘polygenes’’ that were independent of the known crossveinless locus. Waddington based his concept of canalization on such experiments, proposing that environmental stresses and background genetic variability are generally buffered away from certain developmental pathways. Rendel (1959) studied the scute mutant of D. melanogaster (which alters the number of scutellar bristles), selecting both low and high bristle number lines from mutant ﬂies, eventually obtaining a strain with more than the wild-type number by crossing high number ‘‘scute’’ progeny with the wild-type. He found that four bristles appears to be the canalized number, and that genotypes with either less than or more than this number are consequently more variable. Rendel’s interpretation of the above experiment is that the relationship between genotype and phenotype could be expressed as a curve which is initially a straight line, with only a small proportion of phenotypes approaching the optimum value. Selection may then act to widen that zone of the curve, so that a greater range of phenotypes express the optimum. Scharloo (1991) provides a detailed analysis of the frequently nonlinear relationship existing between genotype and phenotype in the context of reaction norms (see also Schlichting and Pigliucci, 1998). According to Waddington (1962), selection acts at two levels. First, it acts to change the primary expression of a genotype and second, to change the zone of canalization. The above-mentioned ‘‘labilities’’ of epistatic systems are clearly evolved characteristics, since it seems most probable that the propensity for ostriches to develop calluses (either through genetic or extrinsic determinative factors) is a function of the manner in which differential canalization has been actively selected. The signiﬁcance of genetic assimilation is that it appears to conﬁrm the hypothesis of certain regulatory pathways in development being differentially susceptible to nongenetic determination factors and to gene mutation in a manner that can be varied. Genetic assimilation of more remote morphosystems occurs in experimental conditions only, and is invariably deleterious in the

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adaptational sense.* Thus, where genetic assimilation occurs with respect to adaptationally positive change, this is clearly an evolved lability operating within the domain of adaptive equilibrium, rather than manifesting a novel evolutionary step—an interpretation that offers no support for a ‘‘neoLamarckian’’ factor in evolution! ‘‘Natural genetic assimilation’’ of the adaptive kind should now be interpreted as evidence for evolved preferential labilities of the developmental system, the control mechanisms of which can be sequestered, alternatively by recurrent genetic or by exogenous determination factors, according to architecture of the selection interface and constitution of the gene pool. This is why many nongenetic determination factor-controlled variables in phenotype plasticity have both a polygenic element and a component arising in the external environment. So far as the selection interface is concerned, genetic assimilation should be favored over phenoplasticity whenever its periodicity becomes greater than t, when gene control will tend to take the place of nongenetic determination factors. Consequently, this particular phenomenon probably tends to evolve when the periodicity of certain variables in the external environment sometimes lies above and sometimes below this particular time frame. Traits of this kind may also tend to express different propensities for genetic as against nongenetic control in different environments: Brakeﬁeld et al. (1996) found that the adaptive polyphenism of the butterﬂy Bicyclus can be genetically assimilated, also that the short day (cold weather) adaptive type is the same as the genetical phenotype of species or subspecies found in colder geographic zones. Natural genetic assimilation thus belongs to the domain of adaptive equilibrium, through the concept of a labile epigenotype. Homeostatic mechanisms of development may thus evolve the capacity to undergo regulation by both genetic and nongenetic inﬂuences in situations where a periodic (or geographically varied) response to ﬂuctuating environmental variables is demanded, and the one common factor in the many examples of traits governed jointly or alternately by genetic and environmental inﬂuences probably lies in the existence of a particular conﬁguration in the dynamic selection proﬁle. In experimental genetic assimilation (as with the Waddington experiments), it is assumed that latent ‘‘labile sites’’ are similarly involved, whether or not the phenotypic differential is an adaptive one. Given that primary adaptive equilibrium clearly demands the existence of differential labilities of the epigenetic environment to recurrent external factors, it is perhaps predictable that canalization will be so constructed as to permit labilities to inﬂuences of this kind. In the above view, therefore, genetic assimilation is an evolved lability and not a substrate for fresh evolution; as indeed argued by Williams (1966), ‘‘The importance of genetic assimilation as a creative factor is minimised’’: Maynard Smith and Szathmary (1995) also discussed the question of inheritance of somatic traits during development. After describing a * In fact, Waddington (1942) considered that the capacity for development of calluses in the ostrich must clearly be dependent on genes in the ﬁrst place, although his data have sometimes been misrepresented as pleading a case for Lamarckian inheritance.

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model for the occurrence of this, they pointed out that this only occurs because development can become adaptive on account of past selectional activity. In reality then, both genetic assimilation and the phenocopy mechanism are best regarded as corollaries of the canalization mechanism, although genetic assimilation clearly has an active role to play in ambient adaptive equilibrium. The inﬂuence of decanalization on expression of novel morphosystems appears in general to manifest a wide receptivity to diverse genetic and nongenetic determination factors. Heritability, Phenoplasticity, and Evolution The familiar heritability equation (R ⫽ h2S ) enters into the question of evolutionary change in the context of phenoplasticity-linked additive gene traits. However, this question is, in reality, largely one which concerns artiﬁcial rather than natural selection, since in evolutionary terms, novel adaptive capacity for morphogenetic change can include developmental lability to diverse determination factors of both endogenous (including genetic) and exogenous origins. From actual observations, however, it is clear that the domain of phenoplasticity is limited to expansions and compressions in continuous variation plus (rarely) simple switch gene-like effects of the genetic assimilation kind. Additionally, in either case the canalization regime favoring such behavior is itself the result of selectional activity acting on the genome. In the same way, certain traits may emerge as phenoplasticity and subsequently pass into the genetic domain, without invoking any need for a Lamarckian explanation. The strategy of canalization may simply be such that minor pleiotropic impingement sometimes comes to occupy a similar position to that of former nongenetic determination factors: Vermeij (1974) stated that the conﬁguration of secondary and higher order venation in early angiosperm leaves was highly variable and often irregular (following Hickey, see Vermeij, 1974), suggesting that more stringent genetic control may develop later when a new trait is evolving. An understanding of the dynamics of nongenetic determination has to be framed in a wider context. Where phenoplasticity expands or contracts, we must also consider the viewpoint of Schlichting and Levin (1986), who argued that a new environment may be one in which average conditions have not changed, but distribution around the average has. These authors also stated that the role of phenotype plasticity has been underestimated as a factor in plant evolution, and that in some cases, it may be more important than changes in the means of character states. The broadness of decanalized receptivity in general cannot be other than a transient state in the evolution of natural adaptive systems, and the available evidence all points to the fact that this wide receptivity will tend rapidly to narrow in the direction of the genetic component. The only exception to this rule lies with phenoplasticity, namely, where environmental control has to be chosen above genetic control, in the face of very short periodicity in the external selection interface (see Chapter 10).

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PATHWAYS OF MORPHOGENETIC CHANGE IN REALIZATION OF ADAPTIVE POTENTIAL What predictions can be made concerning ‘‘size of step’’ when a major anagenetic event takes place? In the past, there has been much controversy concerning the degree to which ‘‘evolutionary saltation’’ can occur, and this question clearly must be reassessed in the light of our contemporary understanding of developmental genetics. In particular, it must be that the ongoing dialogue between canalization and epigenetic noise makes certain demands on ‘‘size of step’’ in the context of evolutionary change. In addition, the existence of the phylotypic stage in vertebrates also suggests that the differential (and intersect) between fabricational and adaptive paradigms may impose certain restrictions (as well as create speciﬁc demands on the canalization mechanism).

Incremental Change versus Saltation References have already been drawn to the likelihood that adaptationally positive morphogenetic change is most likely to relate to ‘‘movement between adjacent systems.’’ In this latter context, the simplest move might be for certain developmental coordinates to alter via scalar transformation, or for quasiautonomous developmental modules to express time shifts relative to one another (see Chapter 16). It is at this juncture that we encounter the criticism of Goldschmidt (1940) that certain diagnostic traits of taxonomic groups apparently have no obvious functional intermediates, either in the fossil record or in theory. In fact, most of Goldschmidt’s cases of supposed ‘‘saltational evolution’’ are now disproved in one way or another, and it is unlikely that the very few examples which can still be postulated in this category really point to genuine ‘‘one-step macromutations’’ in evolution. This question does, nevertheless, require more than a cursory examination here, albeit from a somewhat different angle. The concept of saltation supposes that evolutionary change can occur in single large steps as a result of unit macromutations. The ﬁrst observation concerning ‘‘size of evolutionary step’’ comes from actual data on observed genetic mutations. While many known mutations clearly are ‘‘saltational’’ in terms of degree of phenotype change, this does not, however, imply that evolution can proceed in the same manner. There is a fundamental difference between traumatic mutational effects and large scale phenotype change that has been structured by selection in an incremental manner via iterative, positive mutational activity. Thus, although decanalization seems to favor saltational evolution, the usual massive pleiotropism observed with experimental populations clearly leads to negative pleiotropic balance in Nature. Fisher argued that existing organisms lie close to an adaptive optimum, so that large changes would be very unlikely to allow improvement, compared to smaller, incremental ones. In particular, it must be said that the vast majority of known major mutations are observably deleterious, and this is the circumstance predicted from a consideration of the likely homeostatic structure of epistatic systems, as indeed proposed by Fisher:

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Dobzhansky (1970) stated that most classic major mutations in Drosophila reduce the viability of their carriers owing to negative pleiotropism, and this clearly shows that viability must be vulnerable to deﬁciencies in very many ‘‘major’’ loci. Simpson (1953) discussed the directionality of mutation, observing that the incidence of some mutations is much higher than that of others, and much higher than that of back mutations. However, the dominant direction is not that in which previous evolution has occurred, and most is ‘‘degenerative.’’ Sang (1984) states that lethals are the commonest mutations, citing evidence from the fact that an estimated 60–80% of loci on the Drosophila X chromosome can mutate lethally. Lethals seem to cause death at some critical stage (gastrulation, ecdysis, birth, etc.), while many other deleterious mutations merely depress the adaptive state such that they are selected out over the course of a few generations. Evidently there are various homeostatic constraints which epistatic systems must impose on qualitative changes to epigenetic determination mechanisms operating in that domain where higher translation products of genes and nongenetic determination factors interact in the control of morphogenesis. It is relevant to ask whether positively selected qualitative effects can ever occur ‘‘in a single step,’’ or whether they are not more probably the accumulative result of iterative change of the quantitative kind, thus following a pathway of repeated incremental transformations of structure affecting several morphogenetic coordinates systems—not simultaneously, but in temporal sequence over a long time period: Where evolutionary change has been observed in the context of a nearly complete fossil record (as in Sheldon’s study of trilobites, see Chapter 18), incremental change has frequently been clearly evident. When deciding what is meant by ‘‘saltatory,’’ however, we must also take into account the fact that a number of apparent macroevolutionary steps have been linked to quite simple afﬁne morphotransformations of fundamental phenotype structure. Nevertheless, we must distinguish ‘‘true’’ macroevolutionary events (such as the evolution of a new organ system) from movement between adjacent morphosystems that is, in reality, described by epistatic systems differing in a quite trivial manner. As stated above, it may be this latter movement which deﬁnes the incremental step made by anagenetic change, in the shift between the domains of adaptive capacity and potential (and thus also between ‘‘trivial’’ and large scale evolutionary events). From earlier discussions, we must also give serious consideration to the question of saltational steps being made because of negative pleiotropes being ‘‘carried’’ by positive effects of a large mutation, wherever there is a net increase in ﬁtness and pleiphorism is invoked. It is furthermore possible that some actual saltatory changes are neither iterative nor due to pleiotropic balance, as seen in the instance of certain threshold events in morphogenetic transformation. The capacity of incremental change in a given parameter to produce sudden ‘‘transcendent’’ shifts in form

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has been postulated, for example, with respect to the cheek pouches of pocket gophers and kangaroo rats (see below): Oster et al. (1988) considered this question in terms of bifurcations in their mechanochemical models of morphogenesis: ‘‘We encountered many situations wherein perturbing certain parameters produced dramatic alterations in the geometrical evolution of the model. . . . In traversing the path in parameter space from one set of values to another, a dramatic change in the qualitative behaviour is produced. . . . At some point, an apparent bifurcation occurs to a new stable regime of shapes.’’ Oster’s observations certainly conﬁrm the capacity of developmental systems to produce ‘‘bifurcations,’’ although of course it does not necessarily follow that neomorphic systems originating in this way will also be adaptationally positive. Nevertheless, threshold events of this kind must unquestionably add to the degrees of freedom inherent in the structural component of adaptive potential. However, in general, saltation seems too closely associated with massive pleiotropic effects to constitute a viable pathway to major evolutionary change. Anagenetic progress can only occur if there is minimalization of epigenetic noise, since the modular architecture of the epigenetic landscape will otherwise disintegrate, and it is reasonable to suppose that gradualistic modulation actually allows homeostatic adjustment in the face of accumulation of negative randomization in the epigenetic environment (see Chapter 14). This can be reﬂected in the dichotomy between ‘‘upstream’’ versus ‘‘downstream’’ mutations in the epistatic cascade, in terms of the probability of a positively selected outcome occurring (Fig. 63). The known facts concerning decanalization, genetic assimilation, and the phenocopy mechanism all appear to conﬁrm a natural limit to a saltatory realization of adaptive potential. Epigenetic noise clearly has to be minimalized, if protropism and neotropism are to ascend in the context of an evolving genetic system. The most ‘‘hopeful’’ mutations seem intrinsically likely to be ‘‘downstream’’ ones, and incremental change thus appears the most viable route to evolutionary neomorphism: Raff’s (1996) overview of pathways of evolution holds that master regulators are generally conserved, with changed patterns in their regulation leading to new domains of expression or to changes within the existing domain—or with conserved patterns of expression leading to changed downstream gene activity. Thus, actual changes in master regulators tend not to be involved. Translational Allotropism, Saltation, and Concerted Change The problem of negative pleiotropy in epistatic systems would seem to preclude any consideration of a saltatory origination of novel morphosystems and to demand an incremental, iterative progression between adaptive capacity and potential. Novel (qualitative) mutations may be expected to create negative pleiotropic effects demanding adjustment to gene-homeostatic systems, and

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FIGURE 63 So far as the phenogenetic component of development is concerned, a ‘‘remote morphosystem’’ is unlikely to constitute a positive change other than in the context of incremental change, in that the latter strategy allows incremental homeostatic adjustment against negative pleiotropism.

this might even involve new higher translational factors evolving de novo, rather than via a reshufﬂing within existing systems. However, the question of ‘‘saltatory evolution’’ can be interpreted in different ways, and indeed, it could be taken to include also the question of incremental but ‘‘concerted’’ modiﬁcation to whole suites of structural characteristics. Protropism and neo-

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tropism can involve more than a single effect of a given mutation, so that ‘‘incremental change’’ does not necessarily mean ‘‘one trait at a time’’: Thomson (1988) has argued that development is so buffered that the side effects of a large scale modulation to form may be compensated by secondary changes, such as those observed in the neuromuscular cascade facilitated through changing limb development. He reasoned that changes in one part are bound to affect changes in others, and such changes clearly will not always involve negative pleiotropism. Thomson further argued that assembling the suite of changes between Hyracotherium and Equus by chance accumulation of mutations that individually reduce the digits and reshape the whole limb would be a very lengthy business. The transition from the ﬁve- to one-toed condition can quite probably proceed at a rapid pace following the concerted change mode, since this is not dependent on ‘‘summation of thousands of minute changes.’’ According to Thomson’s hypothesis, ‘‘In terms of number of alleles ﬁxed, the initial change in any major phenotypic shift may well be of the same order as that required for a small microevolutionary change. . . . Whereas a large phenotypic shift that depended on the accumulation of millions of small variants each expressed in different species would require a large number of genetic events, a far smaller number is needed to achieve that effect by changing the control of early pattern formation mechanisms in morphogenesis.’’ Kay (1986) carried out experiments on mouse development in order to investigate the mutual interdependence of various skeletal and muscular character sets. It was concluded that the temporomandibular joint, bony zygomatic arch, middle ear ossicles, and mandibular muscle pattern form a more or less integrated set of developmental trajectories. The effect of vitamin A on chondrogenesis seems to be a key factor in this, with secondary involvement of myogenic tissue being due to the developmental link between skeletal and muscular elements. It was not known, however, how vitamin A alters chondrogenesis (nor, one might add, is it clear how this would ﬁt into the epistatic system controlling morphogenesis, in either a directly genetic or phenoplastic regime). Although positive links between chondrogenesis and myogenesis seem likely, it is also much less evident that interskeletal effects would not be grossly deleterious. Consequently, it would be reasonable to suggest that we should not overemphasize the capacity of translational allotropism to invoke saltational evolutionary change. Mu¨ller (1986) has shown that the interactive determination of skeleton and muscle is limited to certain stages of development, also that some component of this interaction is linked to the apparent atavistic recovery of ancestral states of reptilian grade in the chick embryo. As with Kay’s results, these ﬁndings would appear to add a note of caution to any overenthusiasm regarding the potential of translational allotropism to give rise to widespread neomorphic phenotype states in a manner that could be regarded as constituting dramatic saltational evolution.

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Some component of allotropic gene activity can clearly be intrinsically positive (protropic), suggesting that there are certain modes of developmental modularity which would allow ‘‘broader’’ mutational steps to be taken. Translational allotropism thus clearly offers a convincing rationale for a ‘‘small step–large domain’’ scenario. However, quite apart from the other limitations discussed above, this must be weighed against the fact that many structure integrals are complex assemblages, the subunits of which have had a sequiadaptive relationship to each other during the course of long-term evolutionary change. Many of these subunits contain complex biophysical design details which could not possibly be expected to evolve ‘‘saltationally,’’ even within the context of ‘‘concerted evolution’’: Vermeij (1974) discusses the concept of change in concert in terms of ‘‘correlative progression’’ (following Thomson, 1969), citing an example in the rhipidistian–tetrapod transition in the Devonian involving locomotory, respiratory, sensory, and feeding structures all changing ‘‘simultaneously.’’ This, however, seems an unnecessarily farfetched and highly unlikely extrapolation of the concept of ‘‘concerted evolution.’’ Furthermore, as argued by Carroll (1997), many apparent saltations tend to appear much less dramatic once the actual sequence of change has become better known. Maynard Smith (1983) has also drawn attention to the fact that good evidence exists to suggest that the difference between morphologically distinct species and varieties is generally a polygenetic one, rather than a major gene differential (see Chapter 18 for a discussion of this proposition). Thus, even the translational allotropic effects suggested by Thomson might also be presumed to evolve during periods of incremental change, when any negative corollaries can also be bypassed. The differential here thus seems to be one of ‘‘extent of lateral change’’ within the incremental strategy, rather than ‘‘saltation’’ in the sense of individually large steps being taken at any point. Herein lies a fundamental question concerning the mechanism of macroevolutionary change in adaptive systems that will be investigated more deeply in the analysis of homeostatic constraints to iterative change, namely, whether or not pleiotropic thresholds can be presumed to invariably operate also when iterative (or ‘‘concerted’’) evolutionary change is occurring (see Chapter 14). Other apparent examples of saltational evolution may actually involve a qualitative shift in a single morphogenetic parameter, which nevertheless constitutes only an incremental change in the genome. The threshold for such an event could exist at that point at which simple, stepwise extrapolation of a growth curve uncovers some intrinsic qualitative shift (as postulated by Oster et al., 1988; see above): One good example of ‘‘pseudo-saltation’’ of the above kind lies with the cheek pouches of pocket gophers and kangaroo rats. External pouches seem to have developed as a ‘‘threshold shift’’ from the internal type, owing to the effect of snout elongation. In this, we again observe a corollary arising from the modular structure of development: ‘‘threshold saltation’’ as a special case of translational allotropism of the ‘‘concerted’’ kind proposed by Thomson (see above).

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The question is, of course, do morphogenetic shifts of the above kind actually explain the origin of higher groups? The answer to this question lies in looking at the progenitor states of various evolutionary lineages and considering whether or not evidence exists for a true, compound qualitative adaptive shift at time of origin as distinct from mere ‘‘pseudo-saltation.’’ In general, the former condition does in fact seem to be the norm, and sudden qualitative shifts of the ‘‘threshold’’ kind seem only to involve minor traits (for example, from right-hand to left-hand coiling in mollusc shells). Again, the ‘‘transmutation’’ hypothesis sometimes assumes that the developmental mechanisms concerned with supposed saltation are exactly described by the geometric parameters in question, which is improbable. A rationalization of the term adjacent morphosystems would now be that ‘‘afﬁne morphogenetic transformations’’ form a special subset of the same, in which ‘‘adjacency’’ refers not only to geometric but also to genetic translational coordinates. Adjacent morphosystems must therefore lie at the high end of the probability distribution for the positive selectivity of mutations.* Epistatic Feedback, the Accommodation Principle, and the Loci of Adaptive Potential As we saw in Chapter 9, the trajectory between fabricational and adaptational paradigms of development is topologically accommodative, rather than being abruptly ‘‘end to end.’’ In a similar context, it is furthermore erroneous to think of a complex anagenetic increment being made by ‘‘terminal addition’’ to an existing phenogenetic sequence. Any change at phenotype level has to be organized from the starting point of some precursor state, which means that other adjustments to the trajectory will probably have to be made at the same time. Aside from the question of ‘‘concerted evolution’’ via translational allotropism, there may alternatively be mutational change carrying widespread effects within the temporal sequence of a single morphogenetic trajectory. In this situation, the probability of an early developmental parameter being changed with no effect on later horizons is clearly a function of the degree of ‘‘vertical’’ (temporal) modularity. ‘‘Upstream’’ mutations are thus intrinsically likely to encounter greater resistance than ‘‘downstream’’ ones, being causal to accumulation of ‘‘downstream’’ misalignments as a manifestation of epistatic feedback according to the modular structure of the developmental trajectory in question. The accommodation principle is now additionally linked to a proposal that simple morphogenetic transformations form the most probable steps of incremental change, and that such modiﬁcations must have effects within a certain segment of a morphogenetic trajectory. Accommodation therefore has both ‘‘static’’ and ‘‘dynamic’’ dimensions, for development and evolutionary change, respectively. Incremental change is thus a more likely strategy than saltation with respect to the accommodation principle, in view of the temporal distribution of negative pleiotropy in epistatic feedback that must often be required to be bypassed in order to allow anagenetic change affecting temporally contiguous parameters of the same developmental trajectory. * Of course, some adjacent systems (such as the external cheek pouch trait) are not necessarily geometrically adjacent in the usual sense of mathematical afﬁne transformation.

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The principal biophysical paradigms of development must particularly act to place limits on the higher coordinates of adaptive potential. Of these, the constraints inherent to the phylotypic stage seem generally to present an obstacle to change, and the accommodation mechanism thus probably acts mainly through the lower coordinates of later ontophenogeny (see Chapter 10). Thus, ‘‘downstream’’ loci are best suited to the strategy of morphogenetic transformation. Here, translational allotropic effects may tend to support ‘‘concerted change,’’ on the one hand, and to generate a more transiently active pleiotropic impediment, on the other. The above arguments cannot of course be taken to totally exclude more deeply rooted patterns of change, and examples have been claimed particularly where duplication or reduction of repeated structures is involved, in certain categories of morphogenetic transformation in which downstream effects seem much less likely to create catastrophic disharmony: Thomson (1988) observed that loss of an element from the tetrapod limb can occur through changes at different levels. When a new form appears, this can also occur at several levels, but the greater the change, the earlier the level has to be. For example, new branching or segmentation of the skeletal blastema is impossible at the ossiﬁcation stage and unlikely at the chondriﬁcation stage, since new ossiﬁcation cannot occur without a new cartilaginous blastema. Small scale, late developmental changes thus can never accumulate to produce major modiﬁcations of morphogenetic pattern, and such changes cannot be ‘‘terminal additions.’’ In this example, we must also presume that accommodation is a necessary prerequisite for operation of mechanisms of this kind, but that this is probably ‘‘minor–lateral’’ (spatial ) rather than ‘‘major–vertical’’ (temporal ) in nature. Bottom-Up and Top-Down Strategies in the Epistatic Function Model Changes to the Boolean functions in epistatic systems must lie behind transformation to adjacent morphosystems, particularly since canalizing functions in Boolean networks are presumed to sequester negative alternative systems from expression in the phenotype (see above). Adopting the on/off switch model of the Boolean network as the simplest system, we can see that a given regulator gene may mutate in such a way that it is activated earlier or later in the developmental cycle, or it may alternatively accelerate or decelerate the output of other genes affecting growth rate as a result of hypo- or hypermorph mutation. Clearly then, changes at the regulator level could be due to modiﬁcations to the structure of the Boolean network, where on/off activity is shifted or reversed, or where additional switch genes have been incorporated into epistatic systems—a generalization which must be true in either the presence or absence of the duplication–divergence scenario. We must now continue to pursue the question of whether the changing architecture of positively selected modulations in epistatic systems tends to follow a ‘‘top-down’’ model (the genetic control system being altered incrementally from highest members of the regulatory hierarchy downward) or a ‘‘bottom-up’’ strategy (in the opposite orientation). This question is clearly of

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importance with reference to the dichotomy between quantitative and qualitative modulation, since as we have already seen (Fig. 63), that boundary is particularly likely to concern position of a mutation in a convex epistatic hierarchy rather than degree of mutation or quantity of gene product (a question that is again equally relevant, give or take the presence of duplication or co-option). If we portray an epistatic function such that the temporal hierarchy reads from left to right (input i1 ⬎ i2 ⬎ i3, etc.), then it is easy to see how the bottom-up mutational model compares and contrasts with the top-down one, in consideration of the much greater accumulation of ‘‘knock-on effects’’ in the wake of ‘‘upstream’’ misalignment.

FIGURE 64 Bottom-up and top-down strategies of mutational change in epistatic functions. The mutation at i2 effectively changes all succeeding interactions, so that downstream genes have effectively 0 inputs.

The Boolean function model clearly conﬁrms that neotropic mutational change should tend to lie with the bottom-up model, since this avoids both traumatic change and associated negative ‘‘downstream’’ effects (as indeed we have already proposed above, with respect to the accommodation principle). It thus seems most likely that quantitative (protropic) effects involving minor regulatory mutations only will tend to occur when located toward the ‘‘upstream’’ end of the epistatic hierarchy, since larger changes at this position are more likely to cause traumatic negative effects. Thus, in that domain, only iterative–incremental reorganization avoids epistatic feedback and promotes harmonious major change within the epistatic system. The bottom-up model is, of course, inherently ‘‘incremental,’’ illustrating why ‘‘downstream’’ mutations generally constitute the ideal strategy for morphogenetic accommodation. As a general rule then, qualitative change seems most likely to be linked to the strategy of incremental modulation to the epistatic hierarchy. The most signiﬁcant conclusion to be drawn from this analysis is that a range of ‘‘bottomup’’ type mutations is likely to be associated with relatively simple morphogenetic transformations, and the latter must be seen as the most probable anagenetic step containing a facility to transcend adaptive capacity in realization of adaptive potential, in the gradual shift from a quantitative to qualitative mode of change through iteration. A further proposition that has already been made in the present chapter is that the most radical qualitative changes probably occur as new epistatic systems evolve through neotropism, emerging ﬁrst as ‘‘ﬂat’’ systems, then evolving incrementally toward the ‘‘convex’’ state (namely, via the bottom-up model). A neotropic origin for new ‘‘ﬂat’’ epistatic systems possessing the adaptive potential to become ‘‘convex’’ thus constitutes the most viable incre-

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mental scenario for the largest scale transitions, qualitative morphogenetic changes arising through iterated mutational events of this kind. To what extent this can occur in a more saltational manner is a question that will have to be examined in the context of homeostatic impediments to evolutionary change, and then we shall also be concerned with the question, ‘‘How small is incremental?’’ A very important question concerning the pathway between quantitative and qualitative mutation as convex systems arise from ﬂat ones is that we must clearly also consider the role of gene duplication in neomorphic change. It has already been proposed that duplication is linked to the origin of new epistatic systems, since this is the only way in which divergence of gene function can be achieved while negative pleiotropy is at the same time brought under homeostatic control, and it thus seems likely that duplication must be of particular importance in the neotropic situation. ‘‘Flat’’ systems are essentially additive multifactorial gene sets. Assuming gene duplication as a basis for expansion in the latter domain, then ascending levels of modiﬁer action within different duplicates presumably sculpt convex systems from a ‘‘ﬂat interactivity’’ strategy of that kind, so that more complex anagenetic change in structural phenotype parameters may be linked to duplication in this scenario. In the scheme proposed above, the highest ‘‘upstream’’ TRANS-acting genes such as the maternal (and perhaps also earliest acting zygotic) genes studied in Drosophila (see Fig. 48) most probably only become involved in evolutionary change once phenotypic modiﬁcations have already occurred via mutations of more ‘‘downstream’’ loci. The mutational role of such genes would then be restricted to lower translation in ontogeny alone, namely, where downstream effects are buffered by an evolved temporal modularity. To what extent this restriction might also apply to some of the earlier acting zygotic genes is not clear, especially in view of the known role of the homeotic genes in evolutionary innovation involving duplication–divergence (see below). Neotropism in Mutation of Hox Genes Quite apart from the question of the ascendency of ‘‘convex’’ epistatic systems from ‘‘ﬂat’’ ones, it is also possible that more dramatic mutations of higher level supratranslational regulatory genes may be tolerated, especially in those genes involved in the programming of repeated structure units. Some epistatic systems have been claimed to have originated through ‘‘saltation’’ in this manner, particularly through duplication of a Hox type gene cluster, and evidence thus apparently exists for quantum neotropic change of a kind which appears to bypass the bottom-up option: Comparing different phyla of Metazoa, extra segments and other body regions seem to have arisen through duplication of Hox clusters. Similarly, reductional transformation via a reduced zone of expression of ANT-C seems to have occurred in Insecta compared to Crustacea (Averof and Akam, 1995). The state of the morphogenetic ‘‘substrate’’ must clearly be of importance when there is neotropic expansion of gene expression, in that the outcome of

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such a mutational event must clearly depend on what is already happening in the affected morphospace: Morphogenetic receptivity clearly tends to equal 1.0 for such mutants as bithorax and antennapedia, although there are, of course, different degrees of penetrance for phenocopies of homeotic mutations, depending on what other epigenetic interactions are already extant (see Ho et al., 1983; also see Kauffman, 1993). Partial and/or progressive expansion of the domain of expression of a convex epistatic system may thus provide the foundation for a neotropic system moving from the ﬂat to convex state, given the appropriate morphogenetic substrate. However, this raises the question as to whether duplication of a Hox cluster could actually directly mediate a saltational event. Given the problem of massive negative pleiotropy, it may alternatively be that duplication actually follows a more gradual ingress of an increased zone of expression, and we must therefore beware of the naive interpretation that duplication of a Hox cluster automatically identiﬁes a saltational event. In this situation, presence of that category of morphogenetic receptivity linking to a positive adaptation interface has to become a major prerequisite. This problem will need to be investigated further in connection with the relationship between impediments to evolutionary change and the nature of morphogenetic receptivity itself (see Chapter 14). It must also be added here that ambient evolutionary change must more generally happen in genes ‘‘downstream’’ of the Hox clusters, since most observed modiﬁcations to phenotype form are neither heterotopic nor neotropic in nature, large scale reductional or duplicational transformations and major spatial shifts being obviously of rare occurrence in Nature (see Chapter 16). The question of the ascendency of ‘‘convex’’ epistatic systems from ‘‘ﬂat’’ ones and the role of gene duplication in this will be examined further in the next two chapters, when we come to consider the nature of the genomic source for evolution of new epistatic systems and also to examine viable means of release from impediments such as pleiotropism.

Genetic Mechanisms of Morphogenetic Transformation Irrespective of whether evolutionary change is incremental or saltational, it is clearly of interest to try to match mode of phenotype change with type of mutation. The degree to which this is possible is, however, extremely limited. This observation is due to the nature of the developmental program itself, which appears only to manifest simple geometric coordinates of the analog kind in the earlier horizons of true ontogeny. Time Shift, Rate Change, and Polytropism What do ‘‘downstream’’ supratranslational regulator mutations of protropic or neotropic status actually do to the coordinates of morphogenesis in the context of incremental change? It is possible to postulate, in very general terms, the types of genes which seem likely to be involved in mutational events linked to realization of adaptive potential, although it is at once clear that

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mutations affecting morphogenetic change may in fact operate in quite diverse ways, even with respect to similar phenotypic outcomes. Infratranslational genes may well express linear hypo- or hypermorph activity in terms of purely quantitative effects. However, supratranslational regulators seem intrinsically likely to fall into two major categories of mutational activity, the particular behavior of which must imply signiﬁcant links to the level of associated evolutionary phenomena: • Temporal shift type • Rate change type Kauffman (1993) observed that a time shift may result in greater duration of growth through high epistatic control, but that the same effect could also occur as a result of acceleration of mitosis due to mutations in genes of lower epistatic status: Known time shift mutations include those observed in Caenorhabditis elegans (Ambros and Horvitz, 1984; also see Horvitz, 1988). These lie in the lin-4 and lin-14 mutants, certain of which retard development, causing supernumerary larval molts and nonsecretion of adult cuticle. Other gene loci manifest the opposite tendency. These genes are thought to control the concentration of some substance such that the concentration decreases as a function of time, high concentration specifying acceleration, low, retardation of growth. Time shift and rate change mutations may in fact be easily confused as ‘‘heterochronous,’’ in that their end effects may be identical (see also Chapter 16). Rather more seriously, many morphogenetic changes cannot be reduced to either of the above-mentioned models. In addition to the time shift and rate change mechanisms, a group of cells may simply become longer and narrower, not through any growth differential, but via some positional alteration to their mutual arrangement, which might in turn be inﬂuenced by changes in adhesiveness (see Waddington, 1966). In this context, it is easy to see that there are potentially very many conﬁgurations in the developmental program that could give rise to changes which could be interpreted as ‘‘time shift’’ or ‘‘rate change,’’ but which might in reality have originated through altogether different mechanisms. The most obvious conclusion to be drawn from the above observations on the likely genetic mechanisms underlying morphogenetic change is that the nature of a mathematical (geometric) transform may often be nonhomologous with its morphogenetic equivalent in terms of fundamental developmental mechanisms, the only exception to this rule lying with certain restricted modes of developmental modularity (see Chapter 16). This might be said to identify a ‘‘polytropism law’’ for pathways of morphogenetic change, which hypothesis can be exempliﬁed in view of the rarity of biotic systems expressing ‘‘gnomonic growth’’ (see Chapter 7), namely, in that in the majority of examples, when one form is transformed into another, there will be more than one way of carrying out a given transformation. Simple extrapolation of existing growth parameters may in fact often give rise to adverse change of form (in strong contradistinction to the logarithmic spiral example). This fact is presumably

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also a reﬂection of the digital coding which underlies complex morphogenetic coordinates for more ‘‘downstream’’ phenogenetic activity. As already discussed above, positively selected structural change has the highest probability of occurring in relation to changed structures which have a close topological (geometric) relationship with the morphosystem from which they were derived. However, it is now seen that many pathways may often exist for the expression of even relatively simple afﬁne morphotransformations of the parent state. The general picture with respect to such patterns of change may often manifest ‘‘polytropism,’’ and should not be presumed to be subject to simplistic interpretation in terms of time or rate shift alone. Mutations affecting growth rate or duration may well of course be included among those of special signiﬁcance in generating morphogenetic change, especially of the quantitative kind. However, the mechanisms through which growth changes occur may, as we have seen above, be quite diverse. Mutation may thus not only affect endogenous programs for rate and magnitude of growth for a given morphogenetic object, but could also alter external morphogenetic coordinates, responses to which might lie in cell movement, adhesion properties, shape change, and so on. The type of change involved in this could be ‘‘how a regulator acts’’ or else ‘‘a changed reaction to regulation.’’ Such changes could (for example) be organized around induction systems, either through a decrease or increase in the inductive signal, or through changes in the response to unchanged signals (or by a combination of more than one mode of activity). In this situation, not only are the morphogenetic ﬁgures of evolutionary change ‘‘agnomonic,’’ but also quite similar changes may occur in relation to nonhomologous epigenetic interactions. Accordingly, it has to be assumed that the ﬁgures of afﬁne morphotransformation are polytropic, in terms both of stimulus and of response! The Developmental Role of Downstream Mutations in Realization of Adaptive Potential As has already been suggested above, most changing phenogenetic coordinates are manipulated downstream of the Hox gene clusters, and the coordinates of adaptive potential must generally lie there also. At the present time, much interest is being focused on investigation of a class of realizator genes which constitute the presumed targets of homeotic genes in Drosophila, functioning to form speciﬁed tissue or organ primordia. The salm gene (WagnerBernholz, 1991) seems to be an example, as is Distal-less (see Gilbert, 1997). These particular examples are involved in formation of leg tissue, although the exact means through which activation of genes of this type creates the three-dimensional shape of a developing organ or appendage is not yet fully understood. Following on from the above discussion concerning the diversity of ways in which mutation may act, we can also visualize a very wide domain for the activity of downstream regulators affecting morphogenesis. A developing tissue module speciﬁed by selector genes may subsequently manifest complex morphogenesis on the basis of an internal program controlling cell growth and mitosis, and this program may be differentially organized in different morphozones of an originally homogeneous substrate (for example, a sheet of undifferentiated

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epithelium). The subsequent shape of this developmental module is clearly affected directly by the endogenous genetic program in question, as well as by intrinsic mechanical properties (which latter may, for example, cause a coplanar structure to bend or twist—i.e., extending the Oster model to the tissue level; see p. 186). In addition, we must assume that this developing structure also acts on received information in the form of inductive signals arriving both from adjacent cells and tissues and from more distant signal originating sources such as the endocrine system. The true coordinates of adaptive potential probably do not therefore lie with simple analog coordinates of the kind laid down by TRANS-acting determination factors of early development in Drosophila, but rather in the indirect way in which a complex interactive morphogenetic program relates to emergent phenogenetic coordinates, a view which effectively separates onto-anagenetic from pheno-anagenetic evolution. To what extent can we generalize from the Drosophila model? While very many of the above conclusions probably do apply very widely, it is evident that other developmental systems may differ greatly from that of Drosophila, even with respect to quite fundamental characteristics. In comparison, the nematode Caenorhabditis elegans has four Hox genes that are expressed in the embryo, but with main effects in postembryonic development, namely, in the larval stage. The C. elegans Hox genes also seem to be turned on and off at different times, unlike the ‘‘selector’’ genes of Drosophila. In addition to the different functioning of the Hox genes, cell-to-cell interactions are involved in axis speciﬁcation in the nematode system. With reference to chordate development, some vertebrate signaling systems which seem to be morphogen controlled have not actually been linked to any identiﬁable agent of that kind. Given these and other questions and differences we should not be overconﬁdent in extrapolating too widely from Drosophila to other lineages, other than with the few broad generalizations offered above.

MAIN POINTS FROM CHAPTER 12 1. Adaptive capacity is concerned solely with changing gene frequencies in existing allomorphic loci, while adaptive potential is linked to true neomorph mutation. 2. Evolutionary change in structural traits is linked to mutation of regulatory genes affecting morphogenesis. 3. The concept of morphogenetic potential is linked to the diversity of ways in which temporospatial expression of a supratranslational regulatory gene can change through mutation. 4. The effects of neomorph mutation in allotropic genes are of special interest for realization of adaptive potential. Pleiotropy can be usefully redeﬁned, in this context, as the purely negative effects of mutation in allotropic genes. The positive effects of such mutations can be visualized as being either protropes (expressed within the original allotropic domain) or neotropes (constituting an extended domain of determinative activity). 5. The selectional value of a given mutation is a function of the net contribution to ﬁtness of n multiple effects, and its leading effect lies in the highest

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protrope or neotrope. A pleiophore is any mutational effect that is perpetuated solely because of net positive pleiotropic balance. 6. Much evolutionary change ultimately stems from protropic mutational effects involved in endogenous change within preexisting morphogenetic modules. However, major transitions must originate in neotropic change, where new modules come into being. 7. Gene duplication/co-option is a universal element in evolution, owing to its links with the origination and functional divergence of new epistatic systems, combined with capacity for adjustment of pleiotropic balance. 8. Genic substitution at an allelomorphic locus must be distinguished from genic occlusion. The latter constitutes the addition of new ‘‘upstream’’ regulatory genes to an epistatic system, generally in the context of combined neomorph mutation/gene duplication in the supratranslational domain. Phyletic occlusion occurs when there has been iterative genic occlusion. 9. Epigenetic noise arising from randomization of developmental interactivity constitutes the ultimate source for any expansion of realized morphogenetic potential. Despite the fact that most epigenetic noise will tend to be pleiotropic, this is also the route to realization of adaptive potential. 10. Owing to a general preponderance of pleiotropism, epigenetic noise is usually buffered by canalizing functions in Boolean networks or by other high-level control systems. The homeostatic activity of canalization is responsible for both ‘‘vertical’’ and ‘‘lateral’’ modularity in a morphogenetic trajectory, and is consequently also linked to degrees of freedom in adaptive potential. 11. Change to developmental modularity must often be necessary for realization of adaptive potential, and this can only occur via decanalization. This can be understood through such mechanisms as a passive proliferation of ‘‘off’’ switches in Boolean networks. The effects of this are qualitatively different for mosaic as against regulative strategies of development. 12. Decanalization may unmask an initially broad lability to diverse determination factors, but pathways of determination must ultimately gravitate toward the genetic component in the context of evolutionary change. These factors are clearly manifest in the phenocopy and genetic assimilation mechanisms. 13. Most evolutionary events tend to favor incremental change in the context of afﬁne morphogenetic transformation to adjacent structural states. The possibility of more ‘‘saltational’’ steps occurring must be considered in relation to the opportunity offered by positive pleiotropic balance or by translational allotropism. 14. Protropic mutational change seems most likely to occur with midlevel regulatory genes rather than in ‘‘master’’ (top-level) regulators, whereas neotropic modulation may occur through a ‘‘bottom-up’’ reorganization of lower level regulators in the building of new ‘‘convex’’ epistatic systems from ‘‘ﬂat’’ precursors, frequently in the context of gene duplication and functional divergence linked to developmental co-option. 15. ‘‘Saltational’’ change might be postulated to occur under certain circumstances, as, for example, by direct duplication of Hox genes. However, the latter route seems intrinsically more likely to occur through ontogenetic

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adjustment following on from a more incremental expansion of ‘‘downstream’’ gene expression. 16. Although it appears that the role of many genes involved in neomorphic change could be interpreted in terms of temporal or rate shift mutations, mode of mutational change and outcome at the level of geometric coordinates do not necessarily have a one-to-one relationship, with the possible exception of onto-anagenetic trends and certain restricted modes of change that are linked to high developmental modularity. 17. The dichotomy between early analog and later digital determinative strategies underlies the ‘‘polytropic’’ nature of the way in which mode of mutation relates to phenotype effect.

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In what manner are adaptive capacity and potential reﬂected in the actual physical organization of the genome? The question of adaptive capacity seems to relate naturally to the phenomenon of recombination, long known as the basis for the Mendelian laws of heredity, as shown by the proven link between allelomorphism, the morphology of the chromosome, and the behavior of the latter during meiosis. The facility for organization and reorganization of genetic material on the chromosome has been described in terms of linkage, which mechanism can, however, be shown to derive from more than a single causal factor. The connection between adaptive capacity and stored genetic information is a special propensity of higher organisms, and this constitutes a fundamental difference compared to the situation found at the unicellular level of organization (Stebbins, 1988). In the ensuing analysis, we shall examine further evidence of the deep schism between adaptive capacity and potential in adaptive systems theory, a situation which clearly relates in turn to the differential between adaptive equilibrium and true evolution. In this, we shall have cause to reexamine that special theory centered around the neo-Darwinian synthesis constructed by Fisher, Haldane, and Wright in the earlier part of the twentieth century.

SELECTIONAL FORCES CONTROLLING THE CELLULAR DISTRIBUTION OF GENETIC MATERIAL That the physical organization of genes is clearly partly concerned with the question of epigenetic interactivity is shown by certain aspects of the physical

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distribution of genetic material within the intracellular architecture (as in the cis/trans-regulation system; see Chapter 10). We must, however, consider also the fate of gene allelomorphs in the context of a ‘‘mobile’’ genome structure, the architecture of which is correlated with the nature of a dynamic selection interface, and where some component of chromosomal organization must be separately correlated with facilitation of adaptive equilibrium. It would thus seem self-evident that chromosomal organization derives from two independent mechanisms: facility for recombination (as suggested by the Mendelian model) and facility for genetic interactivity (as evidenced by the requirements of cellendogenous regulation factors). The effects of these inﬂuences are clearly convergent in terms of the way in which they favor particular arrangements of genetic material with respect to chromosome structure. As a consequence, these two independent mechanisms have in fact generally been confused inter se in the past. We have thus identiﬁed two quite independent major factors apparently inﬂuencing the physical organization of genetic material on the chromosome: facilitation of interactivity at the molecular level (for either ‘‘ﬁxed’’ or allelomorphic genes) and coselectivity at the level of the phenon for allelomorphs involved in adaptive equilibrium, where propensity for recombination is clearly the target mechanism.

Linkage as a Corollary of Two Mechanisms Affecting Positional Assignment of Gene Loci Sutton (1903) used the term ‘‘linkage’’ for genes situated on the same chromosome. Linkage can now be understood as constituting the convergent corollary of two inﬂuences affecting assignment of gene loci to chromosomal position. Where locus positioning is due to the demands of recombination, this constitutes recombinatory assignment, and where it is affected by the demands of gene

FIGURE 65 Linkage as the convergent corollary of two mechanisms affecting locus assignment.

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regulation, this is regulatory assignment. Both regulatory and recombinatory assignment can be manifested in either dispersive or condensate distribution (respectively, gene loci distributed widely among different chromosomes or aggregated together on a single chromosome). In regulatory assignment, the dispersive distribution is clearly passive (i.e., when locus position has no effect on facility for regulation), whereas in recombinatory assignment it is active (e.g., when n loci lie on separate chromosomes in order to facilitate random recombination with other loci).

The Recombination Cluster and Linkage Group Concepts We have now distinguished between two fundamentally different forms of behavior affecting linkage in gene-developmental systems. Not all genetic organization is concerned with developmental gene interactivity in the context of epistasis, since the way in which genetic material is physically organized on the chromosome can also be shown to be partly an adaptive response to the structure of a dynamic selection interface. The Recombination Cluster and the Supergene Concept The architecture of the selection interface determines the preferred recombination proﬁle for all allomorphic genes, and this may clearly run from 0 (no recombination) to 1.0 (random recombination), depending on the temporospatial structure of the selection interface in question. At an earlier stage, we saw that a supergene constitutes an interactive gene complex, components of which may or may not manifest ‘‘linkage’’ (Chapter 10). However, the latter term has, as we have just seen, also been used to describe the inﬂuence of two quite different mechanisms affecting chromosomal organization. Clearly we must now distinguish between the true supergene unit and the ‘‘tight’’ recombinatory linkage group (where coselectivity favors a recombination factor of 0), both of which have confusingly been termed ‘‘supergene’’ in the past. That mechanism involving the grouping of gene units which share a common selection interface and thus tending to be inherited as a single unit within the scheme of recombination will be termed here the recombination cluster, since the mechanism lying behind such gene aggregation is not that of epigenetic interactivity within the context of a single (true) supergene, but the need to inherit certain coselectionally favored genes as a discrete unit (a mechanism which clearly removes the oft repeated complaint that recombination ‘‘destroys useful gene combinations’’!): The polymorphic mimetic butterﬂy Papilio memnon has ﬁve loci affecting a coselected group of traits. Even if these genes evolved ‘‘dispersively’’ (bearing in mind the manner in which their ‘‘linkage’’ can sometimes be broken and rare recombination types uncovered), there has clearly been selection for close association of gene units in order that the entire gene complex is always inherited as a single structure. This gene assemblage is therefore not a ‘‘supergene,’’ but a recombination cluster (nor, indeed, is ‘‘epistasis’’ an appropriate term for the selectional forces favoring association of these loci).

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The above proposal is a natural outcome of the reinterpretation of ‘‘classical linkage’’ as the convergent corollary of two mechanisms, of which the recombination favoring element affects the chromosomal distribution of allelomorphic genes belonging to discrete phenons. Exogenous selectional demands met by recombinability are thus concerned with matching gene frequencies with the temporospatial distribution of niche parameters in the context of the recombination cluster, whereas endogenous mechanisms in the gene regulation system control interactivity within (true) supergene units. In general, it will be found advantageous to dismember the former usage of ‘‘linkage’’ in the manner proposed above, in that it is difﬁcult (and indeed, confusing) to discuss function in relation to an entity that is not only an emergent property of a process or mechanism, but of more than one such inﬂuence. It is also evident that ‘‘ﬁtness epistasis’’ really constitutes coselectivity with respect to ‘‘false’’ supergene clusters such as that of P. memnon. Recombination and Adaptive Capacity in Dynamic Equilibrium Recombination as facilitated by sexual reproduction is clearly not related to such differentials as the biophysical paradigm nor to autonomy of the structure integral, but is in part a homeostatic response to anisotropic selection interface structures of the external environment, its principal functional being the subdivision of chromosomal material to create discrete units capable of expressing a greater or lesser degree of independent assortment (in the range 0 씮 1). The function of chromosome formation is, in this context, partly that of facilitation of recombination (or its prevention), as required. Despite the frequent claim that there is no respectable evidence for mechanisms capable of maintaining evolutionary plasticity of the genetic kind (see Williams, 1966), sexual reproduction in combination with the physical organization of allomorphic genes on the chromosome does in fact accomplish this, albeit with respect to adaptive capacity in dynamic equilibrium (rather than in the longer term evolutionary sense with which Williams was presumably concerned). As with our view of the gene pool as ‘‘epicenter of adaptation,’’ this capacity emerges as a corollary of mechanisms working at the individual gene level, and it is not necessary to invoke ‘‘selection acting with respect to forward looking propensities of the genome’’ in relation to this.* Recombination provides the means by which parameters of a ﬂuctuating external environment can be approximately matched with the changing boundaries of the gene pool, so forming the principal mechanism for realization of adaptive capacity with respect to an anisotropic selection proﬁle manifesting some element of stochastic behavior. The required contingent of recombination may of course also act as an opposing force against ‘‘linkage,’’ and is then causal to division of chromosomes, as well as to the crossing-over mechanism. In the latter respect, the recombination cluster clearly constitutes a manifestation of this ‘‘antirecombinational’’ force. The active response to the anisotropic selection interface is thus the recombination system, operating via the meiotic behavior and bipartite structure of * Quite apart from the generation of novel gene combinations, recombination effectively prevents the accumulation of slightly deleterious mutations, as demonstrated by ‘‘Mu¨ller’s ratchet’’ (see Maynard Smith, 1998, for a discussion).

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the chromosome, and recombination thereby facilitates the necessary ﬂuidity in adaptive capacity expressed in the fecundity offset strategy (see Chapter 5). Homeostatic systems linking to a varying selection interface lying in the external environment have, indeed, already been implicated in the selective offset of fecundity, and were examined in relation to the link between adaptive capacity and adaptive equilibrium (Chapter 5). Additionally, recombinability itself must be under genetic control: Discussing the question of evolution of recombination, Maynard Smith (1998) found clear evidence of selection acting in some cases in favor of increased recombination, and sometimes for the converse situation. Mechanisms for the readjustment of chromosomal architecture are known to exist. Transposable elements are genes which move from one part of the chromosome to another, modifying the activity of other genes, some being known to inﬂuence crossing-over frequency. Finally, it is assumed here that any losses incurred in sexual reproduction (as in ‘‘wasteful production of males’’) are offset by compensation for a high level of dynamism in the anisotropic selection interface, with the formation of recombination clusters acting against any negative corollary of recombination itself (see above). Regulatory Positional Assignment and the Supergene Unit: The Regulation Cluster Following on from the above deﬁnition of the recombination cluster, it must also be held that regulation clusters also exist, where linkage is affected through such requirements as those favoring cis-regulation between gene loci of a supergene. While in some instances extremely tight regulatory linkage may be demanded (as shown by members of the homeotic genes), it seems, however, likely that not all regulatory linkage can be explained in terms of cis-regulation, as this is generally understood: The human globin genes are sequentially ordered on the chromosome, following the embryonic 씮 fetal 씮 adult sequence for activation. In a similar example, Maynard Smith and Szathmary (1995) discussed the view that the existing evidence appears not to support simple cisacting regulation with respect to the observed sequential ordering of Hox genes. However, these authors nevertheless concluded that some functional sense probably exists in this (see also Gerhart and Kirschner, 1997). Raff (1996) also states that the collinearity of Hox genes is not due to their functioning as a single regulatory unit, suggesting in addition that the evolutionary conservation of Hox gene order could be an artifact due to small sample size. Regulatory assignment is thus concerned with genes closely associated on the chromosome owing to cis-regulation or to other endogenously active mechanisms of gene regulation, the nature of which latter is not yet fully understood.

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Convergence between Regulatory and Recombinatory Positional Assignment We must clearly beware of confusion between regulatory linkage and propensity for locus association correlated with recombination requirement. Regulatory assignment is concerned with facilitation of endogenous interactivity between different genes and between different functional units within a single gene locus. This is one aspect of ‘‘tight linkage,’’ whereas ‘‘loose linkage’’ is in reality a function either of partial locus association or of passive dispersion, so that the recombination requirement constitutes a force either mimicking or else acting antagonistically to that favoring ‘‘tight’’ regulatory linkage. Where coselective correlation is absolute, the requirement for recombination will obviously tend to 0 (and thus, also, linkage 씮 1). The subdivision of chromosomes is a special case of the recombination drive, and the recombination cluster is, in this context, the opposite expression of the same force, having no correlation whatsoever with linkage factors demanding endogenous functional interactivity. Most signiﬁcantly, the components of true supergenes (epistatic systems) clearly do not necessarily have to be ‘‘linked’’ at all. However, it is also untrue that physical linkage and ﬁtness relationships are conceptually distinct (as suggested by Ridley, 1993), since recombinatory linkage is clearly tailored to adaptive equilibrium.

Dispersive versus Condensate Models of Genome Organization A condensate model of genome organization is one in which the members of a gene set are approximated on the same chromosome owing to the demands either of regulatory or of recombinatory assignment. In the dispersive model, the distribution in question has either been actively ordered (recombinatory assignment) or else it is ‘‘passive’’ (in terms of no demand from regulatory assignment). As we have seen above, a fundamentally dispersive model for genome organization would actually predict a demand for both recombinatory and regulatory assignment, on the basis of the link between adaptive capacity and selection proﬁle, and in correlation with the functioning of genetic mechanisms of determination, both of which would favor the chromosomal model of genome organization. Some genes may follow the dispersive model (a) when no cis-activity is involved or (b) where dynamism in the selection proﬁle favors ‘‘locus dispersion.’’ This situation clearly appertains in particular to additive loci of low contribution to ﬁtness and with no need for regulatory linkage. Mather and Harrison (1949) observed that polygenes for abdominal chaeta number in Drosophila are distributed more or less equally on all the chromosomes, quoting similar results for sternopleural chaeta number, viability, and egg production (see also Mather and Jinks, 1971). Similarly, it has also been noted that microscopic studies show that genes which function together are not necessarily grouped but may be spread around the chromosomes. A dispersive model of genome organization may often, in fact, seem to be the relevant response to an isotropic selection interface. Since there is a single,

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ﬁxed biophysical paradigm in this situation, there is no reason why genetic material should be arranged so as to permit variable patterns of inheritance through perpetuated allelomorphism, unless, of course, cis-acting components of a gene favor linkage as a function of purely endogenous regulatory demands. Thus although the mechanisms of recombination and gene regulation clearly demand chromosomal organization, this is by no means a universal demand with respect to all gene loci.

The Recombination Cluster and Linkage Disequilibrium Owing to the functions of pleiotropism in evolutionary change, the dispersive model of locus assignment may perhaps be regarded as being the hypothetical progenitor gene distribution. At the same time, however, complex gene interactivity may very often demand close integration and therefore, also, tight linkage. ‘‘Dispersive’’ genes may then come to be ‘‘sorted’’ for the reasons discussed above, and these forces will clearly affect different loci to a different extent. The ﬁrst requirement of a dispersive system is that some members of epistatic systems originate externally to the original regulatory gene cluster. A second factor is that ‘‘dispersive’’ genes may often be ﬁxed, in the sense of having no allelomorphic state linked to a dynamic selection interface such that chromosomal position tends to become governed by the recombination factor. The third requirement is that dispersive gene loci are probably TRANS-acting, rather than cis-acting. Many gene units are thus highly likely to be ‘‘dispersive’’ in terms of their panstatic system, but not necessarily of their epistatic system, where regulatory assignment forces seem more likely to be in force, in view of the greater cis-acting behavior of gene units within a single supergene. In view of the preceding argument, the concept of ‘‘linkage disequilibrium’’ (Lewontin and Kojima, 1960) as a description of locus association can now also be seen to be unacceptable, in view of a revised concept of linkage itself. Clearly, recombination clusters such as the Papilio memnon and Cepaea ‘‘supergenes’’ are in coselectional equilibrium (not ‘‘linkage disequilibrium’’), owing to the presence of an active strategy of gene locus assignment on the chromosome, such that recombination frequencies are tailored to a common selection interface for n phenons. ‘‘Linkage equilibrium’’ should therefore not be taken to mean ‘‘randomly recombinable,’’ but the selectively appropriate degree of recombinability within the range 0 씮 1.0. Maynard Smith (1998) considered that ‘‘linkage disequilibrium’’ is favored only in certain closely circumscribed cases such as that of the allomorphic P. memnon supergene, and that ‘‘normalizing’’ selectional interactions give rise to such instances. Given the very large proportion of ‘‘polymorphic’’ variation known to exist in populations, it is reasonable to assume that only a limited proportion of this lies with leading effect selectional interactions linked to predictable recombinational behavior such as would frequently give rise to such close clustering of gene units as those of the examples cited. Coselectional Equilibrium and Anagenesis The ‘‘linkage disequilibrium’’ (coselectional equilibrium) component of locus distribution clearly has no relevance whatsoever to anagenetic change,

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since each new allelic substitution would in the latter instance be regarded as simply passing to ﬁxation before the next, in iterative sequence. The question of ‘‘recombinability’’ cannot therefore apply directly to anagenesis, nor to nonallelomorphic loci in general, since here cis-acting interactivity must have a higher proﬁle in determining locus assignment. The ‘‘lag’’ in reaching ‘‘linkage equilibrium’’ is in fact derived from the selective force causal to establishment and maintenance of that sector of the genome which is actively involved in adaptive equilibrium. This factor will tend to favor adjustment of recombinability, at least for alleles of high contribution to ﬁtness.

Adaptive Capacity and Hybrid Vigor As stated above, capacity for maintenance of adaptational plasticity is one function of the physical organization of genetic material on the chromosome. This leads naturally to the question of the hybrid state existing between chromosome homologs. Sexual reproduction and the meiotic behavior of the chromosomes may often tend to favor hybrid vigor (Chapter 5), and each of these phenomena are clearly mechanisms of the process adaptive capacity 씮 secondary adaptive equilibrium in the context of an anisotropic selection proﬁle, in that they are also linked to the mechanism of recombination. Hybrid vigor may be due to overdominance, where the hybrid has a separate contribution to ﬁtness of the gene pool owing to the existence of alleles that are highly negative (even lethal) in the dominant state, but positive in the heterozygous condition (as in the human AB blood group). It is thus likely that selection will tend to favor hybrid vigor in such circumstances, since this is the state in which adaptive capacity can best be maintained against a ﬂuctuating external environment: Dobzhansky (1970) states, ‘‘Overt genetic diversity is far exceeded by concealed or potential variability, the latter is stored in chromosomes and can be released by recombination. . . . Genetic diversity is maintained, not by new mutations, but by the advantages of heterozygosis, also by environmental ﬂuctuations in time and space that alter the signs/magnitudes of selection. . . . A total suppression of mutation would fail to change the evolutionary plasticity of a species for many generations.’’ It appears, therefore, that hybrid vigor may arise for a heterogeny of reasons. The important corollary of this is that selection clearly acts to favor gene pools with the highest probability of maintaining adaptational ﬂexibility, which latter is clearly greatest where heterozygosity is best perpetuated. Experimental evidence to support this view has also come to light: Dobzhansky (1970) compared the adaptedness of poly- versus monomorphic populations for chromosome inversions in Drosophila, observing that mean ﬁtness can be shown to be highest at certain levels of heterozygosity. Experiments showed that the advantage of hybrid populations lies in a greater intrinsic rate of increase.

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Wallace (1958, 1965) induced new mutations in several genetic strains of Drosophila melanogaster, ﬁnding that the average effect of newly induced mutations is viability increase. Mutability must therefore itself be under genetic control, and it must be tuned to the heterozygous state. Mukai and various co-workers (see Dobzhansky, 1970) further conﬁrmed these ﬁndings on the basis of spontaneous mutations. These apparently controversial results may perhaps simply constitute proof of the reality of the role of recurrent mutation in adaptive equilibrium, assuming that a signiﬁcant component of the mutations in question belonged to a transgeneration facility for reaction to longer term environmental ﬂuctuations (see Chapter 5). In general, adaptive capacity will tend to gravitate toward maximization of hybrid vigor, owing to the degree of bad ﬁt between the allomorphic repertoire and dynamism in the anisotropic selection interface. Hybrid Vigor and the Heterokaryotype The phenomenon of heterozygote advantage also extends far beyond the limits of the single gene locus, to include ‘‘heterokaryotypes,’’ where large sections of chromosome are involved in ‘‘chromosomal polymorphism,’’ and when hybrids are formed between different morphs: The chromosomes of Drosophila often show differentials that are due to inversions. None of the Drosophila inversion variants occurs throughout the range of a species (so that heterokaryotes are common), and the complete array does not occur in any one population (Dobzhansky, 1970). Relative frequencies vary with season, proving the adaptive value of different karyotypes. da Cunha et al. (1959) studied inversion polymorphism in Drosophila willistoni, ﬁnding that central populations were more polymorphic than peripherals, and populations in rich habitats more so than those occupying marginal ones. Dobzhansky (1970) regarded polymorphic inversions as ‘‘supergenes’’ (equivalent to recombination clusters in the present interpretation). If inverted and noninverted chromosomes differ in a single gene, suppression of recombination would make no difference. However, inversions binding together complexes of coselected genes will be favored, functioning as ‘‘super’’ recombination clusters. This may perhaps be a way of temporarily suppressing crossingover with respect to the selection interface reversing within a fairly short time. This situation also clearly falls within the adaptive equilibrium model: Experiments with D. pseudoobscura from the same and different populations showed different selection curves for the same inversions. Dobzhansky and Pavlovsky (1958) similarly found that populations of Drosophila willistoni and D. paulistorum in South America contained over 50% inversion heterokaryotes, but hybrids between allopatric populations lost a heterozygosity prevalence, probably indicating that different complexes of allelic genes were selected in different environments.

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If we suppose that, conversely, some of Dobzhansky’s ‘‘supergene’’ units are too large to be single functional genetic units, it is only necessary to assume that some component of this material is composed of ‘‘ﬁxed’’ genes and/or selectively near neutral loci. It must also be concluded here that ‘‘heterokaryotes’’ in general hold quite a different status to simple heterozygotes. Some modes of heterokaryosis apparently act to create temporary recombination clusters in the manner described above, thus presumably allowing certain leading effect genes to be ‘‘pseudo-linked’’ in response to transient environmental change. However, it seems most probable that this constitutes an adaptive response that is rooted in the domain of secondary adaptive equilibrium, and not in evolution. The term ‘‘recombination cluster’’ as applied to heterokaryotypes is of course an approximation, since such units may constitute only a few leading effect major genes carrying many thousands of minor ‘‘hitchhikers’’ of low selective value (and probably also incorporating ‘‘ﬁxed’’ loci, the chromosomal positioning of which is not crucial to function). In general, it can probably be safely assumed that adaptability is maintained by inversion heterokaryotes, although perhaps only in the restricted sense of perpetuating alternately selected components of the greater gene reservoir. Finally, it must be said that the only deﬁnitive example of positive heterokaryosis lies with the sex chromosomes in the heterogametic sex.

Interaction between Factors Affecting Gene Locus Assignment The intersect between external and internal factors affecting ‘‘linkage’’ is most explicitly exempliﬁed by evolved dominance. Although the genetic mechanisms of dominance itself are clearly endogenous, the adaptive differential demanding such homeostatic adjustment arises through conﬂict in the selection interface in the external environment (see Chapter 6). The demand here for epigenetic homeostasis is also partly determined by the difference between the genotype frequency spectrum in adaptive capacity and the true selection proﬁle within any chosen time frame, and is thus clearly some function of the polynomial expansion; for example, a simple allelomorphic system where (A⫺ ⬅ p2 ⫹ 2pq) ⫹ aa ⬅ q2 carries a higher gene pool ﬁtness than A⫺ ⬅ p2 ⫹ Aa ⬅ 2pq ⫹ aa ⬅ q2. Given a positive selection interface for the two homozygous classes of an allelic locus, then any negative selectional force lying in the heterozygote class will result in an additional homeostatic demand, namely, for dominance to suppress the hybrid state. Dominance is thus ‘‘an endo-homeostatic response to exogenous selection pressure,’’ and its function is partly expressed by a facility contained in the recombination mechanism. The primary function of dominance is thus that of forming a bridge between endogenous and exogenous elements, whenever hybrid depression constitutes an impediment to expansion of adaptive capacity and increase in the adaptive state. There is clearly also some further element of interactivity between recombination and endogenous homeostasis, in that maintenance of heterozygosity not only facilitates realization of adaptive capacity, but may also guard against negative interactivity in the internal environment.

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MAJOR AND MINOR GENES AND THE MOBILITY HIERARCHY IN GENOME ARCHITECTURE Given the array of possible conﬁgurations of the selection proﬁle that genetic systems may respond to and the different factors affecting locus assignment, it seems reasonable to suppose that there may be particular types of genes tailored to suit different selection regimes, and this appears likely to be linked in some way to the Mendelian concept of ‘‘major’’ versus ‘‘minor’’ genes. How can this view now be revised with respect to our contemporary knowledge of the developmental perspective on genetics?

Mobile and Static Genes It has already become apparent that there is a clearly deﬁned ‘‘mobility hierarchy’’ within the genome in terms of the expression and perpetuation of allelomorphism, in that we have already connected the latter to adaptive equilibrium. What other elements of ‘‘mobility’’ exist, and how do they differ from one another? The genome appears at ﬁrst sight to divide naturally into two sectors, the mobile and the static, following the observation that allomorphism favors ‘‘perpetuated mobility’’ (i.e., allelomorphism) and sometimes substitution– ﬁxation, according to the conﬁguration of the selection proﬁle. A naive view of the propensity of genes for allelomorphic ‘‘mobility’’ might perhaps be based on primary gene structure observed at the molecular level. However, many gene mutations are not actually transcribed, and many transcribed genes have no translational product that is subsequently causal to functional change of any kind (see Chapters 11 and 12). Similarly, many genes that are mobile in the sense of expressing functional allelomorphism do not occur in frequencies determined by selection, but follow a pathway of ‘‘genetic drift.’’ A true mobile gene has to be deﬁned as being allomorphic in the sense that it manifests positive interaction with selection, such that the frequency of the allele in question is controlled by deterministic interactions between organism and environment. A corollary of the latter is that a mobile gene will also tend to be ‘‘site speciﬁc.’’ ‘‘Gene mobility’’ is thus a function of expressed allelomorphism plus an active selection interface plus site speciﬁcity; in other words, status within the mobility hierarchy depends, not solely on the architecture of the gene itself, but also on external events. Static genes can be deﬁned as being the equivalent of ‘‘mobile genes in which selection has removed allelomorphism’’ through substitution (and in which mutational sequestration is often also present). Looking more deeply into the relationship between gene and selection proﬁle, the mobile genome sector consists of allomorphic recombinable units linked to adaptive capacity, whereas the static genome sector is made up of nonallelomorphic genes whose chromosomal positioning is determined solely by endogenous parameters concerning facility for gene interactivity. Thus, only mobile genes are actively involved in the recombination strategy, and the mobile sector interdigitates with the external selection interface to form the genetic component of adaptive equilibrium. Phenotype differentials in the mobile sector also tend to be disjunct, qualitative states.

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It should also be understood that the selection interface may of course also favor a continuous range of phenotypes when linked to a dynamic selection proﬁle, so that not all mobile genes are ‘‘major,’’ nor need they consist of a single allelomorphic pair: Mather and Jinks (1971) stated that to ascribe all polygenetic variation to side effects of major differences is indefensible, expressing no doubt that evolved minor (‘‘polygenetic’’) variation exists in the phenotype independently of major differences. Conversely, a large proportion of the static genome sector is that complement which underlies the development of complex, stable superstructures, thus acting on the coordinates of morphogenesis. This domain is protected from the pleiotropic effects of all but the most traumatic mutational activity, expressing sequestration from recurrent mutation, and frequently displaying resistance against impinging higher translational effects through canalization. The static genome sector is thus particularly linked to major morphogenetic coordinates of complex epistatic systems, and forms no part of the active phenon–selection interface inherent to the mobile sector. As discussed earlier, it tends to follow the dispersive model of genome organization, but may be partially condensate in nature. Minor Genes and the Labile Genome Sector The components of the total genome can more accurately be deemed to fall into three categories, the third element being the labile genome sector, that component of the genome expressing allelomorphic activity in the form of ‘‘minor’’ genetic variation. As with the mobile sector, labile genes are allelomorphic but tend to manifest a near neutral selection interface, as well as being non- (or less) site speciﬁc, their frequencies thus tending to be controlled by factors secondary to those of any leading effect mobile genes with which they are associated via chromosomal positioning: Wright found no evidence for any leading factor for continuously variable traits, concluding that additivity of loci and semidominance are the rule for most of the loci concerned and that deviations from these attributes depend on only a few major loci. Mather (1949) likewise concluded that dominance is not a general property of the minor gene differences involved in quantitative variability. There thus exists a form of ‘‘microallelomorphism,’’ controlling phenotypic differentials which tend to belong with labile quantitative variation, rather than constituting large scale qualitative states. Here, the selection interface frequently favors continuous variation by virtue of the additivity and low selectional differential between constituent genotypes, with genome organization tending to follow the dispersive model. Labile allelomorphs will thus often be polygenes affecting minor coordinates of development via the inﬂuence of ‘‘ﬂat’’ epistatic systems (see Chapter 11). Additive variance controlled by the labile sector is only indirectly correlated with true (selectional) allomorphism, and while the mobile sector is clearly structured around the condensate model

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of genome organization, the labile component will tend to meander within a more dispersive format.

Genetic Evolution in Realization of Adaptive Potential What is the genomic source of new genes entering the static genome sector in the context of anagenetic change of the kind discussed in the previous chapter? There is an obvious problem concerning the confusion between labile genes as an independent entity or as ‘‘pleiotropic leakage’’ from the mobile and static genome sectors, owing to the fact that new labile genes must frequently evolve in this context. The key to this problem is that a change in lability within the epigenetic environment due to decanalization is likely to mean that both pleiotropic and protropic or neotropic mutational effects will tend to be expressed in certain zones of development (see previous chapter), namely, as part of the labile sector: Mather and Harrison (1949) stated, ‘‘Most, if not all, genic differences of major effect have simultaneous smaller side effects which could contribute to continuous variation and therefore lead to the inference of a polygene.’’ The architecture of the genome mobility hierarchy should thus be seen as being linked to changing parameters of lability in the epigenetic environment, in that there may exist a greater or lesser degree of developmental buffering against the penetrance of allelomorphism in different developmental domains. Thus, there is a differential distribution of morphogenetic receptivity to the effects of ambient mutational events (see next chapter). It is thus important to see that the ﬂow between static, labile, and mobile sectors of the genome is facilitated by the degree of epigenetic lability encountered during translation. Desequestration is capable of creating a fundamentally dynamic relationship between different parts of the mobility hierarchy, but there must also be a complementary substrate of decanalization capable of permitting gene expression or penetration, whether of formerly buffered-out alleles or via fresh mutational events. Although the mobile genome sector clearly forms part of the structural response to a dynamic niche proﬁle, it is clear that the static sector is responding in part to a quite different selection regime, and we are now particularly interested in the link between isotropic selection proﬁle, anagenesis, and changing epigenetic determination systems. Propensity for realization of adaptive potential must therefore be concealed within the static sector, particularly via capacity for intermittent manifestation of labile allelomorphism, rather than through the medium of ‘‘latent variation stored in the chromosomes and released through recombination’’ (see adaptive topography below). Just as adaptive capacity lies in the gene pool as described by the mobile genome sector, adaptive potential must similarly lie in the relationship between the static genome and changing lability to expressivity and penetrance in the epigenetic environment, which is very much the situation discussed in relation to ‘‘epigenetic noise’’ and the emergence of neotropism in the last chapter. It is thus probable that morphogenetic evolutionary change

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happens through decanalization affecting change to the epigenetic lability in certain developmental zones (the reason this does not arise in the mobile sector being that most mobile genetic material is concerned with substructural traits linked to allomorphism). It is of considerable signiﬁcance that the labile genome sector clearly extends its inﬂuence well into the domain of morphogenetic change, and this is obviously of considerable importance for realization of adaptive potential in the context of incremental change. It should also be noted that the functional gene pool lies predominantly with the mobile genome sector at any point in time. The gene pool is therefore that subset of the total genome that is subject to interaction with a dynamic selection interface structure in the external environment. It is at this point that the true dichotomy between minor and major genes becomes clear. The former lie predominantly in the labile sector, despite the fact that some ‘‘polygenes’’ are genuine members of the mobile sector through manifestation of high contribution to ﬁtness. We must now consider that minor alleles may become aggregated into major genes as a result of evolutionary activity involving the building of complex supergenes in evolved structures such as convex epistatic systems. That minor polygenes do have the capacity to function in the mobile domain seems implicit from our knowledge of certain dispersive genes of additive effect to phenotype form. The capacity of such systems to become involved in evolution of major alleles is also implicit in the observed evolution of dominance from ‘‘background mutation’’ acting in the role of ‘‘modiﬁer’’ effects affecting recessive alleles. That gene clusters evolving from labile to mobile or static sectors may also involve duplication is perhaps suggested by such systems as the globin gene family in mammals (see Chapter 12). The link between the labile genome sector and more complex systems is thus apparently via the additive model for multifactorial inheritance. The effect of incremental change in the transformation between adaptive capacity and adaptive potential through ‘‘bottom-up’’ transgression between ‘‘ﬂat’’ parastatic and ‘‘convex’’ epistatic systems (see previous chapter) could thus be seen as incorporation of diverse microgenetic components into functional units in the context of evolved supergenes, as complexes of ‘‘enhancer– modiﬁer’’ activity. Major and minor genes may often behave respectively as evolved–stable and passive–transient organizational structures, rather than constituting ﬁxed attributes of genomic architecture, in that the qualitative property of the former may usually arise from the quantitative by a process of actively evolved iterative change. In summary, novel–positive major allelic mutations and ‘‘ﬁxed’’ epistatic systems probably arise as ‘‘minor mutations,’’ progressing toward major status through evolution of epigenetic homeostatic mechanisms, both mobile and static genome sectors being viewed thus as a derived response emerging from the labile substrate. Exactly how ‘‘multifactorial inheritance’’ is related to the epistatic system concept is to a large extent a matter of conjecture at present. However, the parastatic gene cluster concept (Chapter 11) will serve as a convenient model on which to base some hopeful speculation.

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At this point it is also necessary to raise the question as to whether or not major genes evolve in situ or from scattered genetic sources. The answer to this question seems to be a ‘‘middle road.’’ It is known that many additive polygenes are capable of independent assortment, also that this situation can be changed by chromosomal readjustment (as with translocation), and it is also known that polygenes can arise through duplication. Given an additive effect of n polygenes on a single phenon trait, a major gene might evolve from n minor genes, either through translocation between nonhomologous chromosomes, or through duplication around the original mutation site, as members of the duplication array undergo modiﬁer-type mutation in the context of an evolving supergene. There is, of course, no reason why both mechanisms should not be involved. This view is further supported by the observation that ‘‘spontaneous’’ major genes are generally observed to be selectively negative and often also disruptive to normal development (hence the maxim that ‘‘most mutations are deleterious,’’ in the view of classical genetics). The facilities of recombinatory and regulatory assignment (along with ‘‘on site’’ duplication events) thus allow transgression between a fundamentally dispersive model of genome organization and a derived condensate model. ‘‘Minor’’ genes may thus assemble as ‘‘major’’ ones, joining either the mobile or static genome sector. The condensate model may thus, in some part, be built from the dispersive, through linked inﬂuences of homeostasis combined with in situ ‘‘modiﬁcation’’ of preexisting gene units via duplication or ampliﬁcation (not, of course, excluding a greater or lesser retained dispersive distribution for those gene units in which ‘‘tight linkage’’ does not constitute either an exogenous selectional or endogenous homeostatic priority). Those supratranslational genes controllant to the essential coordinates of morphogenesis must also resemble the ‘‘mobile supergenes’’ in some respects, but they most probably include a greater complement of CIS- and TRANSacting activity in terms of distantly acting morphogens and extracellular control strategies. Genes that manifest ‘‘ﬁtness epistasis’’ (i.e., coselectional interactions) would also be those most strongly favored by selection. Thus, as is generally believed to be the case, the genetic component of variance will be mainly of the nonadditive type for those genes closely associated with ﬁtness: Additive genetic variance for characters with low contribution to ﬁtness is high, but it is low for characters with a high W element, owing to the fact that the latter will tend to evolve dominance (Fisher, 1930). In the present system, the evolution of dominance is seen as evidence for an incremental buildup of the gene-homeostatic interactive properties of major genes, from that component of fundamentally additive variance which does manifest a positive selection interface. This strategy connects also with the view of Fisher, that the deleterious effects of natural dominants will be modiﬁed and diminished in the same way that the dominance of positive new mutations may be increased: Up until the 1950s, dominance was evolving for Biston betularia f. carbonaria, since heterozygotes in old collections were less pigmented

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than now. Melanism in the peppered moth is therefore not controlled by a single gene, but by an interacting gene complex or (true) supergene, as has been proved by outcrossing melanics with an American Biston species (see Dobzhansky, 1970). These observations provide the best evidence that we have in favor of the view that the melanic form of the peppered moth probably represents something more than mere recurrent mutation. Many examples of observed evolutionary change in fact constitute modiﬁcation of adaptive capacity to new environments brought about by human intervention, as apparently with the classic Biston example and other cases of industrial melanism (assuming of course that the observed ‘‘evolution of dominance’’ does not in reality constitute tertiary adaptive equilibrium!). With respect to morphogenetic change, the above mechanism may well apply to simple neotropic channels (as illustrated in Fig. 60, for example). That more dramatically qualitative modes of change are also possible is additionally shown by the involvement of Hox genes in evolutionary innovation (see previous chapter). The latter problem will continue to to be investigated in Chapter 14. Sequestered Domains in Genome Structure From the above discussion, we should now draw the vitally important conclusion that gene speciﬁcity is clearly a product of evolution, and not causal to the latter. This fact may be concealed by the existence of highly site speciﬁc supergene complexes which in no way represent the outcome of single ‘‘point mutations,’’ being in reality aggregates of linked regulators and structural genes which have been progressively ordered in such a way as to operate as a single unit. The mobile genome sector will be observed to contain a homeostatic element, permitting penetrance for ‘‘internal’’ allelism but controlling that of exogenous inﬂuences, thereby creating the high speciﬁcity characteristics witnessed in much allomorphism. Evolved gene structures thus express a modularity that is also manifested in the developmental substrates they control and which is only lost in the context of subsequent decanalization. The latter process is then a necessary substrate for the subsequent evolution of novel major genetic systems. The observed autonomy of certain gene clusters must then in turn be linked to the degree of modularity expressed by certain developmental trajectories, with particular respect to major coordinates of phenogeny, ontogeny, and embryogeny. The structure of the selection interface shows how the fundamentally free minor genetic system relates to the constrained major one. Mobile genes acquire autonomy through iterative evolutionary adjustment. From this tendency of evolving minor gene systems to adopt ‘‘modiﬁer/enhancer’’ roles has come the epistatic strategy of interactivity within the supergene unit. Adaptive capacity thus tends to operate continuously in the mobile sector, while realization of adaptive potential materializes but rarely and intermittently in the labile domain. This complex architecture of the genome mobility hierarchy can now be summarized as follows:

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Architecture of supergene

Allelomorphs

Incoming pleiotropes

Selection interface

Chromosomal position

Phenotype effects

Labile

‘‘Flat’’ supergenes

Multiple; recessive– additive

Extensive penetrance; uncanalized

Dispersive

Mobile

‘‘Short– linear’’ autonomous

Sequestered

Minor phenon; substructural to structural; continuous variation Major phenon; usually substructural; disjunct variation

Static

‘‘Long–cooptive’’; in convex epistatic system

Few advantages in adaptive equilibrium; simple dominance Only transient

Variable (often near neutral); many are ‘‘hitchhikers’’ Dynamic; frequently of leadingeffect status

Limited penetrance; canalized against

Static

Controlled by recombinatory assignment; condensate or active dispersion Determined solely by regulatory assignment; condensate or else passive– dispersive

Compound structure units; structural

Attempts have been made in the past to slot the gene pool concept into models of how evolution may progress solely as a function of the behavior of the allelomorphic component of the genome. However, little or no account has been taken, in this, of the functional diversity residing in the genome mobility hierarchy (see below).

THE ADAPTIVE TOPOGRAPHY MODEL, ADAPTIVE CAPACITY, AND ADAPTIVE POTENTIAL The well-known adaptive topography model devised by Wright (1931) is not only one of the most enduring mathematical models of population genetics, but also one of the earliest attempts to adopt techniques for the analysis of dynamic systems in biology. Naturally, this model now needs reanalysis in the light of contemporary knowledge. It is perhaps self-evident that the adaptive topography model most aptly ﬁts the role of adaptive capacity in dynamic equilibrium, rather than constituting a description of any evolutionary process that involves neomorph mutation and restructuring of complex epistatic systems, especially considering its basis in the mean ﬁtness of a population in terms of its component genotype frequencies and consequent links with recombination. This model must clearly now be investigated more closely in terms of its relationship to the state of adaptive equilibrium, before going on to reconsider its relevance to questions concerning larger scale evolutionary phenomena. The basis for the Wright system is as follows (the following model being extended to n loci in the complete adaptive topography model): Adopting ‘‘mean ﬁtness’’ as a convenience (in an idealized gene pool with negligible nonselective offset requirement), a ﬁtness surface or adaptive topography is the graph of the mean ﬁtness of the population as a function of gene (or genotype) frequency. If genotypes AA and Aa have higher ﬁtness than aa, then mean population ﬁtness simply

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FIGURE 66 Simpliﬁed adaptive topography for a single allelomorphic locus (X ⫽ mean population ﬁtness, Y ⫽ allelic frequency).

increases as the frequency of AA increases in the gene pool. With heterozygote advantage, however, mean population ﬁtness increases to a peak at the intermediate frequency of A at which the population of heterozygotes is the highest possible.

FIGURE 67 Adaptive topography with heterozygote advantage (X ⫽ mean ﬁtness, Y ⫽ genotype frequency).

Looking at the above system in the light of adaptive equilibrium, the concept of mean ﬁtness (sum of the ﬁtnesses of each genotype in a population times gene frequency) becomes more realistic when we remove an artiﬁcially ‘‘static’’ aspect from the adaptive topography model and substitute a more dynamic selection interface. In the latter situation, with ﬂuctuating W values for a given genotype, gene combinations only tend toward optimum ﬁtness, with an additional complicating factor lying in the time lag between environmental change and adaptive response (which may, in fact, even be compensated for by logistic adjustment). In reality, natural selection does not therefore so much ‘‘guide a gene pool to an adaptive peak’’ as tend to do so, the peak in question having the capacity to change position, owing to the dynamic nature of the relationship between structure of the gene pool and a changing external environment:

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As pointed out by Nei (1987), the breeding structure and ecological condition of a population often change very rapidly, thus much reducing the applicability of Wright’s theory (see also Ford, 1964).* Wright’s view of the adaptive landscape also attracted severe criticism from Fisher, who regarded ‘‘ﬁtness epistasis’’ and pleiotropy as unimportant, taking the converse view that dominance and ﬁtness epistasis merely slow down the rate of increase of ﬁtness, which latter Fisher believed was equal to ‘‘the additive genetic variance of a population at any point in time.’’ Wright, however, quite correctly pointed out the interactivity of genetic systems, his model beginning from three tenets: (1) each character is usually affected by multiple gene substitutions; (2) each substitution generally has numerous pleiotropic effects; (3) the intervening processes involve nonadditive interactions. He thus counteracted Fisher’s hypothesis, from the standpoint that evolution seemed unintelligible other than by selection acting on interactive systems, rather than among alleles at each locus separately. From a contemporary viewpoint, Wright’s concept of interactivity, having been based on approximately random recombination both within and among loci, is totally unrealistic, given the function of locus association in controlling recombinability, namely, for those leading effect components of the mobile genome sector in which Fisher was especially interested. Wright’s attempt to include a universal pleiotropy factor in his adaptive peaks scenario also failed to recognize the relative autonomy of mobile major genes involved in adaptive equilibrium (where substitutions are also unlikely to be numerous!). He thus envisaged a huge number of peaks in his topography, while, in reality, most multiple gene interactions are obviously either negative or near neutral in effect (as well as being frequently impossible in terms of meaningful functionality!): Kauffman (1993) uses a related argument to plead for all-genes interactivity: ‘‘As K increases, the fraction of Boolean functions which are canalising decreases rapidly.’’ However, this would suppose a very large random element in epigenetic interactivity. It is as much a mistake to view all genes as mutually interacting in the developmental model as it was erroneous in classic genetics to view evolution through the ‘‘one gene–one character’’ hypothesis. The answer to the interactivity problem must lie in the probability that smaller numbers of genes controllant to morphogenesis are organized into quasi-autonomous subsets (epistatic system modules). The ambient state of epigenetic interactivity must accordingly be predominantly deterministic in * The concept of ‘‘adaptive landscapes’’ based on Wright’s approach was originally intended to deal with gene recombination phenomena, but was later extended to encompass various other parameters. For example, Raup’s view of adaptive topography concerns a set of adaptationally correlated phenotype traits in cephalopod shell anatomy (and is essentially a morphogenetic landscape linked to ﬁtness value, since the static–homozygous gene units of a convex epistatic system have no ‘‘adaptive topography’’ in the Wrightian sense). Simpson (1953) used a similar model to follow equid phylogeny. These models are perfectly valid, provided that adaptive potential actually exists for realization of any of the projected combinations! However, they are in no way analogous to the Wright model, since the relationship between genotype, phenotype, and mean ﬁtness in the mobile genome sector is neither explicit nor implicit in the Raup–Simpson models.

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nature, and there are then predetermined limits to which randomness can penetrate adaptive systems without causing total collapse. The rigidity of major morphogenetic coordinates stems from canalization of the epigenotype in response to the forces of negative pleiotropy, which must constitute a major impediment to realization of adaptive potential. In turn, this ‘‘rigidity’’ creates a modularity which effectively prevents the kind of ‘‘all-genes interactivity’’ envisaged by Wright and Kauffman, other than for members of the labile genome sector that are of trivial contribution to ﬁtness. The Wright adaptive topography model obviously preceded our contemporary understanding of the developmental perspective concerning the duality of epistasis and heterogeneity of pleiotropism, with particular respect to the regulatory versus structural functions of genes and the allotropic basis of much genetic activity. Loci that act epistatically in a developmental role will in fact generally be nonallelomorphic, other than those genes which tend usually to have minor pleiotropic roles of no consequence to evolutionary change, or even to adaptive equilibrium. Ambient selection interactions will thus tend to be dominated by a relatively smaller number of leading effect mobile recombinable gene loci. Similarly, pleiotropism cannot have free reign in epigenetic interactions generally. In the same way, Fisher’s view was clearly biased toward the mobile genome sector, and was incorrect in entirely dismissing Wright’s (admittedly overemphasized) concern with pleiotropy and interactivity. Thus, Wright’s model particularly concerned the labile genome sector, while Fisher was preoccupied with the mobile, and neither anticipated the changing emphasis in many vital components which was to come from a deeper understanding of the developmental perspective. Adaptive Topography, Adaptive Capacity, and the Shifting Balance Model The basis for Wright’s shifting balance hypothesis lies in movement between adaptive peaks representing n interacting genetic systems affecting the same character, as a function of ‘‘random processes carrying a population against selection pressure.’’ Wright clearly placed far too much stress on recurrent (as against novel) mutation in his shifting balance model, even to the extent of criticizing those ‘‘early geneticists’’ whom he claimed had wrongly assumed that evolution was ‘‘due to substitution of rare, favourable mutations.’’ His view of the fate of a new allelomorph entering the adaptive landscape is thus not acceptable, in that the change induced within the ‘‘landscape’’ will in fact depend particularly on whether the new gene is perpetuated as a semineutral labile component, enters the mobile genome sector as a new component of adaptive equilibrium, or becomes organized in some anagenetic role. In either of the latter two situations, its interactivity will in fact tend to become extremely restricted. Above all else, the changing position of a neomorph gene in an evolving epistatic hierarchy is of paramount importance in understanding the mechanism of realization of adaptive potential: Kirkpatrick (1982) has shown that peak shifts can occur in the absence of chance events in a small population, given (a) environmental change

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and/or (b) mutation (as, indeed, common sense alone would appear to indicate!). ‘‘Exploration of adaptive valleys’’ in the adaptive topography must not therefore be misconstrued as evolution occurring as a function either through reshufﬂing of existing mobile genes or as a randomizing inﬂuence on evolutionary change. The true basis for the shifting balance effect should be viewed as lying partly in the bad ﬁt existing between a dynamic environment and the adaptive response, particularly in view of the intrinsic time lag between the selection interface and adaptive response, speciﬁcally in trivial variation residing in the labile genome sector. The possibility that leading effect selectional activity may switch between different pleiotropic effects of a gene complex is perhaps exempliﬁed by Maniola (see Chapter 12). However, this is clearly a periodic behavior of adaptive capacity and not ‘‘evolution occurring on the basis of quasi-random effects on the interactive functioning of gene alleles’’! The same interpretation obviously applies also to the data for allomorphic variation in Cepaea snails. Movement in and around adaptive peaks must be seen primarily in relation to the dynamic behavior of the peaks themselves, and not as ‘‘evolutionary hill climbing’’ by gene pools. This approach would constitute an entirely valid application of Wright’s model, but major evolutionary change must not be presumed to be a simple linear extrapolation of such events. Continuing with the question of ‘‘adaptive valleys,’’ Wright’s shifting balance model in which random factors are supposedly causal to ‘‘crossing peak saddles against selection pressure’’ (see also Chapter 15) will work well enough for minor genetic variation of low contribution to ﬁtness, particularly if we view ‘‘genetic drift’’ in the additional context of ‘‘bad ﬁt existing between the adaptive response and a variable environment’’ as the catalyst for crossing saddle points. It is unlikely, however, that a mutation of low contribution to ﬁtness could subsequently become a leading effect in evolutionary change, and much more likely that any apparent movement of this kind would appertain at the very most to some subtle modulation within adaptive equilibrium. It is highly signiﬁcant that Wright believed that ‘‘progress under pure mass selection in a panmictic population comes to an end under constant environmental conditions, with ﬁrm establishment of the controlling peak’’ (proof that he overlooked the problem of adaptive capacity in dynamic equilibrium as being the principal function residing in the mobile genome sector). Despite the high degree of relevance of the adaptive topography model to the adaptive response with respect to a dynamic selection interface, Wright dismissed polymorphisms as ‘‘adaptations, end results of evolution, rather than material for further evolution,’’ while at the same time accepting that ‘‘very strong selection at any locus tends, indeed, to reduce that at all others since all selection must be taken out of a ﬁnite reproductive excess.’’ In the present view, ‘‘hitchhiking’’ of minor labile genes is thus much more likely to affect quasi-random recombinability of the kind described by the shifting balance hypothesis, than is any component of true evolutionary change. It is thus

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doubtful whether the Wright model has any value beyond that of constituting a mechanism for transient change in the variational spectrum. By ignoring evolved allomorphism, Wright thus seems to have fallen back on the dynamics of near neutral minor variation in the context of changing recombination perspectives as a description of evolution. Wright likewise saw dominance and epistasis as ‘‘impediments to recombination,’’ presumably on the grounds that ‘‘useful genotypes needed releasing from constraint.’’ These ‘‘constraints’’ are now seen as evolved–homeostatic in the context of adaptive equilibrium, and not as impediments to evolutionary change (however, see Chapter 14). In the present interpretation then, the organization and dynamics of genetic material on the chromosome constitute the physical basis for adaptive equilibrium. However, chromosomal reorganization gives no real insight into evolution, nor can changing domains of recombinatory assignment of preexisting labile alleles bypass an ‘‘upper limit’’ for endogenous change in canalized genetic systems. The true perspective for the Wright and Fisher models thus lies with the labile and mobile genome, respectively. Although Wright dismissed Fisher’s ‘‘one gene–one character’’ approach as entirely unrealistic, neither Wright nor Fisher realized that the mobile genome is speciﬁc to adaptive capacity, nor did either fully understand the signiﬁcance of the leading role taken by a small number of leading major gene allomorphs in determining the architecture of the gene pool. Likewise, Wright did not pay enough attention to the rapid ﬁxation of new alleles of high contribution to ﬁtness, with respect to allelogenetic evolution within the species (see Chapter 8). Fisher’s model is, however, observably correct for major genes of stable allomorphism in the mobile genome, and, similarly, Wright’s system additionally encompasses many valid characteristics of the labile genome. Wright’s close association with the data of artiﬁcial selection seems to have greatly colored his philosophy (just as Fisher was equally polarized in the direction of naturally evolved leading effect allomorphism). Thus the shifting balance hypothesis in particular is perhaps most relevant within the domain of Wright’s area of special interest. Clearly, the differentiation of mobile, labile, and static genome sectors in the context of the developmental trajectory now entirely abolishes the simple Mendelian population model in general as a basis for ‘‘adaptive topography.’’ Developmental perspectives such as Waddington’s concept of canalization and its relationship to the regulator–structural strategy of epigenetic interactivity have exposed inherent weaknesses in the adaptive peaks concept, showing decisively that the diversity of living things cannot possibly be envisaged as ‘‘a multitude of adaptive peaks’’ in the Wrightian sense. All ‘‘permissible’’ genotypes are, in fact, ‘‘adaptive peaks,’’ and any apparent ‘‘valleys’’ they move among are most usually due to drifting microgenetic variation residing in the labile genome sector. In summary, Wright’s ‘‘special’’ theory of the evolutionary process could be adjusted to form an excellent model of the behavior of the near neutral component of the labile genome sector, but a number of additional factors render it inadequate as an explanation of larger scale evolutionary events on the basis of ‘‘release of variance stored in the chromosomes,’’ in the manner

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in which the model has generally been construed. The transgression between dispersive and condensate models of genome organization indicates one way in which this model should be modiﬁed to encompass the ﬁndings of developmental genetics. Of rather greater interest for evolutionary theory is the manner in which the behavior of the mobile genome sector may tend to impede evolutionary progress, and this latter problem forms part of the subject matter of the next chapter.

MAIN POINTS FROM CHAPTER 13 1. Classical linkage is the convergent corollary of two fundamentally different mechanisms that reﬂect separate endogenous and exogenous factors inﬂuencing chromosomal locus positioning. From this standpoint, we arrive at the concepts of regulatory versus recombinational locus assignment, and of the regulation and recombination gene cluster. Regulatory assignment is primarily concerned with the cis-regulative interactivity of genes, recombinational assignment with facilitation of adaptive equilibrium with respect to dynamism in the external environment. 2. There are dispersive and condensate regimes of genome organization, and both regulatory and recombinatory assignment can be manifested in either conﬁguration. However, in regulatory assignment, the dispersive state is ‘‘passive,’’ whereas this condition is actively selected for recombinatory assignment. The condensate state is ‘‘active’’ with respect to both regulatory and recombinational assignment mechanisms. 3. Propensity for recombination is a function of adaptive capacity in dynamic equilibrium, with respect to an anisotropic selection interface. Regulatory assignment is partly concerned with interactivity within the (true) supergene unit (some element of which latter is, however, also linked to dispersive distribution of constituent loci). 4. The genome is probably to some extent fundamentally dispersively organized, but gravitates toward the ‘‘condensate’’ model owing to the inﬂuence of both extrinsic and endogenous homeostatic forces. In this view, the recombination cluster does not constitute ‘‘linkage disequilibrium,’’ so much as coselectional equilibrium. 5. The population genetics usages of the terms ‘‘supergene’’ and ‘‘epistasis’’ should now be abandoned in favor of the developmental interpretations. The recombination cluster replaces the population genetics concept of the ‘‘supergene,’’ and gene loci expressing ‘‘ﬁtness epistasis’’ do not necessarily manifest developmental epistasis. 6. Adaptive capacity will tend to be structured around hybrid vigor, owing to the ‘‘bad ﬁt’’ existing between the genetic component of adaptive capacity and temporospatial dynamism in the adaptive niche. 7. A pronounced mobility hierarchy exists among gene types. The mobile genome sector consists of those loci existing in a state of perpetuated allomorphism. The static genome sector evolves via a purely transient allelomorphic phase leading to ﬁxation in the context of a stable, isotropic adaptation inter-

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face. Gene locus assignment is thus linked to the extrinsic selection interface for the mobile genome sector, and to regulatory interactivity for the static. The labile genome sector is made up of ‘‘minor’’ allelomorphic loci of near neutral status, the gene frequency of which is generally determined by ‘‘hitchhiking.’’ 8. Selectionally positive mutational effects may often originate in the labile genome sector, and new gene clusters may thus evolve from labile to mobile or static domains in the context of ‘‘convex’’ (major) systems arising from ‘‘ﬂat’’ (minor) ones, a mechanism that will tend to occur speciﬁcally in zones of high morphogenetic receptivity. Gene speciﬁcity is in this sense a product of evolution, rather than being causal to the same. 9. The question as to whether duplication of Hox genes (or of other higher supratranslational loci) can create more ‘‘saltational’’ effects in the phenotype must also be referred to the question of morphogenetic receptivity. 10. Wright’s adaptive topography model cannot be accepted as describing any aspect of evolutionary change in adaptive systems, but is instead linked to adaptive equilibrium and genetic drift. A signiﬁcant component of the genome is functionally linked to adaptive equilibrium via the mobile sector, and movement within this domain (rather than evolutionary change) is what is described by the special theory of evolution that was centered around Wright’s adaptive topography model. 11. The reputed inﬂuence of stochastic factors in Wright’s shifting balance hypothesis is rejected, owing to an unrealistic reliance on random events in the active evolutionary behavior of genetic systems.

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As we have already seen, there are clearly very strict limits beyond which evolution cannot proceed by reshufﬂing the existing complement of allelomorphic genes. Essential superstructures, which must have evolved in the context of iterative (albeit transient) allelomorphism, do not express perpetual variation on the basis of a mobile gene complement. Allelomorphic genes manifesting expressivity in the phenotype are generally linked to an anisotropic selection interface, whereas canalized anagenetic supergenes must relate to an isotropic one capable of supporting iterative, directional change which passes through purely transient periods of allelomorphism. Since anagenesis is the principal focus for complex mutational events linked to long-term evolutionary change affecting morphogenetic parameters, it is now necessary to consider the consequences of transgression from the ambient state of adaptive equilibrium to activity of the anagenetic kind. Clearly, realization of adaptive potential in the morphogenetic domain is involved in this, and various impediments to evolutionary change must also be overcome. It has become apparent from previous chapters that certain forces act to retard speciation and anagenesis, as a corollary of the way in which the genome reacts to selection in the face of mutational change and also in terms of the nature of epigenetic interactivity during development. These factors include negative pleiotropic balance, hybrid depression resulting from recombination, and the relationship between adaptive topography and adaptive equilibrium in the mobile genome sector (Chapters 6 and 13). Most signiﬁcantly, the activity of neomorph mutation in large scale evolutionary change must involve modulations to the static genome sector, and this must relate to the dynamics of

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genomic change at higher translation levels—and thus also to the counteracting inﬂuence of canalization. It is now necessary to examine each of these impediments in more detail, and to consider various solutions (and the possible links between them) in the context of an adaptive substrate that would permit evolutionary change to actually take place.

Impediments to Realization of Adaptive Potential The domain of adaptive capacity is controlled by selectional interactions and homeostatic mechanisms which render most ‘‘background mutation’’ to a near neutral (and generally sub- or microstructural) level. What happens when large scale neomorphic mutation occurs in the morphogenetic dimension? As we saw in the last chapter, much microevolutionary mutation merely adds to the mobile genome sector. Recalling the dynamics of the genome mobility hierarchy, in terms of the way in which different parts of the system may interchange, this ﬂow must generally have the highest probability of occurring endogenously with respect to the mobile genome sector itself. Fig. 68 reﬂects the kind of genetic change reﬂected in the adaptive equilibrium model, and such mechanisms are easily understood in the context of the substructural traits of most allomorphism. Genotypic changes operating at lower translation levels in relation to allomorphism can thus be envisaged as being facilitated largely through changes in the mechanism of sequestration, in that strategic loci can be rendered more labile to mutation.

FIGURE 68 Desequestration may release fresh microgenetic alleles from the mobile into the labile genome sector, from which substrate, in turn, new ‘‘modiﬁers’’ may come to be recruited as part of the evolving mobile genome sector itself.

The above is a simple restatement of the deﬁnition that adaptive capacity is expressed in the positive selection proﬁle of the existing and recurrent genotype spectrum, a mechanism which may also expand to incorporate true evolutionary change. To transgress from this scenario toward realization of adaptive potential for anagenetic change in the morphogenetic domain, it is necessary to consider the behavior of a mutation affecting the higher translational domain.

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Macroevolutionary change of this kind must clearly involve supratranslational gene mutation, thus expanding the static genome sector in the context of decanalization. Macroevolutionary anagenesis has already been shown to be determined by the interaction of three factors: • Isotropic selection proﬁle • Large biophysical paradigm distance • Presence of adaptive potential, such that the existing phenotype may progress toward the biophysical paradigm state The isotropic selection proﬁle cannot ‘‘drive’’ anagenesis in the lack of adaptive potential for morphogenetic change, nor is any other component active in lack of interaction with the other factors listed above. From our previous discussions, the higher translation level equivalent of desequestration must stem from decanalization. Homeostatic systems controlling penetrance of pleiotropic effects on epistatic systems may thus ‘‘open’’ or ‘‘close’’ in a manner analogous to sequestration and desequestration, individual genetic factors in this clearly lying higher in the epistatic hierarchy than those affecting mobile major loci. However, it is a misinterpretation to consider ‘‘mobility’’ at this level as being homologous to simple allelomorphism in a polymorphic gene locus. Alternative morphosystems with a positive selection interface are less likely to arise from single mutations in the epistatic system, and known regimes causal to shape change are often of the polygenic (multifactorial) kind. The simplest model would thus be that of a novel multifactorial system arising in the labile genome sector through selective decanalization occurring endogenously to the static sector itself. It is during the dynamic phase in this scenario that solutions to certain impediments must clearly be found, and this has to be a universal problem for macroevolutionary dynamics.

FIGURE 69 Origins of fresh labile genome material through decanalization in the static sector.

Following on from the earlier argument that adaptive potential is generally realized in an incremental, iterative manner, it now seems necessary to consider the corollaries, both of an iterative decanalization scenario and of any salta-

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tional change which might be presumed to occur in this respect. In the above interpretation, the all-genes interaction scenario envisaged in Wright’s adaptive landscape model (see previous chapter) becomes a system in which the mobile, labile, and static genome sectors exist in a mutually quasi-autonomous state which only incorporates a limited domain of interactivity in the face of decanalization at certain key loci in developmental space-time. When this does occur, however, disruption to ambient gene-homeostatic systems seems inevitable, the greatest problem arising here being that iterative mutation must transgress a pleiotropic threshold that is due to generation of ‘‘epigenetic noise.’’ As we have already observed, a further ‘‘threshold’’ structure affecting evolutionary change has been shown to exist in the form of hybrid depression in the context of certain selection regimes, particularly when gene pools that have diverged in allopatry rejoin in sympatry (Chapter 6). Much selectional conﬂict may thus appear in that context, inevitably manifesting some retardation effect on the divergence of incipient species. It has already been proposed that hybrid depression may arise as a function of the degree of divergence between parent genotypes, even in the plesiosympatric situation. To what extent does the resultant demand on homeostatic adjustment constitute an actual impediment to evolutionary change? The anisotropic selection interface may display yet another complicating inﬂuence tending to retard evolutionary change. Looking again at the adaptive topography model of Wright, we can see that gene frequency changes in populations may come to be dominated by factors manifesting adaptive equilibrium, such that other aspects of the dynamics of the gene pool may be rendered such low relative status that progress is either extremely limited or nonexistent in any context other than that of ‘‘perpetuated allomorphism’’ (as argued by Wright, all selection must be taken out of a ﬁnite reproductive excess!). It is thus clear that hybrid nonviability, pleiotropy, and the selectional hierarchy between different components of the genome each demand some form of adjustment, if evolution is to transcend adaptive equilibrium. Both the speciation process and the anagenetic mechanism must therefore incorporate solutions to problems imposed by the intrinsic nature of gene-development control systems, as we transpose from adaptive capacity to adaptive potential. Negative pleiotropy, hybrid depression, and selectional hierarchies can thus be said to retard genomic change in the role of evolutionary impediments, where propensity for change is actually present but encounters an opposing force of some kind. These factors are not ‘‘true’’ constraints in the sense of constituting actual lack of propensity for change (as, for example, with the absence of any endogenous adaptive potential such as would permit anagenetic advance being made with respect to some latent selectional demand existing in the external environment). First, the selectional hierarchy among n pleiotropes of a positively selected morphogenetic change constitutes the pleiotropic impediment, whereby neomorphic change will be retarded whenever pleiotropic balance lies in favor of the nonmutant genotype (see Chapter 12). Second, the selectional hierarchies between parent and hybrid genotypes, and among positively selected alleles of n phenons, constitute the leading effect and recombination impediments, respectively. The leading effect impediment may thus tend to dominate the

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selection interface as adaptive equilibrium whenever the highest selectional differentials lie in an anisotropic rather than isotropic selection proﬁle, and the recombination impediment will be manifest wherever there is hybrid depression. Such factors must evidently be endemic to all manifestations of evolutionary change. Canalization and the Pleiotropic Impediment The canalization–decanalization scenario could be seen as deﬁning a double barrier to evolutionary change. In the ﬁrst instance, a certain proportion of positive changes must be held back as a corollary of intermodular relationships between morphogenetic parameters. Second, any tendency toward decanalization, such as might actually permit expression of positively selected changes, carries the corollary of generation of epigenetic noise and negative pleiotropism, so that anagenetic change must frequently give rise to pleiotropic effects which in turn affect other domains besides the actual target of morphogenetic change. This situation must ultimately reach a pleiotropic threshold, that point in the buildup of negative pleiotropy at which the pleiotropic impediment is invoked. Realization of adaptive potential thus invokes an inherent retardation factor in pleiotropy at all translation levels as a function of a pleiotropic balance law, which states that any change in the phenotype may carry both positive and negative elements, and that a given positive change will only be selected if the net effect over all positive and negative elements generated by that same change is also positive. The pleiotropic impediment thus refers to epigenetic conﬂict caused by negative pleiotropic balance, most signiﬁcantly in the morphogenetic domain, in ‘‘convex’’ epistatic systems: According to Maynard Smith (1998), the selection limit observed in Drosophila bristle number experiments under artiﬁcial selection may be partially an effect of small population size. However, where the supposed selection limit has been surpassed in larger scale experiments, there is nevertheless a return to the original phenotype state, owing to probable lethality of homozygotes. The latter cannot deﬁnitely be linked to pleiotropy at present, but it is thought that lowering of fertility in inbred lines probably is in fact due to pleiotropism. In this example, we perhaps observe the action of a ‘‘pleiotranscriptional’’ threshold only (see below). Quite possibly, the negativity of Waddington’s decanalization phenotypes was based at least partially on translational pleiotropism. The pleiotropic impediment thus acts to impede anagenesis whenever a potentially positive increment is canceled out by negative pleiotropy, and any ‘‘saltational’’ change or continued trend in iterated mutational activity may therefore create constraints on the probability that positive developmental change can be maintained. The phenotype expression of a leading effect protrope or neotrope may thus form the functional selection interface for evolutionary change, while at the same time deleterious sequiform pleiotropes demand some homeostatic adjustment in the epigenotype. Mutational pleiotropy must therefore be the principal target of epigenetic homeostasis during periods of anagenetic change.

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Positively selected adaptational changes are derived from some fraction of a potentially very wide range of possible morphogenetic effects opened up via decanalization, a modiﬁed homeostatic strategy then proceeding, it is hoped, to maximize the perpetuation of positive states from this substrate. Thus the ‘‘labilities’’ controlled by restructured epistatic systems may frequently tend to form a strictly limited subset of a larger number of possible epigenetic interactions. Decanalization is thus a fundamentally negative randomizing force, from which positive developments may appear only in the context of appropriate homeostatic adjustment, and any lowering of epigenetic resistance for a given developmental trajectory must therefore be balanced by an appropriate increase in homeostasis. The pleiotropic threshold may perhaps best be regarded as being a twotiered structure (assuming little or no ‘‘cross over’’ between translational domains). First, there is an infratranslational threshold dominated by substructural effects, and there is also a supratranslational threshold connected with morphogenesis. Clearly, the latter has considerable implications for neomorphic change in complex anagenetic evolution. Adaptive Equilibrium and the Recombination Impediment The recombination impediment originating in hybrid depression must tend to disfavor expansion of the adaptive niche, being focused on selectional conﬂict in a fundamentally cladogenetic selection interface. This factor lies in the hybrid state alone but must also intersect with that component of the pleiotropic impediment residing in the heterozygote, some component of the recombination impediment thus tending to constitute a special case function of the pleiotropic impediment (which latter may in fact include elements which had been resolved by homeostatic adjustment in allopatry, then been reactivated in neosympatry). One aspect of the recombination impediment must therefore be that of magnifying the pleiotropic impediment over and above that level which would have arisen within a single plesiosympatric gene pool. It is thus evident that a signiﬁcant intersect exists between different homeostatic impediments, since the recombination impediment contains a signiﬁcant contribution from the pleiotropic. However, the recombination factor is clearly not an exclusive function of negative pleiotropism, in that a large component must reside in the extrinsic selection interface. This is due to there simply being no complementary niche space in adaptive capacity for the hybrid phenotype (similarly, much endogenous conﬂict may also be due to nonpleiotropic factors). Reexamining in more detail the heterogeny of mechanisms giving rise to hybrid depression in the gene reservoir in the context of the recombination impediment, we can distinguish negative heterozygosis (mainly arising in the plesiosympatric situation) from negative heterokaryosis (especially linked to the neosympatric state), these jointly comprising an impediment to further differentiation of the gene pool wherever cladogenetic potential cannot be realized. In this scenario, sources in plesio- as against neosympatry reﬂect an ascending level of complexity in terms of intensity of the recombination impediment (Fig. 70).

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FIGURE 70 Negative heterozygosis and heterokaryosis in their respective links to plesiosympatry and neosympatry (gp ⫽ gene pool).

Genetic differentiation of species can be due to homeostatically incompatible gene pool differentiation (see Chapter 6), and actual evidence from hybrid nonviability indicates that genetic restructuring in at least a number of leading effect loci is implicated in most speciation events: Dobzhansky (1970) found that the numbers of genes separating even closely related species is large; for example, electrophoresis studies by Hubby and Throckmorton (1968) on nine species groups of Drosophila with three species each showed sibling species pairs having only about 50% of proteins in common (sharing 23–86% of proteins) against an average of about 11.8% shared by nonsiblings. Dobzhansky concluded that even siblings must differ by thousands of genes. No doubt much of this variation is ‘‘near neutral’’ genetic drift. However, it is still true to say that species-to-species differences in functional genes can be large, and evidence for this is abundant—even hybrids between such closely allied species as D. pseudoobscura and D. persimilis exhibit a dramatic drop in viability in backcross progenies (Weisbrot, 1963). In the complex heterokaryosis scenario, hybrids form ‘‘false diploids’’ between genes that were independently adapted to homozygosity, thus giving rise to haplogenes expressing ‘‘nonsense outputs’’ in the hybrid diploid state, and to complexes of nonpairing meiotic chromosomes: The negative heterokaryosis scenario is reﬂected in Haldane’s rule, namely, that the heterogametic sex is absent in many race crosses. Dobzhansky (1937b) showed that one mechanism for this lies in the different chromosomal partitioning of genes in D. pseudoobscura ⫻

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D. miranda crosses, such that a given locus may be on the sex chromosome in one species, and on an autosome in the other. Expanding our earlier treatment of negative heterokaryosis, simple heterokaryosis concerns only the ‘‘nonsense haplogene’’ situation, whereas complex (negative) heterokaryosis involves meiotic failure owing to discrepancies in gross anatomy of the chromosomes. The recombination impediment may result particularly from complex negative heterokaryosis, since the ‘‘simple’’ condition can probably often be resolved by homeostatic adjustment within the gene pool. Negative heterokaryosis thus has more than a single root cause. First, it is a function of the degree of ‘‘developmental distance’’ between parent gene pools with respect to a given phenotype trait, the number of negatively heterozygotic states being increased as a function of independently derived pleiotropisms evolved in allopatric gene pools. Second, it is also compounded by incompletely homologous chromosomal heterokaryotypes in neosympatric gene pools, which may altogether prevent actual chromosome pairing. Heterokaryotic genotypes are of lowered fertility owing particularly to incapacity in meiotic behavior, and it has accordingly been proposed that changes in karyotype are probably perpetuated when they occur in small populations. Consequently, this situation may be difﬁcult or impossible to resolve, either by genome reorganization or through endogenous homeostasis: Dobzhansky and Tan (1936) compared the genomes of two extremely closely related species of Drosophila (D. pseudoobscura and D. miranda), ﬁnding such profound differences that the chromosomes either failed to pair or else formed highly complex pairing conﬁgurations. Homologous genes were found to lie in quite different parts of the chromosome in the two species, some obviously having been translocated. In addition, some homologs could not be traced at all. King (1993) states that species may have the same or different chromosome numbers and that, in general, gene arrangements may be the same or different. However, speciation is usually (but not always) accompanied by chromosomal differentiation, and thus also hybrid incompatibility. The limits of allomorphism for structural level diversiﬁcation within the gene reservoir are quite possibly due to depression of developmental viability, as disjunct morphogenetic proﬁles of homozygous phenotypes tend to become more widely differentiated, and their hybrid genotypes less viable. Large morphogenetic steps may therefore tend to create highly negative hybrid states, the resolution of which situation cannot be a progressive widening of the structural gulf between the two homozygous classes in the absence of a speciation event. In the event of anagenetic change leading to a developmental viability conﬂict in the heterozygote state, this must also be seen as a force tending to oppose iterative evolutionary change, namely, in the absence of speciation (or of cladogenetic substitution).* * However, see also phyletic occlusion (Chapter 17)!

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The recombination impediment has to be understood as ‘‘cladogenetic conﬂict with no propensity in cladogenetic capacity or potential for resolution in the external adaptation interface and/or in the endogenous domain.’’ Leading-Effect Allomorphism in the Mobile Genome Sector The recombination impediment is essentially the negative corollary of a mechanism that is concerned with perpetuation of allomorphism, and it has already been suggested (Chapters 5 and 13) that allomorphism may tend to dominate the selection interface in the context of ambient adaptive equilibrium. In what manner does the latter mechanism also act to impede evolutionary change in the context of a negative corollary of the adaptive response to an anisotropic niche proﬁle? According to the theory of leading effect allomorphism in the context of adaptive equilibrium, a ﬁtness value approaching 1.0 may often be held by just a few gene loci, or even by a single recombination cluster. To understand how an apparently ‘‘essential’’ anagenetic increment may in that context be sidestepped, we have to consider not the absolute adaptive value of the latter, but the contribution of the anagenetic increment in question to overall ﬁtness. If two gene loci are additive to ﬁtness, then the relative W value of either one of them must be less than its own absolute value (in the absence of the other locus). Where many dynamic allomorphs have evolved, the contribution to ﬁtness of an ‘‘anagene’’ is thus diminishing as a function of that of the combined allomorphic component: c

WA ⫽ WA/⌺ Wa

where cWA ⫽ contribution to ﬁtness of the ‘‘anagene’’ and ⌺ W ⫽ total contribution to ﬁtness of all competing allelomorphs. Why, then, are all-combinations genotypes not selected in the above circumstance (the leading effect allomorph cluster along with any useful anagenetic allele)? This option clearly depends on whether the ‘‘anagene’’ in question is on the same chromosome homolog as the leading effect allomorph set, and thus also on that homolog which actually forms the leading effect. This problem may well be soluble through translocation, but this will clearly not happen if the leading effect in question is continually shifting from one chromosome homolog to another in different generations. Recombination clusters are, in all probability, built around a smallish number of allomorphic major genes, the chromosomal distribution of which is linked to the dynamics of the external selective environment. However, although coselected genes do tend to lie in a common recombination cluster, the emphasis may nevertheless tend to shift from one cluster to another as a function of temporal periodicity in the external environment. In this situation then, only members of the leading effect cluster will have their frequencies determined directly by selection. An anagenetic increment of low overall contribution to ﬁtness thus has a chance p of being on the same chromosome homolog as the current leading effect allomorph at any given time. Consequently, its chance of passing to the next generation is more a function of p (and of incidence of crossing-over) than it is of WA. Genes of relatively low contribution to ﬁtness that are not regularly associated with the leading effect cluster will thus tend to have their frequencies determined

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by ‘‘hitchhiking,’’ and there must be some selective threshold below which this is invoked (see Chapters 18 and 19). The leading effect impediment can now be formally deﬁned as that situation in which the allomorphic component of the selection interface is that responsible for directing the adaptive response with respect to any nonallomorphic component carrying a latent propensity for realization of adaptive potential. A small number of leading effect major genes may thus tend to monopolize gene frequency changes in allomorphism, holding back potentially useful gene combinations, including, at times, those forming a component of incremental change in anagenesis (so that Wright’s view of potentially positive genes being perpetuated in the context of the adaptive topography model can in fact be accepted for at least a small quota of anagenetic increments): Mather (1953 and elsewhere) found that the stores of variability held in the chromosomes were not immediately available for selection to interact with, but could be released gradually through iterative crossing-over activity. Consequently, a series of ‘‘selection plateaus’’ may be observed over n generations. This situation is probably analogous to the leading effect impediment as it affects realization of adaptive potential (namely, in its action within the smaller domain of adaptive capacity).* The combined outcome of the leading effect, recombination, and pleiotropic impediments discussed above will clearly be to relegate anagenesis to the status of a rarely encountered mode of change relative to adaptive equilibrium, and even to ambient speciational activity (as indeed observational data appear to conﬁrm). The question we must explore now is, what counteractive mechanisms have to be organized against factors tending to inhibit evolutionary change? In general, it can be shown that retardation factors can be either resolved homeostatically or else selectionally bypassed—that is to say, they can be accommodated through homeostatic adjustment within the existing gene pool or removed by virtue of speciation.

Solutions to the Pleiotropic Impediment It is with the problem of negative pleiotropy that we ﬁnd the greatest challenge to understanding how anagenetic change can progress in the face of developmental impediments. Three solutions can in fact be envisaged to the pleiotropy impediment, although these are not genuinely discrete mechanisms: 1. Through incremental change: Change via small steps incurring little negative pleiotropy constitutes a progressively increasing problem in the longer term, in that translational effects must result in a growing negative balance as iterative change converges on a pleiotropic threshold. However, the incremental nature of iterative change must * It does not of course follow that the experimentally released variation in question actually carries any supplement to adaptive capacity in a natural population!

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allow stepwise homeostatic adjustment to be made, such that large negative pleiotropic balance is avoided. 2. Through positive pleiotropic balance: Larger steps are permitted, when a positive advantage simply outweighs negative effects with respect to a strongly skewed distribution in pleiotropic balance, selection for gross mutational change being great enough to outweigh a heavily negative pleiotropic load (this of course, in turn raises the question as to what actually constitutes a ‘‘quantum morphogenetic step’’!). 3. Through gene duplication: Where neotropic mutational effects have been selected, selectional conﬂict between ‘‘old’’ and ‘‘new’’ epistatic systems can be resolved through gene duplication allowing functional divergence (see Chapter 12). In each of the above strategies, there will be time gaps between increments to allow for homeostatic adjustment, and in fact, the latter circumstance must be ultimately essential to iterative change in linear anagenesis. The essential difference between separate solutions is that, following the incremental step model, opportunity for ongoing homeostatic adjustment is much greater than for the saltational option. Incremental Change and the Polygenes Solution The proposed strategy of anagenesis through iterated, incremental change has already been linked to the observed behavior of genetic systems, namely in the labile 씮 static genome sector transgression, this presumably reﬂecting the transgression between ‘‘ﬂat’’ parastatic and ‘‘convex’’ epistatic systems (see Chapter 13). Minor polygenes affecting shape tend to have small additive effects in the context of multifactorial inheritance, and this mode of change may contain a capacity to circumvent the pleiotropic impediment within certain limits. Classical directional selection proceeds by a simple process of adding or subtracting minor gene alleles, and this pathway seems to constitute a viable strategy for anagenetic shifts that involve only slight afﬁne morphotransformations. The anagenetic ‘‘microgenes’’ in question clearly belong to the morphogenetic equation set. However, the ascendency of anagenetic change via this strategy is to be seen, not merely as iterative and incremental with respect to gene mutation, but also as a function of changing regimes of epigenetic interactivity. The ‘‘polygenes’’ of morphogenetic change must be those regulatory loci in the epistatic system which control growth with respect to geometric coordinates systems of development that are capable of manifesting slight scalar type morphogenetic transformations, while at the same time possessing the adaptive potential to manifest more radical neomorphic change in the longer term. Polygenetic change (on the basis of neomorph mutation) therefore constitutes that incremental solution which has the capacity to form the genetic focus of ‘‘afﬁne morphogenetic transformation’’ leading to more complex domains of anagenetic change. As we have already seen, the emergence of a protropic/neotropic hierarchy in the selection interface could underlie this mode of evolutionary change

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(Chapter 12). The ‘‘anagenotype’’ is seen here as an evolved, major gene structure, expressing minor allelism within a smaller time frame, as a novel ﬂat epistatic system emerges and evolves toward the convex state. Why should the polygenetic strategy of incremental change reach an asymptote? Here, we have to assume that iterative decanalization permitting penetrance of mutational effects in certain morphogenetic domains may also give rise to epigenetic noise beyond a certain threshold point, particularly as the ‘‘iterative–quantitative’’ tends toward an ‘‘accumulative–qualitative’’ mode of change. Morphogenetic systems may only change up to that point at which decanalization releases pleiotranslational effects which tend to depress overall ﬁtness more than any leading effect can raise it. However, in the incremental change option, the pleiotropic threshold is probably capable of ‘‘shunting’’ as homeostatic control evolves over negative substructural pleiotropes, thus permitting that ongoing restructuring of developmental modularity necessary to overcome the pleiotropic impediment. The strategy of incremental change thus offers some advance against the impediment existing in negative pleiotropism. However, this alone clearly cannot explain the rapid changes observed in some fossil lineages. Where more qualitative manifestations of evolutionary change are apparent (as with the expanding expression of Hox genes discussed in Chapter 12), we once more encounter the question as to ‘‘size of quantum step.’’ Returning to the problem of negative pleiotropic effects associated with qualitative ‘‘saltational’’ events in evolution, we must again consider the possibility that incremental change in extension of the domain of expression of ‘‘upstream’’ supratranslational genes may be necessary in order to permit parallel adjustment in the homeostatic domain (so that, for example, duplication of Hox genes might in fact follow a more gradualistic pattern of change in expressivity, rather than to actually mediate instantaneous saltational evolution). The extent to which the latter option may at times be open will of course depend on the level of pleiotropic balance. In the latter context, we also have to investigate more deeply the question of morphogenetic receptivity, namely, in that ‘‘size of step’’ may also be a function of degree of differentiation appertaining to the particular morphogenetic site affected by mutational change (see below). Quantum Change in the Positive Pleiotropic Balance Solution We must now return to the vexed question as to the size of a supposed ‘‘quantum evolutionary step.’’ With relaxation of selection pressure favoring canalization, many potentially positive (or neutral) changes that have been sequestered may emerge in realized morphogenetic potential. As we have already seen, isolation in the context of a peripheral gene pool may invoke this evolutionary substrate, in which situation it would also be expected that there would also be an expansion of pleiotropism. Given degrees of freedom in adaptive potential that link up to some proportion of the expanding morphogenetic landscape, there will consequently be opportunity for fresh anagenetic advance in this scenario. One corollary of the pleiotropic balance concept in its role in the pleiotropic impediment is, as already suggested, that some mutational morphogenetic effects will in fact carry such a great advantage, that negative side effects

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invoked through developmental modularity will simply be ‘‘carried’’ as pleiophoric states (see Chapter 12). There are thus two fundamental orientations with respect to pleiotropic balance, negative (invoking the pleiotropic impediment) and positive (manifesting pleiophorism and perhaps also carrying some capacity for quantum change). The circumstance in which positive pleiotropic balance also constitutes ‘‘saltation’’ will therefore be that situation in which a large morphogenetic step constituting a very substantial positive input serves to outweigh a lesser pleiotropic load. Fundamental to any concept of anagenetic change is the underlying necessity of incremental change, since as we have already seen, many crucial arguments surrounding the developmental perspective of genetic activity unquestionably support this view. However, we must not ignore the possible viability of a positive balance existing between larger changes and an outweighed pleiotropic load. Not all negative pleiotropy can be assumed to constantly present an insurmountable genetic load problem in an actively evolving genome. Subsequent to an event of this kind, we may then presume that the pleiophroic load in question can be progressively lessened and ultimately eliminated over the course of time: Wright (1982b and elsewhere) argued that drastic mutations may be ﬁxed rapidly if the mutation is recurrent and comes to be associated with certain ‘‘modiﬁers’’ (which could of course be interpreted as alleles manifesting control over pleiotropism). Wright also suggested that all classes of molluscs could have evolved via single major mutations with dramatic effect. Positive pleiotropic balance is thus the most likely mechanism by means of which anagenesis is able to make more rapid progress in the face of a negative corollary in pleiotropic activity, and this solution may at times be instrumental in the traversing of a new, major adaptation–niche interface boundary invoking neotropic change (see Chapter 18). How large, then, is a ‘‘saltational step’’ in evolution? First, it has to be argued that there is no reason to suppose that large structural steps are taken, such as would perpetuate a signiﬁcant genetic load in maladaptive structural pleiophoric states in the longer term, and the ‘‘quantum leap’’ in question may indeed only concern the carrying of some component of negative viability in the substructural domain. What the pleiotropic balance model does show, therefore, is that the probability of selection of a neomorph mutation can be raised considerably, allowing for the more remote chance that this may at times also increase the size of the step taken. The quantum modulation hypothesis simply states that a poorly adapted phenotype can be more ﬁt than a competitor lacking any adaptational change in a given morphogenetic parameter, the essence of which strategy is a large positive advance masking a notso-large element of negative pleiotropy. Looking brieﬂy at this problem with respect to the equation set of the adaptive system (see Chapter 6), we can see that the mutant phenotype may simply hold a large area of unshared K (niche space) that is not in fact available to the wild type. In the latter circumstance, competition is not invoked, and ﬁtness is thus affected only by viability differen-

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tials that can often be adjusted logistically in that sector of the gene reservoir that is involved in the adaptive shift event (see also Chapter 18). What form do these ‘‘quantum steps’’ actually take at the phenotype level? The areas where this seems most likely to invoke large morphogenetic steps have already been identiﬁed at an earlier stage. First, whole suites of traits can be changed in the context of translational allotropism or ‘‘concerted evolution’’ (see Chapter 12). Second, certain categories of ‘‘upstream’’ mutations can bypass gross ‘‘downstream’’ pleiotropism. While these categories of morphogenetic transformation do little to resurrect the specter of the Goldschmidt ‘‘hopeful monster,’’ the capacity of such special case morphogenetic transformations to subsequently inﬂuence the adaptive radiation of higher group lineages should not, however, be underestimated. Evidence also exists to suggest that negative pleiotropic effects may indeed become integrated into evolving developmental systems in certain instances, namely, as pleiophoric states. However, this should not be taken as constituting the mainstream path to anagenetic change: Simpson (following Nopcsa, 1923) stated that some evolutionary changes resemble pathologies in other lineages; for example, bone thickening in aquatic vertebrates mimicks pachyostosis. The acromegalous condition of certain vertebrate lineages also appears to derive from a mutation that is generally highly deleterious, apparently having evolved through the medium of translational pleiotropy, suggesting that a complex reorganization of pleiotropy in terms of altered developmental modularity must have been invoked (see Huxley, 1942; also following Nopcsa, 1923). An analogy can also be found in the artiﬁcial selection of domestic animals. In dog breeds with shortened muzzles, the skin is not coordinated with changes in skull anatomy, with the result that it hangs from the head (Stockard, 1941). The latter could well constitute a negative pleiotropic effect if a trend toward shortening of the head were to occur in the wild state, but its disadvantage could be outweighed if the positive step in shortening of muzzle length also happened to be of very large adaptational advantage. A further insight into the pleiotropic balance hypothesis exists with the phenomenon of vestigiation. The genetic load from carrying a functionally redundant structure can clearly be tolerated, provided that the overall depression to the adaptive state is balanced by the gain from a changed niche interface. This scenario also shows that a broken adaptation interface does not necessarily lead to extinction, in that certain components of structure with no functional selection interface may be perpetuated owing to overall selectional balance. In contrast to the above extremes, scalar transformations, duplications, and reductions are much more widespread modes of evolutionary change in the adaptive radiation of higher groups in general, than are the supposed symptoms of massive pleiophorism (see Chapter 16). Solutions to the pleiotropy impediment in general thus lie in a combination of incremental change in the ‘‘bottom-up’’ model, and this probably often links also to the strategy of pleiotropic balance. However, determination of size of

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incremental step may often relate more to ‘‘concerted’’ than to truly ‘‘saltational’’ change (as well as being centered on certain restricted modes of morphogenetic transformation; see Chapters 12 and 16). The Inﬂuence of Gene Duplication in Resolution of Pleiotropic Conﬂict Neither incremental change nor selectional balance seem to offer much prospect of avoidance of a progressive buildup of negative pleiotropism when major morphogenetic change is occurring in an iterative manner. The most probable key to release of adaptive potential from the pleiotropic load lies with gene duplication, which has already been identiﬁed as being a major inﬂuence allowing facilitation of change to developmental modularity (Chapter 12). Clearly mutational activity may often create selectional conﬂict between different developmental modules, when some leading pleiotropic effect is positively selected on the basis of positive pleiotropic balance, thus invoking pleiophorism. The most obvious solution to such greater problems must lie with gene duplication, since this will allow functional partitioning to occur between different pro-, neo-, and pleiotropes over the course of time. If a given epistatic supergene A mutates such that (1) a positive neotrope arises in another developmental trajectory and (2) negative effects appear in the parent trajectory, then duplication (A, A⬘) will allow A to revert back to its original function, while at the same time A⬘ can be co-opted for a different one, becoming homeostatically sequestered within its own developmental trajectory in time. The pleiotropic balance scenario thus creates a selection interface favoring duplication and subsequent functional divergence of supergenes. While this conﬂict may sometimes be solved through differential splicing of a single gene locus, where the selectional differential acting against negative side effects is steep and the epistatic systems involved, highly ‘‘convex,’’ the most appropriate solution will probably lie with gene duplication. In the situation diagrammed in Fig. 71, we can see that if both functionality and developmental modularity between units A, B, and C can be decoupled, then pleiotropic effects resulting from origination of the neomorphic C function can probably be rapidly isolated from A and B. In this way, the overall pleiotropic threshold can be shifted in a dramatic manner. The ultimate release of protropic or neotropic gene effects from the suboptimum state of pleiotropic balance thus depends on a decoupling of function between pleiotropes of a single gene locus, and this can only be accomplished via gene duplication. This situation is clearly of special relevance to the question of mutation in high level regulatory genes of supratranslational status, such as the homoeotic clusters and other top-level loci (see Chapters 12 and 16). Pleiotropic Balance and the Adaptive Topography Model The role of pleiotropic balance also has some points in common with Wright’s view that ‘‘a mutation that is only very imperfectly adapted and has rather deleterious side effects may be the best available mutation to occupy a new niche’’: ‘‘The most likely cause of the origin of a macroevolutionary step is thus presentation of a vacant ecological niche to a species with a

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FIGURE 71 Gene duplication and selectional conﬂict: duplicates of the original A and B genes (see Fig. 59) are now exclusively controllant to C, thus releasing independent functions in output sites (A, B).

population structure that is favourable both for incipient speciation and for operation of the shifting balance model’’ (Wright, 1982a). The adaptive topography model should be seen thus as a dynamic structure, in which the pleiotropic balance mechanism may act to change the framework of adaptive equilibrium. In later publications, Wright incorporated the pleiotropic balance/vacant niche scenario into his shifting balance model in an attempt to extend the latter beyond the domain of microgenetic variation and into that of speciation and macroevolution (see Wright, 1982a). However, genetic drift and adaptive equilibrium are clearly unconnected mechanisms (see Chapters 13 and 15). Some means of bypassing the pleiotropic threshold in the face of iterative neomorph mutation is clearly required in any revision of the adaptive topography model, and the shifting balance hypothesis is entirely inadequate to deal with this.

Solutions to the Recombination Impediment There are clearly two different ways in which the recombination impediment may be resolved: by homeostatic adjustment in the infragene pool domain or else by splitting of the gene reservoir, that is, via the evolution of dominance or else through speciation or species substitution (as already outlined in Chapter 6). Solutions to the Recombination Impediment in Cladogenesis Solutions to the recombination impediment lie in resolution of cladogenetic conﬂict; they depend in particular on whether heterozygosis or heterokaryosis is involved, and also on the degree of complexity of the genotypic system in question—complexity of solution is a function of size of problem. This situation

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can be further illuminated by examining a general model for the cladogenetic selection interface of a gene reservoir over lineage time, this scheme offering a set of reference points for generation of the recombination impediment.

FIGURE 72 Negative heterozygosis develops in the sympatric state, while negative heterokaryosis is more a feature of allopatric divergence.

Solutions to this scenario, indicated in terms of different realizations of cladogenetic drive, can be summarized thus: a. Solutions in the Simple Heterozygotic Domain: The Homeostatic Solution • Dominance is the solution in the heterozygotic domain. The negative hybrid state is eliminated through epigenetic homeostasis alone (⫽ minor cladogenesis; see Chapter 6). b. Solutions in the Complex Heterozygotic–Heterokaryotic Domain • Racial merging or genomic anastomosis occurs whenever divergence between emergent gene pools is not so extreme that one race has great advantage over another and when the hybrid state remains ‘‘reversible,’’ so that two emergent gene pools subsequently re-form as one. This constitutes the proximal–allopatric solution, in which ‘‘two way substitution’’ of gene alleles occurs. • Speciation occurs when divergence is greater, and where depression due to negative heterokaryosis can most readily be solved by reproductive isolation. This may be referred to as the median–allopatric solution. • Cladogenetic substitution or species substitution occurs when genetic divergence between competing gene pools is so great that negative heterokaryosis can only be solved by speciation, and where also no extrinsic cladogenetic potential exists for cosurvivorship in a completely coincident niche intersect, resulting in the elimination of one incipient species. This constitutes the distal–allopatric solution. Cladogenetic substitution has only received passing mention up until now, but this mechanism will be shown to be of considerable signiﬁcance in understanding several manifestations of longer term evolutionary activity (see Chapters 17 and 20). As with speciation itself, cladogenetic substitution constitutes

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an expression of major cladogenesis (in that there is, in either case, a binary resolution of cladogenetic drive, as 1:1 or 1:0 for speciation versus cladogenetic substitution, respectively). Solution in Dominance To summarize our earlier discussion of minor (pheno-) cladogenesis, in the cladogenetic selection interface, negative heterozygosity can be suppressed homeostatically through the action of dominance. The outcome of this process is centrifugal polymorphism, where allelomorphism reaches phenotypic expression solely in the domain of the viable homozygote classes. Dominance is thus tailored to the demands of the cladogenetic selection interface, operating solely within the domain of allelomorphs of a single gene locus. Polymorphic states may therefore tend more to gravitate toward dominance when there is spatial, but not temporal dynamism in selection proﬁle. The dominance solution is essentially bound to a ‘‘low level problem’’ in the recombination impediment, and it clearly cannot proceed beyond a certain limit. Resolution in Genomic Anastomosis and Speciation Speciation clearly constitutes a solution to the problem of the recombination impediment. Greater levels of recombination impediment cannot be solved by homeostatic adjustment, and obviously must require more drastic measures. Quite apart from the speciational solution itself, suppression of hybrid nonviability may very often be observed in racial merging: Dobzhansky (1970) showed that races are not necessarily ‘‘incipient species’’ and also that race formation is reversible. As already stated, species isolation is partly a by-product of the accumulation of genetic differences in allopatric gene pools, but it can also be actively evolved by selection when hybrids are of lowered ﬁtness. However, if relatively few differences have evolved, then genomic anastomosis is the more likely result. The nonviability component of complex negative heterokaryosis clearly lies beyond the control of dominance, and homeostatic control of simple negative heterozygosity is thus unlikely to play a large part in resolving the recombination impediment at that level. Additionally, where gene pools have evolved in the context of longer term allopatry, the option of racial merging is also less likely to remain open. Where suppression of the negative hybrid class is beyond the limits of dominance (as in large structural haplogenes as against minor or substructural traits, and genetic anastomosis is also no option), selection may thus act either to eliminate one genotype or gene pool, or to favor genome splitting in speciation. As has already been postulated, pressure for speciation through reinforcement probably only evolves in the neosympatric case, since only then has there been the capacity for two subgenotypes to diverge widely enough in order to manifest a very large hybrid anomaly. In the plesiosympatric case, the recombination impediment may most usually simply prevent divergence of allelic phenotypes beyond a certain point, thus functioning effectively as an

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impediment to realization of cladogenetic potential. Speciation, genomic anastomosis, and cladogenetic substitution should therefore be interpreted as solutions to impediments on evolutionary change, as well as constituting resolutions of cladogenetic drive. The level of hybrid depression in emergent gene pools can be quite considerable and, as already suggested, will tend to be accentuated in neosympatric populations: Hybrid viability has been investigated between emergent gene pools of an apparent ‘‘superspecies.’’ Drosophila paulistorum has some semispecies, crosses between which occur with difﬁculty, although a few partially fertile matings do occur (see Dobzhansky, 1970). Numerous polygenes are involved in this, and maternal cytoplasm affects the sterility of males. All semispecies are highly heterokaryotic for 89 inversions, some of which are homozygous for a semispecies. Where semispecies distributions do overlap, there is no interbreeding. Ehrman (1965) recorded coefﬁcients of ethological isolation for sympatric versus allopatric strains of two semispecies as being 0.85 and 0.67, respectively, thus showing selection for increased isolation for the sympatric populations. Transitional populations where ‘‘strains’’ cross easily and give fertile hybrids are also found (see also the Coyne–Orr data discussed in Chapter 6). Much evidence has accumulated to show that complex chromosomal differentials form an important component of cladogenetic drive, and this agrees with the view that haplotype differentials lie at the heart of much hybrid depression, namely, in forming the focus of complex negative heterokaryosis: In Drosophila, species differences are more often due to inversion than to translocation (although the latter clearly plays a signiﬁcant role in repatterning, in that changes in chromosome number are brought about by various kinds of translocations; see Dobzhansky, 1970). Some species hybrids of Drosophila are ‘‘homosequential,’’ whereas others differ in several inversions of the paracentric kind. Some taxa have multiple centromeres (Dobzhansky, 1970), which seems to have allowed proliferation of chromosome number in speciation (Erebia butterﬂies and saturniid moths), thus further conﬁrming a role for chromosome mutation in the generation of cladogenetic drive. Finally, reference must again be drawn to the fact that no clear evidence exists to link karyotypic change with anatomical divergence (see Maynard Smith, 1998), which is not surprising considering the link between chromosome structure and recombination.

Solutions to Leading Effect Allomorphism—A Substrate for Anagenetic Evolution Leading effect allomorphism lies behind the recombination impediment and also affects selectional balance in the control of the pleiotropic impediment. This makes it the key factor for realization of adaptive potential in the context of a deﬁnable ‘‘evolutionary substrate.’’ What is this substrate?

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The most obvious solution to the problem of leading effect allomorphism is of course that some anagenetic changes may simply be of such great contribution to ﬁtness that they do in fact actually constitute leading effects in the ﬁrst place. However, given the overriding inﬂuence of allomorphism, this situation would seem most likely to evolve only when there is some form of disruption to the ambient adaptive state. There must be certain proscribed conditions within adaptive systems under which the inﬂuence of leading effect allomorphism at times gives way to directional evolutionary change in the anagenetic domain. The substrate in question seems most likely to emerge in the context of a gene pool manifesting both lowering of competition and relegation of allomorphic heterozygosity to sequiform status in the gene pool. That circumstance within which the evolutionary substrate in question can be manifested clearly contains some element of change that has lead in turn to diminishment in status of adaptive equilibrium with respect to ambient adaptive capacity (of which apparent loss of heterozygosity will then constitute a natural corollary). Such an event could occur, for example, during an adaptive shift toward some new niche resource (see Chapter 17), either endogenously through novel mutation or via extension of dispersal range. In this manner, a ‘‘fugitive’’ gene pool may on occasion manifest some innovation on the basis of which a ‘‘peripherally isolated’’ population becomes the substrate for fresh evolutionary change.* Changes in the domain of heterozygosity and diversion away from the leading effect factor in allomorphism leading to subsequent complete release of an impediment to anagenetic change can only come from contraction of the domain of adaptive equilibrium, and this must therefore constitute the essential factor in a ‘‘substrate’’ population. This interpretation is clearly entirely distinct from the view that stochastic changes in gene frequencies are invoked owing to sampling error, as has often been supposed (see Chapters 13 and 15). Relaxation of selectional regimes maintaining adaptive capacity in dynamic equilibrium consequently holds a vital release factor for evolutionary change. This should, however, not be construed as actual loss, so much as changed status of heterozygosity in the ambient selection interface: Coope (1995) similarly argued that natural populations are exceedingly heterozygous, a wide variety of different genetic combinations resulting in the emergence of a stable wild type. In situations where there is reduced heterozygosity, however, the genetic constraints that maintain species constancy would become weakened, increasing the likelihood of novelties, ‘‘analogous to the early stages of domestication.’’ Similarly, Carson’s reinterpretation of the founder effect (Carson, 1970) concerns permissive selection allowing formerly unﬁt genotypes to survive (the ‘‘ﬂush–crash’’ model). Eldredge and Gould (1972) also argue that the genetic homeostasis of Lerner (1954) must be relaxed in the context of punctuated equilibrium. How* However, we should also bear in mind the fact that such changes are by no means excluded from the endogenous domain (see Williams, 1992, for a critique of the peripheral isolation model of speciation).

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ever, Lerner’s view of the function of canalization is not in accord with that accepted here (see Chapter 12). Clearly, the conditions for evolution include an apparent ‘‘rarity factor,’’ which latter element, of course, creates problems for the actual paleontological location of evolution in action (see Chapter 18). The problem of the leading effect impediment clearly also requires deeper analysis with respect to evolutionary rate (as also of stasis; see Chapters 18 and 19). Morphogenetic Receptivity and the Endogenous Evolutionary Substrate We have now identiﬁed that likely substrate in the external environment under which evolutionary change has the highest probability of taking place. However, it also seems likely that there must also be a complementary ‘‘endogenous substrate.’’ The emergence of novel anagenetic change in the above context must be linked to the presence of some element of functionally redundant or ‘‘vacant’’ morphospace in which decanalization has become localized, so permitting expansion of morphogenetic potential. In this, the ‘‘substrate of anagenesis’’ contains more than a single rarely encountered factor. Solutions proposed to the question of neomorphic evolutionary change in development and the interpretation of dynamics within the genome mobility hierarchy have both postulated epigenetic lability as a vital substrate for certain mechanisms to operate (see Chapter 12). The problem of morphogenetic receptivity in the face of mutational change clearly requires deeper analysis at this stage, namely, in its probable role of constituting the endogenous evolutionary substrate. The question as to whether ‘‘quantum leaps’’ can be permitted in the neotropic mutation of certain classes of ‘‘upstream’’ supratranslational regulatory genes such as the Hox clusters has been raised in earlier chapters, and this problem is clearly linked in turn to the question of pleiotropic balance and morphogenetic receptivity. What circumstances allow the pleiotropic balance mechanism to be most readily absorbed in the role of accumulative, iterated change to major morphogenetic parameters, and in what kind of developmental substrate may decanalization permit rapid anagenetic change via reorganization of developmental modularity in the context of neotropic mutational effects? Decanalization may occur wherever selection pressure against randomization in epigenetic interactions is relaxed, and this seems intuitively likely to occur in certain proscribed morphogenetic zones. Clearly, we must now consider the ambient state of canalization of the morphogenetic substrate concerned. There appear in fact to be three possible developmental substrates for major morphogenetic change. The differential between these substrates reﬂects different levels of morphogenetic receptivity, as an expression of the degree to which a given locus of translation may manifest mutational (and particularly neotropic) change—as a function of endogenous lability and also of modular links to other active parameters in the developmental environment. These substrates are as follows: 1. Active morphospace: structure integrals manifesting a fully active adaptation interface plus a high level of structural differentiation. It

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seems axiomatic that change to active morphospace is likely to involve only minor ‘‘downstream’’ changes to existing parameters, in that here there will be a very low pleiotropic threshold. In this circumstance, the ambient state of canalization therefore seems likely to prevent ‘‘saltational’’ change: ‘‘Concerted’’ (translational–allotropic) change is perhaps the only example of a mutational strategy which does seem to have some limited potential to operate in ‘‘active’’ morphospace. 2. Redundant morphospace: zones of highly differentiated tissue with complex superstructural links to a former adaptation interface that is now at least partially functionally redundant. Functional redundancy must have the capacity to permit relaxation of selection favoring canalization, thus allowing passive decanalization to occur. In this circumstance, the pleiotropic threshold might be expected to be higher, but with greater morphogenetic receptivity than in fully active morphospace (thus with greater capacity to support a large pleiophoric load): The pentadactyl limb of vertebrates, in the adaptive shift from aquatic to terrestrial (or terrestrial to aerial) environments, shows a continuously ‘‘active’’ superstructure in which certain morphogenetic coordinates have nevertheless become functionally redundant in one aspect, while at the same time becoming specialized in a new functional direction. Brusca et al. (1997) discuss the altered expression of genes changing limb morphology (Nelson and Tabin, 1995; also Sordino et al., 1995). In the early limb bud of chick and ﬁsh embryos, Hox genes are only expressed at the posterior end. In the tetrapod foot, however, they are additionally expressed across the distal mesoderm, coincident with the digital arch. This proves that ﬁn rays are not homologous with the digits— and again illustrates the emergence of morphogenetic neotropism in (partially) redundant morphospace. 3. Vacant morphospace: morphogenetic zones with low levels of structural differentiation and a low contribution to overall ﬁtness, in which there may well exist an intrinsically low level of canalization. Here, we may suspect that there may be much greater tolerance of pleiotropy in the context of a higher threshold that would permit the emergence of profound protropic or neotropic effects: The abdominal tympanal organs of certain ditrysian Lepidoptera evolved independently in largely undifferentiated tissue at the abdominal base in several nocturnally adapted lineages. Morphogenetic receptivity (now understood in terms of ‘‘receptivity to neotropic expression of supratranslational regulatory genes’’) is thus high with partial functional redundancy, where decanalization can occur with no net depression of ﬁtness in pleiotropic balance, and it is also strongly manifested in ‘‘vacant’’

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morphospace. The effect of morphogenetic receptivity can thus be seen to be that of presenting a higher pleiotranslational threshold which constitutes an appropriate substrate in which decanalization can safely be permitted expression. Large scale neotropic changes in evolution must therefore be linked to domains of high morphogenetic receptivity and low pleiotropic resistance of that kind. It seems, in fact, intuitively obvious that vacant or redundant morphospace should form the substrate for neotropic change, and fully ‘‘active’’ morphospace for trivial quantitative modulation solely within established morphogenetic parameters. Certain morphogenetic substrates may thus have a more distant pleiotropic threshold than others, and this will be conducive to implementation of greater mutational steps. In broader developmental terms, decanalization can ideally be viewed as a tendency toward randomization of epigenetic interactivity in functionally redundant or relatively undifferentiated low ﬁtness value morphospace, which mechanism manifests a potential to open up certain morphogenetic trajectories to previously canalized determination factors, in both the genetic and nongenetic domains: The role of redundant or vacant morphospace is often evident in the ‘‘preadaptation’’ scenario characteristic of major adaptational changes (as in the vertebrate limb and tympanal organs examples quoted above), and this is clearly linked in turn to the maxim that many superstructures perform more than a single function. The next question is clearly that of how ‘‘redundant morphospace’’ actually comes into being in the ﬁrst place. Niche shift events (see Chapter 17) may clearly act to partially transform active to redundant morphospace (as in the origins of ﬂying appendages in several lineages), thus releasing certain developmental coordinates from intense homeostatic control and creating a morphogenetic receptivity substrate for the process of decanalization. When a niche shift involves some functional change, there may therefore be latent adaptive potential residing in some component of redundant morphospace that is now tending toward a decanalized state. Hence, macroevolution has an innate capacity to ‘‘ﬁnd its own developmental substrate,’’ and decanalization is thus, in some sense, automatically site speciﬁc. How can the panstatic model for neomorphic change in a morphogenetic parameter (Chapter 12) be aligned with the above hypothesis? Morphogenetic receptivity clearly now has to come into the equation. An adaptive shift leads to morphogenetic receptivity being raised in parameter X (see Fig. 60). This is in turn followed by penetrance of neotropic inﬂuences to a zone of increasing morphogenetic receptivity resulting from passive decanalization.* Where morphogenetic receptivity comes into play, we thus witness a situation in which there may be an extension of the domain of allotropic gene expression into additional morphospace, namely, through an increase in epigenetic lability. Another way of looking at the same phenomenon is to consider that the modularity inherent to certain developmental trajectories is permitted some degree of freedom at certain levels. * For reasons given earlier (pp. 243–245), this mechanism will generally be linked to gene duplication.

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Does the existence of a suitable substrate in morphogenetic receptivity now solve the problem as to whether duplication of Hox genes actually mediates saltational evolutionary change? It is in fact not possible at present to say that this is so. First, the levels of pleiotropism and suboptimality of design associated with such an event seem likely to be high. For example, any duplicational transformation involving addition of ‘‘supernumerary’’ limbs or other appendages would have to assume that the appropriate neuromuscular changes could all occur simultaneously through translational allotropism alone—also that central neural control over these appendages would immediately be rendered possible. Furthermore, a more gradualistic solution (as with appearance of ‘‘pseudopods’’ which might at a later stage evolve into true duplicates of other appendages) seems a possible alternative. In the ﬁrst place, pseudopods are quite common developments in many lineages of arthropods and annelids, and, second, some of them (as with the prolegs of lepidopterous caterpillars) actually involve partial expansion of the domain of expression of Hox genes (see Chapter 16). Finally, there is no reason why duplication of homeotic genes should not follow expansion of expression as a mode of control over an advancing pleiotropic impediment; indeed, this is usually assumed to be the case with supratranslational gene duplication in general. Consequently, some level of skepticism must remain concerning the possible role of Hox gene duplication in ‘‘saltational’’ evolution.

MAIN POINTS FROM CHAPTER 14 1. Evolutionary impediments (where ‘‘change should happen but is in some way restrained’’) must not be confused with so-called constraints (‘‘change does happen but is preferentially directionalized’’). 2. Mutational change to an epistatic system meets resistance in the form of pleiotropic impediments, and also from leading effect and recombination impediments, the latter acting to impede adaptive potential for evolutionary change in favor of ‘‘adaptive capacity in dynamic equilibrium.’’ The strategy of adaptive capacity thus holds a particularly strong restraining function over realization of adaptive potential through the inﬂuence of leading effect allomorphism. 3. Leading effect allomorphism may often be held by only a few loci within any limited time frame. Its effect on adaptive potential is to diminish the contribution to ﬁtness of newly evolved nonallomorphic alleles, including those of the anagenetic kind. 4. The recombination impediment is manifested in heterozygosis in the plesiosympatric state, and in complex heterokaryosis in the neosympatric situation. 5. The pleiotropic impediment tends to allow only incremental change, whereas the recombination impediment favors cladogenesis. The former can be bypassed via iterative phenotypic change linked to homeostatic adjustment, positive pleiotropic balance, and gene duplication, and the largest ‘‘quantum leaps’’ can only occur through a combination of all of these factors.

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6. Negative heterozygosis in the recombination impediment can be resolved through minor cladogenesis, and complex negative heterokaryosis, through speciation (major cladogenesis). 7. Profound anagenetic change is unlikely to occur unless leading effect allomorphism can be bypassed. The evolutionary substrate is thus linked to the collapse of adaptive equilibrium (which means not ‘‘loss,’’ but ‘‘selectional irrelevance’’ of heterozygosity). Release from ambient adaptive equilibrium can best be facilitated in gene pools carrying a deﬁnable environmental substrate arising through lowering of both inter- and infraspeciﬁc competition. 8. Decanalization in zones of high morphogenetic receptivity linked to functionally redundant and/or ‘‘vacant’’ morphospace forms the ideal endogenous adaptive substrate for evolutionary change. This substrate could hypothetically allow saltational change through direct duplication of the Hox genes; however, a more iterative mutational pathway seems intrinsically more likely to provide a viable basis for most macroevolutionary change.

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DARWINIAN VERSUS THOMPSONIAN FACTORS IN EVOLUTION

This chapter examines the role of that category of ‘‘evolutionary constraints’’ through which structural changes are preferentially directionalized owing to limited degrees of freedom inherent to certain input mechanisms to the behavior of adaptive systems. In this, special reference will be drawn to the question of how the topology of evolutionary change is determined through morphogenetic transformation, with respect both to factors arising in the external selectional environment and to endogenous inﬂuences deﬁned by the relationship between preexisting structure and the probabilistic behavior of genedevelopmental systems. Here, we are no longer concerned with impediments (which are now assumed to have been bypassed), and the constraints in question are those ﬁrst examined in Chapter 7. In the present endeavor, we are looking more deeply into the ‘‘internal factors’’ approach of Thompson (1917) in the context of its position within a general theory of evolution that cannot be legitimately categorized as being truly ‘‘neo-Darwinian’’ in nature. This leads naturally to the clash between ‘‘structuralists’’ (who support a predominantly ‘‘neo-Thompsonian’’ view of evolution) and ‘‘neo-Darwinists,’’ who are opposed to the notion of any signiﬁcant endogenous factor directing the path of evolutionary change.

EXTRINSIC AND ENDOGENOUS DIRECTIONALIZATION FACTORS IN EVOLUTION Adaptive potential and the biophysical paradigm linked to adaptive niche clearly constitute vital inﬂuences controlling the evolving topography of structure, and in this we encounter the question as to whether endogenous factors

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can somehow drive the directionality of evolution independently of any signiﬁcant input from the external environment. This question has also become entangled with hypotheses relating to the perpetuation of nonadaptive and maladaptive traits, and this problem must be explored at the same time. What endogenous factors are involved in the organism–environment interaction, and in what way do they relate to extrinsic forces tending to draw evolution in the direction of adaptational advance? The answer to this question lies in the architecture of an adaptive cascade describing that hierarchy of causal factors which acts to determine the directionality of evolutionary change.

Degrees of Freedom in the Adaptive Paradigm The complex of deterministic factors affecting the topology of evolutionary change clearly stems from an array of extrinsic and endogenous inputs to the architecture of the structural attractor, namely, in the biophysical paradigm and the structural component of adaptive potential (Chapter 7). Consequently, any analysis must be linked to the question of degrees of freedom existing in these factors. Within this construct, the adaptational paradigm itself concerns those physical laws by which a given mechanism can function in the environment, and different coordinates within this may clearly manifest different degrees of freedom. Certain ‘‘rigid’’ parameters must be closely constrained by factors linked to the fundamental physical laws as they relate to functional requirements of a given adaptation (as with provision of lift in the context of the ﬂight mechanism), while other more labile coordinates may contain a larger number of possible solutions (for example, the range of viable fabricational materials which could be used to construct a wing): The wings of birds, insects, and bats all share certain principal coordinates in terms of essential aerofoil design properties, despite being constructed of quite different fabricational materials, and despite wide divergences between the ancestors of lineages evolving ﬂight in Reptilia, Arthropoda, and Mammalia. It is essential to understand that the biophysical paradigm relates directly to the extrinsic component of adaptive potential residing at the niche interface, so that this factor must not be seen as one that in any way reﬂects ‘‘endogenous constraints.’’ It is in fact the exogenous input to the adaptive cascade, as determined by the niche interface itself.

Degrees of Freedom in Endogenous Adaptive Potential Genuinely ‘‘internal’’ factors affecting the topology of evolutionary change must lie in the endogenous component of adaptive potential. The morphogenetic landscape for equiangular spiral shells (Chapter 7) is a good exemplar for the concept of endogenous adaptive potential, which latter consists, as we have seen, of the adaptationally positive subset of this array. From the architecture of adaptive potential as described by the viable component of morphogenetic potential, we thus arrive at a further set of degrees of freedom in the adaptive cascade, and clearly there is also an intersect between degrees of freedom as expressed in the biophysical paradigm (‘‘the number of ways a given function

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may be carried out’’) and those in adaptive potential (‘‘the range of morphosystems actually within reach’’). The structural attractor of the adaptive system accordingly lies in the intersect between the biophysical paradigm and architecture of adaptive potential. The endogenous component of adaptive potential thus acts to constrain the selectional attractor, which latter is seen as an intersect between extrinsic and endogenous factors determining the range of possible viable solutions to a given functional problem in the interplay between complex deterministic factors operating in the adaptive system and stochastic processes tending to impinge on them. Slightly extending the earlier scheme (Fig. 37, Chapter 7), we can now additionally indicate how the topology of evolutionary change must be determined following a trajectory of iterative mutational change.

FIGURE 73 Topology of evolutionary change, following the architecture of the structural attractor.

The number of degrees of freedom manifested in the system shown in Fig. 73 clearly forms one basis for directionality in evolution arising from endogenous factors, while at the same time in no way excluding an adaptationist analysis. The major question here is clearly, can purely endogenous adaptive potential in any way ‘‘drive’’ the topology of evolutionary change independently of the inﬂuence of the adaptive biophysical paradigm? This question has become one major focal point in the dichotomy between classical Mendelian and contemporary developmental genetics.

Darwinian versus Thompsonian Transformation Factors and the Endogenous Selection Interface The Darwinian element in the structural attractor clearly lies with the niche interface and adaptational paradigm. Endogenous factors lying in the structural

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component of adaptive potential likewise form a heterogeny of elements which may now be conveniently grouped together as ‘‘Thompsonian factors.’’ Purely Darwinian transformation factors may thus be deﬁned as any morphogenetic change which constitutes an advance toward the adaptive biophysical paradigm, while a major subset of Thompsonian transformation factors similarly relates to endogenous elements affecting movement via realization of morphogenetic potential.* The Darwinian input seems intrinsically likely to predominate in phenogeny, where an external adaptation interface is by deﬁnition fully active. The endogenous Thompsonian element may, on the other hand, predictably have a much greater inﬂuence in ontogeny sensu stricto, in that topological changes may tend here to simply follow the most parsimonious pathway in a sequence of adjacent morphosystems lying in the fabricational route to the phenotype state. ‘‘Pure’’ ontogeny could then be the main focus of rigidly Thompsonian transformations of development, since fabricational parsimony is the focus of the endogenous selection interface (see Chapter 9). Degrees of freedom intrinsic to the biophysical paradigm may then tend to be greater for Thompsonian than for Darwinian transformations, for fabricational precursor states evolving around developmental parsimony paradigms that have no active function in the external adaptation interface. Thompsonian solutions may therefore predominate in earlier development whenever adjacent systems also carry a lower energy expenditure. Ontogeny sensu stricto may seem thus to afford the strongest evidence for the hypothesis that Thompsonian ‘‘self-ordered’’ systems have been selected in evolution, with respect to elements of superstructure for which extrinsic biophysical paradigms have fallen into functional redundancy but which subsequently have come to form essential fabricational trajectories. However, this does not necessarily automatically exclude a Thompsonian element from also occurring in phenotype traits, and indeed more recently, there has been a considerable upsurge of interest in this question. Since extrinsic Darwinian and endogenous Thompsonian factors inﬂuencing the topology of morphogenetic change clearly do exist in reality, they must also contribute in different ways to differentials between diverging genotypes during the course of evolution. What inﬂuence do extrinsic versus endogenous factors actually have on differentiation and divergence of form as cladogenesis subdivides a lineage, and as anagenesis introduces linear structural progression into the phyletic scheme? Endogenous factors appear to particularly illuminate the self-organizational element expressed in some structuralist interpretations (see below), but to what extent does the apparently acceptable inﬂuence of structure-driven modulation for ontogeny apply also to the phenogenetic phase of development, as expressed in the active adaptation interface of the phenotype? * Note that Thompson also studied some aspects of the biophysical paradigm! However, apart from this, he was a major exponent of the criterion of ‘‘self-organizational’’ or endogenous factors in evolution; in his own words, ‘‘I have tried . . . to lay emphasis on the direct action of causes other than heredity.’’ Thompson did not in fact discriminate between extrinsic and endogenous elements, and this is probably linked to his relative isolation from the mainstream evolutionary thought of his time.

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In summary, a primary dichotomy clearly lies between extrinsic and endogenous inﬂuences, leading to manifestation of apparently niche-driven exogenous (Darwinian) and structure-driven endogenous (Thompsonian) transformation factors, respectively. A question clearly remains as to the inﬂuence of the latter element in determining the architecture of the ﬁnal phenotype state. Before attempting to answer the above question, we should also look a little more deeply into the Thompsonian input. In the diagram shown in Fig. 74, we can see that endogenous constraints link to morphogenetic potential, while at the same time many of Thompson’s seemingly ‘‘internal’’ factors really relate to parameters of extrinsic adaptive potential in terms of the biophysical paradigm concept (see Chapter 7). These facts should be borne in mind in consideration of the relationship between structuralism (see below) and the work of Thompson.

STRUCTURALIST MODELS OF EVOLUTIONARY TOPOLOGY The broad concept of structuralism, the view that morphogenetic differentiation in evolution can in some way be driven by purely endogenous propensities of the genetic system to the greater or lesser exclusion of adaptation and/or selection, has sometimes been used to emphasize the ‘‘self-organizational’’ aspect of the topology of structural change, and sometimes as evidence favoring a predominantly nonadaptive component in evolution. Goodwin and Trainor (1983) deﬁned structuralism as ‘‘analysis in terms of developmental mechanisms and the families of forms they can generate.’’ However, different interpretations within this broad view vary in the degree to which nonadaptivity is presumed to be invoked. ‘‘Hard’’ structuralism must also be seen as introducing a quite different perspective on endogenous factors to that originally envisaged by Thompson (see Bonner, 1966), in that he did not attempt to deny the inﬂuence of selection in his own interpretations of evolution (although paradoxically, Thompson did doubt that it served as a progressive force). Only an extreme view of structuralism would, however, attempt to make the supposedly nonadaptive element apparently indigenous to certain Thompsonian transformations a general rather than special mechanism for evolutionary change, thus ignoring the pivotal role of adaptation and natural selection. In contrast, a ‘‘softer’’ constraintive model of structuralism would obviously take a much less polarized viewpoint. In general, it would perhaps be better to consider the ‘‘soft’’ structuralist viewpoint as being closer to a ‘‘neo-Thompsonian’’ model.

Hard Structuralism and Autogenesis The purest form of structuralism is frequently linked to the concepts of selforganization and spontaneous order. However, such inﬂuences can only be truly identiﬁed in autogenesis (following Plate, 1913), where form is determined directly by chemical or physicomechanical properties of growing cells or tissues in a strictly autonomous manner (as with the apparently direct interaction between development and the gravitational force, or in the Turing model; see

FIGURE 74 tionary change.

Interactivity of Darwinian and (all) Thompsonian factors affecting the topology of evolu-

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Chapter 10). True autogenesis has been implicated mainly for cellular level structural determination, and in terms of body form in certain simple multicellular organisms (although an effect on certain elements of form has also been claimed for some higher organisms): The radially symmetrical blastoderm of the chick embryo becomes a bilaterally symmetrical structure under the inﬂuence of gravity. Thomson (1988) discusses the self-assembly of ﬁngerprints: since the potential number of combinations is so large, each is unique. This again could be said to invoke a structuralist element in morphogenesis. In the last mentioned example, we observe that nonadaptive differences at the phenotype level may perhaps tend simply to occur in trivial coordinates where they apparently make little or no contribution to ﬁtness. The autogenetic function thus lies with that part of developmental topology determined by the physicochemical behavior of cells and tissues, apparently irrespective of direct, active control systems in the epigenetic code. This clearly could be equated with a ‘‘hard’’ structuralist model, namely, in the elimination of any need for the involvement of selection. However, the extent to which autogenesis penetrates complex phenotype superstructure in higher organisms is a more difﬁcult question, and it can be shown also that the concept of autogenesis itself is only fully acceptable under an adaptationist interpretation (see pp. 336–337).

Soft Structuralism and the Simpsonian Nonadaptive Differential Leaving the extreme view of autogenesis aside, a more promising hypothesis for an apparent nonadaptive factor in evolution might lie with the Simpsonian concept of a nonadaptive differential, and this also forms one possible rationale for a ‘‘soft’’ view of structuralism. The weaker version of structuralism sees constraints arising from the fact that there are only a limited number of developmental mechanisms. One can additionally distinguish ‘‘structure-driven’’ traits as ‘‘carrying’’ nonadaptivity in a sense that is more linked to ‘‘constraint’’ in the sense of factors inﬂuencing directionalization. This aspect can be explored following the view of Simpson, who thought that little evidence for truly maladaptive divergence existed (apart from in trivial characters), but also referred to ‘‘a large number of examples of dichotomies between groups,’’ which he thought were probably nonadaptive as differences: Simpson (1953) proposed the existence of a nonadaptive differential between cephalopod and vertebrate eyes, also citing the one versus two horned condition in rhinos as an example of ‘‘adaptively oriented selection acting on adaptively unorientated materials that limit possible avenues of change.’’ Stebbins (1950) likewise held that many differences in plants are of this kind. Simpson stated that adaptation is, in the above examples, ‘‘intergroup as against extragroup,’’ that is to say, certain structural differences have emerged directly from endogenous adaptive potential differentials between unrelated lineages. The outcome of differential realization of topologically different structural states with no selectional differential could thus be expressed in the

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generation of adaptationally equivalent states correlated with divergence of lineages during speciation. This is essentially a reformed structuralist interpretation—not autogenesis, but ‘‘n ways of achieving exactly the same adaptational goal.’’ Much apparent ‘‘nonadaptivity’’ could in fact constitute a nonadaptive differential, rather than true maladaptivity. We can now see a meaningful dichotomy emerging between ‘‘nonadaptivity’’ in the sense of truly maladaptive traits (as would emerge only in the context of pleiophorism; see Chapter 12) and nonadaptive features in the sense of a Simpsonian nonadaptive differential. From this point on, we shall therefore choose to use the latter terms in the strict deﬁnitions just given. Much of the argument surrounding the existence or nonexistence of ‘‘nonadaptive evolution’’ in fact centers around this dichotomy, and it is necessary to avoid semantic traps of this kind in any rational analysis. Paradoxically, the adaptationally equivalent states concept seems to rescue nonadaptive evolution actually within the context of adaptationism, the Simpsonian concept being an apparently acceptable rationale for the origins of nonadaptive diversity patterns (rather than noadaptive traits, as such). There are, however, two possible interpretations of the nonadaptive differential, assuming that the differential between two structural states genuinely lies, not in any relative adaptational dichotomy, but in degrees of freedom in the structural attractor alone. The nonadaptive differential could clearly be either structure-driven (endogenous adaptive potential) or niche-driven (biophysical paradigm). This dichotomy can be summarized as follows: 1. Structure-driven: Major coordinates of the adaptational paradigm may be intrinsically ‘‘free,’’ allowing more than one structural solution to exactly the same functional problem. Nonadaptive differentials would then lie between n biophysical paradigm states of equal adaptive value, thus allowing purely ‘‘structure-driven’’ differentiation of form: Plants should show greater freedom in the adaptative paradigm than animals, since they are less bound by dynamic biomechanical systems. There may (for example) be n different leaf arrangements with exactly the same photosynthetic capacity. Niklas (1988) holds that although the form of terrestrial plants is limited by physical constraints imposed by the performance of metabolic and structural requirements, there is no optimal design, only a domain within which various geometries are possible, each being as satisfactory as any other. 2. Niche-driven: True adaptationally equivalent states might alternatively arise owing to degrees of freedom in the endogenous morphogenetic potential, as a ‘‘reformed structuralist solution’’: The particular leaf arrangement of a plant species may simply be that most readily generated by a given developmental system, and may differ from that of another species, merely because of disparity between developmental systems giving rise to a particular form. However, this apparent dichotomy can be shown to be a naive view of the reality (see below). In particular, it is not at all clear that model 2 is not just

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model 1 translated into the language of structuralism! This view of the ‘‘soft’’ structuralism mechanism clearly needs closer analysis.

Interaction Between Darwinian and Endogenous Thompsonian Factors in the Adaptive Cascade Following the two seemingly independent modes of nonadaptive differentiation proposed above, and returning to Simpson’s example of the one versus two horned rhino dichotomy, it is easy to see how the same interpretations could apply (assuming no adaptive differential exists between one and two horned states): • Niche-driven: two equivalent solutions in the biophysical paradigm, Darwinian (⫽ exogenous) nonadaptive differential • Structure-driven: two equivalent solutions in morphogenetic potential, Thompsonian (⫽ endogenous) nonadaptive differential We have thus postulated the existence of niche- versus structure-driven diversiﬁcation as two apparently independent models for the supposed nonadaptive differential, either of which mechanisms could (hypothetically) generate adaptationally equivalent states, but only the second of which constitutes ‘‘structuralism’’ in the sense of being an endogenously driven mechanism. To appreciate the fundamental underlying interdependence of niche-driven versus structuredriven factors it is necessary to continue to investigate the way the biophysical paradigm and adaptive potential interact in determining degrees of freedom in the structural attractor. The train of events leading to determination of preferred directionality of morphogenetic change begins with the link between adaptive niche and biophysical paradigm in the interaction between the latter and endogenous adaptive potential, in terms of the degrees of freedom residing in each. In a dynamic model, we must therefore hold that Darwinian and Thompsonian transformation factors can only affect the topology of modulations to structure in a mutually interacting manner, since degrees of freedom in endogenous adaptive potential must interdigitate with complementary parameters in the adaptational paradigm. The above axiom can perhaps be most easily understood in relation to the changing relationship between the adaptive paradigm and morphogenetic potential as a common function of change in size. The question of degrees of freedom in the biophysical paradigm clearly holds a signiﬁcant input from absolute size (as with the relationship between mechanical structures and gravitation), and this can be used to illustrate the ongoing dialogue between ‘‘external’’ and ‘‘internal’’ inﬂuences, even where an exclusively endogenous element might at ﬁrst glance be suspected to be in operation: The dimensional component can easily be identiﬁed in the different physical paradigms for wing form in very large as against very small organisms, for example, comparing birds with chalcid wasps; similarly, in limb proportion differences between large and small mammals, also in the upper size limit of Arthropoda arising from the diffusion law

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and the structure of the tracheal system. Allometric transformations to limb structure, for example, show predictable correlations with demands intrinsic to the fundamental physical laws as body size increases as a function of the fact that area increases as a squared power, and volume (and thus also mass), as a cubic power of linear dimension. An absolute size change can mean either a positive or a negative change, relative to preexisting values, and any modulations of this kind will tend to affect the intrinsic nature of the adaptational paradigm, whenever design is constrained by size as a function of interaction between biophysical systems and gravity. However, this must not be interpreted as being an ‘‘endogenous’’ transformation factor, since size change must inevitably also reﬂect niche shift. Consequently, the dimensional spectrum of the structural attractor invariably constitutes an intersect between the endogenous component of adaptive potential and the biophysical paradigm with respect to the interface between organism and the real dimensions of sub- and hypoparametric niche space.* Accordingly, biophysical paradigm and adaptive potential must be envisaged as each participating in the range 0 씮 1.0 in terms of their respective indigenous degrees of freedom in a composite structural attractor. In the above scenario, the inﬂuence of endogenous adaptive potential on the structural attractor may be high and is frequently narrowly channeled. Freedom in the adaptational paradigm can be high also but is often low (owing to factors discussed in Chapter 7), thus implying a lower likelihood of ‘‘freedom’’ in the niche-driven element. Thus, degrees of freedom in endogenous adaptive potential element alone cannot be implicated as the causal factor in relation to an apparent nonadaptive differential, since there must invariably also be a complementary element residing in degrees of freedom in the exogenous adaptive paradigm. Darwinian and neo-Thompsonian factors are thus exclusively interactive, so that no structuralist hypothesis can be based solely on the input from endogenous constraints to this interaction, other than in terms of permissible range of solutions determined by freedom in the biophysical paradigm in its links with adaptational demands residing in the external environment. Thus the concept of exclusively ‘‘structure-driven’’ transformation factors is an unrealistic evolutionary scenario (although this term may nevertheless sensibly be used to denote the predominant inﬂuence of endogenous adaptive potential in relation to a given diversity pattern). In conclusion then, we must consider the possibility that topology of evolutionary change probably cannot be exclusively structure-driven, since freedom in morphogenetic potential has to interdigitate with freedom in the external adaptation interface. The epithets ‘‘niche-driven’’ and ‘‘structure-driven’’ (or ‘‘Darwinian versus endogenous Thompsonian’’) only identify the relative signiﬁcance of certain factors in determination of degrees of freedom in the structural attractor. Following this view, * The question of pleiophoric states linked to allometric laws has also become an important argument in favor of the perpetuation of maladaptivity in evolution. However, a consideration of the interplay between extrinsic and endogenous factors determining the architecture of the structural attractor raises questions concerning the validity of such claims (see below and Chapters 16 and 17).

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• Endogenous adaptive potential may greatly limit avenues of change, where the biophysical paradigm could actually have allowed many possible solutions. • Similarly, a large repertoire in attainable morphogenetic potential remains utterly dependent on the existence of some complementary propensity for positive advance in relation to the degrees of freedom residing in the adaptive paradigm, before this can be reﬂected in realization of adaptive potential. There therefore appears to be no way in which Darwinian and structuralist factors can operate independently of each other, and this precludes the possibility of ‘‘endogenously driven evolution,’’ as well as of any large nonadaptivity element emerging from this source. However, there still remains the distinct possibility of a Simpsonian nonadaptive differential in diversity patterns (which, however, seems unlikely to constitute a manifestation of any exclusively ‘‘endogenously driven, spontaneous order’’ mechanism leading to true ‘‘nonadaptive evolution’’).

EVIDENCE FOR STRUCTURALISM AND NONADAPTIVITY IN NATURAL ADAPTIVE SYSTEMS Several competing models for evolution of diversity patterns have become evident in the foregoing analysis, ranging from an extreme structure-driven interpretation, on the one hand, to a ‘‘panadaptationist’’ viewpoint, on the other. How can the various structuralist models that have been discussed now be assessed on a biosystematological basis, and what status does nonadaptivity hold in this context? In the ﬁrst place, it must be said that the structuralist paradigm does not in fact constitute an automatic plea for either non- or maladaptivity in evolution, despite a tendency for the neo-Thompsonian element to be slanted in that direction by some workers. However, it is this aspect of structuralism which we must discuss ﬁrst. The next stage must clearly be ﬁrstly to examine certain other models that have been proposed in support of a non- or maladaptive input to diversity patterns. Concurrently, it will also be necessary to delve more deeply into the apparent heterogeny of the Simpsonian ‘‘nonadaptive differential’’ concept already mentioned above.

Autogenesis, Nonadaptive Structuralism, and Stochastic Factors in Evolution In what sense does an endogenous force exist in evolution such as could be involved in the generation of nonadaptivity? This question is obviously especially linked both to autogenesis and also to the inﬂuence of stochastic factors of external origin affecting the generation and perpetuation of nonadaptive traits in the context of models of ‘‘genetic drift.’’ These seemingly diverse hypotheses emerging from separate structuralist and neo-Darwinian schools of thought do in fact appear to share certain common attributes.

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Autogenesis and Endogenous Adaptive Potential Can ‘‘autogenesis’’ at any time be regarded as being a source of truly nonadaptive divergence in the endogenous component of adaptive potential in general? The best evidence for a self-organizational element in determination comes perhaps from the reaction–diffusion mechanism (Chapter 10), which is particularly associated with the generation of periodic patterns. The main difﬁculty with accepting this as evidence of a signiﬁcant autogenetic input to nonadaptive evolution is that, with the exception of trivial variation around preexisting repeated patterns, such systems seem likely to constitute a later superimposition over the actual origination mechanism underlying an incremental pattern of evolutionary change, for example, as the fabricational paradigm of ontogeny comes to embrace phenogenetic modules in the context of ontogeny. As was suggested earlier, the largest inﬂuence of apparently autogenetic factors most probably lies with ontogeny sensu stricto, rather than with the adaptational paradigm of phenogeny: The fact that digit number is so deeply canalized in higher vertebrates may in fact tend to support the above view, as does the initially autonomous nature of the development of cartilage, muscle, and tendons. It could be argued that the physicochemical bases of autogenesis should in fact simply be viewed as forming part of the epigenetic control system of development, in the same way as hormonal and environmental determination factors may come to form part of epistatic systems, rather than as constituting a force which impinges on development independently of any selectional manipulation of genetic control systems. In support of this view is the fact that, as a general rule, nongenetic determination factors of any kind are only allowed penetrance in development as a function of actively evolved and maintained epigenetic labilities (that is to say, they probably do not constitute modes of actual origination). In conclusion, although there is no reason to suppose that reaction– diffusion systems cannot create nonadaptive differentials at the phenotype level in the domain of interspeciﬁc diversity, there is no proof that they actually do so, other than for a limited repertoire of largely trivial traits manifested in near neutral infraspeciﬁc variation. It must also be pointed out that complex anagenetic change is of an entirely different order of complexity than that created by the reaction–diffusion mechanism, especially bearing in mind the likelihood that the principal function of such systems may be to provide positional information, rather than to directly create superstructural phenotype pattern. Returning now to the question of the supposedly limited inﬂuence of natural selection on systems controlled by autogenetic forces, the only component of adaptive potential which might be supposed to have the capacity to manifest nonadaptive differentiation on the basis of autogenesis relates to an element in certain repeated patterns. However, even this view is not borne out by sound evidence that no selectional differential exists between (for example) slightly different color patternings of insect wings or in the distributions of

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setae or trichiae on body surfaces of various animals (on the contrary, the astonishing detail with which model patterns are replicated in mimic species seems to suggest that ﬁne detail in such traits as color pattern is frequently under very strong selectional control): Raff (1996) similarly concludes that experimental evidence lends little or no support for the strong version of structuralism and that the results of developmental genetics show that self-assembly is an incomplete model for development, also pointing out that Kauffman’s (1993) proposal for the origins of cell types as attractors in genetic Boolean networks remains untested. Adaptive potential (not autogenesis) is the true root of any ‘‘endogenous’’ transformation factor, and this concept must be widened to encompass ‘‘selforganizational’’ factors also. If this sometimes includes nonadaptive differentiation, there may be good reason to suppose that this tends usually to be restricted to that situation where a large number of degrees of freedom in the adaptive paradigm permit wider expression within the spectrum of morphogenetic potential than is generally the case with anagenetic paradigms; however, the small amount of good evidence for ‘‘genuine nonadaptive evolution’’ supports only the near neutral intraspeciﬁc model, as typiﬁed, for example, by the observed variation in human ﬁngerprints. Structuralism and the Shifting Balance and Founder Principle Models Given that autogenesis is merely one component of endogenous adaptive potential, in what manner can random factors operating in the gene pool be presumed to promote nonadaptivity or maladaptivity in evolution of the phenotype? Apparent support for an extension of the nonadaptive differential hypothesis into the domain of species differentiation has been claimed with respect to two particular models in the ﬁeld of population genetics. In addition, it might be said that genetic drift actually provides a mechanism whereby ‘‘hard structuralism’’ might actually contribute to species diversity patterns. The Shifting Balance Model It might be proposed that truly non- or even maladaptive changes can be perpetuated through the inﬂuence of stochastic factors, via Wright’s shifting balance model (Chapter 13). Attempts have thus been made to link random processes in the gene pool to non- or maladaptive divergence. However, while Wright’s concept of random processes causal to crossing peak saddles against selection pressure may at times be partially acceptable within the context of the nonselective offset strategy (Chapter 5), the evolutionary effect of this is likely to be minimal, and certainly not ‘‘random evolution’’ linked to speciation. The Wright model really only viewed stochastic effects as assisting selection in promoting homozygosity, with particular respect to alleles manifesting a very low contribution to ﬁtness. The true signiﬁcance of random mortality in the behavior of adaptive systems probably lies with the fecundity offset mechanism, in the context of transient states of change within a larger dynamic structure, and negative or neutral variation that is perpetuated in this way may generally tend also to be largely substructural.

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Wright’s concept of ‘‘movement into valleys of the adaptive landscape’’ via sampling error in small populations constitutes a problem for parameters carrying a larger increment to ﬁtness, in that ‘‘valleys’’ are clearly adaptationally negative areas! The effect of ‘‘passing through valleys’’ will only rarely be to ‘‘discover fresh peaks to climb,’’ and will generally tend merely to lower the rate of change for certain allelic frequencies (or, if we attempt to extend this mechanism to encompass changes of greater contribution to ﬁtness, to endanger extinction! ). In the developmental (as against Mendelian) understanding of genetics, it is also axiomatic that a very large proportion of hypothetical ‘‘valley genotypes’’ are actually impossible in organic terms and cannot therefore be realized through randomizing inﬂuences, other than in the limited context of artiﬁcial selection: Dobzhansky (1970) correctly concluded that ‘‘adaptive valleys’’ constitute ‘‘a metaphor for the multitude of gene combinations that are not formed at all or are eliminated on account of the low ﬁtness of their carriers.’’ Furthermore, where ‘‘valleys’’ represent genotypes of low adaptational value, they can only be perpetuated long enough to take part in evolutionary events if they are supported by logistic adaptation, and the nature of such events will probably be limited to microevolution. It is thus difﬁcult to visualize any signiﬁcant connection between ‘‘genetic drift’’ and the complex epigenetic interactivity observed in a complex epistatic system controlling major morphogenetic parameters, such as would underlie iterative movement in a morphogenetic program, toward a distant and complex paradigm state in the selectional attractor: Maynard Smith (1983) discussed the controversy over ‘‘passage from one adaptive peak to another,’’ in which Fisher and Wright could not agree. His view was that the facts of coadaptation and of hybrid inviability and infertility do not provide evidence that populations have, in the past, crossed ‘‘adaptive valleys’’ (although he also thought that there might be evidence in certain kinds of chromosomal change that this mechanism might sometimes be implicated). Fisher maintained that natural populations are usually too large for random drift to be of any real signiﬁcance in the shifting balance model, and also showed that ‘‘local optima’’ probably do not exist in topographies with a large number of dimensions. Two situations crucial to the shifting balance model lie in particular with difﬁculties linked to negative heterozygosity and ‘‘epistatic ﬁtness interactions’’ between genes. While Wright’s interpretation is perfectly valid for short-term microevolutionary activity, it should be clear enough that, so far as the longer term evolutionary behavior of adaptive systems is concerned, the ﬁrst problem can readily be resolved through evolution of dominance, and the second by adjustment to recombination. The Founder Principle Model The founder principle is essentially a special case scenario linked to Wright’s shifting balance hypothesis as this links in turn to speciation: ‘‘The most favor-

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able situation for a nonadaptive differentiation of species . . . is passage of one of them through a bottleneck of small population size during which one or more nearly neutral genes happens to become ﬁxed.’’ From our previous discussions of the shifting balance hypothesis, it seems unlikely that this mechanism could contribute anything more than trivial ‘‘noise,’’ although some authors have subsequently developed this hypothesis in the context of an alternative mode of speciation to the selectionist model. It must be said at the outset that the fact that species differentials are much more profoundly expressed in sexually reproducing forms than in asexuals (see Maynard Smith, 1983) is enough to dispel any notion of a large input from chance factors. Wright’s own data on selection coefﬁcients and on aspects of recurrent mutation considered relevant to his genetic drift model conﬁrm that the latter is speciﬁcally concerned with minor variation, and his own comments on the inﬂuence of pleiotropic effects seem to dismiss random drift as being of any real signiﬁcance (as indeed argued by Fisher). The founder principle (so far as the input from genetic drift is concerned ) can therefore only relate to substructural alleles of low contribution to ﬁtness, and does not constitute a rationale for the occurrence of large scale random non- or maladaptive inputs to evolution. Any tendency toward perpetuation of negative genes through the effect of small population size would surely be rapidly counteracted once the population had again expanded. The situation where it is claimed that larger scale evolutionary change can proceed in this manner can only apply to transient events in the evolution of adaptive systems, and drift does not appear to be a mechanism with any potential for a general role in the ‘‘spontaneous generation’’ of complex diversity patterns on a non- or maladaptive basis: In one other analysis, Nei (1987) likewise concluded that the supposed genetic drift factor due to sampling error as a result of small population size was an unlikely scenario, noting that this had previously been dismissed by Fisher and Ford. Both the supposed perpetuation of negative or neutral mutations and loss of positive ones through random mechanisms such as the founder effect probably apply in reality to movement below the level even of adaptive equilibrium, rather than to any buildup of random genetic interactivity such as might lead to nonadaptive differentiation of species. Furthermore, capacity for recovery from any such activity is probably built into the genome, there being no doubt that tertiary adaptive equilibrium functions through recurrent mutation, as is clear from observed spontaneous mutation rates: Strickberger (1968) listed the then known spontaneous mutation rates of many different organisms. Dobzhansky (1970), discussing the Strickberger data, observed that genes in the same species may have mutabilities differing by at least two orders of magnitude. Dobzhansky also concluded that random drift and mutation should be seen as opposing forces tending toward loss and replenishment of genetic variability. Garcio-Bellido (1983) examined the founder hypothesis as one possible explanation for certain traits that are distributed among dro-

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sophilids in such a manner that no linear phylogeny can be constructed, yet which do not seem to form part of the usual mutational genetic repertoire of the group. While it was thought at ﬁrst that these traits might possibly be combinatorial novelties arising by chance, founder explanations failed in view of the likely segregation of alleles capable of recovering polymorphism (indeed, some ‘‘good’’ species and even generic traits have actually been found in infraspeciﬁc variation within D. melanogaster alone; see Chapter 21). The founder principle (in its ‘‘nonadaptivity via genetic drift’’ interpretation) is thus clearly negated by the dynamic nature of adaptive capacity, in that any ‘‘missing variation’’ will generally tend to be regained through controlled recurrent mutation. In some instances, the founder principle has been used to explain gene frequencies in situations where selection is clearly not present (for example, the incidence of polydactylous dwarﬁsm in the Lancaster County Amish community; see Strickberger, 1968). Similarly, where good evidence for a founder effect has apparently been recorded, this has generally applied to short-term manifestations of change, and not the longer term perpetuation of neutral or maladaptive structural states in the generation of natural diversity patterns. Likewise, the existence of species diversity in island faunas (such as the Drosophila species in Hawaii) tells us nothing about the way the founder effect has actually affected morphodifferentiation of species. ‘‘Founders’’ (as immigrants) are not necessarily lineage progenitors in the sense of invoking random drift that is instrumental in determining the course of anagenetic events over the longer term of evolutionary change, although a founding population may well inﬂuence certain microevolutionary aspects of species divergence via residual adaptive capacity in the sense of manifesting a ‘‘genetic bottleneck’’: Grant (1998) discussed the ongoing controversy over the occurrence of speciation in island faunas, in view of a supposed founder effect based on reorganization of sets of interacting genes accounting for genetic changes that would occur ‘‘irrespective of ecological or behavioural factors.’’ As stated by Barton (1998) the likely effect of a genetic bottleneck depends on the fraction of heterozygosity that is lost; however, the existence of ancient polymorphisms (as with Cepaea species) tends, in any case, to rule out severe bottleneck problems (Klein et al., 1993). The strongest negative evidence concerning the validity of the founder principle lies in the fact that bottlenecks actually induce little reproductive isolation in artiﬁcial populations of Drosophila (Rice and Hostert, 1993). Carson (1968, 1970) has also reinterpreted the founder principle in an entirely different light (see Chapter 13). A more realistic assessment would be that the founder effect is predominantly one of forcing a gene pool out of its ambient state of adaptive equilibrium and into one in which a new substrate for evolutionary change emerges (Chapter 14).

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No good evidence has therefore been found to support any one population genetics model of ‘‘non- or maladaptive divergence,’’ so far as either genetic drift or the founder principle is concerned. With realization of adaptive potential, we should not in any case be searching for the phenotypic outcome of randomization factors, since it must be supposed that all neomorphic mutation (even in the domain of deﬁnitively Darwinian traits) must in some way be ultimately linked to stochastic activity (and thus, in a highly restricted sense, ‘‘spontaneous order’’) in the genetic system. Systems occurring by ‘‘self-organization’’ form part of a much larger morphogenetic landscape that is contained in adaptive potential, only a small proportion of which has a probability of being adaptationally positive by virtue of geometric coordinates matching those of the adaptational biophysical paradigm. The data of Raup (Chapter 7) conﬁrm that it is indeed the adaptationally positive component of morphogenetic potential that is actually perpetuated in evolution, and while we may chose to examine the genetic system behind morphogenetic potential in terms of inﬂuence from stochastic factors, this does not constitute ‘‘self-organization’’ in the strict sense of a generally nonadaptive or maladaptive differentiation of form. Most signiﬁcantly of all, both the shifting balance and founder models must be seen within the context of adaptive capacity, and maladaptive traits cannot be ‘‘ﬁxed by chance’’ in this scenario, since in the context of neomorphism in realization of adaptive potential, the origination of novel pleiotropic effects is also demanded. Genetic Chaos and Nonadaptivity Only the overwhelming inﬂuence of random mechanisms can be proposed to support a strict view of ‘‘nonadaptive autogenesis’’ in the role of ‘‘spontaneous order from chaos’’ in the endogenous domain. Is this really a viable hypothesis? King and Jukes (1969) take the extreme view that ‘‘evolutionary change is not imposed upon DNA from without, but that it arises from within.’’ A more fundamental role for self-organization has also been proposed by Kauffman (1993), who states, ‘‘In sufﬁciently complex systems, selection cannot avoid the order exhibited by most members of the ensemble. Therefore such order is present, not because of selection but despite it.’’ In fact, it has become clear that selection is capable of changing the endogenous inputs to adaptive potential in such a way as to circumvent any such constraints, certainly in the longer run of anagenetic evolution. In other words, the ‘‘order’’ alluded to is one stage in an iterative dialogue between structure and selection, and ‘‘endogenously controlled order’’ itself thus becomes a function of iterated selectional activity. The endogenous element in adaptive potential is therefore not due to a universal random interactivity of genes, nor does it in any way constitute a predominantly nonselectionist input to evolution via self-organization. Epigenetic determination systems are clearly deterministic structures, and any argument based on an ‘‘all-genes interaction’’ seems to attempt to force natural adaptive systems into a random or chaotic scenario. Large scale multiple pleiotropisms in the majority of major mutations also

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show that ‘‘spontaneous order from chaos’’ is an unlikely interpretation for the origin of diversity in morphogenetic systems, in that a fundamental dichotomy exists between ‘‘adjacent–adaptive’’ and ‘‘remote–deleterious’’ changes to morphogenetic coordinates. The stochastic element in evolution lies exclusively with decanalization of highly speciﬁc, closely localized coordinates, supported by a much larger deterministic epigenetic environment, and only in this greatly restricted sense can organic systems perhaps be said to be ‘‘poised between order and chaos.’’ Similarly, the ultimate order retrieved from expansion of pleiotropism is channeled in an iterative manner, on strict homeostatic principles, and therefore cannot be construed as being in any way an expression of spontaneous order. We must now ask to what extent is the decanalization transition just alluded to actually equivalent to ‘‘all-genes interactivity’’? The structure of a generalized panstatic system (Chapter 10) suggests that this domain is actually strictly limited. The probability of interaction between ‘‘remote’’ genes will be a function of their preexisting homeostatic state: greatest for redundant structure units, and least for members of an active, complex epistatic system. Labile genes may arise (as with gene duplication) in ‘‘ﬂat’’ systems linked to redundant or vacant morphospace, but even this cannot be construed as being a truly stochastic mechanism: Wolpert (1990a) discussed Kauffman’s view (1987) of the possibly self-organizational origin of cell types, similarly concluding that it is unlikely that the state cycles of Kauffman are at all analogous to cell differentiation, and that there exists no reason to believe that evolution has acted on randomly constructed nets. Genetic chaos thus seems an unlikely candidate for the origins of spontaneous order in evolution. Furthermore, the supposedly non- or maladaptive element that is reputedly linked to this in the context of actual input to diversity patterns can, as we have already argued earlier, realistically be seen from three angles only: 1. The pleiotropic balance model shows that negative material may be ‘‘carried’’ by a net positive structural change. A given morphogenetic mutation could thus be taken as having leading adaptive coupled with pleiophoric–maladaptive parameters. However, this postulate must carry with it the maxim that pleiotropic imbalance is likely to constitute a purely transient phenomenon, rather than being a major input to longer term evolutionary patterns (see also Chapter 17). 2. Suboptimality may be a corollary of multiple functionality (see Chapters 7 and 17). This can hardly be regarded as being a structuralist interpretation, however. 3. Alternatively, all morphogenetic changes may be truly adaptive, but certain coordinates with high degrees of freedom may perhaps express adaptationally equivalent states (namely, following the Simpsonian nonadaptive differential concept). All of the above mechanisms may be presumed to lie behind the apparent nonadaptive differentiation of species and higher groups, although the last mentioned scenario clearly remains speculative and hypothetical.

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Evidence for Soft Structuralism in the Simpsonian Nonadaptive Differential The hard structuralist model of endogenously generated patterns arising independently of leading effect selectional or adaptational factors is clearly untenable. In particular, true maladaptivity can only be envisaged in terms of a more or less transient corollary of adaptational change. A closer analysis of ‘‘soft structuralism’’ must clearly assess the validity of the less extreme view of Simpson, namely, that nonadaptive differentials (rather than truly nonadaptive states) may exist and be perpetuated in natural diversity patterns. Does the adaptationally equivalent states concept genuinely allow soft structuralism on predominance of degrees of freedom in the structural attractor? The adaptive cascade (see p. 326) clearly indicates that biophysical paradigm and adaptive potential operate interactively, but this clearly does not exclude the possibility of a nonadaptive differential being invoked. As we have seen, a true nonadaptive differential could be expressed in terms of speciﬁc coordinates of the interface between structure and niche, in that there may be n solutions to a functional problem in realization of adaptive potential, all of which nevertheless represent an increase in the adaptive state relative to the parent form, but not with respect to each other. The correct interpretation of ‘‘Simpsonian structuralism’’ could hypothetically lie with the maxim that ‘‘freedom in adaptive potential’’ really means ‘‘how many attainable adjacent morphosystems can be realized, which constitute an equivalent step toward the adaptational paradigm?’’ However, we must now consider the additional complication that although ‘‘freedom in the biophysical paradigm’’ relates to the probability that more than a single suboptimal state may fulﬁll a given function, there is no proviso that all solutions will necessarily carry an exactly equal increment to the adaptive state. In attempting to analyze the nonadaptive differential concept more deeply, it will be useful to begin by investigating Simpson’s original examples more closely. Some structural differentials between bat and bird wings may indeed fulﬁll exactly the same function, thus constituting partial adaptationally equivalent states, and so reﬂecting an apparently authentic nonadaptive differential between bird and bat wings that is due to dichotomies originating in endogenous adaptive potential alone. This naive interpretation is, however, open to the criticism that the reason apparent adaptationally equivalent states exist is not that ‘‘adaptational paradigms are the same and only fabrication differs’’ but that the organisms expressing such differentials do not in fact share a common selection interface, namely, in that the latter is described only through the medium of a partial niche intersect. Two structural states belonging to discrete species may thus perform the same fundamental function, yet will most probably also contain some sequestered selectional differential that is not actually manifested through direct competition, owing to the existence of a large component of unshared niche space. The fabricational differentials of ‘‘minor’’ structural coordinates are thus not necessarily ‘‘adaptationally equivalent states’’: If, for example, cephalopod and vertebrate eyes were to exist in species manifesting a completely coincident selection interface, one would certainly outcompete the other. The reason this does not happen in

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Nature is simply that much of the adaptation interface of vertebrate and cephalopod species amounts to ‘‘unshared niche space.’’ The adaptive topography for mollusc shell shape investigated by Raup and others (see Chapter 7) lends no support to any nonadaptive differential interpretation, given clear evidence for maxima and minima centered around particular expressions of shell structure. Raup’s morphogenetic landscape for shell structure in cephalopods (see also Raup and Stanley, 1971, 1978) could perhaps be interpreted as a set of adaptationally equivalent states representing various permutations of an underlying developmental theme. However, steep gradients expressed in the frequency distribution for real organisms indicate that this is probably not the case, since some forms are clearly of higher frequency, expressing adaptational superiority to others. This is of special interest in the context of structuralism, since surely in nonliving parts, we might expect the highest probability for manifestation of any supposed endogenously generated nonadaptive differential. The same author’s work on several other groups of organisms on the basis of conﬁgurations of four parameters of shell morphology (crosssectional shape of cone, rate of whorl expansion, position and orientation of generating curve, and whorl translation) also uncovers a decisively adaptational differential in operation in the graph of ‘‘possible as against actual morphospace,’’ which identiﬁes a very large ‘‘possible’’ zone that is in fact completely unoccupied by real forms, living or otherwise. Furthermore, the four lineages studied occupy virtually nonoverlapping regions of geometric space, a fact which Raup attributes to the quite different lifestyles of the brachiopods, bivalves, gastropods, and coiled cephalopods. Diversity in shell form is thus not merely a reﬂection of the range of possible shapes that can be generated by the developmental system, but a special subset of this array that is sculptured by the demands of selection in relation to the degrees of freedom residing in adaptive potential. It can thus be seen that the supposed ‘‘nonadaptive differential’’ between remotely related lineages can more realistically be interpreted in terms of a nonselective differential. Consequently, Simpson’s higher group exemplars must be rejected. It must also be said that, if the existence of adaptationally equivalent states is a force causal to perpetuation of differentials in signiﬁcant morphogenetic coordinates, then it is surprising that so many complex structure paradigms manifest a strong tendency toward evolutionary convergence between even remotely related higher group lineages. If such states constituted purely endogenously generated differentials of no consequence to ﬁtness, then there would be no reason whatsoever for them to converge from origins that are often dramatically dissimilar, as they certainly do in very many lineages. A logical conclusion here would be that these states must have been suboptima in the ﬁrst place, thus manifesting an active selection interface; however, the term ‘‘suboptima’’ must not be taken as an automatic reﬂection of non- or maladaptivity in the sense of negative pleiotropy (see Chapter 17).

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To what extent can Simpson’s model now be supposed to explain differences between closely related species? Quite apart from the obvious observation that the Raup data cited above have repercussions at lower levels in the taxonomic hierarchy, there are other objections to the concept of the nonadaptive differential. The supposed extrinsic model for ‘‘Simpsonian structuralism’’ (based on true adaptationally equivalent states arising through the existence of degrees of freedom in the adaptational paradigm) can be more critically examined through the architecture of a hypothetical cladogenetic selection interface linked to infraspeciﬁc variation. Nonadaptive differentials emerging from cladogenetic activity should be demonstrable between species. In reality, it is not difﬁcult to ﬁnd possible examples of this (for example, in taxonomically species-rich groups manifesting apparently ‘‘trivial’’ interspeciﬁc differentials). However, the fact that the differentials in question are not frequently found as characteristics of infraspeciﬁc variation also, leads one to suppose that undetected adaptational differentials may in fact exist, and indeed may even have been linked to generation of cladogenetic events in the ﬁrst place. Nevertheless, an alternative structuralist hypothesis could be that nonadaptive pleiotropic differentials may sometimes arise in allopatric populations, then be perpetuated in speciation, on the basis of selection acting on quite different leading effects which do hold a true adaptive differential (the traits in question perhaps contributing nothing more than a trivial input to hybrid depression in the cladogenetic selection interface). Second, it could be argued that the founder principle (pp. 338–341) might in fact sometimes permit the ﬁxation of a few near neutral traits within species limits. This explanation could perhaps explain the quasi-random distribution of character states sometimes reported in highly speciose lineages. The lack of major nonadaptive differentials expressed in infraspeciﬁc variation does not then entirely disprove the existence of adaptationally equivalent states, since it could be argued that this can occur because of ‘‘invoked speciation’’ or quite trivial ‘‘carried’’ factors, as discussed above. However, these possibilities constitute nothing more than minor ‘‘noise’’ in the species diversiﬁcation mechanism, and they can form no part of any structuralist rationale for a major input to the evolution of diversity patterns in general. The best apparently prima facie evidence for adaptationally equivalent states in Nature perhaps lies with structure systems that are inherently quasirandom and which relate particularly to unusually high degrees of freedom in the biophysical paradigm itself, as with the multiple vegetative parts of plants and many segmented appendages of arthropods. Known examples include the conﬁguration in spiral scales in repetitive plant structures such as those studied in sunﬂowers and pine cones following the Fibonacci series: Thompson (1917) showed that the Fibonacci series expressed in plant phyllotaxis is merely the next order in simplicity to an ‘‘opposite’’ arrangement, and this could well constitute a nonadaptive differential arising entirely from slightly different developmental potentials. Here it might indeed be supposed that ‘‘true neighbouring morphologies in evolution reﬂect transformations to neighbouring forms in the family of forms generated by the underlying developmental mechanisms,’’ as in the fundamental

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structuralist view (Kauffman, 1993). Stated this way, however, there is nothing necessarily self-organizational here (in the sense of nonselectional evolution) giving rise to interspeciﬁc differentials, never mind differences between higher group taxa. The nonadaptive differential concept is thus only valid within very strict limits, in terms of certain labile coordinates of the adaptational paradigm that will be the same in different lineages (for example, certain fabricational attributes of a specialized structure), and it probably only exceptionally steps beyond that limitation other than in the context of inherent lability in the adaptive paradigm itself. Conclusive proof of a true nonadaptive differential may ultimately lie with advances made in the area of teleonomy (see below), and will only come from a deeper understanding of the developmental genetics of the traits in question. For now, the case seems evidently ‘‘not proven’’: Williams (1966) discusses the work of Pittendrigh (1958), who proposed the term teleonomy for explicit recognition of functional organization in organic systems (an approach that has some points in common with the Rudwick paradigm). Williams also proposes that teleonomy should seek to link proximate function with the evolutionary perspective. From the present standpoint, the greatest problem facing such an endeavor would no doubt be that concerning the supposed nonadaptive differential indigenous to the structuralist hypothesis!

PANADAPTATIONISM AND A REFORMED STRUCTURALIST MODEL Given that both hard and soft structuralist models clearly fail as general explanations of the evolutionary process, in what sense can adaptationism be claimed to completely encapsulate the problems encountered in the preceding analysis of the ‘‘structure-driven’’ factor in evolution?

The Panadaptationist Model So far, we have neglected to discuss the panadaptationist view that all changes in the phenotype conform to direct requirements of the adaptive paradigm, with no input whatsoever from the limits of endogenous adaptive potential—thus excluding any element of constrainment and any possible input from either maladaptivity or nonadaptive differentiation. This particular model may, however, constitute nothing more than a ‘‘straw man hypothesis’’ that is but loosely linked to a real dichotomy between contemporary and earlier supposedly neoDarwinian viewpoints on the generation of organic diversity patterns. The panadaptationist interpretation seems at once intrinsically less probable than some structuralist models, and it is unlikely that it is given serious consideration by a majority of evolutionary biologists at the present time. Such a hypothesis would clearly be negated at the outset from the standpoint that the structural attractor is deﬁned by interaction between both extrinsic and endogenous inputs, so that endogenous adaptive potential must always input

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some element of constraintment. In a fourth hypothesis below, we shall observe that the panadaptationist model is in fact a much less likely contender than a reformed structuralist model in which the adaptive differential exists, but is actually facultative to some form of adaptive shift.

The Facultative Adaptive Differential The nonadaptive differential model is closely related to another, more probable hypothesis which can be proposed as constituting a more viable endogenous input to structural diversiﬁcation. This is based on the concept of a facultative adaptational differential. In this model, that complement of degrees of freedom residing in the endogenous component of adaptive potential is actually ‘‘facultative’’ to changes in the niche, so that the latter is then in turn facultative to reciprocal change in the adaptive paradigm. Degrees of freedom in adaptive potential lying outside the domain of the existing adaptive niche thus constitute the parameters of the facultative adaptive differential, and the real structural attractor is thus greater than the intersect of adaptive potential and biophysical paradigm (inasmuch as the latter was determined by the original niche interface). Adaptive potential is thus deﬁned according to an existing and ‘‘prospective’’ niche interface (that is to say, it is partly linked to free, adjacent niche space in the exogenous domain), and the adaptive paradigm is thus in turn directed toward the same wider zone. Here, we can see that the facultative adaptive differential evolves as an adaptive shift, equivalent to qualitative change in the niche (this concept will be explored further in Chapter 17). It is necessary, at this juncture, to point out that the term ‘‘niche-driven’’ must not be taken to imply demand for a single adaptive response. A ‘‘nichedriven’’ (or ‘‘Darwinian’’) response simply means any adaptive response that is conducive to an advance in ﬁtness in terms of some component residing in the niche interface, and this can include a latent propensity to invoke an adaptive shift. It is now evident that some proportion of the totality of selectionally positive morphosystems in morphogenetic potential may contain endogenous adaptive potential that is not wholly expressed by the existing adaptational paradigm relative to the extant niche, realization of which holds a modulating function acting on the adaptational paradigm itself, thus invoking niche shift. It is therefore a fundamental axiom that degrees of freedom in adaptive potential and adaptational paradigm can (in this sense) be partially mutually additive: There could, for example, be an adaptive differential between one and two horn states in the rhino example, that was primarily structuredriven, then secondarily niche-driven, rather than having occurred through any requirement in the original niche interface that speciﬁcally demanded adaptational differentiation on the basis of horn number (thus also with no need for an exact nonadaptive differential between one and two horned states). In the above scenario, we are simply saying that the inﬂuence of morphogenetic potential need not lead either to maladaptive change or to the nonadaptive differential scenario, but that the architecture of the adaptive niche may

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often be actually altered through realization of endogenous adaptive potential. The facultative adaptive differential concept thus constitutes a reformed view of the structuralist hypothesis in which true adaptational differentials arise through structure-driven (Thompsonian) transformation factors. However, this reinterpretation of a structuralist input to the diversiﬁcation mechanism is, to some extent, simply a ‘‘cart-before-horse’’ manifestation of Darwinian evolution, and not a plea for a nonadaptationist or self-organizational element, to any greater extent than that encountered with evolutionary change linked to preexisting extrinsic adaptive potential (in the usual sense in which ‘‘Darwinian evolution’’ has been construed). The ‘‘facultative structuralist’’ model really only reﬂects the fact that most morphogenetic changes tend to constitute relatively simple afﬁne morphogenetic transformations of the parent system, and that positive elements in this may play some interactive role in determining the exact parameters of niche through the mechanism of an endogenously invoked adaptive shift. In reality, great difﬁculty may of course be experienced in assigning a given adaptive shift to its correct category within the heterogeny of structuralist hypotheses: The external cheek pouches of pocket gophers (Chapter 12) could perhaps constitute a Simpsonian nonadaptive differential with respect to the internal condition, but changes of this kind might perhaps best be construed as being a facultative adaptive differential invoking some change in the adaptive niche.

Reformed Structuralism and the Directionalization Function in Anagenetic Evolution Nei (1987) discussed the view that chance is a key element in Darwinism. Similarly, it has been held that mutation is random with respect to gene function (see King, 1972, summarizing the ‘‘neo-Darwinian’’ viewpoint of earlier authors). From this standpoint comes also the edict held by earlier population geneticists that there is enough variation in existing genotypes such that new mutations are of no special signiﬁcance for populations to respond to environmental change—in which scenario, macroevolution can be construed as being nothing but ‘‘accumulative microevolution.’’ These views are, of course, entirely negated by any analysis of endogenous adaptive potential, even in the severely restricted form of the facultative adaptive differential hypothesis, as well as by the concepts of the biophysical paradigm and adaptive potential (as of course also by the developmental as against Mendelian view of genetic interactivity). The structural attractor is clearly directionalized because of a complex of constraining factors, and ‘‘true structuralism’’ is therefore, a subset of the directionalization function (Chapter 7) in that it does not in fact ‘‘constrain’’ evolution (in the sense of preventing speciation, for example), but serves to determine directionality in the anagenetic sequence. The facultative structuralist model should thus be viewed as one of several signiﬁcant directionalization functions operating in anagenetic evolution, and this must not be equated with ‘‘spontaneous order.’’ Morphosystems tend toward the biophysical paradigm state, owing to intrinsic directionalizing mechanisms tending to shift morphogenetic systems toward the structural attractor,

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despite the fact that this medium is clearly ultimately linked to stochastic events (as shown by the comparative rarity of positive neomorph mutations). Directionalization and the Role of Nonadaptive and Maladaptive Traits In what sense can nonadaptivity and maladaptivity now be said to form a component of structural diversiﬁcation in an evolutionary lineage? It is clearly necessary to consider the leading effect in the selection interface, in order to say whether a given morphogenetic transformation is truly adaptive, nonadaptive, or maladaptive. On this basis, all nonadaptive traits must constitute a nonadaptive differential, and all maladaptive ones must be either pleiophoric states or else functionally redundant, vestigiating structures. Certain classes of morphogenetic transformations seem perhaps inherently likely to carry a corollary of pleiophoric mal- or nonadaptivity. Possible substrates for a quasistructuralist interpretation of evolution will be considered in greater detail in the next chapter. The largest component of apparently genuine nonadaptive differentiation may lie with certain domains within the ontogenetic rather than adaptational paradigm. Here again, however, we must consider that an endogenously disseminated selection interface lies behind changes in this domain, through the medium of fabricational parsimony (Chapter 9). The status of several of the above phenomena must also be transient, at least in the longer term (see Chapters 16 and 17 for an extended discussion of these questions).

MAIN POINTS FROM CHAPTER 15 1. The dichotomy between Mendelian and developmental genetics approaches is focused in the apparent conﬂict between ‘‘Darwinian’’ (nichedriven) and ‘‘neo-Thompsonian’’ (structure-driven) inputs to evolution. 2. Darwinian factors lie in the extrinsic adaptive paradigm, while endogenous Thompsonian factors link to degrees of freedom in the developmental program itself. Darwinian factors thus seem intrinsically more likely to predominate in phenogeny, and Thompsonian ones in ontogeny (sensu stricto). 3. The structuralist model seeks to emphasize the endogenous Thompsonian element in evolution of the phenotype, in terms of a ‘‘special’’ theory which stresses the importance of self-organization and spontaneous order. 4. The ‘‘hard’’ version of structuralism receives but little support from the observations of developmental genetics, although it could perhaps be of greater signiﬁcance for certain parameters of early ontogeny (and for phenogeny itself in simple unicellular organisms). 5. A reformed view of ‘‘soft’’ structuralism does not seek to dismiss the importance of the Darwinian adaptive paradigm; in particular, a nonadaptive differential could in theory evolve via interaction between structure- and nichedriven factors. In general, however, Darwinian and Thompsonian factors should be seen as being exclusively interactive in the context of the structural selectional attractor. Endogenous Thompsonian factors cannot therefore operate in the absence of the Darwinian element, nor vice versa.

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6. Stochastic and ‘‘emergent’’ factors arising from genetic mechanisms cannot be used to support any hard view of structuralism, as an alternative to the inﬂuence of natural selection. Even the apparent adaptive equivalent states scenario postulated by Simpson can generally be better explained following a fundamentally Darwinian paradigm. However, a purely ‘‘panadaptationist’’ interpretation of evolutionary topology is equally unacceptable. 7. A facultative adaptive differential constitutes the most probable level of inﬂuence for a leading endogenous Thompsonian paradigm in evolution. However, this circumstance is, in a sense, a ‘‘cart-before-horse’’ manifestation of the Darwinian model. 8. The supposed inﬂuence of non- or maladaptivity in evolution can be examined in the context of two principal factors. The ﬁrst lies with a ‘‘transient– pleiophoric’’ element, but the majority is linked to ‘‘suboptimal–adaptive’’ traits arising from the widespread incidence of multiple functionality. In a reformed view of structuralism, any expression of mal- or nonadaptivity must therefore be considered to be a transient phenomenon, rather than a leading factor (unless this is linked to a complex isotropic selection vector which demands sacriﬁce of optimal design in favor of multiple functionality). 9. A reformed interpretation of the Thompsonian input further emphasizes the likelihood of a directionalization function operating in evolution, as well as predicting the observed predominance of parallelism and convergence.

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From the last chapter, we arrived at some theoretical understanding of those developmental factors affecting directionalization in realization of adaptive potential in the context of the structural attractor. The question of what kind of morphogenetic transformations actually do occur in evolution (and in particular, which occur most often) must now be investigated in much greater depths. In the present chapter, we should also seek to resolve certain ongoing problems concerning the nature of suboptimal adaptive states in anagenesis, in consideration of those options that are theoretically feasible in relation to the actual modes of morphogenetic transformation operating in natural adaptive systems. Answers to these questions are clearly crucial to an understanding of the relative roles of several special theories of evolution that have been put forward in the past, including in particular, the various adaptationist versus structuralist hypotheses examined in the last chapter.

THE DEVELOPMENTAL TOPOLOGY OF MORPHOGENETIC TRANSFORMATION The ﬁrst question we have to ask is clearly, what range of possible morphogenetic transformations can be postulated to occur, given our knowledge of the mechanisms of development in relation to known strategies of mutational change to genetic systems? It is only with the answer to this question that we can attempt to link the behavior of gene-developmental systems with major manifestations of the evolutionary process or to understand the problem of perpetuated suboptimal states.

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The Developmental Roots of Morphogenetic Transformation While it has been convenient up until now to discuss pathways of morphogenetic change in terms of ‘‘afﬁne morphotransformations,’’ the nature of the developmental process is clearly such that ‘‘afﬁne’’ does not necessarily mean ‘‘genetically adjacent.’’ Similarly, many adjacent morphosystems are not actually afﬁne transformations in the usual geometric sense. The question as to what actually constitutes an afﬁne morphotransformation in evolution is thus evidently not the same as in a simple geometric example, in that we really need to know what kind of morphogenetic transformations actually lie within the bounds of probability for developmental systems. The Concept of Poised Morphosystems It would seem reasonable to assume at the outset that some morphogenetic transformations are intrinsically more likely to happen than others. Numerous alternative morphosystems may lie latent within morphogenetic potential, capable of being dislodged from the ambient state by mutational activity, linked to change to the regime of canalization. In this context, certain alternative morphogenetic states can be considered to be ‘‘poised’’ (Kauffman, 1993) in the sense of being particularly liable to realization through mutational activity—support for this view perhaps coming from the binary choice strategy observed in development (‘‘the binary epigenetic code’’) and the known behavior of factors linked to decanalization. In addition, poised morphosystems must also lie close to that range of adjacent states actually comprising a component of the existing repertoire of phenoplasticity. Poised morphosystems can be construed as constituting that set of states within total morphogenetic potential (see Chapter 7) which can be most readily realized on the basis of adjustment to a given epistatic system by virtue of the most probable conﬁgurations of its mutable member genes. In more general terms, poised morphosystems are ‘‘that component of morphogenetic potential with the greatest likelihood of realization.’’ The existence of poised morphosystems is perhaps most clearly demonstrated by the phenocopy mechanism (see Chapter 11), where a similar phenotype outcome is reached through a range of different determination factors of genetic or nongenetic, endo- or exogenous origin. Kauffman (1993) also points out that transformations affected by the phenocopy mechanism are readily subject to genetic assimilation, deducing thus that many morphosystems do indeed tend to be poised between few alternatives, and that variations at many different points in the system can therefore lead to the same transformation. Genetic assimilation can occur when the characteristics of an environmentally determined trait are created in the absence of the causal agent, after prolonged experience of the latter by a laboratory population (see Chapter 12): The bithorax mutant phenocopy of Drosophila is known to arise from a variety of inducers, and it can also be ‘‘assimilated’’ (Waddington, 1957; etc.). Genetic analysis has shown that the genes concerned did not belong to the known BX-C complex (see Kauffman, 1993), which agrees with Kauffman’s concept that certain elements within the morphogenetic landscape are poised on the edge of expression.

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Clearly, the concept of poised morphosystems is additionally supported by the manner in which polygenes and nongenetic determination factors are known to interact in determination of the phenotype state. Furthermore, it is also evident that the poised morphosystems concept is predicted by the Boolean network structure of epistatic systems, and proposed mechanisms for realization of adjacent morphosystems are again implicit in the canalization–decanalization scenario (see Chapter 12). Likewise, the morphogenetic receptivity hypothesis (Chapter 14) clearly links to the pivots about which morphosystems are ‘‘poised.’’ Poised morphosystems may also correspond to adjacent adaptational paradigms (as, for example, with many environmentally determined parameters, where canalization is clearly structured around primary adaptive equilibrium). Adjacent versus Alternative Morphosystems The concept of poised morphosystems is clearly only of signiﬁcance when linked to adaptive potential, as against negative mutational change. Given that realization of adaptive potential driven factors is identiﬁed as holding the key to major evolutionary change, how can this concept be linked in turn to the structure of developmental systems? In examining this question, we shall consider the probable role of adjacent morphosystems as being equivalent morphogenetic states that are both topologically and genetically related to the parent developmental system. Clearly, only a small fraction of morphogenetic states derivable from a poised system has the capacity to be adaptationally positive, and it seems most probable that these will usually tend to lie in the adjacent category. The concept of poised morphosystems thus leads naturally to the notion of adjacent morphosystems as an expression of the relationship existing between the morphogenetic landscape and adaptive potential. The effect of loosening epigenetic homeostatic mechanisms may then be to release adjacent morphosystems from sequestration, via the mechanism of decanalization. More distant (and adaptationally positive) morphosystems are thus probably usually reachable only by passing through n adjacent systems (rather than via saltatory changes), in that ‘‘one step’’ alternative states are deemed much less likely to encounter a positive selection interface. An alternative morphosystem differs from an adjacent one in being topologically distant from the fundamental system, thus probably also expressing a differential in complex alloparametric (rather than simple synparametric) determination (see Chapter 12), unless (rarely) arising through a single ‘‘macromutation.’’ For the above reasons, simple transformations of form might be expected to be among those adjacent morphosystems most commonly realized, and alternative morphosystems involving more complex modes of morphogenetic transformation seem more likely to occur as an emergent feature arising from iterative change via adjacent morphosystems, rather than forming single macroevolutionary steps of anagenetic change. The concept of poised morphosystems can now be more explicitly deﬁned as relating to adjacent plus that category of alternative systems lying topologically and/or genetically close to the parent epistatic system, thus having a high probability of realization in the context of decanalization:

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Vermeij (1974) considered one aspect of morphogenetic potential in terms of ‘‘versatility,’’ using the family of sinusoidal spirals given in polar coordinates in the equation rn ⫽ an cos n␪ as an exemplar (pointing out also that this equation describes such apparently dissimilar curves as the straight line, parabola, rectangular hyperbola, lemniscate, cardioid, and Caley’s sextic). Vermeij argued that provided the above parameters can vary independently, considerable versatility can be contained in such an equation. Given some degree of differential developmental lability with respect to the latter factors, the sinusoidal spiral equation thus relates to a family of adjacent plus alternative morphosystems. The connection between versatility and the poised morphosystem concept clearly lies in the degree to which independence of parameters lying in hypothetical morphogenetic curves actually does exist in reality, in relation to extant and ‘‘probable’’ genetic systems. The adaptive potential element in this clearly concerns the extent to which some subset of the possible range of form contained in a given equation actually provides equivalent or improved adaptive function. ‘‘Versatility’’ is therefore essentially equivalent to degrees of freedom in morphogenetic potential as a function of ‘‘poisedness.’’ Iterative Incremental Change and Alternative Morphosystems Many morphogenetic transformations must lie in small adjustments to epistatic systems of the kind observed in multifactorial determination, rather than in disjunct shifts toward gross alternative morphosystems of the kind occurring (for example) in the BX-C genetic assimilation example (the latter category of macromutations being generally of highly negative selectional status). The essential selectional drive for larger scale transformations clearly links to the relative simplicity of passage to adjacent morphosystems, in that incremental change may lead to more complex transformations via a temporal sequence of related forms. It may then be that neomorphic change most usually constitutes iterative paramorphic transformation (see p. 365), rather than evolutionary saltation.

Models for the Analysis of Morphogenetic Transformation What directional parameters are likely to be encountered in the realization of poised morphosystems in the context of evolutionary change? Various models have been proposed in the past to explain morphogenetic transformations in evolution; however, it is evident that many early workers had formulated hypotheses that are now seen to be far removed from any realistic assessment of developmental potential. Early Models of Morphogenetic Transformation The nineteenth century transcendentalist embryologists attempted to understand the role of development in evolution through ‘‘recapitulation,’’ which was, to some extent, a hard structuralist interpretation. According to Haeckel and other nineteenth century recapitulationists, adult traits were believed to

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pass to the embryo stage in the event of evolutionary change occurring, thereby ‘‘recapitulating phylogeny.’’ In contrast, von Baer held that the embryo simply resembles the ancestral embryo, with no recapitulation. The recapitulationists furthermore proposed a mechanism comprising ‘‘terminal addition with condensation’’ in which development is supposedly accelerated as ancestral features are ‘‘pushed back’’ into the embryo. The paleontologist Agassiz brought phylogeny into the study of recapitulation through his investigations with fossil lineages. The notion of paedomorphosis was later introduced by Garstang (1928) as contradicting the recapitulationists’ claims, so that retardation then became of equal importance to acceleration, the original Haeckelian view of heterochrony thus constituting a reference to ‘‘contradiction of the biogenetic law.’’ At a later stage, de Beer (1958) deﬁned eight morphogenetic modes of evolutionary change, which enlarged the concept of heterochrony to encompass various forms of apparent temporal displacement. He proposed three principles: (1) qualitative novelties can appear at all stages; (2) characters can and do change in time or order of appearance; (3) heterochrony plays a part in phylogeny. Gould (1990) dismissed most of de Beer’s eight modes of heterochrony, also adopting Giard’s progenesis in place of de Beer’s paedogenesis. For de Beer’s other paedomorphic process involving retardation, Gould adopted Kollmann’s term neoteny, progenesis plus neoteny thus constituting paedomorphosis sensu Garstang. Gould also introduced a clock model in a revised concept of heterochrony, which clariﬁed and extended the meaning of much of the earlier terminology, and he also made valuable contributions to an understanding of the causality of heterochrony through contemporary ecological principles. The history of the study of morphogenetic transformation can therefore be seen to have been peppered with transcendentalism, anomaly, contradiction, and confusion, until the work of Gould. Many problems still loom, however, over the reinterpretation of nineteenth century recapitulation and certain other applications of terminology. The de Beer view of heterochrony did not in fact cover all means of morphogenetic transformation, and many problems still remain with understanding how developmental mutation links to other more frequently encountered modes of change, in particular those of the allometric kind, as studied by Thompson (1917) and Huxley (1932). Perhaps the greatest problem in the confusion surrounding the link between development and evolution lies with the inadequacy of former concepts of structural paradigms of development, since Haeckel, von Baer, de Beer, and Gould did not recognize the fundamental dichotomy existing between ontogeny sensu stricto, embryogeny, and phenogeny. Much of the controversy over the reality of recapitulation, for example, probably lies partly with the fact that some authorities laid special stress on embryonic states, while others were preoccupied with the free-living juvenile. How, then, can de Beer’s view of heterochrony and other models that have been proposed in the past now be incorporated into a broader system embracing all potential morphogenetic transformations of developmental systems? To answer this question, it is ﬁrst of all necessary to identify how the coordinates

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of development partake in ‘‘heterochronous’’ and other transformations of form. Only then can the related question of developmental topology be approached more realistically. Root Coordinates of Morphogenetic Transformation in Development The ﬁrst stage in the reanalysis of morphogenetic transformation must be to ascertain what actually constitutes a change in a developmental program. We can begin from the maxim that the position of any point in development can be designated by four coordinates, one temporal plus three spatial, where t ⫽ time, and x,y,z ⫽ 3-space. According to the concept of adaptive equilibrium in relation to the canalization of epistatic systems, there will in fact frequently be a set of parameters within which a given developmental trajectory is free to expand or contract on a temporal or spatial axis (namely, according to the domain of phenoplasticity). Here, the position of a reference point must therefore be judged according to its relationship to a ‘‘permissible zone’’ that can be termed the plesiomorph ﬁeld. Thus, if a given transformation lies within the domain of adaptive capacity, the system has expressed no transformation relative to the ambient probability distribution for the (t; x,y,z) coordinates. The state of apomorphosis is thus described solely by transformation which transcends the domain of the plesiomorph ﬁeld by virtue of neomorph mutation. Thus, only movement which transcends adaptive capacity actually constitutes ‘‘transformation’’ in the context of a broader evolutionary analysis. Adjacent Morphosystems and Realization of Adaptive Potential From the above analysis, there is clearly a link between the adjacent morphosystems transition and transgression between adaptive capacity and potential. Movement from adaptive capacity to potential is equivalent to movement between plesio- and apomorph ﬁelds, and an ‘‘adjacent’’ transition can therefore mean realization either of adaptive capacity or potential. The shift toward an adjacent morphosystem can also constitute an incremental step toward a more distant paradigm structure that can be reached via integration of several such steps. The latter situation is clearly vital for the realization of adaptive potential in the context of anagenesis, and it is thus likely that iterative shifts in the adjacent domain form the usual pathway to realization of (positively selected) alternative systems. Many adjacent systems will therefore belong to adaptive capacity (as indeed they often do in phenotype plasticity regimes), while adaptive potential relates to more remote morphogenetic transformations. More explicitly, adjacent morphosystems described by changing epistatic systems undergoing decanalization form the most probable pathway from adaptive capacity to adaptive potential. The roots of certain larger morphogenetic changes may, in this way, lie in primary adaptive equilibrium. A major inﬂuence in the ‘‘decoupling’’ of developmental trajectories thus lies with phenotype plasticity, where the growth rates of phenogenetic cell lineages have been integrated into the developmental landscape via differential lability to nongenetic determination factors arising in the external environment, and where the gene-developmental system has been structured around adjacent morphosystems differentiated by the phenotype ⫽

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genotype ⫹ environment equation. Only in this much restricted sense, can genetic assimilation be linked to evolutionary change. A Minimum Model for the Analysis of Morphogenetic Transformation The most useful ‘‘minimum model’’ would obviously be one that allowed derivation of all conceivable morphogenetic transformations from a common root. Here, we require the adoption of certain convenient reference frames in order to discuss fully the implications of morphogenetic transformations. A useful reference frame can be taken as constituting the geometric (i.e., morphogenetic) coordinates of a given structure unit at time tj. Temporal reference frames of this kind, as superimposed on the root model introduced in Chapter 9, constitute ‘‘expansions at a point’’ drawn where the frame cuts the growth curve. An integrative model thus illustrates the four-dimensional structure of development in the context of an idealized and schematized representation. An expansion of our earlier diagram (see Fig. 43, Chapter 9) allows geometric states of development to be extracted at various points in a morphogenetic trajectory (Fig. 75). The axes of a reference frame as shown in the expanded diagram are t (temporal); x,y (⫽ 2-space), at t points (⫽ X axis), the model thus showing structural coordinates drawn at certain intervals from the primary growth curve, being purely ‘‘geometric’’ with respect to the former. This system will now serve as a convenient root model, from which various derived states can be explained.* Looking in more detail at consecutive reference frames in the diagram shown in Fig. 75, we can examine the behavior of Cartesian spatial coordinates in the minimum model as development proceeds. The ﬁgure shows simple scalar transformations of the geometric coordinates of a structure unit undergoing morphogenesis; however, it is clearly not possible to go on to analyze more complex transformations of this system unless we consider the simultaneous activity of at least two morphogenetic trajectories (Fig. 76). This approach displays a more complex situation with respect to uniform changes in purely scalar coordinates, also indicating that other manifestations of morphogenetic transformation will also need to be examined in a similar manner. Our speciﬁc point of interest in the above model clearly lies in the manner in which the root coordinates of chosen reference frames can conceivably be modiﬁed through mutational change affecting morphogenesis, linking this with expanding expression of morphogenetic potential in the context of gravitation toward the structural selectional attractor discussed in Chapter 7.

Theoretical Models of Morphogenetic Transformation The possible topological pathways between adjacent morphosystems can now be analyzed in the context of developmental afﬁne transformation, looking at the topological behavior of speciﬁcally deﬁned morphogenetic reference frames during evolutionary change. The term ‘‘afﬁne morphogenetic transformation’’ * In the above model, it should be borne in mind that ‘‘developmental time’’ is, in reality, a probability distribution (see above). ‘‘Static points’’ in ﬁgures representing morphogenetic transformation are therefore equivalent to ‘‘centra’’ of the probability distribution in question.

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FIGURE 75 A morphogenetic reference frame sequence shown as a series of expansions at a point in the fundamental growth curve for development; the ﬁnal adult phenotype state (right-hand side) emerges progressively from an ontogenetic sequence (state 1). The second state in the sequence is pheno-ontogenetic, the third, phenogenetic.

(modiﬁcations of form which do not alter the purely geometric straight-line relationship) clearly has a special meaning in developmental terms, in that we need to consider transformation in several dimensions. What possible transformations of form are theoretically possible? Transformation Factors in Scalar, Positional, and Temporal Dimensions There must be three fundamental categories for the analysis of morphogenetic transformation factors: • Scalar transformation factors change the dimensions of Cartesian geometric coordinates. • Positional transformation factors change the spatial locus of a given structure unit or morphogenetic object within the overall trajectory of development.

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FIGURE 76 Two morphogenetic trajectories manifesting independent developmental change in different spatial coordinates.

• Temporal transformation factors change the time frame locus of a structure unit or developmental object. Of the above, temporal and positional transformations can be categorized as being translations. We can visualize this by looking at these propensities in the context of three developmentally adjacent reference frames (Fig. 77). Universal and Speciﬁc Transformation Factors Mutational change may affect only limited areas of development, or else it could have extremely widespread effects during development. We must now ask, what is the developmental domain of a given morphogenetic transformation factor?

FIGURE 77

Scalar transformation (top), and temporal and positional translation.

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The domain of transformational effects may clearly be universal or speciﬁc: Universal: Constant effect for all values of x,y, thus affecting all coordinates of development equally (as in increase or decrease in absolute size). Speciﬁc: Different effect for different values of x,y, thus affecting some developmental objects (structure units or integrals) and not others (for example, one unit enlarges or diminishes, while others remain unchanged; or a translation occurs through a temporal shift that is unique to a single morphogenetic trajectory). Universal scalar transformations clearly express no real neomorphic transformational change in the phenotype, their effect being uniform throughout the entire spatial trajectory of development. Universal temporal transformations also have no true neomorphic effect, the entire developmental sequence merely expanding or contracting on the temporal axis, with no transformational effect. Speciﬁc transformations are thus clearly those of special interest. In this scenario, the effect of a transformation factor is different for independent developmental modules. Consider the minimum model of the outcome for two developmental trajectories simultaneously. In the scheme shown, we can already identify certain major expressions of morphogenetic transformation as they have been described by classical embryologists (heterochrony and allometry being examples).

FIGURE 78 The effect of speciﬁc transformational factors for temporal, positional, and spatial transformations.

Isotopic and Anisotopic Transformation Factors It is now further necessary to examine speciﬁc transformation factors in terms of how a given pattern of change actually affects the coordinates of a single structure unit. Speciﬁc transformational factors can affect the dimensional coordinates of an object structure unit in either of two ways:

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Isotopic transformation factors equally affect all dimensional coordinates of a given structure unit: An isotopic spatial transformation factor will simply scale an ‘‘object’’ structure unit in terms of absolute size, with no change in shape. Anisotopic transformation factors affect separate dimensional coordinates of a structure unit in a different manner (there may, for example, be n factors affecting spatial coordinates s1, s2, . . . , sj): Anisotopic transformation factors will be causal to some complex transformation of a given object structure unit, thus affecting actual shape change.

FIGURE 79 Anisotopic and isotopic transformation factors (root system on left-hand side).

It is also evident that the differential between isotopic and anisotopic transformation factors reﬂects the dichotomy between two different levels of morphogenetic transformation arising from apomorphic gene mutation (see Chapter 12). Some transformations are only paramorphic, that is to say, they represent either recurrent states or else ‘‘reshufﬂings’’ of preexisting structure, thus involving no actual shape change. Only when the latter does occur are we confronted with true neomorphic transformation of form.* It is important to see how true neomorphic transformations differ from those affected by isotopic transformation factors (Fig. 80). It is essential to realize that, in such factors as heterochrony, heterotopy, and allometric transformation, the primary geometric relationships of a trait remain constant, whereas in the neomorph case they are changed. Speciﬁc–isotopic transformation factors are thus equivalent to paramorphic transformation (see above). We can expand Fig. 80 to incorporate both neo- and paramorphic effects for iso- and anisotopic transformation factors in terms of scalar, positional, and temporal dimensions (Fig. 81). * It therefore follows that not all neomorphic gene mutation is neomorphic in terms of phenotype change.

FIGURE 80

Anisotopic effects as neomorphic transformation (shown to the right-hand side).

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FIGURE 81 Neo- and paramorphic effects of morphogenetic transformations in scalar, positional, and temporal domains.

Anisotopic–speciﬁc transformation factors are clearly of exceptional signiﬁcance in their capacity for true neomorphic change in the context of macroevolutionary anagenesis, whereas paramorphic transformations are more linked to a reshufﬂing of preexisting structure. However, as we shall see, the importance of the latter mode of change must not be underestimated in terms of realization of adaptive potential, an observation that must in large part be due to the easier evolutionary path facilitated by mutation acting on a developmental modularity regime that is closely akin to preexisting selectional modularity (see Chapters 7, 9, and 12). Simple versus Complex Neomorphic Transformation Yet one other layer of complexity must now be added to the minimum model. It is useful to examine a point of interest in the root model graph, and to further consider its behavior in relation to possible parameters of morphogenetic change arising simultaneously in both the spatial and temporal domains, for example, looking at translative changes (Fig. 82). Simple transformation lies exclusively in the spatial or temporal domain, whereas complex translation lies in both simultaneously. Clearly, much anagenetic change may well tend to belong in the complex zone. In the general model, complex neomorph structures are due to the combined inﬂuences of scalar, positional, and temporal transformations, and this underlines the fact that the classical heterochrony–recapitulation mode of analysis often seems to concentrate on ‘‘exception, rather than rule’’ in the investigation of modes of major evolutionary change, thus constituting an oversimpliﬁcation of the reality. New morphogenetic axes must also have been required in relation to signiﬁcant neomorphic changes such as (for example) the evolution of the

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FIGURE 82 Complex translation (where Y represents the spatial plane, and X, the temporal).

autopod in the earliest amphibious vertebrates (see Chapter 14), and this in turn links to the question of alternative versus adjacent morphosystems (see above). It seems intrinsically likely that complex neomorph structures of that kind cannot reasonably be expected to evolve saltationally, and we should here be thinking instead of repeated morphotransformations of the paramorphic kind as constituting the most likely pathway to more complex neomorphic states, on a basis of incremental change in the context of longer term iterative, anagenetic change. Special Transformation Factors of Development in Paramorphic Transformation It has been shown above that neomorphic transformation is not considered to be affected by universal or by isotropic transformation factors, and that this criterion serves to deﬁne a somewhat heterogeneous class of transformations identiﬁable as paramorphic, namely, those that are closely adjacent in terms of topology, and thus usually also of developmental modularity. It is necessary to seek a deeper understanding of the dichotomy between neomorphic and paramorphic transformation factors, particularly since the latter provide valuable information on the interpretation of supposed maladaptivity in the perpetuation of apparently suboptimal states during the course of anagenesis (see Chapter 15). Clearly, paramorphic transformation is to be equated with temporal, positional, or spatial reshufﬂing of unaltered parent developmental modules, and this includes universal transformations, along with heterochrony and heterotopy.* * Naturally it is difﬁcult to draw a ﬁrm line between paramorphic and neomorphic transformation. However, the dichotomy between ‘‘adjacent’’ and ‘‘distant’’ morphosystems clearly requires at least a provisional dialectic.

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Several paramorphic transformations appear to be peculiar to organic systems. For example, prolongation–truncation of development (special case scalar transformation expressed in some manifestations of heterochrony) is a further element which cannot be said to constitute afﬁne transformation in the usual mathematical sense, but which is dislocative with respect to the positional coordinates of a certain morphogenetic object. Following the root model:

FIGURE 83 Prolongation of development (with no other effect on the topology of the parent system) as a further mode of paramorphic transformation.

Duplicational and reductional transformation also constitute special case paramorphic transformations of the positional (i.e., heterotopic) kind. A given structure unit or other morphogenetic object may be duplicated or developed in multiple replication (as with the increase in leg number in some arthropod lineages, for example), or there may conversely be a reduction in number of appendages (as in the arthropod lineage which gave rise to the insects). Eclosion line shift can also cause apparent ‘‘transgressive translation.’’ This constitutes that mode of paramorphic transformation through which the temporal locus of the eclosion line changes. True transgressive translation (a speciﬁc temporal translation of the neomorphic kind which crosses the eclosion line independently of any eclosion line shift) may also occur when adaptational coordinates pass to fabricational function to become traits of ontogeny. Morphogenetic translation (real or apparent) may, in either way, come to transgress the boundary between phenogeny and ontogeny, a former adult state becoming a fabricational precursor state, thus leading to the appearance of adult traits in

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the prephenogenetic stages of development. Consequently, even recapitulation constitutes a heterogeny in terms of the dichotomy between neo- and paramorphic transformation factors: At what point might a shifting eclosion line have come into play? A juvenile stage may have been retained in the parent body for a longer period, or else an advanced embryo may have been ejected earlier, and transgressive recapitulation could occur by the former means alone. It may be of special interest from the viewpoint of incremental change in evolution that a useful working hypothesis could consider that interphenon distance is most usually equivalent to adjacent (⫽ afﬁne) transformations of the paramorphic kind during periods of viable mutational change. At a later stage, we shall go on to consider the possible relevance of paramorphic transformations to the question of perpetuated suboptimal adaptive states in the phenotype (see Chapter 17).

OBSERVED MORPHOGENETIC TRANSFORMATIONS How do observed expressions of morphogenetic transformation actually conform with theoretical predictions? Patterns of change that have been widely recognized include recapitulation, allometry, heterochrony, and heterotopy, all of which can readily be matched with predictable morphogenetic transformations of development. Enlargement and reduction are the simplest transformation systems observed in Nature, and these are obviously linked to many modes of evolutionary activity, from phenoplasticity to speciation and beyond. Allometry and heterochrony are also well documented modes of adaptive response, and these relate in turn to a considerable heterogeny of mechanisms in the domains of both spatial and temporal morphogenetic transformation. Scalar transformation is perhaps most easily understood in terms of classical allometry, which has been the subject of extensive analysis since the classical work of Thompson (1917) and Huxley (1932). Heterotopic (positional) transformations have perhaps tended to attract less attention than has heterochrony. In terms of morphogenetic transformation, this category also includes rotation and duplication–reduction. It is clearly of considerable interest to note even at this stage that several of the above transformational systems belong to that category which has here been identiﬁed as being paramorphic, rather than neomorphic. The question of whether this is due to paramorphy being the commonest system operating in Nature, or whether such systems are simply those most easily analyzed in simple geometric terms will, however, have to be examined closely. It is perhaps now pertinent to look more deeply into the heterogeneous category heterochrony. By deﬁnition, classical heterochrony is speciﬁc temporal translation of somatic tissues relative to the germ line, for example, where adult somatic traits are in some way suppressed in favor of juvenile ones, or vice versa. The main divisions of heterochrony are thus paedomorphosis and peramorphosis (following Gould, 1977; also Alberch et al., 1979), and the

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relative temporal position of germ line (reproductive phase) versus somatic traits clearly forms an important input to this scenario. In paedomorphosis, juvenile traits have become associated with ancestral adult states, while peramorphosis constitutes the opposite scenario. Following Gould, two modes of paedomorphosis occur, the ﬁrst of these being neoteny, corresponding to prolongation of the juvenile phase for certain somatic modules of development. The other is progenesis: reproduction moving to a juvenile phase, with truncation of development. Clearly, however, no interpretation of heterochrony encompasses anything like the entire range of observed morphogenetic transformations, and even the narrowest deﬁnition of the term obviously constitutes a considerable heterogeny in terms of mechanism and process, especially with the inclusion of peramorphosis and recapitulation. ‘‘Heterochrony’’ thus already has several meanings (Haeckelian, de Beerian, and Gouldian), and although Gould has demonstrated the obvious heterogeneity of causality for heterochrony in its broadest sense, others have since applied the term too widely. In the Gouldian sense, heterochrony is an approximation for simple-speciﬁc temporal translation, and as such, the concept undoubtedly retains some degree of validity. It should perhaps also be said at this point that both heterochrony and allometry have received much attention in the classical literature, more so than is perhaps actually justiﬁed. The link between theoretical and real manifestations of morphotransformation may usefully be summarized as follows (so far as purely isotopic transformation factors are concerned) (Fig. 84). The categories of morphogenetic transformations shown are, of course, approximately those belonging to the provisional ‘‘paramorphic’’ domain. There follows a deeper analysis of the principal manifestations of morphogenetic transformation.

Allometric Transformation Allometry is the simplest and most easily understood mode of morphogenetic transformation. All aspects of scalar transformation are considered here as manifestations of allometry, although many authors in fact restrict the latter term to those expressions which occur as a corollary of change in body size. Three principal expressions of allometric transformation exist, one of which constitutes neomorphic change, the other two being paramorphic: 1. Minor allometric transformation occurs when a speciﬁc isotopic factor S affects all dimensions of a given structure unit equally (namely, in the context of true geometrical similarity). This is clearly a paramorphic scalar transformation. All relative size changes belong in this category. 2. Major allometric transformation occurs when anisotopic scaling factors s1, s2, . . . , sj affect different dimensions of a structure unit separately: s1 * x, s 2 * y * , . . . ; in this case, a neomorphic transformation (shape change) is clearly effected (Fig. 85). 3. Coallometric transformation occurs when scalar transformation to a structure unit occurs as a speciﬁc corollary of change in absolute

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FIGURE 84 Isotopic transformation factors and equivalent terminology in the classic literature.

body size. This is seen as a paramorphic transformation derived from that situation where different modules of development carry different allometric equations that are linked in some way to growth itself: Huxley (1932) recognized the existence of modules in development which expressed ‘‘a constant partition of growth intensity’’ inter se, by virtue of the existence of regular differences in growth rates between certain trajectories. He analyzed this situation as heterogony, through the medium of the equation y ⫽ bxk (where y is the magnitude of some differentially growing structure and b and k are constants), with k accordingly manifesting different values in different developmental trajectories. This is, of course, the widely studied equation of allometric growth extended to encompass differential growth in quasiautonomous modules of the developmental landscape. In coallometric transformation, any increase or decrease in absolute body size that is due to prolongation of development has an automatic corollary in paramorphic transformation, owing to the different growth functions operating in different morphogenetic trajectories. This circumstance is clearly linked to the question of pleiophoric mal- or nonadaptivity raised in the previous chapter, and this problem will be examined further (see below).

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FIGURE 85 Major allometric transformation. The upper trajectory has manifested a scaling effect, and the lower trajectory expresses no change, so that speciﬁc scaling transformation is manifested in major allometric transformation.

Paedomorphosis and Peramorphosis as Heterochrony Temporal translation involving movement of one somatic morphogenetic object relative to another constitutes either peramorphosis (translation of adult states to the juvenile phase) or paedomorphosis (juvenile traits appearing in the adult phase).* Paedomorphosis may involve movement of somatic modules only, * Various subcategories have been deﬁned within paedo- and peramorphosis sensu lato, of which the most discussed have perhaps been postdisplacement (where one or more features of the descendant develop at a later stage with respect to the rest of the organism) and predisplacement (‘‘the peramorphic opposite of post-displacement,’’ following Raff, 1996).

FIGURE 86

Paedomorphosis and peramorphosis. A late stage in the upper morphogenetic trajectory appears earlier as a result of acceleration relative to the lower trajectory (peramorphosis). The penultimate stage in the lower module is shown being translated to the ﬁnal phenotype stage owing to an arrestment effect (paedomorphosis; see neoteny below).

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namely, in neoteny (as in Fig. 86), or else it can alternatively involve acceleration of the germ line combined with developmental truncation, namely, in progenesis. (Fig. 87). Coupling of sexual maturation is obviously essential to truncation of development in progenesis, and this in turn illustrates the essential role of speciﬁc translation in the context of ‘‘true’’ heterochrony. Gould (1977) cites many apparent cases of progenesis:

FIGURE 87 Progenesis as truncation of development coupled with earlier maturation of the germ line (䊊 ⫽ germ line).

Included are well-known examples in living salamanders, as also in many other lineages. A typical molluscan example from a fossil lineage may be illustrated by certain ammonoids in which an adult condition in suture length progressively penetrates more juvenile stages, the descendant attaining the same sutural complexity as its ancestor at only one-ﬁfth the size (following Newell, 1949). Paedomorphosis does not involve truncation or dislocation in that circumstance where somatic juvenile traits are selectively translated to the adult stage, with maturation occurring at the normal time (see neoteny): Neotenous effects have been extensively documented in human evolution—also in domesticated animals such as the dog (particularly in relation to prolongation of learning potential). Although some proportion of these traits is no doubt open to other interpretations (see Raff, 1996, for a critique), many are apparently authentic. The ‘‘hypermorphic’’ mandibles (the so-called pilifers) of some ditrysian moth pupae are clearly derived from the preceding larval stage of development. Similarly, the pseudo-exarate state of zygaenoid

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moth pupae apparently constitutes an example of neoteny, considering the incidence of the traits concerned in other prepupae of a similar general grade of evolution (Brock, 1990a, and new observations). Looking at the above interpretations from a wider viewpoint, it is evident that paedomorphosis and peramorphosis in reality constitute convergent morphological corollaries of a heterogeny of mechanisms. Peramorphosis and Recapitulation Peramorphosis (Alberch et al., 1979), in its broadest sense, describes a particularly wide range of temporal translations of the somatic kind, which must clearly be examined within the context of the major paradigms of development with special reference to the position of the eclosion line and external adaptation interface. Peramorphosis may be taken to include recapitulation and can either be manifested entirely within the trajectory of phenogeny or else penetrate ontogeny. Examination of the peramorphosis–recapitulation heterogeny following the root model for morphogenetic transformation clearly uncovers several manifestations of speciﬁc translation in the adult 씮 juvenile orientation. In the diagram shown in Fig. 88, it is clear that recapitulation could occur either in the pheno- or ontogenetic domain, or else pass between these two domains. Firstly, when translation of a developmental state to an earlier phase occurs within phenogeny as a result of prolongation of growth, this is often termed peramorphosis, whereas if it occurs in the embryo, then we have a manifestation of ‘‘true recapitulation.’’* Strictly speaking, a recapitulative state can usually be supposed to be a joint ontophenogenetic structure (as shown in Fig. 88), and it is really only position in relation to the eclosion line which determines whether we are witnessing peramorphosis or true recapitulation: The classical exemplar for intraphenogenetic translation lies with the diphycercal 씮 heterocercal 씮 homocercal transition in tail structure in teleost ﬁshes. Pheno-ontogenetic translation involves translation passing from the freeliving state to an embryonic one, and this is clearly a fundamentally different mechanism from intraphenogenetic translation: The branchial pouches in mammalian embryos are not needed, except for function in morphogenesis of the visceral skeleton, aortic arch system, branchial musculature, and associated endocrine glands. A remote ancestral adult trait thus appears in ontogeny in a descendant lineage according to a requirement in the fabricational as against the exogenous adaptive paradigm (see Thomson, 1988). Morphogenetic translation can presumably also occur actually within the domain of the embryo itself: von Baer noted that the vertebral column of the chick develops ‘‘earlier than it should,’’ according to recapitulationist theory, and this circum* Ridley (1993) includes peramorphosis as part of an enlarged ‘‘recapitulation.’’

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FIGURE 88 Recapitulation as retrotranslation of morphogenetic objects in the phenogenetic and ontogenetic domains.

stance evidently indicates phenogenetic translation of the recapitulatory kind extending progressively more deeply into ontogeny. In this situation, it seems probable that adaptational function is being restructured in terms of fabricational parsimony. The dichotomy between intraphenogenetic and intraontogenetic translation (speciﬁc translation occurring entirely within the domain of phenogeny and ontogeny, respectively) thus also centers on the distinction between adaptational and fabricational paradigms and on the degree to which fabricational parsimony has disrupted ontogeny. Finally, it must be realized that much ‘‘recapitulation’’ applies solely to limited coordinates, rather than, as the early recapitulationists imagined, to whole structures: Cope recognized two categories for the biogenetic law of von Baer (‘‘the general features of a higher group appear earlier in the embryo

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than do the special features’’): one category in which entire adult traits are pushed back and another in which recapitulation occurs part by part (see Gould, 1977). The question of recapitulation only arises when translation has occurred, and when this involves simple speciﬁc translation of some developmental module. Von Baer’s law (see above) is clearly an observation that ﬁts the rule that major morphogenetic coordinates are those least likely to be modiﬁed in the transgression from phenogeny to ontogeny. It is thus a superset of Haeckel’s law concerning recapitulation, and the latter phenomenon thus constitutes an occasional special case outcome of a more general mechanism. Owing to the probable links with fabricational parsimony already mentioned, any structuralist interpretation of recapitulation and the biogenetic law must be rejected, and such phenomena must now clearly be investigated further in the context of the morphogenetic accommodation principle, as the latter is linked to neomorphic anagenesis.

False Recapitulation and Hypermorphosis As we have already seen above, ‘‘false recapitulation’’ can occur, either as a corollary of prolongation of development or of eclosion line shift. In the former instance, there may be peramorphosis where extended growth is reﬂected in coallometric differentials. Hypermorphosis is thus a further expression of peramorphosis, in which extended growth (prolongation) is reﬂected in coallometric patterns of diversiﬁcation (see above).

FIGURE 89 False recapitulation of morphogenetic objects (A) owing to postdisplacement of the eclosion line and (B) as a corollary of prolongation of development.

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Heterotopy Speciﬁc positional translation (⫽ classic heterotopy) is particularly exempliﬁed with ontogeny and the assembly model of development, in that positional translation of structure units is a mechanism occurring most prominently and dramatically during earlier development: Most spatial coordinates of gastrulation, for example, are complex heterotopic morphotransformations of ancestral structures which must have had very different positional coordinates, and this is also linked to the fusing of modular trajectories in development (see Chapters 9 and 10). Many adult features clearly also constitute heterotopic change of one kind or another, and this mode of change has evidently been linked in particular to the origins of new higher group lineages.

ADAPTATION AND MORPHOGENETIC TRANSFORMATION Given that most predictable avenues of morphogentic change are also observed in Nature, what causal factors in the adaptation interface are linked to transformation mode?

Adaptive Shifts and Suboptimality in Paedomorphosis It should by now be clear that the phenomenon of morphogenetic transformation, in general, must be identiﬁed by and linked to causality lying primarily in adaptive strategy, rather than lying with any hard structuralist interpretation (and particularly avoiding the standpoint of Haeckel, who held the view that ‘‘phylogeny is the mechanical cause of ontogeny’’): An extreme example of the above thinking can be seen in the view of Weissmann (see Gould, 1977), who thought that the ‘‘recapitulated’’ color patterns of mature sphingid moth larvae proved the Haeckelian interpretation, since they are clearly nonadaptive in juveniles (a hypothesis that is hardly borne out by even the most casual observation!). The early literature on recapitulation abounds with unqualiﬁed pronouncements of the above kind, and many earlier interpretations of ‘‘heterochrony’’ probably belong in the same category. Following failure of the ‘‘transcendentalist’’ approach to interpretation of developmental perspectives in evolution, moves were later made to adopt a more realistic interpretation. Most signiﬁcantly, Gould (1977) ascertained that paedomorphosis tends to occur in the context of a changing adaptive strategy linked to complementary change in the immediate external environment: Gould pointed out the link between amphibian paedomorphosis and activity of the thyroid gland; some of these paedomorphic forms are facultative with respect to external inﬂuences, while others are ﬁxed,

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and facultative paedomorphosis has been speciﬁcally linked to ﬂuctuating environmental factors. Gould also raised the question of body size in the context of structure and dynamics of populations, showing that much paedomorphosis can be reinterpreted in this light. So-called r-selection will predominate when the density independent component of selection is in control, and progenesis can thus be seen as a mechanism which facilitates a shift from K- to r-selected environments (and thus from selective to nonselective mortality; see Chapter 4). This adaptive shift is furthermore clearly correlated with a leading factor in a trend toward small size. Likewise, Gould also showed that neoteny is often similarly linked to a K-adapted strategy. Gould tested his r/K strategist theories against classical examples of progenesis and neoteny, showing convincingly that the existing evidence largely agreed with his theory, pointing out that the literature abounds with examples of facultative progenesis linked to exploitation of ephemeral and superabundant resources: The environmental determinants of progenesis were highlighted with regard to the data of Snyder and Bretsky (1971) on the dwarfed fauna of the basal Maquoketa (Ordovician) formation, a progenetic assemblage seemingly adapted by r-selection via shortened generation time accompanied by earlier development of sexual maturity. It is thought here that evidence exists for the presence of a high stress environment and superabundant food. Paedomorphic cecid midges revert to normal sexual reproduction in crowded conditions. Similarly, aphids switch from a paedomorphic– parthenogenetic to sexual mode of reproduction as winter approaches. Likewise, parasites are often r-selected and progenetic, and paedomorphosis in salamanders is commonest when the surrounding terrain is harsh (Sprules, 1974a). McNamara (1988) showed that the relative frequency of neotenous as against progenetic trilobites showed a marked increase between Cambrian and Postcambrian strata, apparently reﬂecting a progression from logistic to structural adaptive response. With regard to neoteny, Gould (1977) stated that trends toward greater size and complexity link to three features apparently correlated with K-selected regimes: (1) a primary role for structure in adaptation; (2) a tendency toward size increase; (3) usually a delay in absolute time of maturation. Phyletic Senescence, Paedomorphosis, and Phenogenetic Convergence Why should a K-selected lineage return to being an r-selected one? The reason must lie with changing competition regimes. A formerly benign lineage niche (see Chapter 6) may become ‘‘overworked’’ owing to pressure from phyletically remote lineages of higher adaptive state, sometimes leading to a condition reﬂecting phyletic senescence in a less versatile lineage. A lineage is said to be senescent when the structural component of the adaptive ensemble has become irreversibly specialized (that is to say, when it lacks adaptive

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potential for further adaptational change to a changing external environment) and when it exists in a state of progressively expanding niche intersect with one or more other lineages containing superior adaptive capacity and potential. This scenario has signiﬁcance for paedomorphosis when the highest residual adaptive potential of the lineage in question is restricted to the logistic component of the adaptive ensemble (and where the latter is contained in the more ‘‘primitive’’ juvenile stage, as implicated in the remarks of Takhtajan, 1954). Progenesis is particularly common in living survivors of the lower amphibious vertebrates, for example, and this could be taken as evidence of lineage senescence. Gould also observed that paedomorphic hemidactyline salamander species are mostly subterranean, living at the edge of their presumed ancestral range. Changing niche proﬁle can thus be viewed as part of an adaptive cascade following on from senescence of lineage. Lineage senescence may then be characterized by an element of regressive adaptive shift, hence the apparent links with vestigiation and heterochrony. The reason progenesis is easily facilitated in the context of lineage senescence may of course often be partly due to adaptive capacity having been constructed around periodic reversals of niche proﬁle, and this may not mean that the niche parameters in question are necessarily ‘‘lost’’; conversely, they might simply be preoccupied by superior competitors or by some cyclic geophysical factor: Iterative paedomorphosis in Pleistocene Bermudan land snails is clearly linked to shortage of lime in the soil, suggesting another probable mode of link between heterochrony and amphigenesis. The usual orientation of evolutionary change may be that the gene pool is tending to expand into free adjacent niche space by virtue of structural progression toward a stable adaptive paradigm. Niche proﬁle can, however, also retrogress by contraction, and this may be a periodic behavior. Paedomorphosis may then be expressed in the phenoplastic component of the adaptive response, so that tertiary adaptive equilibrium and amphigenesis could here be seen as being processes for which progenesis forms one possible mechanism. The outcome of a displaced adaptational biophysical paradigm of the ‘‘heterochronic’’ kind can be termed phenogenetic convergence, namely, that mechanism through which there is speciﬁc temporal translation of one or more somatic modules from adult to juvenile, and this may sometimes constitute amphigenetic change. A niche shift model for progenesis supposes adaptational convergence between adult and juvenile with respect to certain somatic traits, the adult having (at least partly) come to occupy the juvenile niche. Thus, the niche displacement theory advanced by Gould is conﬁrmed in terms of competition factors leading to a retreat from structure-led to a logistic-led adaptive strategy. In contrast, neoteny is clearly not a function of phyletic senescence, despite being an element of paedomorphosis. However, the principal of phenogenetic convergence (of a different kind) can equally well be invoked to explain the paradigm shift responsible for the projection of juvenile features into the adult

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stage. Hence, solutions to adaptational problems engineered by the more ‘‘hostile’’ niche regimes of some phenogenetic stages may become valuable to adults in view of a changing external environment, and such factors as extension of the juvenile learning phase may constitute an important inﬂuence with neoteny. Although ‘‘paedomorphosis’’ constitutes a heterogeny of diverse effects of more than a single process, Gould’s theory concerning the broader features of paedomorphosis is fully acceptable (given certain qualiﬁcations concerning actual developmental mechanisms that will need to be explored further), and his ﬁndings must now to be linked to deeper roots in the structure of the adaptive system as a whole. Clearly, several interacting mechanisms are involved in the generation of morphogenetic transformation. These cannot be fully understood from the standpoint of any one discipline but need the integrated approach of biosystematology, which looks at activity throughout the adaptive system. Extending the analysis of heterochrony into that wider domain constitutes the ﬁrst step toward a more realistic interpretation of other modes of change.

The Adaptive Signiﬁcance of Classical Allometry As with heterochrony, two entirely different interpretations exist for coallometric transformation. One view sees allometry as an obvious route to the widespread origin of nonadaptive (and even of maladaptive) differentials between species (cf. Huxley, Gould), while the other view seeks an explanation in terms of adaptation. In fact, both heterochrony and allometric transformation have been used to support structuralist views of the evolutionary process, and this problem will need to be reassessed in terms of the relative inputs to adaptive shifts of endogeneous versus extrinsic factors. The laws of allometry are no doubt closely linked to the nature of the biophysical paradigm, for example, in the way gravity interacts with the latter (see Chapters 7 and 15). However, this does not mean that the entire developmental program is designed so as to anticipate all manner of size linked allometric changes, and the possibility of coallometric traits entering the diversity pattern purely as a corollary of other leading effects must not be ignored. As a general rule, it seems probable that most allometric change of the neomorphic kind seems intrinsically likely to reﬂect direct adaptational differentials. However, this may not apply to coallometric transformation, with the exception of that situation where absolute size is in fact built around the capacity of developmental systems to manifest appropriate coallometric adjustments within a certain range. The question of perpetuation of mal- or nonadaptive states ‘‘carried’’ by coallometric transformation and in patterns of morphogenetic change in general will be taken up again in the next chapter.

Terminal Addition–Condensation and Morphogenetic Accommodation One of the greatest dangers in applying classical heterochrony to the analysis of evolutionary change lies in the easy assumption that paramorphic transformations of that kind can serve to explain all phyletic transitions. Nowhere is the danger in this approach more obvious than in recapitulation, in which

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retrotranslation in the temporal dimension was at one time supposed to constitute a general law, such that any divergences from this law could be designated by a pecuniary nomenclature (hence the origin of such terms as heterochrony, caenogenesis, and so on; see Gould, 1977). As we have already seen, paramorphic translation may well lie close to the strategy of incremental change in anagenesis, but it certainly does not describe the longer term integration of multiple, iterative morphogenetic transformations of complex function integrals. Peramorphosis is, in broad terms, the opposite of paedomorphosis, with apparent translation of some adult somatic trait to the juvenile phase. As with heterochrony in general, simple peramorphosis creates nothing structurally new, but simply adjusts what was already present. Peramorphosis is also clearly a heterogeny within which recapitulation constitutes one subset, and the latter can also be shown to be an evolutionary corollary of more than one causal mechanism (for example, it is obvious that phenogenetic recapitulation cannot be the same thing as ontogenetic recapitulation). Clearly, the old ‘‘terminal addition’’ model of recapitulation must now be investigated in terms, not of paramorphism in heterochrony, but of morphogenetic accommodation in the context of true neomorphic change in the adaptational paradigm for complex anagenesis (see Chapters 9 and 12). That neomorphic recapitulation does indeed at times occur is evident from the presence of structural traits in ontogeny–embryogeny which have no direct adaptational function in the absence of an active adaptation interface, and where the latter must clearly have been present in some ancestral form. The illusion of ‘‘terminal addition–condensation’’ is, however, better understood in terms of special case morphogenetic accommodation, and a closer study of the latter mechanism will serve to explain why apparent recapitulation sometimes occurs, but usually does not! Recapitulation and the Accommodation Model All manifestations of recapitulatory translation can be encompassed within the broader concept of morphogenetic accommodation. In the accommodation model, progress toward adaptive and fabricational paradigms should be seen as two separate processes, but must nevertheless be viewed in terms of a morphogenetic continuum. In the model shown in Fig. 90, recapitulation simply constitutes that manifestation of morphogenetic accommodation in which limited developmental coordinates manifest simple temporal translation in the developmentally contiguous pheno-ontogenetic domain, in the evolution of neomorphic change in the phenotype, namely, in that circumstance in which an originally phenotypic stage becomes a necessary fabricational precursor state for a changed phenotype (‘‘every preceding stage becomes imperative for the development of every succeeding stage,’’ Takhtajan, 1954). Certain paramorphic transformations clearly also favor the merging of fabricational and adaptational paradigms. If the temporal span of embryonic development lengthens, this could allow capture of the earliest phenogenetic state. Iterative coupling of ontogenetic compression, eclosion line shift, and terminal addition would thus create that substrate necessary for morphogenetic accommodation which might sometimes be expressed as ‘‘recapitulation.’’

FIGURE 90 Accommodation and recapitulation. Ontogeny evolves toward the fabricational paradigm (left), phenogeny toward the adaptational paradigm (right); accommodation is then largely centered around an interdigitated paradigm state in the domain of pheno-ontogeny (center).

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Morphogenetic accommodation really relates to an interdigitated adaptational–fabricational structure paradigm which may be modiﬁed greatly when there is retrotranslation, or when a phenogenetic state is captured by a shifting eclosion line coupled with prolongation of the quiescent state in development. The accommodation model thus clearly does afford evidence for heterochrony in the form of ‘‘peramorphosis–recapitulation.’’ However, these latter phenomena are really best seen as being special case emergent properties of several dynamic mechanisms. It is probably worth closing this discussion by asking the obvious skeptical question: does ‘‘transgressive recapitulation’’ genuinely occur in the absence of an eclosion line shift? In general, any upstream mutation with no grossly negative downstream effects will be perpetuated provided that there is a net adaptive gain. If the locus in question controls geometric coordinates throughout a developmental trajectory, then there is no reason why this should not at times invoke accommodation of the recapitulative kind, via translation of a structure unit manifesting a high element of modular dissociation—whenever the selective advantage relates to a terminal trait and accommodation involves the preterminal state becoming a fabricational precursor to that state.

Caenophenogeny and Recapitulation That recapitulation should not be regarded as anything other than a rare, special case corollary of the evolutionary process is evident from the very widespread manifestation of so-called caenogenesis (caenophenogeny; see Chapter 9), which can be seen in the potential for sharp niche divergence between juvenile and adult stages (Fig. 91). In simple phenogeny, the juvenile 씮 adult niche transition may tend to be initially logistic-led in the adaptive ensemble (see Chapter 1), moving toward a more structure-led state in the adult, whereas in caenophenogeny, it is more visibly structure-led throughout. Caenophenogeny does not ‘‘disrupt phyletic change,’’ but merely sets up tangential directions with respect to additional adaptational paradigm structures at different stages of development; in extreme examples this may also lead to superimposition of a supplementary, ‘‘adventitious’’ embryo phase, as with the pupal stage of holometabolous insects. Caenogenesis clearly tends to oppose any tendency toward recapitulation, whereas simple phenogeny may at times favor a diverse range of manifestations of peramorphic translation, as indeed recognized by the early transcendentalists. Interpretation of these observations does, however, clearly belong to the usual paradigm of adaptive evolution.

MORPHOGENETIC TRANSFORMATIONS IN SPECIATION AND IN THE ORIGIN OF HIGHER GROUPS What are the relative frequencies of different manifestations of morphogenetic transformation in Nature, in relation to normal patterns of speciation and in the origins of higher group lineages?

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FIGURE 91 Caenogenesis occurs when two or more phenotypically adjacent states manifest a disjunct morphogenetic transition via an interposed ontogenetic phase.

Clearly, universal scalar transformation is observably the commonest mode of evolutionary change, certainly in the context of ambient speciation. Simple scalar transformation also appears to be a very common mode (although it may here be difﬁcult to ascertain in actual practice whether para- or neomorphic examples are the most numerous). Given that major allometric transformation is abundantly evident in many taxonomic hierarchies, it does seem likely that neomorphy is a frequent transformation factor in terms of a great many ﬁxed species differences. Classical coallometric transformation has, of course, also been widely reported in the literature.

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Paramorphic transformations seem also to be predominant in certain lineages at certain stages in their evolution, there being no doubt that some have undergone various transformations of this kind at some stage. ‘‘Heterochronic’’ translations in general have been quite widely recorded, although they appear usually to be considerably less abundant than scalar transformations, at least in extant lineages. This includes progenesis, neoteny, and various manifestations of peramorphosis. Until recently, heterotopies have tended to be overlooked, although this mode of morphogenetic transformation has clearly played a leading role in the origins of a great many higher group lineages, as well as in species diversiﬁcation in general. Complex morphogenetic transformations are much less likely to concern ambient species-to-species discrimination characteristics than are any of the preceding modes of change, being much more in evidence in the differential between higher taxa. Similarly, true recapitulation is a feature conﬁned to somewhat isolated examples, and complex heterotopy also seems linked to certain relatively rare occurrences in Nature (some of which latter nevertheless have profound effects on the generation of diversity pattern). A very tentative outline hierarchy for the probability of occurrence of different modes of morphogenetic transformation might then be as follows: universal transformation ⬎ minor allometric ⬎ major allometric ⬎ ‘‘other paramorphic’’ ⬎ simple neomorphic ⬎ complex neomorphic. In general, there are many constraints acting to make complex neomorphic change slow–incremental, as against the probably much greater propensity for rapid change inherent to simple paramorphic transformation. However, many claims which have been made in the past seem to overstress the role of certain modes of paramorphic translation in evolution: McNamara (1990) stated that he believed that the vast majority of anagenetic trends are ‘‘heterochronoclines’’. However, considering the fact that heterochrony is both the corollary of several quite diverse primary mechanisms (and thus difﬁcult to diagnose in practice) and is also frequently linked to phyletic senescence and amphigenesis, this would seem to be an unhelpful statement (see also Raff, 1996, for a criticism of ‘‘heterochronic’’ interpretations of paleontological data in general). As we have already seen, the most developmentally adjacent systems appear to be the commonest with respect to ambient speciational activity, and these do not generally fall into the category of heterochrony. Paedomorphic Origins of Higher Groups It has been further argued that paedomorphosis is of special importance in the kind of evolutionary breakthroughs involved in the origins of higher taxa, the classical explanation being that this mode of mutational change facilitates escape from specialization. Paedomorphosis cannot, however, be the main causal force underlying the evolutionary radiation of major taxa, if only for the reason that we are then left with a need to explain the original Baupla¨ne from which paedomorphic change occurred in the ﬁrst place! Similarly, the

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functional interpretation of progenesis advanced by Gould (1977) offers but little support for this mechanism as a major force in evolution (indeed Gould did in fact offer a thorough refutation of many spurious claims for a paedomorphic origin of phyla). In contrast to progenesis, neoteny seems to present a greater opportunity for exploration of long-term evolutionary advancement; for example, Takhtajan (1954) concluded that angiosperm plants are of neotenous origin, and the same force has been much in evidence in human evolution. Nevertheless, we must bear in mind the ‘‘polytropic’’ view of the actual developmental basis of many apparent ‘‘heterochronies’’ as previously discussed in Chapter 12 (see also Raff, 1996, for a more extended criticism). Heterotopy in Macroevolution As we have already noted, there is little doubt that heterotopy has been a signiﬁcant force in evolution, with special regard to ontogenetic change. The same mechanism is certainly also evident in major positional translations of certain phenogenetic traits, such as components of the cephalic skeleton, blood vascular system, and nervous system in relation to the aquatic 씮 terrestrial transition of early vertebrates. More recently, support has even materialized from DNA analysis for the inversion theory of chordate origins (following Garstang, 1928), so that not all apparently extremist interpretations of heterotopy can be automatically dismissed! Duplicational and reductional heterotopic transformations have also evidently played a major role in the early evolution of multicellular organisms, a circumstance that is also predicted from purely theoretical considerations (see Chapter 11): Simpson (1953) stated that two complementary trend types occur widely, and are linked to origins of higher groups (including phylum and class): (1) numerous similar parts diversify and reduce in number (for example, dermal bones of the vertebrate skull) and (2) few parts increase in number and become more uniform (as with increase in the number of vertebrae in snakes). Examples are also well known in the derivation of ﬂowers from shoots, and of compound ﬂowers from simple. Similar mechanisms have obviously been instrumental in the adaptive radiation of the classes of Arthropoda. Neomorphy versus Paramorphy in Macroevolution As we have seen, many major evolutionary changes seem to have occurred through quite simple afﬁne morphogenetic transformations, in the context of paramorphy. However, in terms of longer term macroevolutionary change, it must be supposed that thresholds for complex neomorphic transformations will inevitably tend to be crossed when n structure units are undergoing relatively simple morphogenetic transformation in temporal sequence, and when modular interactivity in development is also progressing toward some more distant paradigm state through iteration of incremental steps. This scenario may include, also, some element of ‘‘concerted change’’ (see Chapter 11). The question as to whether or not any higher group could have originated by virtue of a single complex neomorphic saltation is, of course, much clouded

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by the fact that we generally only witness the end points of iterative trajectories of morphogenetic change, with but fragmentary access to the initiating structural changes which must have taken place at the root of a higher group lineage. However, it is quite possible that major pivotal points may be rapidly encountered when duplicational and reductional transformations occur, with more complex anagenetic events tending to follow in the wake of such occurrences. In that context, we might then envisage a special case scenario for saltational evolution in the context of paramorphic transformation (against which we must also bear in mind those problems discussed in Chapter 14 in connection with the likelihood of a more incremental pathway to duplication of parts such as increase in leg number in arthropods!). Of particular interest in the present analysis of the evolution of adaptive systems is the question as to whether or not the ‘‘easiest’’ modulations of form are also those most frequently manifested in Nature, since any such ﬁnding might perhaps tend to support a structuralist rather than adaptationist interpretation. There is, however, no simple answer to this question, in that easy solutions may simply constitute incremental steps toward more complex neomorphisms, which latter may be the states we are actually attempting to analyze (usually in isolation from any direct evidence as to their derivation in the very remote past!). In general, although it is possible that some higher group lineages may originate through simple paramorphic transformation (paedomorphosis, duplicational transformation, and reductional transformation), the later emergence of a wider contingent of diagnostic traits is probably always linked to iterative change toward some neomorphic state.

MORPHOGENETIC TRANSFORMATION AND THE MECHANISMS OF DEVELOPMENT Which developmental mechanisms connect with different expressions of morphogenetic transformation, and how are these linked to the adaptational perspective? The above questions have proved increasingly difﬁcult to answer, as we move away from the traditional typological approach to comparative morphology. Firstly, it is essential to return to the distinction between process, mechanism, and emergent corollary, and to note that, in particular, a single emergent property may be realized through the action of more than a single mechanism. Following an interpretation linked to the behavior of the adaptive system as a whole, a process describes some survivorship strategy, whereas a mechanism lies in the functional (here, developmental) means through which that process is manifested. In this context then, morphogenetic translation of the progenetic kind is the mechanism for a process linked to a changing adaptive strategy associated with environmental change, and certain classical modes of morphogenetic transformation (for example, paedomorphosis and recapitulation) certainly include convergent properties that have arisen from quite diverse primary mechanisms (Fig. 92). Morphological concepts often reﬂect heterogeneous corollaries of diverse developmental mechanisms in the above manner, as was the case with paedo-

FIGURE 92

Process, mechanism, and corollary in mode of morphogenetic transformation.

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morphosis and recapitulation. The latter must not therefore be misconstrued as being primary evolutionary processes or mechanisms, if we are to avoid the typological approach inherent to classical morphology. It is clearly now necessary to return to the question of underlying developmental mechanisms for morphogenetic transformation, as ﬁrst discussed in Chapter 12 (see pp. 252–253). In this, it has become plainly evident that yet another layer of complexity has now been superimposed on the already difﬁcult question of the relationship between mutation, developmental mechanism, and pattern of phenotype change.

Signiﬁcance of Developmental Modularity for Paramorphic Transformation Factors One signiﬁcant conclusion drawn from the earlier analysis of developmental mechanisms in Chapter 12 was that developmental modularity is of critical importance in terms of movement between adjacent morphosystems. The genome will tend to become partitioned for adaptationally independent structure integrals, especially where this incurs qualitative biophysical paradigm differentials in a complex morphogenetic trajectory, and it seems intrinsically likely that it is this element of modularity which permits realization of many of the observed manifestations of developmental transformation. In particular, this must be the basis for those factors affecting heterochrony, and morphogenetic modularity must tend in general to render most expressions of paramorphic transformation an easy option, while at the same time demanding an incremental change strategy for more complex neomorphic change (see above): Gould (1977) notes also, ‘‘Hypermorphosis assumes the dissociation of maturation and somatic differentiation. . . . Consequently, delayed maturation permits extrapolations of somatic features.’’ The same rule also applies to other manifestations of heterochrony. The decoupling of germ line and growth observed in certain manifestations of heterochrony is obviously of prime importance, and it seems certain that reproductive organs do in fact generally tend to manifest a high degree of mutual developmental autonomy: Gould (1977) stated, ‘‘If growth and development can be dissociated even by simple stimuli, then heterochrony is easily exploited.’’ Gould also discussed evidence for the autonomous development of the genital glands of batrachians. This condition is regarded as being nearly universal in living amphibians, and developmental modularity thus constitutes a signiﬁcant factor in explaining the frequency with which heterochrony is expressed in that lineage. Clearly, hormones must often be involved in such paramorphic transformations as heterochrony, coallometric transformation, and prolongation– truncation of development: The hormonal control systems facilitating developmental dissociation of different morphogenetic trajectories in insects have long been known.

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In attempting to understand heterochrony through developmental modularity, we must of course also take into account Waddington’s remark (1966) that we really have to deal, not with separate organs, each with its own growth rate, but rather with continuous gradients in growth rate which vary gradually from one part of the body to the next. Nevertheless, the concepts of ‘‘dissociation’’ and modularity in certain developmental trajectories do evidently hold good for Gould’s heterochronic examples. However, the degree to which this modularity is diagnostic of a structuralist strategy will require closer inspection, and again this seems particularly true with respect to modularity of the germ line in progenesis. Considering the question of Huxley’s heterogony (and coallometric transformation in general) as a further product of developmental modularity, it is now relevant to ask whether such relationships can also be predicted from certain factors intrinsic to modularity itself. It is known that for functional reasons, certain organs and appendages have size limits imposed by virtue of physical limitations, especially due to factors relating to gravitational forces. It is also clear that, where there is a size distribution between juvenile and adult, there will already be a heterogonic adjustment function operating on development. It thus seems likely that heterogony may often tend to constitute an evolved relationship, built around speciﬁc structures in the adaptational paradigm which demand such adjustment (in the same way, isogonic growth patterns must be linked to structures which do not have this relationship with the adaptational paradigm; see Thompson, 1917). Consequently, developmental modularity will actually tend to be built around adaptationally positive allometric relationships, which may often also extend into the domain of phenoplasticity. Both heterochrony and classical allometry may thus often constitute adaptationally convenient shifts to adjacent morphosystems, give or take some element of ‘‘carried’’ suboptimal adaptation. The extent to which the latter actually penetrates an evolutionary lineage in the longer term is, however, another question (see Chapter 17). In general, paramorphic transformation is based on simple extrapolation of existing modularities, whereas neomorphic change derives from iterative paramorphic modulation. This need not necessarily carry a high risk of ‘‘overextrapolation’’ in the sense of frequently giving rise to signiﬁcant pleiophoric states in adult structure.

Mutational Regimes of Morphogenetic Transformation Given that morphogenetic transformations in general tend to occur through movement between adjacent morphosystems made possible by the existence of poised morphosystems in the context of developmental modularity, the genetic components of these mechanisms have been presumed to be largely based on mutations in regulatory genes of epistatic systems controllant to morphogenesis, speciﬁcally in rate and timing changes. Developmental Mechanisms and Polytropism Morphogenetic transformation might be presumed to occur through changes affecting the Cartesian coordinates of morphogenesis via changes in

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various components of the developmental program. However, as we have already seen from the polytropism law (Chapter 12), there are several ways in which developmental systems can produce the same phenotype effect: Arthur (1997) proposed that change in concentration of hormones may have effects similar to Thompson’s allometric transformations. Against this, we must also consider the view that the relationship between genes and the phenotype is frequently nonlinear and certainly not ‘‘one-to-one’’ (Oster et al., 1980), also the fact that phenotypic coordinates generally tend to emerge from CIS-acting determination factors (see Chapters 10 and 11). Raff (1996) has in fact argued that in allometry, relative growth of body parts seems to be a product of the functions of a large number of growth promoting substances, including circulating hormones that promote overall growth. Some hormones also have speciﬁc local effects, and others can stimulate production of local growth factors. Finally, many properties of growth actually arise autonomously in individual structures. Additionally, Bryant and Simpson (1984) have shown that differential growth is not necessarily due to differential growth rates, and might be related more to positional information in certain circumstances. Some expressions of developmental translation may of course be genuinely timing based, some rate based; many, however, will involve other, more complex modes of determinative activity. Changing developmental topology is thus polytropic—in that the same topology of change can often be ordered by n different input mechanisms (changes in the distribution of positional information, modulations to cell movement, adhesion, growth, and mitosis, effects of Newtonian morphogenetic factors, and so on; see Chapter 12). This rule is particularly exempliﬁed by certain manifestations of paramorphic transformation, since at the most basic level, even timing and rate change mutations may easily be confused inter se, acceleration–retardation and changed timing of activation of a gene set clearly having the capacity to create the same heterochronous effect as a result of two fundamentally different mechanisms (Fig. 93). Interpretations of heterochrony in relation to limb development have also been shown to be subject to very different developmental mechanisms: Hampe (1960) carried out experiments involving operations on the limb bud, inserting a barrier between the early chick tibia and ﬁbula. This resulted in an elongated ﬁbula resembling that of Archaeopteryx. Gould (1982) interpreted the latter as evidence of ‘‘heterochrony and induction,’’ but it clearly involves neither, since only detachment of part of the ﬁbula and its incorporation into the tibia is implicated (the transformation in question was actually a positional translation of the heterotopic kind). Wolpert (1982) has also stated that ‘‘what may appear to be heterochrony could be the result of a change in spatial organisation.’’ As stated by Raff (1996), phenotypic outcomes in general have often been confused with heterochronic mechanisms. Clearly some heterochronies are in

FIGURE 93

Heterochrony as the convergent effect of two mechanisms.

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fact timing-based, both for the phenotype and for underlying genetic mechanisms, while some are only so with respect to the former. Horder (1983) also criticized allometry and heterochrony interpretations that have been made on the basis of supposed ‘‘rate genes,’’ stating that it is unrealistic to think of single, organ-speciﬁc controllers of growth, and that the latter must be viewed as a complex balance between combinations of multiple positive and negative forces (following Harrison, 1969). Heterochronic approaches may thus often tend to be teleological in the way that Haeckel’s approach to development was: In this connection, Ambros and Horvitz (1984), studying the nematode C. elegans, found morphogenetic mutations with a genuine heterochronic function affecting timing of cell division, thus apparently conﬁrming the view that at least some developmental trajectories do in fact manifest a high level of autonomy and modularity, such as could permit authentic heterochronic transformation (see Chapter 12). Comparison of different nematode genera by Skiba and Schierenberg (1992) also uncovered heterochronies in terms of embryonic cell lineage. Raff (1996) argues that the evolutionary signiﬁcance of changes caused by mutations such as lin-14 of C. elegans will, however, depend on which aspect of the phenotype is the target of selection, which might not always be a heterochronic phenotype effect. Similarly, a ‘‘heterochronic result’’ does not in fact mean that a timing mechanism is involved at all, nor that selection was acting on any aspect of timing in the sense of underlying genetic events. Heterochrony can perhaps best be deﬁned according to phenotype effect (which, of course, will often be that aspect containing the active selection interface), and it would be better if that term were to be restricted to that domain (thus accepting the prospect of underlying developmental mechanisms being quite heterogeneous). Ideally, we now need to replace ‘‘acceleration/ retardation’’ with the view that changed timing and rate change are often interchangeable for a given topology, also accepting that other, more complex factors may also be involved. Acceleration is only one mechanism in heterochrony, and acceleration and temporal displacement may also not be alternatives, so much as combined mechanisms in some instances. It is nevertheless true that developmental dissociation between certain morphogenetic objects is an approximate reality for certain expressions of paramorphic change, and this is certainly highest for somatic versus germ lines (as shown by Gould with respect to progenesis). Some morphogenetic mechanisms therefore can be almost a linear function of mode of transformation. However, any attempt to invoke true developmental heterochrony as a general explanation of all apparent temporal translation is likely to meet with considerable difﬁculty. In this conclusion, we can see something in the nature of ‘‘attempting to simplify a complex situation, but verging dangerously close to oversimpliﬁcation’’! According to Raff (1996), the most signiﬁcant theoretical claim which can be made for heterochrony is that it represents a dissociation between events in ontogeny, namely, the selection of one developmental pathway over another:

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A good example is that of the axolotl, where neoteny has occurred via a single switch gene affecting thyroxin production. Gonadal maturation does not require this, hence it is dissociated in development (however, this is of course quite a different interpretation from that in which growth rates and/or timing are directly implicated). Raff 1996 also argues that local control of growth suggests that dissociations should be frequent in evolution. They are visible in mosaic evolution (see Chapter 21) and through changes in allometric relationships. Allometric Transformation, Gene Duplication, and Co-option The majority of ambient evolutionary changes in the morphogenetic domain appears neither to be saltational nor heterochronic in any real sense, but rather, to be based on extrapolations of preexisting form in the context of relatively simple allometric transformations of one kind or another. Most evolved major genes are substructural, but most loci affecting morphogenesis in the context of infraspeciﬁc variation are minor polygenes affecting allometric parameters. The inference is that structural evolution tends generally to be incremental, and that incremental change can probably be readily and rapidly extended along preferred parameters via gene ampliﬁcation or duplication (see also Chapter 14). Such mechanisms cannot simply be diagnosed as heterochrony or rate change, but may involve complex emergent properties arising from a wide range of fundamental growth patterns. Heterotopy and Gene Duplication As we have already seen, duplicational and reductional transformation are special case paramorphic translations of the heterotopic kind. Interestingly enough, evidence has appeared which suggests that this may have been linked to the duplication of certain high level regulatory genes of the Hox kind (see Chapters 12 and 14 regarding the question of saltation here). This level of morphogenetic evolution is clearly conﬁned to rare events surrounding the emergence of new higher group lineages: Slack et al. (1993) hold that Hox genes have been instrumental in originating the body plans of the phyla. This may be partly true in the sense that the adaptive potential of Hox genes probably lies in their capacity for duplication–specialization in the particular context of metamerism. Arthur (1997) also argues that the origin of body plans was associated with Hox gene duplication, although modiﬁcation of phylum level body plans may have had more to do with altered temporospatial expression, than with duplication (see Carroll et al., 1995). Averof and Akam (1995) viewed the crustacean 씮 hexapod transition as one determined particularly by restriction of Antp expression in the insect lineage. The above hypotheses seem to conﬁrm the view of Arthur (1997) that a few ontogenetic divergences in early evolution were more dramatic than any later ones. Further evidence for the inﬂuence of reduction has come also from atavism, as in the effect of the disruption of Hox-2 genes causal to partial transformation of the second pharyngeal arch into a copy of the

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ﬁrst in mouse embryos, coupled with the presence of a supernumerary, reptilelike cartilaginous structure resembling the pterygoquadrate cartilage (see Gilbert, 1997). Similarly, the larval prolegs of Lepidoptera, long thought to be nonhomologous with the ‘‘true’’ legs, are now known to be due to expression of the same gene (Distal-less) controlling development of the thoracic legs (Panganiban et al., 1994), thus invoking partial ‘‘atavistic’’ recovery (by partial duplicational transformation) of the early arthropodan state (albeit in a manner in no way reﬂecting the phylogeny of the arthropod classes!). Not all hypotheses concerning gene mutational events linked to the origin of higher group lineages can be taken at face value, however. Maynard Smith and Szathmary (1995) have pointed out a ﬂaw in some of the assumptions that have been made in the attempt to assess the role of certain genes in the diversiﬁcation of higher groups, in that the major Baupla¨ne of embryos must once have been functional adaptations to particular ways of life. From that standpoint, we must clearly guard against the supposition that developmental coordinates now under the control of upstream genes with large scale ontogenetic effects must have occupied the same determinative zone in remote ancestors, rather than having originally manifested a more downstream function. As concluded by Maynard-Smith and Szathmary, the genetic signaling system of animals may be more ancient, and more conservative, than the form it determines. Nevertheless, the above criticisms probably have less relevance to the duplication–reduction scenario than to most other aspects of developmental transformation. The question of duplication–reduction links again to that concerning modularity of developmental trajectories, and to the adaptive potential residing in repeated functionally uniform structures to develop viable avenues of diversiﬁcation through gene duplication in strategic regulators of epistatic systems. As we saw earlier (Chapter 12), the strategy of parts duplication may constitute a means of large step mutational change that does not incur a very high pleiotropic burden. However, even the existence of a high morphogenetic receptivity (Chapter 14) does not remove the many difﬁculties over a truly saltational view of duplication of homeotic genes (see Chapter 14).

MORPHOGENETIC TRANSFORMATION FACTORS AND THE QUESTION OF SUBOPTIMAL ADAPTIVE STATES The question of Darwinian (niche-driven) versus Thompsonian (structuredriven) transformation factors was explored in Chapter 15. To what extent do observed manifestations of morphogenetic transformation conﬁrm the ﬁndings of that analysis?

Directionality in the Adaptational Paradigm and the Question of Nonadaptivity Certain aspects within the wide heterogeny of mechanisms involved in morphogenetic transformation have been cited as evidence for nonadaptive and even

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maladaptive evolution, and various arguments have been raised to validate the apparent role of ‘‘structuralism’’ in this equation. Arguments of this kind have been by no means conﬁned to the recent structuralist literature: Rensch (1959) argued that ‘‘non-directedness’’ is apparent when all possible solutions to functional problems have seemingly been realized, citing types of horns in antelopes as ‘‘undirected evolution.’’ This argument is, however, much weakened by the author’s own admission that species recognition constitutes a likely function in this example! Rensch also argued that ‘‘all possible forms seem to have been tried’’ in (for example) marine isopods ‘‘without apparent purpose,’’ and he also described certain ‘‘grotesque’’ transformations as ‘‘tolerable byproducts of phylogenetic increases of body size.’’ Similarly, Gould and Lewontin’s argument (1979) for a titanothere horn size trend as an example of nonadaptive evolution is no more likely than any proposed adaptationist interpretation (as, for example, with regard to sexual selection). Coallometric transformation has in fact been used to promote a structuralist view of evolution since Thompson (1917) and Huxley (1932). The apparent pleiophoric corollary in coallometric transformation can be visualized following a simple model in which two adjacent morphogenetic trajectories (a, b) are growing at different rates (ax, by). In the event of increase in size via prolongation of growth, it is clear that the absolute size ratio between states an and bn at a given point during development must change as a corollary of the different growth equations operating in the two trajectories. Given some element of freedom in the biophysical paradigm, a train of adaptationally equivalent states for a and b might perhaps then be manifested. However, in the event of more dramatic change, it may also be that some element of maladaptivity will emerge, since there must clearly be only a limited range of adaptationally permissible a:b ratios. Nevertheless, it must also be appreciated that, in the longer term, selection will tend to favor change in the allometric equations in questions, so that in time there will be gravitation toward an altered adaptive paradigm. In this situation, we witness a reiteration also, of the selectional balance problem in relation to the complex isotropic selection interface (see Chapter 4) in that, in the present example, change in size can only be positively selected up until that point at which a negative corollary in some other phenon is encountered. The question of transience in trends of the above kind will be examined more closely in the next chapter. Further arguments have been raised concerning the supposed importance of nonadaptive evolution in heterochrony by Gould (1977): ‘‘Selection will often act primarily on the timing of development, leaving morphological consequences ‘free-ﬂoating’ and therefore especially available for incorporation into major evolutionary shifts. . . . If such co-optation of neutral and nonadaptive features often characterizes the origin of higher taxa and structural innovations, then an understanding of trends in unselected characters becomes especially important.’’

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To what extent does true pleiophorism actually enter the above scenarios, and how is this linked to the concept of the facultative adaptive differential introduced in Chapter 15? In apparent examples of nonadaptive evolution of the above kind, we may actually be witnessing some manifestation of the facultative adaptive differential (see Chapter 15), linked to the higher probability of occurrence of paramorphic transformation as against true neomorphy in certain selective environments (such as that, for example, of rapid adjustment in the face of drastic environmental change). As with the coallometric transformation scenario, it seems unlikely that any pleiophoric corollary in non- or maladaptivity surrounding the origin of higher groups could, in this manner, become part of a longer term ‘‘trend,’’ other than in the restricted sense of transition to an improved adaptive state (i.e., in much the same sense as the gradual loss of redundant structures occurs in the context of vestigiation). Strong evidence for the probable transience of the suboptimal adaptive state of paedomorphosis comes from the observation that many paedomorphs are not strictly heterochronic in the sense of reﬂecting discrete, independently shifting holistic modules of juvenile–adult structure: Reilly (1994) showed that certain ‘‘heterochronous’’ changes in salamanders are only partial transformations of the paedomorphic kind, also that some supposed ‘‘facultative paedomorphs’’ really only express phenotype plasticity. This view can be extended to encompass many of the well-known exemplars of paedomorphosis, in that paedomorphic adults are by no means exact replicas of ancestral juveniles, with respect to attributes other than time of gonadal maturation. Gould envisages progenesis as ‘‘one of the few processes that can accomplish a redirection of selection and lead to the unbinding of morphology.’’ However, the latter hypothesis now needs to be looked at in terms of a possible logistic component-led adaptive ensemble combined with a continued adaptation interface for juvenile structural traits which may sometimes lead to the generation of transient pleiophorism. One other remaining problem with the r-selection interpretation of paedomorphosis thus lies with the emphasis Gould places on the concept of ‘‘unbinding of morphology’’: Gould (1977) states, ‘‘Mechanisms for directional biasing are abundantly available in such themes as allometry and developmental channeling. . . . Heterochrony proclaims the plausibility and commonness, through speeding or slowing of developmental rates, of biases towards increasing juvenility or adultness of derived taxa.’’ Stated in this way, it is very easy to see the link between the ‘‘weak structuralist’’ view of heterochrony–allometry and the concept of the facultative adaptive differential. Huxley (1942) also believed that nonadaptivity (even maladaptivity) is widely perpetuated in diversity patterns. This view must also be balanced against the counterarguments that have been raised in favor of an adaptationist interpretation. Clearly, both allometry and heterochrony need to be rigorously reexamined in the light of the facultative adaptive differential concept. In all probability, the non- or maladaptive trends in question can be explained in

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the light of facultative adaptive differentiation via paramorphic transformation, in the sense that many of these traits may in fact be linked to the adaptive shift mechanism in that manner. In this sense, we should seek a broad relationship between Kauffman’s poised morphosystems concept, paramorphic transformation factors, and facultative adaptive divergence—in the context of a manifestation of transient suboptimal states, rather than as evidence for generation of predominantly non- or maladaptive diversity patterns that are permanently incorporated into higher level taxonomic hierarchies. As with the other paramorphic transformations, duplicational and reductional transformation likewise seem to have been important mechanisms of the same constraintive model of ‘‘reformed structuralism’’ at certain stages in evolutionary history, and again there seems no good reason to suppose that a large element of nonor maladaptive divergence is involved in this. Thus, while paramorphic transformations of the heterochrony or recapitulation kind seem to offer the most hopeful support for a ‘‘weak’’ structuralist interpretation of evolutionary events, this most probably constitutes a facultative adaptational differential that is in turn linked to a variable element of transient suboptimality. Where certain manifestations of recapitulation do appear to hold convincing evidence of a leading role for self-organizational factors in evolution, this seems only to be true in relation to the fabricational rather than adaptational paradigm, with little or no penetrance to the phenotype state in the majority of examples. The role of evolutionary constraints in the narrowing of degrees of freedom in adaptive potential thus appears to be the only structuralism-like element in the facultative adaptive differential factor (see Chapters 7 and 15).

Suboptimal States in the Context of the Adaptive Shift Given that there seems to be evidence in support of the persistence of suboptimality in such paramorphic transformations as progenesis and in certain other manifestations of heterochrony and allometric modulation, to what extent can the implied links with pleiophorism be applied to the adaptive shift concept? In reality, there are in fact two entirely different mechanisms by means of which suboptimal states could be originated and transiently perpetuated in adaptive systems. Pleiotropic balance has already been discussed as being one of these options. The other is that of multiple functionality deriving from the fact that an adaptive shift in behavior may change the adaptation interface with respect to some structure unit or integral (see Chapter 7). It naturally follows that acquisition of some new function will generally mean a change in the balance between different mechanisms linked to a single morphogenetic object. The difference between these two options is simply that, in the pleiophoric mechanism, new pleiophoric states are generated as a result of morphogenetic innovation, whereas with the second scenario, suboptimality is linked to changing balance between different functions manifested by a single structure unit or integral in the context of partial functional redundancy in certain (preexisting) structural parameters. Any attempt to resolve the above questions in the context of an allembracing theory must clearly also take into account the role of the facultative

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adaptive differential thought to be associated with many function shifts (see Chapter 15). Looked at in this light, the multiple functionality solution seems intrinsically more likely to be the usual explanation of suboptimality in natural adaptive systems, rather than that of perpetuated pleiotropism. We shall return to the question of suboptimality in the next chapter, in the context of the fate of the evolutionary lineage. For the present, it will be useful now to observe that two different models of the facultative adaptive shift exist so far as suboptimality is concerned: one is that centered around multiple functionality, the other concerning pleiophorism in the context of paramorphic mutation. The signiﬁcance of heterochrony and coallometric modulation may then frequently lie with the facultative adaptive differential hypothesis, thus identifying a deterministic rather than stochastic role for the leading effect directing these phenomena. In general, most evolutionary change is predominantly neomorphic, but paramorphy has special signiﬁcance in the context of incremental change, although this should not be seen as a recipe for nonadaptive diversiﬁcation. Most mutational change affecting morphogenesis probably lies in simple major allometric transformation, but the fact that diverse forms of ‘‘heterochrony’’ form the next most common aspect of evolutionary change in some lineages has led to much confusion and controversy over the supposed inﬂuence of a supposed nonadaptive or maladaptive element in evolution. As we have seen, the steps of incremental change may often lie in paramorphy. When neomorphic transformation toward a more distant structural paradigm is linked to iterated incremental change expressed in n structure units of one or more function integrals where paramorphic transformation involving heterochrony seems to have played a lead role in this, we frequently identify a further correlation with lineage senescence. In general, it seems very likely that the persistence of maladaptive states is much more widely expressed in the context of vestigiation than in paramorphic transformation linked to negative pleiotropy, despite the fact that the latter has been cited as evidence for a signiﬁcant non-Darwinian element in evolution by several authors.

Ontogeny and Recapitulation Not all heterochrony can be relegated to a diminished status within the concept of the facultative adaptive differential. It was argued above that endogenous Thompsonian factors seem likely to be manifested particularly at those horizons of development governed by the fabricational rather than adaptational paradigm, a syndrome that is perhaps most clearly conﬁrmed with respect to ontogenetic heterochrony of the recapitulation kind. Given that ontogenetic coordinates are often held to be the most rigid in development, how can it be that endogenous Thompsonian transformation factors can be claimed to be active in that domain? Quite apart from the fact that some major coordinates of early development clearly do show evolutionary plasticity at times, the likelihood also exists that many mutational changes to ontogenetic coordinates have actually occurred at some earlier stage in the evolution of a lineage, when the coordinates in question lay in the more labile ontophenogenetic interdigitation zone. The mechanism through which pheno-

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genetic coordinates can later become ontogenetic parameters must then lie with temporal translation of certain developmental coordinates and modules, in the greater context of morphogenetic accommodation. Before leaving the present topic and going on to examine the architecture of the phyletic lineage, we must also draw a wider overview of the signiﬁcance of the observed range of attainable morphogenetic transformations. It is clear that we have to conceive of a developmental system containing the adaptive potential, both to generate the entire range of ‘‘afﬁne/paramorphic’’ transformations discussed in the present chapter, and also to integrate these modulations into adaptationally viable neomorphic forms by means of anagenetic iteration. It can only have been in the aftermath of the assembly of a developmental system of this kind that the evolution of the observably vast range of form in multicellular organisms was actually able to take place.

MAIN POINTS FROM CHAPTER 16 1. Beginning with a root model of development, we can seek to analyze the topology of evolutionary change through the concepts of poised and adjacent morphosystems, examining an array of possible domains of action for scalar, positional, and temporal modes of morphogenetic transformation. From this standpoint, we can view realization of morphogenetic potential in terms of gravitation toward a structural attractor, in the context of the three principal biophysical paradigms of development. 2. The simplest morphogenetic transformations can be termed paramorphic, as against true neomorphic patterns of change. Paramorphic transformations constitute slight extrapolations of existing developmental coordinates and modularity, generally where developmental and selectional modularity are one and the same thing, whereas neomorphic mutation involves actual shape change. Paramorphy includes such ‘‘special case afﬁne morphotransformations’’ as prolongation–truncation, duplication–reduction, and eclosion line shift. Complex neomorphic change may occur in more than a single domain (scalar ⫹ positional ⫹ temporal). 3. In general, simple paramorphy is probably commonest in infraspeciﬁc and ambient speciational change, while neomorphy (especially of the complex kind) tends to be linked to the origins of new higher group lineages. Complex neomorphy is probably generally derived from iterative paramorphic change (notwithstanding the possibility that some higher groups may have originated through direct paramorphy, via paedomorphosis or duplication–reduction). 4. Observed morphogenetic transformations appear to ﬁt the predicted behavior of theoretical models, as described by classical allometry, heterochrony, recapitulation, duplicational transformation, and other simple extrapolations of ancestral form. 5. Certain classical modes of morphogenetic transformation actually constitute heterogeneous corollaries of more than one genetic and/or morphogenetic mechanism. In different manifestations of paedomorphosis, differentials tend to lie in different exogenous selectional regimes, whereas in peramorphosis

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sensu lato they may lie in separate onto- versus phenogenetic biophysical paradigms linking, respectively, to endogenous and external selection interface structures. 6. The ‘‘terminal addition’’ of classical authors must be viewed in terms of morphogenetic accommodation, which has a dynamic as well as static aspect. In this view, ‘‘recapitulation’’ is equivalent to ‘‘special case accommodation.’’ 7. Developmental modularity is fundamental to morphogenetic transformation. However, there are often polytropic developmental origins for modes of change observed at the phenotype level. Thus, while morphogenetic transformations can be readily mapped ‘‘in theory,’’ the phenotype map may tend to ﬁt the developmental only when there is analog as against digital programming of morphogenetic coordinates. Despite evidence for a direct link between mode of morphogenetic transformation and that of genetic mutation with respect to certain forms of heterochrony and heterotopy, many examples are nevertheless subject to diverse interpretations under the ‘‘polytropism law’’! 8. Heterochrony can only refer to the temporal placing of morphogenetic objects of the ﬁnal phenotype stage in relation to each other, with respect to the ancestral relationship. It need not mean ‘‘heterochronic mutations’’ in the sense of earlier or later ‘‘on’’ switching of genes, or of differential rates of growth. In fact, the phenotypic outcomes of truly heterochronic mutations need not actually manifest ‘‘heterochrony’’ at the phenotype level! 9. Duplication of Hox clusters may sometimes have been causal to rapid paramorphic duplicational transformations of phenotype form. However, the diagnostic traits of many higher group lineages clearly also include many iterative changes that must have occurred subsequent to such events, and most evolutionary change lies with mutation of regulatory genes lying lower in the epistatic hierarchy. 10. Certain paramorphic transformations are of special interest in the context of generation of pleiophoric suboptimal adaptive states. This mechanism is not, however, to be construed as constituting ‘‘normal evolutionary progress,’’ but may often tend to be linked to evolutionary senescence in the context of phenogenetic convergence between adult and juvenile stages. Apparent links between coallometric transformation and pleiophorism are much more difﬁcult to prove, unless adaptive function is objectively known. 11. The largest apparently ‘‘structuralist’’ element in morphogenetic transformation lies with the ontogenetic biophysical paradigm. However, this reﬂects the existence of an endogenous selection interface, rather than ‘‘maladaptive or nonadaptive evolution’’ or strict ‘‘self-organization.’’

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A phyletic lineage is formed by all descendants of a species. However, a major point of interest clearly lies with that class of lineage formed by a major (Renschian) cladogenetic event. The manner in which adaptive potential is realized in the context of the adaptive cascade discussed in Chapter 15 leads naturally to the question of how different mechanisms operating in this are differentially expressed throughout the trajectory of a lineage. How do the various regimes of morphogenetic transformation link to manifestation of evolutionary mode in general, and how is the latter subsequently expressed in the architecture of the lineage, as adaptive potential is realized in the context of both changing and static adaptation interface structures? Clearly, important questions must now be raised as to the relative signiﬁcance of pleiophorism and multiple functionality in view of the apparent existence of suboptimal adaptive states in anagenesis. Also, to what extent do anagenesis and cladogenesis represent independent mechanisms in the trajectory of a major phyletic lineage? The modus operandi for investigation of the above questions clearly differs quite dramatically from the neo-Darwinian method that was rooted in a special theory linked to the adaptive topography model of Wright. An understanding of the relationship between the Thompsonian view and that centered around contemporary developmental genetics in the context of adaptive systems theory is clearly crucial to resolution of outstanding problems.

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ADAPTIVE SHIFT AND ANAGENETIC SEQUENCE An understanding of the way in which a changing adaptive strategy affects initiation of novel anagenetic evolution clearly requires closer examination of the dynamics of the structure–niche link in the adaptive ensemble. In this, we must continue to explore the question of the adaptive shift, and also the facultative adaptive differential concept introduced in Chapter 15.

The Adaptive Shift It has already become evident that many structure integrals express multiple functions, thus manifesting more than a single adaptation interface, so that there must be some form of functional hierarchy among the latter. Clearly, this hierarchy can also change, and in addition, entirely new structure–niche links may also be established through the action of adaptive shifts, following qualitative change in the adaptation interface occurring through heritable change in the adaptive ensemble. The facultative adaptive differential (Chapter 15) was in fact deﬁned in terms of change in the niche interface corresponding to the broad concept of the adaptive shift, and we now need to look more closely into that cascade of events in evolutionary change which might be demanded in the aftermath of a qualitative adaptive shift: Eyes used in the terrestrial medium differ from those appropriate to aquatic functioning because of different refractive indices in air and water. The adaptive shift from an aquatic to a terrestrial environment must therefore have placed fresh demands on the longer term adaptive response in the earliest land dwelling organisms (Selden and Edwards, 1989). Gould (1990) raised the problem, ‘‘We have no term for the causal formation of an attribute for a reason other than its current utility. . . . Many exaptations (changes of function) occur within a level as a result of phyletic constraints, forced correlations, and developmental linkages.’’ Gould also stated that the key concept for such (reputedly) maladaptive trends is ‘‘hitchhiking’’ (pleiophorism). However, given the concept of the adaptive shift, there would seem to be no reason why an ‘‘exaptation’’ should pass through a maladaptive phase linked to pleiotropism affecting morphogenetic parameters. It is already clear that most components of adaptive capacity probably express more than a single function, and have thus passed through some adaptive shift or other in the past. That certain suboptimum states may be carried in this circumstance is self-evident. However, the principal source of maladaptivity in this will more likely center around partial functional redundancy and vestigiation with respect to certain traits that were linked to the preshift adaptive strategy. The past phylogenetic history of an adaptive shift does, of course, also inﬂuence degrees of freedom in adaptive potential, as indeed recognized by Gould: Selden and Edwards (1989) have drawn attention to the fact that the arachnid book lung is inefﬁcient, and would not have evolved directly

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in any group originating on land. This is an example of an adaptive shift which clearly imposes many restrictions on consequent evolutionary direction in an organ. However, this example clearly follows the multiple functionality explanation of suboptimality, rather than the pleiotropic. Continuing with the theme of the adaptive shift, it would seem that there must be certain changes which manifest a key role in redirecting evolution in a phyletic lineage. In the context of a major adaptive shift, parametric niche space may come to encompass not only some new limiting resource, but also the subparametric niche space of the resource in question (as, for example, when the parasitic wasp encountered in Chapter 2 comes to prey on a moth larva with a semiaquatic habit). A primary (i.e., ‘‘true’’) adaptive shift is said to occur when an entirely new niche interface is established, and this mode is clearly expressive of qualitative change in the adaptive ensemble, also having the potential to subsequently invoke generation of a new anagenetic sequence. Such changes are also likely to be linked to migration into new habitats (see Stebbins, 1988). A changing adaptation interface must therefore constitute one substrate for potential neomorphism in the adaptive response: Changing behavioral specialization has been decisively implicated as the driving force in the origination of many taxa, wherever the relationship between speciation patterns and adaptive niche has been examined closely. Classic examples include the geospizine ﬁnches (Lack, 1947) and African Great Lakes cichlid ﬁshes (see Greenwood, 1981). In the same way, the key features of many higher groups have been linked to changes in habit correlated with the adaptive niche. A primary adaptive shift may originate (and even be perpetuated) as a behavioral or metabolic trait. As a corollary of this, the adaptational paradigm for structure may also be altered, so that niche change is succeeded and complemented by neomorphic change in the structural component of the adaptive response, leading to the origin of novel directional parameters in anagenetic evolution. An adaptive shift can also be partial or ecliptic, according to the manner in which the functional hierarchy between different components of a structure integral subsequently changes. A partial adaptive shift merely adds to the existing complement of n functions (n ⫹ 1), whereas an ecliptic shift ultimately obliterates some original function. A pivotal adaptive shift occurs at that point in an anagenetic sequence at which the hierarchic balance in a structure integral manifesting multiple functionality changes in favor of the most recent primary adaptive shift (whether partial or ecliptic), such that the latter comes to form the leading effect in the selection interface. Primary and pivotal adaptive shifts are clearly of paramount importance in the evolution of the anagenetic sequence, as (for example) in the acquisition of adaptive capacity for ﬂight (Fig. 94). Simpson (1953) similarly described evolutionary ‘‘threshold effects’’ in which selection acting in a new direction comes to that point at which it

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FIGURE 94 Outline anagenetic sequence for origins of ﬂight, showing primary and pivotal adaptive shifts in the context of an ecliptic adaptive shift.

counteracts the old, and the link between Simpson’s ‘‘prospective adaptation’’ (Chapter 7) and this threshold effect clearly constitutes the pivotal adaptive shift proposed above: The threshold effect is exempliﬁed by the swim bladder of osteichthyan ﬁshes, in the context of prospective adaptation for lung breathing in the terrestrial environment. A similar exemplar comes from the modiﬁcation of part of the primitive vertebrate jaw to form the malleus and stapes of the inner ear, these separate functions having no doubt been homogeneous at one stage. In the same way, the jaw bones were originally gill supports in lower chordates. Givnish and Sytsma (1997) observed that the key innovation in the adaptive radiation of cichlids of the African Great Lakes lay in the pharyngeal jaw, freeing the outer jaw to specialize for particular prey. The division of function in terms of mechanical support and water conduction in tracheids is believed to have been a key factor in angiosperm evolution (Takhtajan, 1954).

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Realization of adaptive potential in a novel anagenetic sequence thus involves some qualitative change in the niche interface by virtue of a primary adaptive shift, a change which may ultimately invoke some complementary modiﬁcation in the structural component of the adaptive response. An adaptive shift must therefore correspond to some positively selected, qualitative change in the adaptive ensemble, which may be coincident with a cladogenetic event resolved in speciation, or with intraspeciﬁc change within the framework of anagenesis. An adaptive shift that is behavioral in origin will, of course, be undetectable in the fossil record, and ‘‘unprovable’’ (as the root of an anagenetic sequence) in the extant fauna: The moth larva Cosmia trapezina displays a carnivorous habit (as do a few other lepidopteran species), but with no apparent structural specialization in relation to this. There is, of course, no evidence that this will lead to any structural change such that a new higher order lineage could be founded in the future! However, other lineages of predatory insects display very many specializations linked to feeding behavior, all of which must have emerged from simple behavior shifts of this kind. Carroll (1997) discusses a similar example in the marine iguanid Amblyrhynchus, which inhabits an aquatic niche yet entirely lacks any structural or physiological specializations for this habit (following Dawson et al., 1977). The existence of a cryptic adaptive shift of the above kind is most likely to be traced through ‘‘evolutionary anachronism’’ in lineages for which a good fossil record exists (that is to say, there may be no means of placing extinct taxa in a lineage to which they belong, if their only modiﬁcation lies in a behavioral shift). All anagenetic sequences thus begin with a primary, and many also pass through a pivotal adaptive shift. However, the subsequent evolutionary behavior of a lineage clearly depends on whether the primary adaptive shift will become linked to adaptive potential facilitating a structural response. The pivotal adaptive shift is clearly of supreme importance in determining the course of anagenesis, whenever such circumstances permit. Before leaving the question of adaptive shifts, it is also important to realize that certain new traits may congeal from characteristics originating in two or more different function integrals, when a new function emerges (this may more often to be linked to sexual selection rather than to the origination of a complex anagenetic sequence). Evolutionary Anachronism and Threshold Events in Realization of Adaptive Potential There may obviously be a very long delay following a primary adaptive shift manifested solely in behavioral change before some positive mutation represents a complementary structural advance, a scenario that can be said to constitute evolutionary anachronism. This phase may also be followed by a large element of suboptimality in design: Thomas and Spicer (1986) have argued that lack of cuticle and stoma in the earliest land plants would have been linked to inefﬁciency in

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photosynthesis caused by gas diffusion, but that limited competition at this early phase would have allowed this situation to be tolerated. Following a long ‘‘waiting term,’’ an eventual modulation in the structural domain may in turn deﬁne a mode of morphogenetic change that can then be relatively easily expanded, for example, on the basis of gene duplication, or where concerted evolution by translational allotropism is implicated (see Chapter 12). Evolutionary anachronism is easily explained as a combination of degree of constraint presented by ‘‘paradigm distance’’ and degrees of freedom in adaptive potential (Chapter 7), and it may ultimately link with subsequent threshold events generating a rapid exploration of potential for further change: A specialized conducting system and extensive structural support only became desirable in plants after the adoption of a fully terrestrial mode of life, when acquisition of an erect habit would have been linked to advantage in distance dispersal in the context of exposure to higher wind energies (Thomas and Spicer, 1986). The phenomenon of evolutionary anachronism is thus linked to the complexity of the genetic system involved, including its state of canalization and degree of developmental modularity. In addition, there must also be some input from the activity of other retardation factors discussed in Chapter 14. Greater freedom of adaptive potential through the emergence of ‘‘vacant’’ and/or partially redundant morphospace may also be linked to threshold events, as appears to have been the case with major transformations of the vertebrate limb in the transgression between aquatic and terrestrial, and terrestrial and aerial environments (see Chapter 14). Adaptive shifts determine the adaptational paradigm and therefore also the selective environment into which poised morphosystems (see Chapter 15) enter, thus directing adaptive potential in a preferred orientation. The adaptive shift is therefore ‘‘the pivot around which the adaptive response must turn,’’ in order to manifest a selectionally positive neomorphic state. The Function Shift The term ‘‘adaptive shift,’’ as it has been used up until this point, clearly constitutes something of a heterogeny. A novel anagenetic sequence is initiated by a primary adaptive shift, which in turn must then be succeeded by a series of function shifts manifesting further topological change to structure within the same directional parameters as the structural attractor deﬁned by the primary adaptive shift. The adaptive shift sensu stricto is thus a qualitative change in which both a new adaptation interface and a new adaptational paradigm are established, whereas a function shift expresses only quantitative change relative to a preexisting niche interface, as function progresses toward the adaptive paradigm state.

Adaptive and Function Shifts in the Context of Niche Space As we have seen, a true adaptive shift constitutes a qualitative change in the niche, while a function shift involves only quantitative modulation within a

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deﬁned trajectory of anagenetic change. There are however, two ways in which a function shift may progress: • In 움 mode, by expansion or contraction in the context of real adaptive niche space (parametric, subparametric, or hypoparametric): the existing niche resource may come to be exploited in a wider spatial domain (or, alternatively, it could contract in the face of competition). • In 웁 mode, by expansion or contraction purely within the domain of niche hyperspace: Here, we shall adopt the terms intensiﬁcation and dilution in place of ‘‘expansion’’ and ‘‘contraction’’ (see below). Niche dilution is perhaps epitomized by functional redundancy or vestigiation (which may occur, not only in response to a changing external environment, but also as a cladogenetic response to competition). The dichotomy between an adaptive shift and a function shift can best be described by an idealized example (simplifying 3-space in two dimensions for the limiting resource and adopting the Z axis for expansion in niche hyperspace). The simpliﬁed model shown in Fig. 95 illustrates true niche expansion

FIGURE 95 An adaptive shift (top) can expand or contract in a qualitative manner in real niche space; a function shift (bottom) can do likewise in real niche space, or in the domain of niche hyperspace (Z,Y axes), in quantitative change only.

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and contraction in the X,Y domain and niche intensiﬁcation and dilution in the Z,Y. In this system, adaptation space is integrative over an evolutionary time frame, an important point of interest lying in the differential between the relative contributions of 움 and 웁 function shifts, comparing early with late anagenesis (see below). The axes of anagenetic change must of course lie in all dimensions. It can be shown that there are signiﬁcant links between mode of function shift and the nature of evolutionary activity in the structural adaptive response. The problem of the logistic component also raises important questions in the context of variable evolutionary rate that will have to be examined at a later stage (see next chapter).

Adaptive and Function Shifts in the Anagenetic Sequence Many minor adaptive shifts may occur during the evolution of a lineage, a majority perhaps being manifested in trivial allomorphic or amphigenetic trajectories of structural change, sometimes remaining entirely behavioral in nature. However, a primary adaptive shift may at times be causal to initiation of a new anagenetic pathway, and the pivotal adaptive shift will then be of special interest in the analysis of large scale anagenetic evolution. An anagenetic sequence is described by a series of adaptive and function shifts in the structural adaptive response, the latter acting to determine a characteristic topology, as realization of adaptive potential proceeds toward the adaptive paradigm state in the context of the isotropic selection interface. The anagenetic sequence is thus reﬂected in a train of iterative structural changes forming a topological link between preadaptive and adaptational paradigm states. The adaptive niche may thus expand with respect to any domain within the functional hierarchy of niche space (including function intensiﬁcation), as efﬁciency in exploitation of the niche resource increases and as structure moves toward the selectional attractor in a unidirectional manner. However, in the tangential model of binary resolution (see Chapter 6), where adaptational change tends toward a hostile niche, niche-expanding becomes niche-contract-

FIGURE 96 Trajectory of an anagenetic sequence, via niche-expanding or niche-intensifying adaptive and function shifts.

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ing and the function shift may also manifest ‘‘niche dilution’’ in the Z,Y domain, in a parallel manner. A general model incorporating all possible aspects of anagenetic change thus encompasses both of the above systems.

FIGURE 97 Niche contraction in the context of the anagenetic sequence.

Adaptive and Function Shifts in the Facultative Adaptive Differential In the above scenario, anagenetic progress does not continue on the basis of expansion of niche space alone, since design improvements will contribute also to the function intensiﬁcation dimension. Most signiﬁcantly, while the adaptive shift is clearly often behavior-led in origin, the alternative prospect of manifestation of structural adaptive response constitutes that medium through which a facultative adaptive differential (Chapter 15) may usually be manifested. It should also be understood that the contractional model is a valid adaptive response within the context of a tangential resolution of the cladogenetic selection interface.

ARCHITECTURE OF THE ANAGENETIC SEQUENCE We have seen that any given anagenetic sequence may express evolutionary activity in several dimensions: qualitative change (adaptive shifts) or else function shifts in either real or hyperspatial dimension. Also, the relative inﬂuence of the last two modes of change must be of particular signiﬁcance in contouring the behavior of the anagenetic sequence over time.

␣-Anagenesis and ␤-Anagenesis Function shifts associated with a long-term anagenetic sequence may include both niche-expanding and niche-intensiﬁcation activity. The former may tend to predominate during earlier anagenesis (since entry into a new adaptive niche must present the greatest capacity for increase in the limiting resource), the latter at later stages (since although the limiting resource is of ﬁnite volume, it may nevertheless be ‘‘penetrated more deeply’’ through improvements in the

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biophysical efﬁciency of existing behavior and structure systems). In the earlier 움-anagenetic stage, expansion in real space via 움 function shifts may thus tend to predominate, whereas in 웁-anagenesis, change within the domain of niche hyperspace will become progressively more signiﬁcant. The domain of 움-anagenesis is thus deﬁned as that phase during which changes in the adaptive state arising from 움 function shifts tend to be greater than those linked to increase in biophysical efﬁciency relative to an unchanging biophysical paradigm, and 웁-anagenesis is, accordingly, the reverse situation. Lineage senescence (see Chapter 16) is that phase in which niche-contracting adaptive shifts tend to predominate in the face of competition from other phyletic lineages.

␣-Anagenesis As we have just seen, 움-anagenesis is largely controlled by function shifts where expansion or contraction in the domain of real niche space predominates. It involves modulations linked to (particularly parametric) niche space via processive behavior (Chapter 2), being essentially nutrition seeking in nature and thus clearly associated with the criterion of biomass of the limiting resource. An example might be the adaptive shift between terrestrial and aquatic environments, simpliﬁed in the diagram shown in Fig. 98. As indicated, expan-

FIGURE 98 움-Anagenesis and 웁-anagenesis and the incidence of niche-expanding versus nicheintensifying function shifts.

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sion of fundamental parametric and sub- or hypoparametric niche space runs parallel with function intensiﬁcation in the domain of niche hyperspace, but the latter may tend to continue well beyond the end of the cascade of function shifts associated with expansion in real space (namely, during 웁-anagenesis).

␤-Anagenesis and the Extant Sequence 웁-Anagenesis is predominantly concerned with change in niche hyperspace, and thus may more often tend to be linked to hyperspatial expansion or contraction within sub- and hypoparametric niche space, being concerned with reﬁnement of existing adaptive strategy (as with optimization of orientation and search activity). It is very important to consider the likelihood that extant fragments of anagenetic sequences probably mainly reﬂect the activity of 웁-anagenesis, while true 움-anagenetic sequence fragments will generally have passed to extinction (see Chapter 20). The 웁 phase thus tends to be reﬂected in the extant representation of highly complex structure integrals which have taken a very long time to reach the adaptational paradigm state, and in which late modiﬁcations contribute relatively little to ﬁtness. In this latter situation, allomorphism and cladogenetic activity will usually tend to monopolize the adaptive state (see Chapters 14 and 18) and state-to-state differentials in anagenetic traits will now tend to be ‘‘trivial–incremental’’ in nature (rather than expressing the kind of radical restructuring events characteristic of 움-anagenesis): ‘‘Rationalization’’ in wing venation design in insects is manifested in long sequences of gradual change that are largely preserved in the extant fauna (as, for example, in the ditrysian Lepidoptera, Brock, 1971). However, the stages leading to evolution of wings themselves have passed to extinction. Observed temporal trends in the accumulation of iterative changes in anagenetic sequences generally seem to follow a rapid start followed by gradual tailing off, as exempliﬁed by the Westoll–Schaeffer data on the evolution of Dipnoi and coelacanth lineages (see Schaeffer, 1952). This no doubt reﬂects the dichotomy between the larger selectional gradients experienced during 움-anagenesis, as against the leveling out which occurs as the 웁 phase approaches the adaptive limit of an anagenetic sequence. Vestigiation and Ontoanagenesis A common feature of 웁-anagenesis is the occurrence of vestigiational trends resulting from functional redundancy in the wake of the primary shift of the lineage. The evolutionary corollary of this is that there will be a ‘‘retrogressional’’ trend toward atrophy and eventual loss with respect to certain structure units or integrals. The biophysical paradigm for vestigiation is clearly not a direct adaptational one, since it will involve such selectable gains as counteracting energy wastage. A vestigiational trend often follows a path of size reduction in a speciﬁc structure unit or integral, succeeded by eventual loss.

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Anagenesis may thus follow either an external adaptational paradigm or an internal fabricational one, and the latter is essentially ontoanagenesis (as against phenoanagenesis).

Anagenesis and the Directionalization Function The biophysical paradigm must become progressively more tightly constrained as anagenesis progresses from the 움 to the 웁 phase, therefore so, too, must adaptive potential and the structural attractor do likewise. Mutational change may also tend to become more directionalized, with realized adjacent morphosystems consequently having a greater probability of being adaptationally positive (i.e., assuming that at least some component involves duplication of existing genes in the evolving epistatic system in question). However, directionalization clearly cannot be linked to facilitation at gene level; rather, it must essentially constitute a narrowing of adaptive potential arising from degree of complexity as tangential divergence becomes a less likely option. This axiom must clearly also have a profound inﬂuence in determination of the direction of further anagenetic evolution, and this situation is obviously also linked to the facultative adaptive differential model. This directionalization function may be presumed to evolve early in 움-anagenesis, and (most signiﬁcantly) it may subsequently also form a signiﬁcant input to the probability of parallel evolution occurring during the 웁 phase. The principal components of directionalization thus reside in reciprocal activity between adaptive potential and the biophysical paradigm, leading to a progressive restriction of degrees of freedom in both, as a function of emergent complexity: That some form of directionalization function must be in operation is most clearly apparent in certain major transitions that are thought to have occurred in a remarkably short period of time, as (for example) in the mesonychid–cetacean transition (see next chapter). The directionalization function is thus a complex evolutionary corollary of several mechanisms emerging early on in the anagenetic sequence, part of which lies in ‘‘developmental constraints’’ (which should now be seen in this revised light, rather than as factors actually inhibiting evolutionary change). Transient and Perpetuated Suboptimal States in the Phyletic Lineage The question of suboptimality has been raised with respect to such factors as multiple functionality and partial functional redundancy, and a further explanation of course is that suboptimality is clearly also linked to coallometric modulation and heterochrony (see Chapters 15 and 16): Raff (1996) identiﬁes what he calls ‘‘nonrandom variational sources’’ in dissociation, duplication–divergence, and co-option, arguing that such factors arise from the modular organization of development. One view of the suboptimality witnessed in anagenesis is that any complement of morphogenetic pleiophorism might be expected to be removed somewhat slowly (presumably through changes in the modularity of interacting

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epistatic systems), so that maladaptive traits may become prominent features of diversity patterns. However, it should be predictable that suboptimality (whether through pleiophorism or partial redundancy in relation to an ecliptic adaptive shift) will in time be eradicated in the wake of gene duplication and other modes of rationalization in an evolving adaptive system, so that there is thus an inherent transience in any maladaptive corollary of evolutionary change. The only remaining question is obviously, how long is transient in evolutionary terms? The likely answer is that there will probably be limited ongoing iteration of an anagenetic sequence unless negative pleiotropism can be brought under control, given the inﬂuence of a pleiotropic impediment (Chapter 14). Pleiophorism therefore seems to be an inherently transient phenomenon (as well as being probably most manifest in the substructural domain). The situation with regard to multiple functionality is, however, rather different. Considering the generation of net gain and induced suboptimality in the context of a major adaptive shift, it is not possible to make a deﬁnitive choice between any of the structuralist models discussed earlier (Chapter 15) in terms of which best describes the trajectory of a ‘‘generalized’’ anagenetic sequence. The problem as to which factors determine the topology of morphogenetic change must clearly be resolved, not in a single static model, but in a dynamic one describing the tenets of the adaptive cascade as this applies to macroevolutionary anagenesis. The perpetuation of suboptimality will, as has already been argued, tend to manifest a built-in transience with respect both to pleiophorism and to an ecliptic adaptive shift. However, even the pleiophoric state might at times be of longer duration than ambient speciation time, thus making some real input to diversity patterns: Stanley (1998) discusses the example of the giant panda (Ailuropoda) studied by Davis (1964), in which particular skull and other traits appear to be pleiotropisms of certain mutations acting on hypertrophy of the head, with pleiophoric factors tending to restrict locomotion (a question here is of course whether these factors are truly maladaptive, or simply neutral in terms of the adaptive niche of the lineage in question). The trajectory of a long-term, complex macroevolutionary anagenetic sequence will, however, presumably remove any really signiﬁcant input from maladaptivity of the pleiophoric kind, a conclusion that is surely supported by the high incidence of convergence between unrelated phyletic lineages. Although parallelism is easily explained on the basis of conformity in preadaptive states and genetic systems for closely related lineages, convergence between remotely related lineages can really only be explained following the view that suboptimality is ultimately overcome in the course of an anagenetic sequence. A great many anagenetic sequences must therefore contain the capacity to bypass the many constraints inherent to adaptive potential in the longer term, rapidly for pleiophorism, and more slowly for partial functional redundancy linked to multiple functionality. Thus, where suboptimality persists over a very long time, this may often be linked to that mode of multiple functionality in which (a) combined functions are perpetuated in the context of a purely partial

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adaptive shift and (b) dual functionality is permanently detrimental to degrees of freedom in endogenous adaptive potential for one or both functions (as indeed reported, for example, with many aspects of plant form; see Niklas, 1988). The generation of suboptimal adaptive states should therefore tend to predominate in early (움-) anagenesis (as indeed seems to be the case), but the major coordinates of superstructure will subsequently graviate toward a tightly constrained adaptive paradigm in the longer term, with the exception of certain restricted categories of nonecliptic adaptive shift. Anagenesis thus does not generate trains of adaptationally equivalent or maladaptive states which form the basis of natural diversity patterns, but rather it follows a cascade of evolutionary events determined ultimately by the nature of the structural selectional attractor, thus emphasizing the interactive function acting between Darwinian and (endogenous) Thompsonian factors (see Chapter 15).* In the relationship shown in Fig. 99, we can see that a general law of optimization in organismic design holds that the state of optimization of a superstructure is a function of time lapse since occurrence of an adaptive shift and degree of both functional and developmental autonomy from other structure integrals. In a long-term dynamic model then, the adaptive cascade may tend to begin partially structure-driven owing to a facultative adaptive differential factor in the adaptive shift, but it also ultimately converges on a constrained adaptational paradigm state. Anagenesis must ﬁrst of all establish a set of major (‘‘rigid’’) coordinates, then it may proceed to slowly modify minor (‘‘labile’’) ones; it is the latter alone which manifest suboptimality. Owing partly to the dichotomy between rigid and free coordinates, and partly to the maxim that many structures fulﬁll more than a single function, most primary adaptive shifts are probably suboptima in purely biophysical terms, which is why complex anagenesis tends to manifest a protracted linear progression toward optimum form. It also follows that much ambient speciational activity may tend to add transient pleiotropic states to the trajectory of an evolutionary lineage, so that within any given time frame, some element of pleiophorism may well be evident in the species diversity pattern.

INTRASPECIFIC AND TRANSSPECIFIC MODELS OF ANAGENESIS Speciation and anagenesis have so far been discussed as independent entities in the generation of a phyletic lineage. However, it is clearly not possible to consider seriously the progress of anagenetic activity without simultaneously examining the role of speciation in this. Indeed, one of the greatest problems concerning the mechanism underlying evolutionary mode lies with the question, does an anagenetic sequence proceed through interspeciﬁc or intraspeciﬁc evolution? * It is, of course, not strictly true that the ‘‘ﬁnal adaptational paradigm’’ is determined at the start of the anagenetic sequence. However, certain major coordinates will clearly be implicated in the initial adaptational paradigm.

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FIGURE 99 A sequence of suboptimal adaptive states (arising from pleiophorism and/or functional change) gradually converges on the ‘‘true’’ structural attractor, so that any inﬂuence of pleiotropic balance or (more signiﬁcantly) of multiple functionality in perpetuating non- or maladaptivity is most strongly expressed near the origins of a lineage.

In attempting to answer the above question, we must ﬁrst of all ask, in what way might anagenetic progress be dependent on speciation events? (And conversely, to what extent could anagenesis be controlled purely by intraspeciﬁc evolution?) Does speciation necessarily precipitate anagenetic change or, indeed, is the former activated by the latter. In what ways might the incidence of speciation vary between 움- and 웁-anagenesis? Central to these problems is

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the fundamental question as to whether or not anagenesis and cladogenesis can be regarded as being totally independent mechanisms.

Is Speciation Necessary for Anagenesis to Occur? It is of course quite certain from observation that it is clearly not necessary for speciation to occur in order for selection to act on continuous variation in an iterative manner. Furthermore, species isolating mechanisms appear to be most readily favored in the role of an adaptive response to a negative hybrid genome (see Chapter 6), so that the usual causalities of speciation do not seem to indicate any necessary inﬂuence coming from anagenesis. Similarly, where anagenetic forces are in operation, we can assume that very high levels of niche intersect appertain to the intraspeciﬁc situation, seemingly with little or no cladogenetic potential in the adaptive niche that could facilitate speciation, at least in the sympatric domain. However, at the same time it must surely be totally unrealistic to envisage any longer term anagenetic sequence of the macroevolutionary kind occurring in the absence of concurrent ‘‘punctuation’’ by, and consequent inﬂuence from, major cladogenetic forces—especially considering the likelihood of hybrid depression arising from anagenetic change in different components of the gene reservoir, where allopatric divergence has occurred. The question now becomes, under what conditions does cladogenetic potential arise, such that anagenetic change is punctuated by speciation? To explore the above questions further, it is ﬁrst of all necessary to compare and contrast cladogenetic with anagenetic selectional forces, underlining the fact that the differential between these resides in the architecture of the selection interface itself. In this, we shall see that gene pool isolation is not a necessary requirement for anagenesis, since the anagenetic selection interface is fundamentally different from that of cladogenesis. The cladogenetic selection interface relates to gene pools diverging in allopatric populations (with two at least partially independent adaptive niche domains, K1 and K2), and also to the viability component of the adaptive state for the hybrid class (see Chapter 6). However, in the anagenetic selection interface, niche K2 may simply constitute a subset of K1 (for example, a poor ﬂier occupies some subset of the same niche space as a good ﬂier), and an anagenetic sequence is essentially the iterative condition for the latter scenario. Consequently, unary resolution of antagonistic selectional forces (one genotype eliminated:one surviving) rather than genome splitting or cladogenetic substitution must frequently constitute a likely mode of advance for anagenesis. In contrast, in the cladogenetic model the hybrid class tends to be negative owing to developmental viability creating cladogenetic drive tending to favor genome splitting. A cladogenetic selection interface also assumes that the adaptive niche would have some independent, ‘‘unshared K’’ component, whereas with anagenesis, K2 is as we have already seen, simply to be a subset of K1. However, the manner in which either clado- or anagenesis may express apparent unary resolution may clearly lead to difﬁculty in interpretation. This can be examined with reference to the simplest situation, where a single allelic pair is undergoing cladogenetic, as against anagenetic evolution (Fig. 100).

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FIGURE 100 Cladogenetic selection interface (left) has unshared K in the mutant genotype (equivalent to Kaa), also some KAA not available to the mutant phenotype. In the anagenetic selection interface (right), Kaa is simply a subset of KAA.

With anagenesis, there is iterative expansion of the domain of Kaa, generating no conﬂict in the selection interface such as could give rise to a cladogenetic force capable of binary resolution in speciation. The positively selected mutant state simply corresponds to a superset of the parent one, so that the fate of the latter may (given a high selectional differential) be that of elimination. We thus assume that ‘‘a’’ may tend toward elimination in the anagenetic model, with ﬁxation of A and loss of a in the context of unary resolution (outcome 1:0). This is quite different from the 1:0 binary resolution scenario of species substitution (see Chapter 6 and below). The essential aspects of the differential between ana- and cladogenetic selection interface structures can be summarized as shown in Fig. 101. Thus, not only does anagenesis differ with respect to selectional balance in the selection interface, but it can be further deﬁned as holding adaptive potential for iterative linear change in the phenotype by virtue of its relationship with a unipartite and distant biophysical paradigm in the structural attractor. These differentials between cladogenetic and anagenetic potential help in understanding both separate and interactive roles of cladogenesis and anagenesis in macroevolutionary change, although this is, however, insufﬁcient to completely distinguish between anagenetic and cladogenetic ‘‘substitution’’ (see below). Anagenesis, Species Substitution, and Phyletic Occlusion Major cladogenesis obviously proceeds by speciation (see Chapter 6). What mechanism similarly underlies anagenesis?

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FIGURE 101 Differentials between cladogenetic and anagenetic selection interfaces.

As we have seen above, anagenesis concerns niche expansion where the domain of the newly evolving adaptive niche is generally a superset of the original niche. If in a similar context, all genotypes of an iterative sequence are perpetuated in time, we then have a simple expansion of variance manifested in labile change in the domain of continuous variation. However, with true anagenesis there is also an element of apparent genomic substitution, so that only one or a few terminal states tend actually to be perpetuated as the anagenetic sequence proceeds, owing to the existence of a steep selection gradient between different members of the iterative sequence:

FIGURE 102 Phyletic occlusion: earlier genotypic states in an anagenetic sequence tend to pass to extinction as the adaptive niche expands (⫻ ⫽ occlusion of genotype complementary to subset niche volume).

The sequence of apparent iterated genomic substitution in which progressive morphogenetic transformation tends toward a static biophysical paradigm state constitutes that mechanism that we have already termed phyletic occlusion (see Chapter 12). Thus, as speciation is the mechanism of major cladogenesis, so too phyletic occlusion is that of anagenesis. Phyletic occlusion can now be futher construed as constituting ‘‘pseudo-extinction’’ as a speciﬁc corollary of anagenesis itself (see Chapter 20), owing to iterative genic occlusion in the epistatic system of a single developmental object linked to a static biophysical paradigm (see Chapter 12).

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The occlusional scenario of anagenesis further clariﬁes the differential between unary resolution in anagenesis and cladogenetic substitution (Chapter 12), and this can be seen to be linked to the greater paradigm distance appertaining to a complex anagenetic selectional attractor (which clearly must tend to invoke an iterative pattern of change following the occlusionary model). Other differentials between phyletic occlusion and cladogenetic substitution also need to be taken into account, especially considering the fact that hybrid depression may be a factor in either the clado- or anagenetic selection interface. It should be apparent that with cladogenetic substitution, two species may be coincident with respect to isotropic niche parameters yet differ in the anisotropic component of the total niche interface. However, there can in contrast be no leading effect anisotropic element in the selection interface of anagenesis. One substitutional species may also be superior on the basis of a eurytropic niche interface, only part of which is coincident with the adaptive niche of a second (stenotropic) species. In the latter scenario, elimination of one emergent species can again be seen to be linked to a cladogenetic, rather than anagenetic selection interface. The Isopatric Selection Interface and Phyletic Occlusion Under what conditions does anagenesis lead to phyletic occlusion, as distinct from mere expansion of variance? We must now examine a selection interface structure likely to be generated by anagenesis, one that is also conducive to expression of phyletic occlusion. Each term along an anagenetic sequence can be assumed to have a certain ﬁtness differential relative to each precedent term in the sequence. Hypothetically, we may now envisage several terms in some sector of an anagenetic sequence as being sympatric within a given time frame, in that situation where n phenotype states representing successive increments toward an adaptive paradigm are held in a single isopatric selection interface (in reality, that segment of the anagenetic sequence in which sympatry for n contemporaneous increments is at least a probability). This structure can be shown to contain an isopatric selection gradient between members of the set (namely, in the event of actual sympatry being realized). In this mechanism, we also witness a highly signiﬁcant corollary of the duplication, divergence, and co-option scenario discussed in Chapter 12, in that steep selection gradients are very likely to evolve between initial suboptima and anagenetically transformed states in that situation. In the foregoing scenario, we may consider that the selectional differential between a0 and aj states in an isopatric selection interface contains a capacity to affect the probability of infraspeciﬁc genomic substitution, particularly for adaptive states that are topologically well separated in the iterated sequence. We are thus now looking at the selectional differentials between contemporaneous anagenetic states, in their potential to undergo mutual competitional activity through dispersal movement into a sympatric state. In the absence of any cladogenetic potential, anagenetic change thus clearly possesses an intrinsic capacity for iterative, incremental buildup of large selection differentials be-

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tween genotypes of a gene reservoir, particularly during the 움 phase, where an intrinsically steep selection gradient is most likely to exist. This situation can be illustrated by a (completely artiﬁcial!) curve in which ﬁtness between a0 and aj terms in an anagenetic sequence is increasing and rate of increase diminishing as a function of time (as would be expected, given the inability of function shift to continue to expand the niche at the same rate indeﬁnitely in the face of a ﬁnite limit to adaptive potential). Provisionally using a much simpliﬁed logistic system, dW/dt ⫽ r ⫻ W ⫻ (1 ⫺ W ) where W ⫽ ﬁtness and r ⫽ average increase in ﬁtness per anagenetic increment. Initial ﬁtness W0 is initially determined relative to an optimum state (Wj), the latter being equal to 1.0. The main artiﬁciality is that anagenetic increments are equally spaced in time. In the present context, we shall merely be examining any portion of such a curve in which the increase of Wj relative to W0 is tailing off in the gradual approach toward the adaptive limit at Wj ⫽ 1.0 (the entire curve constituting the intrinsic selection gradient of anagenesis; see pp. 425–426).* The probability of phyletic occlusion (P0) of any term (An) in this sequence is clearly a function of the ﬁtness differential between isopatric terms in the iterated sequence. In other words, P0 is some function of

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t⫽j

t⫽n

dW/dt

where n and j are the furthest separated isopatric states in the chosen curve sector. To understand how phyletic occlusion is invoked in the context of the isopatric selection interface, it is useful to compare the An term with a nearby Aj state, as against a more ‘‘distant’’ term (such as A0) in the same sequence. Clearly, the selectional differential between A0 and An states is much more likely to invoke phyletic occlusion of A0, than that between An and Aj is with respect to An, given realization of sympatry between these terms, since the accumulated selectional differentials are widely different. The probability of phyletic occlusion is clearly also highest in the zone of high selection gradients (to left in the curve in Fig. 103), while smaller increments to ﬁtness would more likely be reﬂected in a simple increase in variance (i.e., toward the righthand side of Fig. 103). Stemming from the question of phyletic occlusion occurring in the above manner, two further areas of interest now need to be examined: 1. The possibility of chronopatric speciation occurring via lineage anagenesis 2. The effect of any cladogenetic potential which might develop within the framework of the same gene pool carrying the anagenetic selection interface * It should be understood that the adaptive state tends to 1.0 at any point for any extant member in the isopatric selection interface (i.e., when lying in the same time horizon, but in sequestered allopatric gene pools), whereas relative adaptive states (equivalent to W ) become ⬍1.0 for sympatric members.

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FIGURE 103 Fitness differentials between A0, An, and Aj states in an isopatric selection interface for an anagenetic sequence (freehand curve).

Chronopatric Speciation Phyletic speciation (sensu Simpson, 1953) describes that situation whereby genomic change incurred in a lineage could with time be considered in hypothesis at least to have established speciation by virtue of degree of change with respect to the ancestral genome. Simpson’s view of phyletic speciation was, however, clearly typological, unless we consider the evolution of species isolating mechanisms as constituting an integral part of this process: Simpson (1944, 1953) regarded the question of the criterion of reproductive isolation as applied to noncontemporaneous species as a ‘‘pseudoproblem,’’ considering that (for practical purposes), species succeeding each other in time should simply be deﬁned according to degree of difference observed in extant related taxa. The concept of chronopatric speciation, as deﬁned here, encompasses Simpsonian phyletic speciation but also demands reproductive isolation, which latter could occur either via the recognition model or through some other mode of prezygotic isolation.* Chronopatric speciation thus includes the possibility that a lineage may have actively changed, not only with respect to genome architecture and outward form, but also in prezygotic species isolating mechanisms. The Paterson speciﬁc mate recognition system hypothesis (Chapter 6) constitutes an ‘‘active’’ model for prezygotic isolation, while the ‘‘passive’’ one includes nonreproductive behavioral changes, the corollary of which tend also to preclude mating encounters, physical barriers to reproduction, and so on. * Postzygotic isolation mechanisms (including chromosomal models) do not in fact constitute speciation, quite irrespective of their facility for increasing cladogenetic drive (see Chapter 6).

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The difference between chronopatric and recognition models of ‘‘autospeciation’’ is that there is no necessary allopatric aspect to the former, and additional passive elements to prezygotic isolation are also incorporated. Chronopatric speciation is thus clearly linked to sympatric speciation (from which it differs in incorporating an essential temporal dimension). It is important also to realize that many elements that could form part of a more typological view of phyletic speciation are also encompassed by the chronopatric model: Both phyletic speciation and the chronopatric model could in fact be postulated for certain ‘‘phylospecies’’ observed in fossil lineages. However, there is obviously a great practical difﬁculty with the problem of making value judgments concerning the presence or absence of reproductive isolation in such circumstances! Either approach might be applied to the data of Sheldon (1987) on the continuous evolution of trilobite lineages, where several unbroken anagenetic sequences (recognized by systematists as comprising more than a single species, and even two separate genera in one case) show no evidence of cladogenetic activity. However, such examples cannot be tested for loss of gene ﬂow at any point, and it will probably be impossible to decide at which point (if any!) reproductive isolation (passive or active), could be presumed to have taken place in these circumstances. No a priori reason actually exists that would deny the possibility that speciation could in fact occur when the genome has changed to the extent that reproduction is ‘‘passively’’ precluded by one mechanism or another. However, the probability that passive phyletic speciation will frequently occur must also be weighed against evidence that widely divergent gene pools do in fact very often retain the capacity for hybridization, suggesting that ﬁnal species isolation is probably more frequently evolved on the basis of the reinforcement model (see Chapter 6). A further danger clearly exists in the supposition that the degree of change required for speciation to occur can only happen in peripherally isolated populations, since even a ‘‘peripheral’’ population must be speciating with respect to its own founding population! The confusion here is that, in adopting the term peripheral, we are actually referring to a condition under which the substrate of evolutionary change may develop, rather then identifying a single step speciational event that was somehow instantaneously invoked in the founding population in the context of geographic isolation. Simpsonian phyletic speciation is no doubt often a confusion with the early paleontological deﬁnition of ‘‘species’’ when applied in practice, and there will also be a danger in making value judgments regarding the chronopatric model on the basis of fossil evidence alone. Although chronopatric speciation might indeed occur as a corollary of anagenesis, the question of buildup of a cladogenetic selection interface must be more important, since it seems unlikely that divergence in prezygotic isolation mechanisms could be invoked on the basis of anagenesis in the absence of some element of bidirectional change in the adaptive niche. It may usually be more realistic to ask whether there has been opportunity for tangential cladogenesis in an anagenetic sequence, and not ‘‘how long can a series of

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iterative anagenetic increments become before a chronopatric speciation event occurs?’’ The above questions clearly need to be restructured within the context of the structure of the gene reservoir: how much anagenetic change can occur in a gene pool before there is neosympatry in the gene reservoir, and before capacity for normal binary resolution in cladogenesis is evolved? In attempting to answer these questions, we must not confuse the issue (as Simpson and others have done) by assuming that anagenesis is simply equivalent to ‘‘phyletic speciation.’’ From the viewpoint of the isopatric selection gradient, it would appear that there must indeed be conditions under which rate of phyletic occlusion is simply much greater than that of buildup of cladogenetic potential, namely, by virtue of steepness of the intrinsic selection gradient. Phyletic occlusion thus has the potential to create the highest possible evolutionary rate, owing to the latter being a function of the size of the niche interesect (which will here approach 1.0), and also since differentials in eurytopy and anisotropic niche parameters probably implicate a much slower rate of elimination for the species substitution option. In contrast, speciation results from a smaller niche intersect, usually given also a much larger negative developmental viability in the hybrid genome, plus the existence of extrinsic cladogenetic potential in the form of free adjacent niche space. Hence, an anagenetic sequence may possess the capacity to evolve at a rate far greater than that for ambient speciation without encountering any signiﬁcant element of cladogenetic potential, owing to the differential between relative ﬁtness values over an iterated sequence giving rise to rapid anagenetic change within a smaller time frame than that required by allopatric evolution of cladogenetic potential. This scenario favors the intraspeciﬁc model, at least for earlier (움-) anagenesis, without in any way precluding ‘‘punctuation’’ by speciation or cladogenetic substitution when greater tangential cladogenetic forces do appear: Simpson (1953) observed that the high rate of change in paracone height in the dentition of the fossil horse genus Merychippus was not linked to high intraspeciﬁc variation, a situation which would exactly ﬁt the concept of a 1:0 output in unary resolution, as postulated above for a steep gradient in the anagenetic selection interface. It follows that 움-anagenesis must manifest the highest rates of phyletic occlusion and cladogenetic substitution. During 웁-anagenesis, when the leading factor will tend to lie more with parameters of adaptive equilibrium, the above rulings will clearly not apply (see Chapter 19), since there will by then presumably have been more time for buildup of cladogenetic potential in the gene reservoir in the face of a much diminished selection gradient in the anagenetic sector.

Anagenesis, Speciation, and Selection Gradients Given that anagenesis and speciation relate to independent selection interface structures (and placing aside the question of chronopatric speciation), what

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happens when both anagenetic and cladogenetic potential are actually present? There must be certain conditions here under which either anagenesis or speciation will tend to predominate. Clearly, speciational ‘‘punctuation’’ of anagenesis will not occur until there is enough cladogenetic potential for this to happen. As we have already seen, anagenesis itself has no intrinsic capacity for cladogenesis. We must therefore consider the existence of a joint ana- and cladogenetic interface in order to see which mode will tend to predominate, and the outcome here will obviously depend on the balance between forces favoring anagenesis as against cladogenesis. If cladogenetic potential is small in this scenario and the ﬁtness increment is higher for anagenesis, the former may simply tend to be lost altogether. That is to say, if cladogenetic drive is associated with earlier anagenetic states which pass to phyletic occlusion before cladogenetic potential has had time to expand, some elements of cladogenetic potential may simply be carried to extinction along with the occluded anagenetic states. Conversely, when an anagenetic trait has a low contribution to ﬁtness relative to some tangential cladogenetic factor, anagenetic rate will be lowered and its selection interface will thus tend either to disappear altogether or (more probably) to transcend the speciation event in question, thereby continuing in parallel over n subsequent speciations. Thus, when the ﬁtness increment is highest for cladogenesis, ‘‘anagenesis may hitchhike to parallelism’’:

FIGURE 104 Joint cladoanagenetic selection interface, showing an anagenetic sequence ultimately bifurcating as cladogenetic potential is realized.

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No reason exists which could possibly preclude the continuation of an anagenetic selection interface following speciation, any more than one could say that a polymorphic locus could not retain its survival value following a speciation event, as indeed is known frequently to be the case. The polymorphisms of three species of Maniola butterﬂies are similar, and the polymorphic locus controlling shell color patterning in Cepaea nemoralis snails is found in other species also. There is no intrinsic reason why an anagenetic selection interface should not behave in the same manner. The Intrinsic Selection Gradient of Anagenesis and the Anagenetic Integral Curve Under what conditions would anagenesis actually present such a high selection pressure, so as to predominate over speciation in the manner described above? To answer this question, it is ﬁrst of all necessary to brieﬂy examine the links between opportunity for speciation and the high rates of change that have been postulated for anagenetic change in the aftermath of a major adaptive shift. We can investigate this problem in relation to the W gradient which apparently exists between 움- and 웁-anagenesis, as implicated in evolutionary rate curves. As we have already seen, the W increment will clearly be highest during 움- and lowest with 웁-anagenesis. What evidence exists for the supposedly steep selection gradient between 움- and 웁-anagenesis? Simpson (1953) held that in anagenetic evolution, ‘‘rate of change should be higher the farther from the optimum, should decrease as the optimum is approached—then drop to zero when the latter is reached.’’ He also stated, ‘‘The direction of selection should be continually towards the optimum . . . and its intensity should vary with distance from the optimum.’’ Simpson illustrated the above concept, modifying the data of Westoll (1949) to reﬂect anagenetic increments rather than evolutionary rate, for patterns of gradistic change in the evolution of lungﬁshes relating to skull proportions, nature of dermal bones, dentition, ﬁn morphology, etc. These data were supplemented by Schaeffer (1952), who compared Westoll’s data with his own concerning the coelacanth lineage. Both lineages evolved rapidly during an earlier phase, but evolutionary rates gradually tailed off and relative stasis prevailed over a long period of time. Long (in McNamara, 1990) reasoned that one of the major factors guiding lungﬁsh evolution was the changeover (adaptive shift) from marine to freshwater habitats between the early and middle Devonian. Anatomical changes during the period are apparently linked to this transition, particularly in relation to acquisition of air breathing, and this in turn was apparently linked to climatic variations experienced in the new freshwater habitat. The circumstance of high evolutionary rate linked to a major adaptive shift is also seen in the transition over only 3 million years between obligate terrestrial and fully aquatic forms in the mosasaur

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lineage, where 63 character transformations occurred, against a total of 153 over the entire 23 My existence of this clade (Caroll, 1997). The lungﬁsh example clearly follows a suite of structure integrals acting in consort as a function integral (Chapter 7), and it is interesting that the Westoll– Schaeffer all-characters gradistic analyses nevertheless approximate to the kind of curve one might expect from the point of view of the predicted selection gradient suggested by Simpson, namely, for a compound rather than ‘‘unit’’ anagenetic sequence. Fenster and Sorhannus (1991) reexamined the Westoll–Schaeffer data, making several criticisms of the way interpretation had been imposed in the past, so that one can really only accept the broad trend of ‘‘anachronism’’ followed by rapid change, then deceleration (rather than actual calculated rates) for the data in question (nevertheless, it is also pertinent to point out that the Westoll– Schaeffer approach still retains a greater degree of robustness, in that taxonomic and phylogenetic criteria were explicitly excluded). Following Simpson’s somewhat intuitive exposition, we can now postulate how the rate at which evolutionary increments reach phyletic occlusion varies, on the basis of a temporal selection gradient intrinsic to anagenesis itself. In reality, or course, observed curves are unlikely to be anything more than approximate probability distributions, and there may be more than one form that such a curve may actually take: Hayami (1978) proposed that where selection acts to limit body size, the evolutionary rate trend should be sigmoidal, while MacFadden’s (1988) trend for mesostyle crown height in evolution of the horse was apparently exponential. The simplest selection gradient model is based on the assumption that the quantitative trend is linked to distance from adaptive limit, as anagenesis proceeds and as opportunity for expansion presumably diminishes, carrying a gradual decrease between the 움 and 웁 phases of anagenesis as niche-expanding adaptive shifts are gradually replaced by progressively smaller function shifts. This model is simply an extension of that introduced earlier in the context of the isopatric gradient in anagenesis, now viewed as constituting part of a greater whole, in which latter we encounter a gradual approach to an asymptotic value close to the adaptive paradigm state. The intrinsic selection gradient of anagenesis (see p. 420) is thus a projection of the isopatric gradient over the time course of an entire anagenetic sequence, from A0 (primary node) to Aj (⫽ adaptive limit) states, and assuming an approximately sigmoidal relationship. It is further necessary to discriminate clearly between the evolutionary rate curve for an anagenetic sequence (which can only be a declining dW trend, as portrayed by the Westoll–Schaeffer data; see p. 411) and the anagenetic integral curve. Assuming ideally that each dW step is equivalent to gene ﬁxation of an anagenetic increment, then the graph of 兰 W forms the anagenetic integral curve (Fig. 105). The curve shown is, of course, an artifact. A logistic integral curve would clearly be an ‘‘orthogenetic’’ rather than an anagenetic one, since adaptive potential cannot possibly be presumed to emerge ‘‘to order,’’ either by way of equal steps in increase in ﬁtness, or with time. This ‘‘orthogenetic selection

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FIGURE 105 The anagenetic integral curve (‘‘freehand’’). Addition of fresh incremental steps decreases toward an adaptive limit at the end of 웁-anagenesis.

gradient,’’ however, constitutes a useful ‘‘straw man hypothesis’’ with which to examine the greater reality of the anagenetic integral curve itself, and the ﬁrst step in linking the orthogenetic gradient to an anagenetic one is to consider that the latter could be considered as forming a probability distribution around the former. Thus, true step sizes or widths have been artiﬁcially ‘‘calibrated’’ in the orthogenetic curve. In the anagenetic integral curve, basal increments will be more linked to adaptive shifts (and thus to higher intrinsic W differentials), whereas later values will tend to constitute function shifts with lower intrinsic capacity for large selectional differentials. The general trend of such a curve remains approximately logistic. However, the adaptive limit will generally tend to be a state of dynamic equilibrium rather than a stable state, given the inﬂuence of such factors as the dimension spectrum of the selectional attractor (see Chapter 7). The curve shown in Fig. 105 can be compared with the Hayami, McFadden, and Simpson–Westoll–Schaeffer examples (the last two of which could obviously form subsets of the complete logistic curve). The present point of interest is of course that the anagenetic selection gradient curve identiﬁes a ﬁtness differential between different phases of anagenesis, which is of special relevance concerning the probability of the occurrence of speciation or species substitution as against anagenetic occlusion. How is the curve actually related to the degree of selection acting in favor of anagenetic as against cladogenetic change? Clearly, the slope gives the speciﬁc intrinsic selection gradient of anagenesis, and anagenesis will tend to predominate over speciation in the steeper, earlier part (움 phase) of the selection gradient curve (namely, where dW/dt is greatest). Accordingly, the opposite trend will occur in the later (웁 phase) component, since as the selection gradient diminishes, there is a greater probability that cladogenetic potential will evolve to higher levels. It is important to see that the raw anagenetic integral curve quite artiﬁcially excludes consideration of contributions to ﬁtness of any other component of the genome. However, this need not detract from the essential object lesson

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at this stage, which is that the greater proportion of observed anagenesis lies in the distal region of the curve, while the steep end of the gradient belongs to the usual ‘‘basal gap’’ observed in most higher group lineages. In addition (and most signiﬁcantly of all), the balance of anagenetic and cladogenetic inﬂuence is differentially distributed according to the topology of the intrinsic selection gradient. Further uses for the raw anagenetic integral curve can be found in provision of a framework for discussion of those factors tending to depress the rate of change in real adaptive systems. It will be shown that there are two main factors acting to lower the intrinsic selection gradient of anagenesis, the ﬁrst emerging as a function of ingress from adaptive equilibrium, the second being due to stochastic inﬂuences arising in the external environment (see next chapter). Allopatric Speciation and Minor and Major Phyletic Occlusion The phenomenon of phyletic occlusion now requires closer examination, especially in view of factors evolving in the allopatric scenario. Clearly, not all anagenetic change will actually be sympatric. Some must be occurring in independent spatial domains, and the anagenetic selection interface will in fact therefore behave differently, according to whether or not capacity for reproductive isolation has evolved in allopatric gene pools. Phyletic occlusion can therefore happen in either of two ways: • With gene ﬂow: minor phyletic occlusion via infraspeciﬁc competition • Without gene ﬂow: major phyletic occlusion via transspeciﬁc competition This dichotomy can be illustrated as shown in Fig. 106. Minor phyletic occlusion thus constitutes that situation where allopatric differentiation of the gene pool has not occurred, while major phyletic occlusion is invoked only where there has been gene pool divergence in allopatry, and where extinction is occlusional, owing to a leading effect lying in an anagenetic selection interface (that is to say, when the leading effect relates to a differential that evolved via iterative genic occlusion). In contrast, true cladogenetic or species substitution (Chapter 6) occurs when a substitutional event is led by a cladogenetic rather than anagenetic selection interface, and where genic substitution (rather than occlusion) constitutes the predominant genetic element in evolutionary change. The only way in which early and late anagenetic states may actually compete in the isopatric selection gradient of anagenesis scenario is of course by neosympatry of formerly isolated gene pools of the gene reservoir in question. Here, the selection interface of anagenesis is resolved by elimination of one gene pool via major or minor phyletic occlusion. The salient point in deciding whether phyletic occlusion or species substitution occurs now lies with the balance existing between respective contributions from anagenetic as against cladogenetic inputs to the selection interface in question. In particular, the actual occurrence of speciation in allopatric gene pools clearly does not rule out subsequent phyletic occlusion in the neosympatric state, provided only that the substitutional selective force lies in the anagenetic selection interface.

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FIGURE 106 Major phyletic occlusion occurs when two actively evolving gene pools derived from a parent lineage become neosympatric at a later stage, and that sublineage evolving at the faster intrinsic rate (left-hand side) eliminates the slower one (right-hand side) via occlusion (compare with the sympatric state and minor occlusion - Fig. 102).

Similarly, cladogenetic substitution will occur when the leading effect lies in the cladogenetic domain. The above discussion has stressed the intrinsic selection gradient of anagenesis as a model of evolutionary change in relation to the balance existing between anagenetic and cladogenetic inputs to a compound selection interface. A more complete picture of the interaction between emergent species concerns all other contributions to ﬁtness in a compound selection interface, and this

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question will be explored in connection with the benign–hostile niche scenario (Chapter 18), and also in the context of ‘‘species sorting’’ (Chapter 20). Species selection (see Chapter 6) obviously constitutes yet another component. Time Frame, Anagenesis, and Cladogenesis Speciation clearly requires a time frame long enough to allow allopatric divergence, whereas this particular scenario is not a necessary requirement for the intraspeciﬁc model of anagenesis. The conﬂict between forces favoring infra- as against transspeciﬁc evolution may thus be closely linked to the time span requirement for anagenetic change as against that required for signiﬁcant allopatric cladogenetic potential to appear in the gene reservoir. Intraspeciﬁc anagenetic evolution may therefore tend to predominate whenever the rate of phyletic occlusion in realization of adaptive potential is greater than the rate of population fragmentation and dispersal. Only when ambient speciation time is less than anagenetic does the former override the latter. Again, this tends to support the view that the large ﬁtness differentials appertaining to earlier 움anagenesis constitute the most probable substrate for a leading contribution from the domain of intraspeciﬁc evolution. In the question of the interaction between speciation and anagenesis, we must also consider the inﬂuence of competition between (and often distantly related) species in driving anagenesis. Bock (1972) examined the role of species interactions in macroevolution, and his assertion that interspeciﬁc competition is of considerable importance in driving anagenetic change cannot be questioned. However, the main thrust of Bock’s argument is centered around postspeciational cladogenesis (see Chapter 6), and thus does not deal adequately with those aspects of adaptational change that are not linked directly to species– species interactions, including infraspeciﬁc competition and selectional regimes arising within the gene pool, subsequent to speciation. Bock’s analysis also does not take into account the question of species substitution (occlusional or otherwise). The question of species–species interactions will be examined again in the context of evolutionary rate, in the next chapter (see also Chapter 20). What other factors linked to time frame determine whether minor or major phyletic occlusion or speciation occurs? Rate of iteration within the anagenetic sequence is obviously also crucial in this, and we must not assume that a hypothetically large selection gradient in early anagenesis is more important than existence of actual adaptive potential for iteration of an anagenetic trend! The Intrinsic Selection Gradient of Anagenesis and the Directionalization Function As anagenesis proceeds, there must be a cascade of events following the founding Renschian phyletic node of the new lineage and centering around the opening up of canalized gene epistatic systems. This is essentially a ‘‘postthreshold scenario’’ in the unraveling of anagenetic evolutionary change, manifesting the likelihood of a period of high evolutionary rate occurring in the immediate wake of the ﬁrst structural response to an adaptive shift. The key to this hypothesis may lie partially in the relative ease of linear–allometric morphotransformational change as the developmental basis for n successive incremental steps of anagenesis, and in the likelihood of a threshold effect

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whereby a pivotal anagenetic step may rapidly be followed by others extrapolating the same afﬁne morphotransformation, for example, via gene duplication or ampliﬁcation: Waddington (1939) stated, ‘‘Granted that a character is dependent on the interaction of many genes, it will be easier to continue a line of evolutionary change for which many of the modiﬁers are already present, than to start off a completely new line. Thus, the unidirectional nature of trend evolution is not particularly surprising.’’ In summary, many incremental steps of anagenesis (simple afﬁne transformations of form plus some element of iterative progression to alternative morphosystem states) probably have the capacity to occur by intraspeciﬁc evolution, and larger iterative steps of that kind are not necessarily altogether dependent on speciation occurring. In this scenario, of course, selection pressure for cladogenetic change will sometimes be greater than that for anagenetic change, and sometimes vice versa, and we must therefore by no means ignore the considerable signiﬁcance of interactivity between clado- and anagenetic forces at any point. Of particular importance is the conclusion that the structural response to an adaptive shift (and to the pivotal adaptive shift in particular) has a directionalizing effect on subsequent structural changes in the anagenetic sequence, a fact already suggested from other considerations (see Chapters 7 and 10). There must in turn be a large degree of reciprocal facilitation between the directionalization function and the intrinsic selection gradient model discussed above.

PHYLOGENY AND THE ADAPTIVE ZONE How do cladogenesis and anagenesis interact in determining the longer term architecture of lineage? This interaction is described by phylogeny, which seeks to reﬂect the topology of evolutionary change in the trajectory of a lineage. As we have seen above, the characteristics of phylogeny must be determined by two principal mechanisms, speciation and phyletic occlusion. How do these factors affect the form of the phyletic lineage in the longer term? Phylogeny describes the interaction between cladogenesis and anagenesis in the evolutionary history of a phyletic lineage, and the term can now be formally deﬁned as constituting the temporal–sequential relationship existing between speciational, amphigenetic, and anagenetic events, in that it excludes only that element of evolutionary activity lacking any directionalized topology in phenotype structure. As we have already seen, infraspeciﬁc anagenesis may tend to predominate during the 움 phase, with progressively greater input from speciation during the 웁 phase. This view offers a broad outline for closer inspection of lineage architecture.

The Phyletic Node The term node has a special topological meaning in biology, conforming to a speciation point that may or may not also be expressed beyond the domain

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of a substructural differential, thus conforming speciﬁcally to the locus within a lineage at which gene ﬂow has ceased between two diverging branches. An ambient cladogenetic node is deﬁned simply by any speciation point, while the larger macroevolutionary nodes of cladoanagenesis may be deﬁned as Renschian nodes. A cladogenetic node is invariably linked to a speciation event. The Anagenetic Node The term lineage usually describes the trajectory in time of n anagenetic sequences coupled with a greater or lesser number of speciation events in a single line of evolutionary descent, thus describing both occlusional and speciation events. In this scenario, there are clearly two types of phyletic node, namely, the cladogenetic and anagenetic. These obviously constitute qualitatively different phenomena, since anagenesis cannot always be described as a series of cladogenetic branching points. An anagenetic node is, in practice, manifested in any recognizable structural increment in the adaptive response that is unidirectional over the course of lineage time (thus excluding amphigenesis). To that extent, it is an arbitrary construct (in that our capacity to ascertain the presence or absence of associated chronopatric or any other mode of speciation will generally be severely limited by practicality!): Incremental steps in the progressive sclerotization of the mesothoracic parepisternal suture in ditrysian moths (Brock, 1971) can probably be presumed to be ‘‘equivalent to trans-speciﬁc change.’’ However, the only evidence we have for this resides in the observation that this parameter is not variable within a species in the extant fauna (which could simply be due to the fact that any incremental step of this kind may be of such high selective advantage as to incur rapid ﬁxation, which could clearly happen in the context either of phyletic occlusion or via speciation). Analysis of an anagenetic sequence will often have to be based on incremental steps deﬁned by living species, so that each anagenetic ‘‘step’’ is presumed for purely practical purposes to have been approximately coincident with at least one ambient cladogenetic node in the past. The anagenetic node may thus be formally deﬁned as being any discrete structural increment in an anagenetic sequence that is presumed to have been coincident either with a cladogenetic node or with an occlusion event. The complete phylogeny of a lineage is thus described by a temporal sequence of cladogenetic and anagenetic nodes. However, the linear sequence of anagenetic nodes will be to some extent an artifact, for the reasons just stated. The Ambient and Renschian Cladogenetic Node A cladogenetic adaptive shift may often be initiated by behavioral change alone, but there may subsequently be some complementary structural change, the degree and nature of which will depend on the form of the adaptational paradigm, paradigm distance, and adaptive potential. This may at times constitute a Renschian cladogenetic node conforming to a linked cladoanagenetic selection interface with respect to the primary adaptive shift of a lineage, such

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that two diverging lineages come to occupy qualitatively different adaptive zones (see Chapter 6 and below). Such ‘‘cladoanagenetic nodes’’ will tend to be linked to 움-anagenesis: The divergence of the hesperioids (skippers) and true butterﬂies was clearly a Renschian cladogenetic node, distinct from the ambient divergence of species within a single genus of butterﬂies. Following the occurrence of a Renschian node, further niche shifts may often tend to be largely minor–quantitative rather than major–qualitative; hence, the Renschian node itself has special status in the lineage sequence, in its relationship with the primary adaptive shift. Renschian nodes will thus tend to be clustered around 움-anagenesis, while ambient cladogenetic nodes will be universal, with highest incidence in the 웁 phase. Renschian phyletic nodes are also closely linked to the adaptive zone concept (see below).

The Adaptive Zone and Adaptive Grid Concepts Simpson (1953) introduced the concepts of adaptive grid and zone, although his deﬁnitions of both phenomena were somewhat imperfect, resulting in some disparity in the interpretation of both terms by subsequent authors. Simpson deﬁned the adaptive zone as a relationship between ‘‘adaptive types’’ and discontinuities in nature, not a geographical, physical, or environmental zone, but ‘‘a characteristic reaction and mutual relationship between environment and organism.’’ He reasoned that discontinuities between adaptive zones ‘‘as seen now or at any other point in time . . . are generally quite clear and ﬁxed’’; for example, ‘‘A discontinuity between aerial and aquatic life seems inherent in the permanent distinction between air and water.’’ He also saw adaptive zones being juxtaposed in a ‘‘grid’’ which could be ‘‘crossed’’ in a phylogenetic sense. Thompson (1917) foresaw the adaptive zone concept and, to some extent, gave a better indication of its nature than did Simpson (see below). There follows a radical reconstruction of the adaptive grid and zone assemblage on the basis of a more biosystematological approach. The Adaptive Grid as an Occlusional Zone, and the Adaptive Isthmus The adaptive grid (here termed the occlusion zone) has to be redeﬁned as being that locus at the root of a complex anagenetic sequence that is linked to ‘‘lost morphospace’’ resulting from endogenous extinction factors arising from phyletic occlusion in an anagenetic sequence, as evident in much observed ‘‘vacant morphospace.’’ It is thus ‘‘the adaptive isthmus at the bottom of the isopatric selection gradient of anagenesis,’’ leading from one bounded adaptive zone to another (see below). The occlusion zone must enlarge as anagenesis proceeds, and its dimensions are clearly linked to steepness of the isopatric selection gradient of anagenesis. There must also be bounded versus apert adaptive zones in Nature, the latter relating to that situation in which a lower selection gradient has permitted some degree of survivorship in the transitional zone between two adaptive zones. The occlusion zone is a dynamic structure, tending to reach an asymptote toward the close of 움-anagenesis, once the contribution to ﬁtness of further

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anagenetic advance is no longer great enough to invoke any proliferation of occlusionary events, and when tangential cladogenesis has come to dominate the selection interface. The occlusion zone may, in the trajectory of an adaptive isthmus, link to a compound anagenetic sequence characterized by activation of several fresh structure integrals, each containing many structure units linked to a distant paradigm state. In this sequence, earlier stages tend to be occluded by virtue of the high selection gradients intrinsic to 움-anagenesis: As with several known examples of zonal transition in which an adaptive grid is said to have been crossed, the autopod of terrestrial vertebrates cannot possibly have evolved in a single step, and the transitional stages must have rapidly passed into extinction. This event took place in an occlusion zone comprising the adaptive isthmus between the aquatic and terrestrial adaptive zones, and which carried a series of adaptive states that were suboptimal with respect to that zone lying ‘‘above’’ the transitional zone itself. The outcome has been the phyletic occlusion of very many transitional structural states from the extant fauna. As stated at an earlier point, the greatest manifestation of phyletic occlusion will be seen in lineages in which realization of adaptive potential has involved genetic and developmental duplication and co-option or pleiophorism. The Adaptive Zone Concept We must now further investigate Simpson’s exposition of the nature of the adaptive zone in terms of his concept of differences between adaptive types which are ‘‘not arbitrary . . . but correspond to actual discontinuities in nature’’: Simpson held that ‘‘occupation of a zone is either when it is empty—or when a superior competitor arrives from elsewhere.’’ Recent evidence on origins of mammals suggests that divergencies had already taken place before the demise of the dinosaurs (Hedges et al., 1996). However, the mammals did not proliferate until a range of adaptive niches had subsequently been rendered vacant by extinctional events elsewhere. Thompson (1917) similarly held that a ‘‘principle of discontinuity’’ is inherent in classiﬁcations, ‘‘Nature proceeds from one type to another . . . being deﬁned by physicomathematical conditions of possibility.’’ For example, magnitude determines the necessary parameters of eye structure in very large as against very small animals, and structural paradigms for terrestrial as against aquatic animals differ profoundly owing to the viscosity differential between these two media. We must now ask whether a ‘‘vacant adaptive zone’’ does actually exist. In fact, the adaptive zone is not an entity existing in Nature, other than in the context of being progressively deﬁned by iterative evolutionary activity in the adaptive system, and Thompson’s observations appear to offer a better opportunity for reassessment of the adaptive zone concept from the standpoint

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of the architecture of the structural attractor, as deﬁned by inputs from the newly deﬁned concepts of adaptive potential and the biophysical paradigm. Different coordinates within the structural attractor have different degrees of freedom as determined by the biophysical paradigm for function, and there may be no to a few possible coordinates for certain mechanisms (i.e., for any one position within the dimensional spectrum). The structural attractors of remote lineages occupying a similar lineage niche may then tend to share certain ‘‘rigid’’ coordinates at the equivalent position in their respective biophysical paradigms. These coordinates are, of course, those with few (or no) degrees of freedom, and it is clearly this component of the structural attractor that constitutes a constrained portion of the total adaptive paradigm which forms the Simpsonian adaptive zone. Since an upper limit exists to the number of constrained coordinates in the structural attractor (and since many more may exist in minor coordinates), large areas of intersect between independent lineages must occur in the former. The adaptive zone can now be more explicitly deﬁned as being determined by the most constrained major coordinates of the structural attractor as a speciﬁc function of limits to degrees of freedom existing in both adaptive potential and the adaptational biophysical paradigm. Principal components in the adaptive zone will thus tend to be linked to such vital parameters as position in trophic level, large scale areas of shared niche space in the sub- and hypoparametric dimensions, and the dialogue between absolute size and gravity. Most signiﬁcantly, the adaptive zone is also bounded by an occlusion zone of greater or lesser proportions. The input to the adaptive zone from the niche must clearly lie in restriction of the total number of degrees of freedom residing in the biophysical paradigm. The adaptive zone is thus extrinsic to the organism, only in the restricted sense of being partly deﬁned by extrinsic niche potential. However, its real existence depends on realization of that potential, in the context of the total organism– environment interaction. Convergent structural ‘‘ecotypes’’ thus do not so much identify ‘‘discontinuities in Nature’’ as reﬂect the existence of the grid–zone assemblage, particularly via the concept of constrainment of major coordinates of the adaptational paradigm (from which taxonomic discontinuities arise purely as the emergent corollary of a process). Many authors in fact mean ‘‘niche’’ or ‘‘environment’’ when they use the term ‘‘adaptive zone.’’ However, an adaptive zone is really part of an holistic adaptive system containing both niche and organism(s) occupying it, thus being identiﬁed from principal niche parameters, on the one hand, and complementary structural specializations, on the other.* Adaptive Radiation With the Renschian phyletic node, two lineages may diverge on the basis of a dichotomy, such as, for example, that existing between benign and hostile * One further note of caution here has been raised by Maynard Smith, who points out that although the six-legged design of insects lies with the fact that six is the smallest number of legs which permits an insect to take half its legs off the ground without falling over, the view that there are strict laws which determine that only certain types of organisms exist is a kind of ‘‘physics envy’’ affecting some biologists!

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environment, and this scenario may also expand beyond the limits of a single cladogenetic event. Thus Renschian cladogenesis need not be dichotomous, but can also involve a rapid sequence of phyletic nodes linked to n qualitative adaptive shifts, where adaptive potential has access to several alternative adaptive zones: Simpson (1953) viewed adaptive radiation as being equivalent to more or less ‘‘simultaneous’’ occupation of n different adaptive zones, and he thought that this mode of radiation probably typiﬁed the so-called Cambrian explosion and many other higher group diversity patterns. Givnish and Sytsma (1997) deﬁned adaptive radiation as evolution of diversity of ecological roles and attendant adaptations in species of a lineage. Adaptive radiation is thus due to the occurrence of a rapid succession of primary adaptive shifts, resolved in Renschian cladogenesis in the context of a single phyletic lineage. The key to adaptive radiation therefore lies with multiplicity of (qualitative) dimensions in free, adjacent niche space in a cladogenetic selection interface. Simpson stated that increase in genetic variability is fundamental to adaptive radiation, in the ‘‘release from centripetal 씮 centrifugal selection.’’ He also held that adaptive radiation can occur at any point in a lineage, but that it most often occurs near its origin; he also pointed out that this is not the only way new adaptive zones come to be occupied, since they can occur through successive invasions. Both modes are common in Nature, and the radiation mode is often linked with the ‘‘episodic’’ nature of many evolutionary patterns (see Chapter 18): The major types of vertebrates appeared slowly over about 200 My, and not by adaptive radiation. Conversely, cladistic trees for the origins of the placental orders tend to be ‘‘bushy’’ (see Lewin, 1996). Adaptive radiation has been very widely reported in other lineages. According to Stanley (1990), adaptive radiations have produced most taxa above the genus level. In the same way, not all adaptive radiations necessarily lead to major cladoanagenetic divergence: The Galapagos ﬁnches express adaptive radiation at a lower taxonomic level (see Carroll, 1997, for a summary), as do very many speciational assemblages. Recent adaptive radiations in fact tend to be most apparent on islands and in isolated lakes, as with this and other examples.

Parallel Evolution, Evolutionary Reversal, and the Adaptive Zone There are two fundamental axioms of phylogeny in relation to constraining inﬂuences on the topology of lineage, both following on naturally from the concept of the adaptive zone. Whenever degrees of freedom in the structural attractor for anagenesis are constrained toward a value of 1.0, (a) the effect of interaction between cladogenetic nodes and anagenesis will be to invoke parallel evolution in the anagenetic domain, and (b) the inﬂuence of amphigene-

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sis will be to create evolutionary reversals, when there has been a return to a former adaptive zone.

FIGURE 107 Parallelism and amphigenesis in lineage topology.

In the generalized scheme shown in Fig. 107, an anagenetic sequence proceeds in parallel toward the adaptational paradigm state, irrespective of cladogenesis, and lineage topology is simply a0 씮 a1 씮 a2 씮 a3 씮 aj. The same sequence is shown alternatively expressing amphigenetic reversal. It has already been shown that there will be a tendency for progressive constrainment of the adaptational paradigm as an anagenetic sequence evolves and matures, and the inﬂuence of the directionalization function thus acts to further narrow the channels of morphogenetic change. The constrained coordinates of the adaptive zone are thus instrumental in the determination of parallelism and convergence between independently evolving lineages. At least some major coordinates of the structural attractor will tend to be intrinsically narrowly deﬁned, this being an interactive effect of degrees of freedom residing in the adaptational paradigm and in adaptive potential. In movement through an occlusion zone to a newly deﬁned adaptive zone, further constrainment of the selectional attractor may occur following evolution of the ﬁrst structural adaptive response in the anagenetic sequence, the latter subsequently acting to directionalize the anagenetic sequence by further restricting the limits of adaptive potential. Mechanisms of this kind clearly constitute signiﬁcant inputs to the directionalization function. Parallelism will thus be the normal mode of anagenetic progression for any highly constrained structural attractor, and therefore may often constitute ‘‘normal progress’’ for anagenesis, toward the 웁 phase. This is a function, not only of narrow adaptational paradigms, but also of homeostatic constraints imposed by canalization within

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complex epistatic systems during the progression from the preadaptive to paradigm state. These mechanisms clearly act to channel adaptive potential (and thus also the adaptive response) with respect to a given adaptational change occurring in discrete but genetically related genomes: Numerous examples of parallelism have been documented. In Lepidoptera, for example, the climbing proleg (Hinton, 1955) and secondary body vestiture of the larval stage, closing of the mesothoracic parepisternal suture in the adult thorax, and pupal obtection (fusion of parts in connection with changing mode of adult emergence) all manifest multiple polyphyly (Brock, 1971 and elsewhere). In fact, very few ‘‘evolutionary trends’’ that have so far been identiﬁed in any developmental stage of Lepidoptera suggest much likelihood of monophyly with respect to any one anagenetic sequence, so far as the suprafamilal phylogeny of the order is concerned. Simpson (1953) gave examples of trends manifesting parallel anagenesis in dentition (such as hypsodonty) in Equidae and in various traits of the echinoderm genus Micraster, the latter following Rowe’s work (1899), which uncovered trends in 11 apparently independent characters (increasing relative breadth and length, forward migration of the mouth, etc). Olson (1944) described parallel trends in therapsid reptiles, all lineages of which became more mammal-like in numerous characters. Heterophyly (where a plant has quite different leaves in the juvenile stage compared to the mature state) is just one of many traits manifesting apparently widespread parallel evolution in the plant kingdom (see Thomas and Spicer, 1986). Clearly then, the observed propensity of the selectional attractor to invoke widespread parallel evolution in phylogeny is closely linked to the adaptive zones concept. These maxims are of prime importance when we come to consider the relationship between topological and evolutionary parsimony (Chapter 21). At the latter stage, we shall see also that evolutionary reversal through amphigenesis is a very common element in the generation of biotic diversity patterns. Adaptational Divergence Obviously, not all postcladogenetic anagenesis is manifested in parallelism or amphigenesis. Many adaptational paradigms or adaptive potentials will be less constrained and will thus manifest divergence. This again is clearly a function of greater number of degrees of freedom in the structural attractor, this in turn arising from the indigenous labilities of adaptive potential and the nature of the adaptation interface.

MAIN POINTS FROM CHAPTER 17 1. Functional change evolves via the adaptive shift mechanism, through qualitative change in the adaptation interface. An adaptive shift may be partial

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or ecliptic, and a pivotal adaptive shift occurs when a new function comes to predominate over an old one. 2. Adaptive shifts can be behavioral in origin (‘‘prospective adaptation’’) or else originate in structural change, as in the facultative adaptative differential mechanism. 3. The concept of evolutionary anachronism describes the time gap between a behavioral adaptive shift and its ﬁrst complementary structural adaptive response. This period can be of considerable duration. 4. Progress toward the structural attractor generally involves an iterated train of function shifts involving only quantitative change in the adaptation interface. Function shifts can evolve either in 움 mode (expansion or contraction in real niche space) or in 웁 mode (intensiﬁcation or dilution in hyperparametric niche space). 5. An anagenetic sequence is described by a series of adaptive and function shifts gravitating toward the structural selectional attractor in the context of an isotropic selection interface. Spatial change can be expansive in the context of a benign niche, or contractional in a hostile one. 6. In the 움 phase of anagenesis, 움 function shifts predominate, whereas in the 웁 phase, 웁 function shifts form the leading evolutionary force. 7. Transient suboptimality is a common feature of complex anagenesis. However, both pleiophorism and redundancy in the context of multiple functionality ultimately diminish during the 웁 phase, with further gravitation toward the adaptive paradigm. The trajectory of a complex anagenetic sequence may thus originate in a suboptimum adaptive state, but will gradually converge on the structural selectional attractor with time, through vestigation with respect to functional change, and via homeostatic adjustment in the context of pleiophorism. 8. The structural attractor becomes progressively more narrowly constrained during the course of an anagenetic sequence, thus expressing directionalization. 9. As major cladogenesis proceeds via speciation, so too anagenesis does so via phyletic occlusion in the context of iterative change linked to steep selection gradients and presence of an isopatric selection interface. The degree to which anagenesis can proceed without speciation depends partly on the possibility of chronopatric speciation. 10. The question as to whether or not anagenesis can proceed in the absence of speciation has to be examined in the context of fundamental differences between the anagenetic and cladogenetic selection interface. Anagenesis has a fundamental capacity to occur solely through infraspeciﬁc evolution (notably during the earlier 움 phase), and it clearly often carries a propensity for continuation via parallelism on a transspeciﬁc basis when speciation does occur. Again, the cladogenetic selection interface may manifest unary resolution in cladogenetic substitution in a manner resembling anagenetic progress, a circumstance which may be further complicated in the presence of a joint cladoanagenetic selection interface. These theoretical points seem unlikely to be resolved in practical circumstances, owing to the difﬁculty experienced in objective interpretation of paleontological data.

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11. Where anagenesis occurs in the context of a neosympatric selection interface, we witness major phyletic occlusion, while in the intraspeciﬁc mode, there will be minor occlusion. With cladogenetic substitution, allopatric unary resolution is, in contrast, led by a cladogenetic rather than anagenetic selection interface. 12. The intrinsic selection gradient and anagenetic integral curve form a basis for an understanding of the anagenetic mechanism, as also for further investigation of evolutionary rate. The intrinsic selection gradient reﬂects a changing selection interface during progressive occupation of new niche space, as structural change gravitates toward an adaptive limit. The anagenetic integral curve in turn describes the addition of incremental steps to an anagenetic sequence with respect to a given selection gradient. Predominance of anagenesis eventually gives way to a progressively higher incidence of speciation as the slope of the anagenetic integral curve diminishes. 13. Phylogeny is an expression of the incidence of cladogenesis and of anagenetic change in the history of an evolutionary lineage, as reﬂected in a temporal succession of cladogenetic and anagenetic phyletic nodes. There are ambient and Renschian cladogenetic nodes, according to the nature of evolutionary change incurred. 14. Macroevolutionary events may invoke a partitioning of adaptive systems to form adaptive zones, a phenomenon linked to the inﬂuence of phyletic occlusion. An adaptive zone is reﬂected in manifestation of certain major coordinates of the structural attractor, with important inputs from trophic level, absolute size, and shared dimensions in sub- and hypoparametric niche space. 15. Some adaptive zones are bounded and some apert, according to the steepness of the anagenetic selection gradient in the adaptive isthmus between ancestral and descendant zones. The occlusion zone constitutes that area of ‘‘lost morphospace’’ in an anagenetic sequence leading to a new bounded adaptive zone. This phenomenon is especially linked to the mechanism of duplication and co-option. 16. The adaptive zone factor is frequently responsible for the generation of widespread parallelism and convergence. It also inﬂuences the incidence of amphigenesis, wherever a selection proﬁle manifests anisotropic behavior with a periodicity not less than that of ambient speciation time. 17. Adaptive radiation occurs when n adaptive zones are almost ‘‘simultaneously’’ occupied by different branches of an evolving lineage.

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The question of how a phyletic lineage develops in the longer term leads naturally to that concerning the rate at which evolutionary change occurs. As we saw in the last chapter, anagenesis frequently manifests a steep intrinsic selection gradient. In addition, it is of interest to examine the ways in which the ‘‘base rate’’ can be altered through extrinsic inﬂuences. It is at this point that we encounter a further special theory that has emerged from twentieth century paleontology, largely through the writings of Simpson, Gould, and Eldredge. This component is sometimes termed ‘‘episodism,’’ although in recent years episodic evolution has been more widely discussed as punctuated equilibrium. The clash between ‘‘punctuationism’’ and ‘‘neo-Darwinism’’ has been riddled with controversy in the past. In particular, ‘‘hard’’ punctuationism has become bogged down with confusion over the speciation process, partly owing to a Hennigian inﬂuence and partly owing to an ill-considered input from the Paterson model. The structuralist program has also been incorporated into punctuationism, owing to an outdated view of the role of genetic drift in speciation, as well as to confusion over the roles of pleiophorism and multiple functionality in evolution. It is pointless to attempt to ‘‘return to Darwin’’ in order to resolve the above controversies. First, the fossil record was inadequately known in Darwin’s time. Second, Darwin’s own view of genetics was highly erroneous. Third, very little was known concerning the role of development in evolution in Darwin’s time. In addition, we have already seen that some neo-Darwinian interpretations do in fact carry a quite large (and probably quite false) structuralist element!

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Perhaps the most general argument in favor of episodism sensu lato is that this phenomenon appears to be a predicted behavior in the evolution of adaptive systems.

Frames of Reference for the Measurement of Evolutionary Rate Haldane proposed that evolutionary rate be measured in darwins according to the following formula: rate ⫽ [ln(x2) ⫺ ln(x1)]/⌬t

darwins

where x1 and x2 are measurements taken for an evolving trait, so that 1 darwin (1 d) is equivalent to a factor of e ⫽ 2.718 per million years. Despite the intended universality of the above equation, it is clear that many different frames of reference may be examined in relation to evolutionary rate, and the precise nature of the temporal criterion is clearly of special signiﬁcance in this, as are direct data from the equations of population genetics. The criteria for measurement of evolutionary rate must clearly also take evolutionary mode into account, and we must additionally consider the nature of the actual structural locus of evolutionary change. Above all else, it should be immediately obvious that the instantaneous rate of change in evolution must not be equated with the averaged-out rate of lineage, given that an anagenetic sequence cannot possibly be presumed to be actively changing at all points in time (also because of direct evidence in the fossil record that evolution is frequently highly episodic in nature). Fenster and Sorhannus (1991) give a critical account of the criteria that have been used for measurement of evolutionary rate, concluding that there is in fact no superior method in current usage. Temporal Criteria Evolutionary rate can probably only be analyzed directly with reference to very small time frames, notwithstanding the fact that information from such sources can be used to illuminate large scale manifestations of certain factors inﬂuencing rate of change. There is thus a problem concerning choice of temporal reference frame, which might, for example, suggest very high rates for artiﬁcial selection experiments or for gene frequency changes in the context of adaptive equilibrium, while simultaneously giving utterly misleading ‘‘slow’’ rates for longer term evolutionary events (see Gingerich data, below). Thus, at one end of the spectrum, it would be quite feasible to examine evolutionary rate in relation to level of activity within the narrower but inappropriate conﬁnes of oscillatory variational change alone (as has often been done). At the other extreme, we might chose to look at the manifestation of rate of change in relation to very long-term activity in the context of a major anagenetic sequence. The latter is one focus of special interest here, but this question cannot be approached sensibly in absence of an analysis of base rates operating at much lower levels. Mode Criteria The two main modal foci of interest for analysis of evolutionary rate of lineage clearly must lie in speciation versus anagenesis. The ‘‘frame of reference’’

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is therefore not necessarily an exclusively temporal one, but also concerns differentials appertaining to the presence or absence of major cladogenetic activity. There are thus two fundamentally different dimensions in which longer term evolutionary rate might be measured: rate of topological change along the trajectory of an anagenetic sequence, and rate of speciation. In the ﬁrst case, we are looking at degree of linear structural change, while in the second, the focus of interest obviously lies solely with the frequency of genome splitting. These are, to some extent, independent criteria, since ‘‘explosive’’ speciational periods are not necessarily linked to great anagenetic change, nor is rapid anagenesis automatically linked to species proliferation. Nevertheless, a large interactive element between these two modes must also exist (see previous chapter): Fenster and Sorhannus (1991) stated that Simpson’s analyses of evolutionary rates involved a mixing of taxonomic versus ‘‘morphological’’ rates, and it should be noted that Campbell and Marshall (1987) suggest that there is no correlation between these two different approaches, so far as echinoderms are concerned. Structural Locus of Lineage Rate One further point of note is that, unlike speciation rate, differentials in rate of anagenetic change are speciﬁc to certain structure units or function integrals. One component of structure may be undergoing rapid evolutionary change, while others exhibit stasis within the same time frame. It is also a fundamental axiom that all organisms exist in a state of stasis and adaptive equilibrium with respect to at least some gene loci, and that expressions of evolutionary rate vary from one phenon to another over a larger time frame. Similarly, evolutionary rate may also vary from one structure unit to another, even within the context of a single structure integral: Simpson (1953) looked at rates of change in unit characters in equid teeth, including hypsodonty or increase in height of cheek tooth crown relative to horizontal dimension. Horses became larger and more hypsodont during the course of long-term evolution. However, although hypsodonty constitutes a unit character, its components (paracone height and ectoloph length) evolved at different rates. Clearly then, morphogenetic change may be ‘‘one coordinate at a time,’’ even where there is a phyletic history of functional correlation between different components of a structure integral. As we progress from the evolutionary rate of a single phenon to that of a structure unit and thence to function integral, we also move into the domain of evolutionary rate of lineage. In that domain, it must at once be accepted that the Haldane formula is less than competent as a true measure of evolutionary rate (see the Gingerich data below).

EVOLUTIONARY RATE AT THE LEVEL OF LINEAGE Evolutionary rate can be regarded as a simple function of W within the framework of time t (generation time) and in the simplest iterative sense, namely,

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for ﬁxation of a single apomorph allele over n generations. Rates of change in gene frequency are thus easily analyzed at time t, but how do we extrapolate evolutionary rate to the domains of speciation and anagenesis? The links between W and the equations of population dynamics have already indicated a more complex relationship between selection and the behavior of an adaptive system (see Chapter 4), and this situation will clearly need further investigation. Evolutionary rate must be some complex of W. To understand what this function might be, it is ﬁrst of all necessary to decide what are the valid criteria of comparability, and to examine the likely inputs to evolutionary rate from the mechanisms of cladogenesis and anagenesis.

Valid Criteria of Comparability If we now examine the criteria of evolutionary rate of lineage further, it will be seen that not only could these apply quite differently to cladogenesis and anagenesis, but they could also be applied in different ways with respect to lineage architecture. We could, for example, consider evolutionary rate differentials along the trajectory of a single anagenetic sequence, as, for example, in the intrinsic selection gradient of anagenesis (i.e., in the 움 phase compared to 웁 phase; see previous chapter). Alternatively, we might choose to compare two different lineages inter se. Much more interestingly, we could also choose to compare evolutionary rates for the same anagenetic sequence evolving in parallel in two or more related lineages. This analysis again points to the fact that questions concerning evolutionary rate have often tended to be used in a noncomparability context in the past: Simpson (1953) held that ‘‘morphological and taxonomic rates are not comparable,’’ admitting that his own comparisons between remote lineages such as mammals and molluscs were hazardous. Evolutionary rate clearly must not be investigated on the basis of meaningless cross-comparisons where the criteria of comparison themselves lack relevance to any biological question. In the latter context it is evident, for example, that we cannot compare qualitative differentials, since there is no sensible scalar methodology that could apply to such a comparison. Degree of change cannot be measured in genuinely equivalent terms in qualitatively different anagenetic sequences or speciation regimes. A more instructive approach should focus on two main foci of interest, broadly described as ‘‘within and between lineage’’ strategies. It is feasible to look at how evolutionary rate varies within the trajectory of a single monophyletic lineage (see Simpson’s horotelic range below), and it is also valid to consider how the same anagenetic sequence evolving in parallel in two or more independent lineages expresses an evolutionary rate differential in manifestation of allotely, the latter constituting an additional and highly revealing frame of reference. Thus, ‘‘between lineage’’ comparisons are excluded, unless we are comparing the same anagenetic sequence across closely related lineages in the context of allotelic rates. Theoretical goals are obviously quite different for the analysis of horotely and allotely. The former is clearly linked in some way to the 움-/웁-anagenesis

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dichotomy and to the intrinsic selection gradient examined in the previous chapter (thereby affecting both clado- and anagenesis), whereas allotely is presumably concerned with the effect of different environmental regimes affecting separate lineages. Allotely can in fact be shown to form a most instructive focal point of investigation of evolutionary rate as it effects the analysis of causal mechanisms, especially as this in turn affects the unraveling of phylogeny (Chapter 21). Comparison of allotelic rates clearly constitutes a useful approach to the analysis of anagenetic rates in particular, although parallel comparisons of evolutionary rate on the basis of cladogenetic differentials can also be made. However, in the latter case, the input data may relate more to rate of change in the geophysical dynamics of the external environment, and the absolute spatial dimensions of sympatry and allopatry may obviously vary greatly between different lineages, thereby rendering cross-comparisons in speciational rates completely irrelevant in the context of any search for endogenous factors! Speciation rate is, however, in no way excluded from the anagenetic sequence, since anagenesis will of course be ‘‘punctuated’’ by speciation. Thus, although it is useful to examine speciation and anagenesis separately, in that their respective causal factors are in many ways fundamentally different, there is nevertheless a signiﬁcant interactive function between speciation rate and rate of anagenesis. Horotely, Bradytely, and Tachytely Simpson (1953) used three terms relating to evolutionary rate (see also Stebbins, 1949): • Horotelic for the usual distribution of ambient rates observed during the long-term phylogenetic history of a lineage • Bradytelic for exceptionally slow rates bordering on evolutionary stasis and leading to the existence of relict taxa in the extant fauna • Tachytelic, referring to rates involving rapid phyletic change of the kind often associated with the origins of a new higher group lineage, namely, in the occlusion zone (see previous chapter) Tachytely was explicitly stated to be linked with phyletic evolution (sensu Simpson), the horotelic range being more linked to the activity of cladogenesis. The differentiation of evolutionary rates within a single anagenetic sequence has already been partially examined in a related context as 움- and 웁anagenesis, in the context of the intrinsic selection gradient, and this must have some relationship with Simpson’s concept of horotelic range: Simpson (1953) stated that any large group seems to have a range of rates, with a mean or modal value within the proposed horotelic range. Related lineages commonly differ in evolutionary rates, and within larger taxonomic groups there is generally an average or modal rate. Average rates differ from one lineage to the next. Three avenues of exploration led to Simpson’s concept of brady- and tachytely. Tachytely was partly diagnosed on account of backward extrapolation to time of origin for certain major groups, in view of the existence of wide ‘‘extant

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gaps’’ in the living fauna, plus actual evidence in the fossil record for periods of remarkable dynamism in evolutionary change. Returning to the intrinsic selection gradient of anagenesis curve, we can identify tachytely in that sector deﬁning early 움-anagenesis, and in the same way, Simpson’s horotelic range must be linked to that later sector in which the rate gradient is more noticeably diminishing. Bradytely can be shown to lie elsewhere, however, and is in no way to be equated with the terminal asymptote in the fundamental intrinsic selection gradient of anagenesis curve itself (see below). Other authors have recognized more rate levels than Simpson (including Gingerich, who discussed four categories). In the present work, we shall also look at hypotelic rate (see below). Comparison of evolutionary rate need not be limited to paleontological data (where, however, the only direct knowledge of time scale can be gleaned), but may also be extended to the neontological domain. In the latter context, Simpson accepted Ross’s (1951) application of his own terminology for discussion of evolutionary rate in neontological data on caddisﬂies. Observed Evolutionary Rates There exists a real danger of confusion between evolutionary rates observed for dynamism within allomorphic variation (adaptive equilibrium) and those for speciation or for novel mutation leading to anagenesis, particularly where paleo- and neontological data are compared inter se. Horotelic rates versus rates of change under purely artiﬁcial selection regimes have sometimes indeed been directly compared in this context. Similarly, many ‘‘taxonomic’’ comparisons have been brought forward in the past that can have little or no objectivity: Gingerich (1983) discussed 521 estimates of evolutionary rates varying between 0 and 39 d, using the Haldane equation. Evolutionary rate for artiﬁcial selection was 5 orders of magnitude greater than the highest natural rate. However, these data clearly compare allomorphic with anagenetic rates, thus confusing patterns of change occurring within and beyond the boundaries of adaptive capacity. This approach also ignores intercalated periods of relative stasis, so far as longer term evolutionary rate is concerned. As stated by McCune (1997), any estimate of divergence time will confound divergence during speciation with divergence after speciation. Within the context of acceptable objective data, apparent agreement between low horotelic rate and higher group status anagenetic traits has been claimed (‘‘as slow as about that expected from genetic drift’’), despite the fact that estimates of tachytelic evolution surrounding the origin of new higher group lineages are higher by many orders of magnitude (Simpson, see above). Of course, extrapolation of the latter kind is difﬁcult to carry out in an objective manner. No doubt the scarcity of actual data on tachytelic rates is due to the much lower probability of fossilization during periods of rapid innovative change, especially where this is occurring in an infraspeciﬁc context, in a geographically restricted area! Nevertheless, good data on evolutionary rates have certainly come to light from a number of sources:

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MacFadden (1988) studied the evolutionary rate of traits in the molar teeth of horses using Haldane’s formula. Values were approximately 0.05–0.1 d (15–30%), compared to rapidly evolving mammals, where values of 1–10 d were observed. MacFadden (loc. cit.) states that rapid rates occurred noticeably in the adaptive shift between browsers and grazers during the Miocene. Rates in general were not high (lying within the horotelic range), but they are nevertheless much less than observed for several lineages of mammals at the same time. Speciation rates have also been measured: McCune (1997) cites rapid speciation rates of 0.01–1.4 my, exceptionally fast (0.0015– 0.3 My) in some lineages of ﬁshes. These authors also believe that sympatric speciation can be much faster, as this would involve selection acting directly on mating systems. While ambient anagenetic rates seem frequently to be quite small, Simpson had also drawn attention to examples where much greater rates must have occurred (as with the origins of the Chiroptera and Cetacea). Most signiﬁcantly, however, Simpson’s concept of a horotelic range is clearly borne out by actual data from the fossil record. Evolutionary Rate and Molecular Clocks The question of evolutionary rate must not, of course, be limited to observations on comparative anatomy, and genetical studies have also sought to analyze the problem. Molecular clocks have been proposed as an objective basis for estimates of evolutionary rate. However, this criterion should not be confused with degree either of morphogenetic change or of taxonomic diversiﬁcation. Again, much controversy still exists over the functionality of many molecular criteria described as ‘‘evolution,’’ and rate of neutral substitution may tell us little or nothing about the evolutionary process. Ideally, the molecular clock can hopefully place an absolute time scale on lineage phylogeny. However, it does not follow that rates measured in DNA have any meaning in terms of changes in topology of superstructure: Dobzhansky (1970), in his discussion of the data of Sarich and Wilson on primate evolution (1967), also pointed out the element of circularity in the reasoning behind molecular clocks and evolutionary rate. Of much greater importance than the accumulation of near neutral mutations in redundant DNA is the question of true molecular evolution in active epistatic systems. However, our present knowledge suggests again that there may be little correlation between molecular evolution in regulatory genes and rate of change in topology of superstructure (see also Chapter 21).

CAUSAL FACTORS OF EVOLUTIONARY RATE IN CLADOGENESIS Both intrinsic and extrinsic factors must be involved in the determination of evolutionary rate. Which kind predominates for cladogenesis?

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Various inﬂuences on evolutionary rate can be identiﬁed within the framework of the cladogenetic selection interface, some tending to impede the speciational process (as with homeostatic factors), while others can be seen to facilitate speciation (free adjacent niche space, etc.; see Chapter 6).

Intrinsic Factors of Cladogenetic Rate Which intrinsic factors might be presumed to have the capacity to speed up or decrease the rate of speciation? The limits of dominance in suppression of a too large contingent of hybrid depression could imply pressure for speciation, where cladogenetic forces might otherwise have been resolved through centrifugal polymorphism. However, this would be presumed to link with some more fundamental causal factor in the external environment, and presumably it would also concern very many allelomorphic loci, with respect to the question of speciation. An increased mutation rate in allopatric populations would clearly lead to greater cladogenetic drive, presumably leading to high levels of negative developmental viability in the neosympatric gene pool as well as to more rapid evolution of postzygotic isolation mechanisms, thus also to a greater probability of speciation. The absence of genetic potential for major cladogenesis probably tends to result in elimination of one emergent gene pool (cladogenetic substitution), and thus again may indirectly lower selection pressure for further anagenetic change in the surviving species, given the subsequent absence of a postspeciational selection interface. Conversely, where such potential is present, there must be intrinsic pressure acting to favor further divergence between emergent species.

Extrinsic Factors of Cladogenetic Rate Extrinsic factors must be of paramount importance for wide divergences in rate of speciation, especially considering the fundamental role played by degree of niche intersect, free adjacent niche space, and (in particular) by the spatial distribution of competing gene pools. The principal external inﬂuence on evolutionary rate differentials could be described as a dialogue between spatial behavior of the abiotic niche, geographical distribution, and dispersal within the gene reservoir. If, for example, the external environment is subjected to large scale land mass movement over gene reservoir niche space, then speciation may greatly accelerate, given certain conditions in dispersal. The principal extrinsic factors involved are therefore concerned with temporospatial distribution of the gene reservoir and geophysical dynamism in the external environment. The inﬂuence of the external environment clearly also includes the presence or absence of predators and competitors: Acceleration of evolutionary rates owing to opportunity arising from the absence of an interspeciﬁc minor niche intersect is most apparent in island faunas, and is then frequently expressed in a highly predictable

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manner in such traits as an adaptive shift in plant species toward dropped seeds, from ancestral forms with a wind-borne dispersal strategy; loss of ﬂight in winged animals; and various other parameters linked to reduced dispersal (see Grant, 1998). These changing adaptive strategies seem likely also to carry certain corollaries for anagenetic change in the longer term. Benign and Hostile Environment and Binary Resolution of Renschian Cladogenetic Potential The balance of free adjacent niche space in resolution of cladogenetic potential decides whether speciation actually happens or whether some emergent gene pools of a gene reservoir are merely eliminated through species substitution. Binary resolution of cladogenetic forces of the Renschian (i.e., cladoanagenetic) kind implies the existence of some fundamental dichotomy between adaptive niches with different selection regimes, which factor can lead to different evolutionary rates being perpetuated over long periods of lineage time. The axial force may then be linked to a cladogenetic choice between adaptive shift to higher versus lower adaptive states in the organism–environment interaction. Here, an ‘‘r strategy’’ constitutes the tangential resultant of a cladogenetic force (as the ‘‘loser’’ lineage in binary resolution), thus sacriﬁcing ‘‘penetrability’’ of the limiting resource in favor of sequestration from competition in a hostile environment via a niche-contracting adaptive shift. There is thus a causal link between the adaptive cascade and evolutionary rate of lineage that can be identiﬁed in the choice between benign and hostile niche. In the latter instance, the differential lies in the degree to which selectional sequestration affects the interaction between ‘‘substrate’’ (positive mutation) and ‘‘reagent’’ (selection) (see Chapter 6). Where this is perpetuated over lineage time, there will be a lowering of selectional activity in the context of the hostile niche and, consequently, a lowering also of cladogenetic potential for resolution of antagonistic selectional forces in speciation. This is therefore a factor which could affect either clado- or anagenetic evolutionary rate. The dichotomy between benign and hostile niche and the effect of this on evolutionary rates in general will be examined in more depth in the context of adaptive corridors (see below).

CAUSAL FACTORS OF EVOLUTIONARY RATE IN ANAGENESIS As with cladogenesis, there are several mechanisms operating within the anagenetic mode that can be identiﬁed as affecting evolutionary rate, and, again, some impede and some facilitate evolutionary change. We must once more ask which of these factors are the most signiﬁcant?

Endogenous Factors of Anagenetic Rate Endogenous factors affecting evolutionary rate in anagenesis are those inﬂuences arising within the lineage gene reservoir itself. Certain of these factors

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must have a very large input to the horotelic range (as with 움- versus 웁anagenesis), although others may tend to act mainly as developmental constraints on initiation of the adaptive response, rather than retarding anagenetic progress directly—thus manifesting a major effect predominantly at the root of the lineage. Certain of the following factors should therefore be seen, not as direct inﬂuences on evolutionary rate, but as constraints on adaptive potential, only indirectly affecting rate of change. Endogenous factors do not invariably act as constraints, since there is also a domain of facilitation residing with directionalization. Additionally, certain supposed constraints are probably imaginary, rather than real. Reputed constraintive and facilitative factors affecting evolutionary rate can be listed as follows.

I. Constraintive Factors Hard Selection Haldane (1957) drew a distinction between ‘‘hard’’ and ‘‘soft’’ selection, considering that one gene substitutes for another by means of extra mortality in hard selection, which would tend to lower the evolutionary rate owing to the existence of a negative corollary arising from a tendency toward decrease in absolute population size leading to population crash. However, two major problems exist with Haldane’s hypothesis. First, a newly selected gene can be expanding the niche via an adaptive shift (see Chapter 17), in which circumstance no extra mortality is invoked, either ‘‘taken from previous mortality’’ or ‘‘added on top’’ (as, for example, with acquisition of the ability to eat a new food plant in herbivorous species). Second, hard selection is irrelevant with respect to density dependent mortality factors, since the value of s is then a function of N and a population will not therefore automatically be driven toward ‘‘crash’’ by selection in this context. In reality, hard selection concerns incremental adaptational dygenesis and not selection (see Chapter 20). Provided that rate of change is not too high and logistic capacity manifests a high level of plasticity, this problem should be easily counteracted through modulation to fecundity. It seems in fact that it is very unlikely that hard selection could have any signiﬁcant effect in anagenesis, since fecundity is subject to much lability from behavioral or phenoplastic adjustment and recurrent polygenetic modulation in the context of secondary and tertiary adaptive capacity. It thus seems unlikely that increasing r would present anything other than a transient challenge, so that any negative corollary in hard selection would rapidly be followed by a shift toward a softer regime. Paradigm Distance and Evolutionary Anachronism Realization of adaptive potential in the advance toward a distant structural paradigm must inevitably be a slow process. The more this involves compound anagenesis, the slower is the evolutionary rate and the greater is the time lapse between primary adaptive shift and pivotal phyletic node (evolutionary anachronism; see previous chapter). This syndrome clearly reﬂects the gulf existing between the preadaptive state and compound structure of a remote biophysical paradigm for a major adaptive shift. Consequently, a gene pool

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may survive in a new niche by virtue of some behavioral (or minor structural) adaptive shift that is not supplemented by any further morphogenetic change until some rare combination of genetical events occurs: A very long history of arthropod evolution existed before invasion of the terrestrial environment occurred, and again between the earliest terrestrial radiation and subsequent adaptive shift to an aerial environment. The very great structural modiﬁcations that were necessary for these transitions to occur no doubt reﬂect the correlation between paradigm distance and evolutionary anachronism. Paradigm distance (see Chapter 7) therefore seems more likely to affect anachronism than evolutionary rate directly. However, progression toward a complex biophysical paradigm state involving many structure units or integrals must also invoke considerable retardation of evolutionary rate, compared (for example) to minor allometric transformation, and this will affect the averaged out (as against instantaneous) rate of change over a longer period. The Canalization Paradox and Evolutionary Anachronism Canalization is concerned with repression of impinging pleiotropy on the development of essential features (see Chapter 12). Paradoxically, this mechanism must also tend to suppress change occurring within many canalized parameters which actually contain latent adaptive potential for positive change, thus acting as a constraint on evolutionary rate owing to a lowering of degrees of freedom in the structural component of adaptive potential. Many examples of apparently low evolutionary rate could be due to developmental constraints of this kind, namely, where potentially useful mutational change cannot bypass the homeostatic impediment imposed by canalization. Thus, even where a potentially large selectional advantage is apparent in them, adjacent morphosystems may be thus hidden as an emergent corollary of canalization. The canalization strategy and paradigm distance together constitute a threshold that is centered particularly on the primary adaptive shift. However, these apparent impediments may tend to be removed in the aftermath of the ﬁrst structural adaptive response, and a greater component of directionalization may then be facilitated along with considerable acceleration of evolutionary rate. Thus, endogenous factors are mostly ‘‘prepivotal’’ in the anagenetic sequence, not really inhibiting evolutionary rate once change has actually started occurring in a preferred direction.

II. Facultative Factors Soft Selection Returning to Haldane’s analysis (see above), in ‘‘soft’’ selection, nonselective deaths are simply compensated for by selective mortality. Under the latter regime, much higher evolutionary rates would theoretically be possible, selective mortality being substituted for ambient mortality, with no corollary in population crash. This view, however, also requires revision in the light of the selective- and nonselective offset strategies (Chapter 4), as indeed in the functional link between the Lotka–Volterra equation set and the equations of

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population genetics, thus having very limited application to anagenesis. Neither hard nor soft selection take note of selection for a new gene causal to an adaptive shift which involves actual expansion of the niche, thus lowering and not increasing mortality (see hard selection above). The dichotomy between the criteria usually examined by population geneticists and a wider evolutionary view of genetic change in the context of the developmental model obviously constitutes a recurrent problem in the attempt to look for links between major patterns of evolutionary change and the known behavior of genes. Genetic and Epigenetic Factors Signiﬁcant facilitative factors for evolutionary rate lie mostly in the changing architecture of developmental modularity in the epigenetic environment, in the link with changing canalization regimes. At the genetic level itself, factors such as differential sequestration or mutation rates and propensity for gene duplication are clearly of great signiﬁcance in this context, as with changing parameters in pleiotropic balance (see Chapter 12).

Extrinsic Factors of Anagenetic Rate Evolutionary rate in general is determined by a heterogeny of endogenous plus extrinsic factors derived from both clado- and anagenetic sources (selectional regimes, limits of adaptive potential, canalization, etc.). However, we must make a distinction between those largely endogenous factors tending to retard initiation of anagenesis, and the mainly extrinsic ones tending in particular to affect allotelic rates in the longer term. The Effect of Benign and Hostile Niche on Evolutionary Rate Extrinsic factors affecting evolutionary rate arise in the external environment, speciﬁcally in the lineage niche. The value of allotelic rates lies in the manner in which the behavior of the same anagenetic sequence evolving at different rates in paralleling lineages can shed light on the signiﬁcance of the benign versus hostile niche dichotomy, in terms of how the latter can be extended to encompass the macroniche in the context of the isotropic niche proﬁle—and this must at times constitute the functional link in the development of evolutionary rate differentials between lineages diverging at a major Renschian node. Here, it is also clear that our analysis of evolutionary rate must additionally take into account the input from logistic adjustment. While steep selection gradients may be observed during 움-anagenesis, it does not necessarily follow that design improvements carrying a large input to adaptive potential always establish a selection interface capable of generating rapid evolutionary rate. If mortality factors are predominantly stochastic in nature, then selectional activity will be low in the structural domain, and this will be reﬂected in low evolutionary rate. Evidence for differential rates between paralleling lineages can thus be used to examine the effect of projection of the benign–hostile niche dichotomy into lineage time, where such factors inﬂuencing evolutionary rate have a supraspeciﬁc effect that is sustained well beyond the domain of ambient clado-

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genesis. The question of the inﬂuence of the benign–hostile adaptive niche dichotomy must be approached in two stages. First, we must examine how different selectional regimes affect the base rate of evolution in the context of the equation set of the adaptive system. Following this, we must go on to examine certain other consequences of both the benign and hostile niche in the context of the greater phyletic lineage. Evolutionary Rate in Equations of the Adaptive System The benign versus hostile niche dichotomy has been identiﬁed as a signiﬁcant factor in determination of a large differential in certain axial versus tangential resolutions of major cladogenetic potential. How can this mechanism be understood through the equation set of the adaptive system? It is ﬁrst of all necessary to see how evolutionary rate arises at the population level in order to examine the question of how this may be projected to the lineage level. Low evolutionary rate must at times be equated with low selection pressure, and the latter may then be a corollary of lowered competition. Even with high population numbers, this situation could in fact occur in the presence of high levels of ‘‘passive’’ competition, that is, where no heritable differential exists between survivors, namely, in that circumstance where mortality factors are predominantly stochastic in nature. The causality for competition levels in a given gene pool would then lie with the degree of incidence of stochastic as against selectional mortality, so that low selection pressure must therefore have some link with the fecundity offset strategy (Chapter 4). In the context of the nonselective offset, reproduction ‘‘overshoots’’ precisely because of the problem of stochastic mortality factors; therefore, evolutionary rate must be some function of the differential between fundamental and real adaptive states, speciﬁcally as an index of the level of deterministic activity between organism and environment. Thus, there is a causal link between evolutionary rate and the phenomenon of r versus K population regulation strategies. So-called r-strategists have a low fundamental adaptive state, and K-strategists have high Af, since the former will always be linked with increased fecundity, purely as an offset to stochastic mortality. How then can the benign–hostile adaptive niche scenario and its apparent inﬂuence on evolutionary rate be represented in the equation set of the adaptive system? Given that competitional regimes have been implicated (see above), a dichotomy must be identiﬁed between ‘‘active selectional’’ versus ‘‘passive logistic’’ competition. It is useful at this point to brieﬂy recollect the manner in which density dependent selection affects the evolutionary rate of lineage, in consideration of effects relating to the so-called benign–hostile adaptive niche dichotomy: Niche type

Level of density dependent selection

Hostile Benign

Low High

The effect of the benign–hostile niche dichotomy in the equation set of the adaptive system can then be understood as follows: ‘‘shared K’’ is the popula-

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tion ceiling operating with respect to competition space (K being deﬁned as a limiting factor linked to density dependent mortality), while stochastic mortality factors are those that are not actually linked to selectional mortality. We can now consider a factor, J, which expresses the probability of individual-toindividual encounter of the kind constituting a competitional element linked to a heritable differential between genotypes, so that J thus reﬂects the level of selectional as against stochastic mortality acting on a population. The concept of J can furthermore be extended to include sequestration from selection, to thus encompass a complex input from different hostile niche regimes. J thus reﬂects the collective inﬂuence of stochastic mortality factors in the external environment and/or any endogenous factors tending to facilitate ‘‘competitional bypass.’’ To understand how evolutionary rate is affected by J, it is necessary to recall that the coefﬁcient of ﬁtness W can be located in the Lotka–Volterra equation set, speciﬁcally in the 움 factors. Accordingly, it must be that J affects W through interaction with the latter: dN1/dt ⫽ rn1 ⫻ N1 ⫻ (K ⫺ N1 ⫺ J ⫻ 움21 ⫻ N2)/K, etc. Thus, whenever J ⬍ 1.0, W will be depressed as a function of the differential between active and passive competition, and only when J ⫽ 1.0, is W a direct function of 움. Accordingly, J will be high in the benign niche, thus allowing a deterministically organized structural adaptive response, but it must be low in the hostile niche, so reﬂecting a predominantly logistic adaptive response with limited penetration of selection and thus also low evolutionary rate. Stochastic inﬂuences thus lie diversely with random mortality factors in the hostile niche, and/or in generally low mortality levels owing to sequestration. The genetic scenario for evolutionary rate differentials can now be partially understood as follows: in the hostile niche, some ‘‘good’’ genes are retarded through stochastic mortality, and some ‘‘bad’’ genes may even tend to be perpetuated through stochastic survivorship. However, any perpetuation of negative genes via stochastic survivorship factors is transient and never iterative, whereas any decrement to the ascendency of positive genes in an anagenetic sequence will in fact tend to have an iterative effect on evolutionary rate. The hostile niche may also manifest sequestration from the action of selection (for example, shelter from predation) and is thus not to be seen as a decrement caused exclusively by ‘‘stochastic override’’ of selectional activity. Here, s is depressed, not so much through stochastic mortality factors, as through diminution of the level of mortality itself. Stochastic survivorship factors are thus incorporated into the rationale for differential evolutionary rates where competition in the lack of any heritable differential is expressed, and evolutionary rate may also be depressed where bypass is manifested in the sequestration strategy, so that the effect of the above factors on evolutionary rate may perhaps often tend to be a compound one in the hostile niche. Before leaving the question of factors affecting evolutionary rate of lineage, we must also realize at this point that it is entirely unrealistic to assume that lineage rates operate at some predetermined steady rate. There will obviously be many periods of time when no change at all is occurring (owing to lack of

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adaptive potential, for example). Consequently, evolutionary rate as described by the above equations does affect ‘‘instantaneous’’ rate, but is not directly synonymous with lineage rate, this fact having already been anticipated in our earlier treatment of the intrinsic selection gradient of anagenesis in terms of a probability distribution (see previous chapter). This problem of intercalation will be investigated further at a later point (see below). The signiﬁcance of the benign–hostile niche dichotomy is that this will ultimately affect the averaged-out rate in a manner describing the dichotomy between base rates in (for example) bradytelic as against ambient rate lineages, while being of particular interest with respect to the seemingly paradoxical phenomenon of allotelic rates.

EVOLUTIONARY RATE OF LINEAGE AND THE ADAPTIVE CORRIDORS CONCEPT How can allotelic differentials in population evolutionary rate be extrapolated to the level of phyletic lineage? The basic assumption in attempting to answer this question is that the anagenetic sequence continues to expand the adaptive niche within the context of a benign or hostile environment, and that this continues over a cascade of subsequent speciation events owing to the presence of an isotropic niche proﬁle with respect to the benign–hostile niche dichotomy itself. From this situation, we arrive at the concept of an evolutionary rate that describes the adaptive corridor of a lineage, deﬁned in terms of an extended temporal dimension to the benign–hostile niche dichotomy, in terms of gravitation toward predominantly structural versus logistic attractors (see Chapter 6). In this analysis, it is necessary further to conﬁrm our deﬁnition of ‘‘frame of reference.’’ We have already excluded allomorphic patterns of change from the domain of evolutionary rate, in order to concentrate on effects observed at the lineage level. In the analysis of evolutionary rate differentials between lineages, it is clearly most pertinent to look at changes in anagenetic evolution (with or without associated speciation). That is to say, we are concerned for the present with factors inﬂuencing unidirectional change in the domain of speciation time and beyond, building on principles established in the above investigation of rate differentials at the population level.

Allotely and Lineage Rate As indicated earlier, scales for comparing evolutionary rate in terms of speciation and anagenesis in different lineages are valueless with respect to qualitative differentials. It is, for example, pointless to compare patterns of speciation in insects with that in mammals, owing to gross differentials in the respective geomorphology of gene reservoir space alone. Likewise, it would be valueless to attempt to compare the anagenetic evolution of the vertebrate wing with that of the eye, even within the same lineage. Rather less obviously perhaps, a comparison between 움 phase anagenesis in one lineage and 웁 phase in another also affords no useful information. Unequal rates for the same anagenetic sequence following a course of parallel evolution in different lineages (allotelism) thus constitutes the only valid evolutionary scenario for analysis of causal-

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ity. Only with allotely is it possible to separate extrinsic from endogenous factors, given that very large differentials in endogenous adaptive potential seem unlikely in closely related lineages manifesting anagenetic parallelism. The allotely approach clearly also excludes differentials between 움- and 웁anagenesis, so that we are not concerned with evolutionary rate differentials during the course of a single anagenetic sequence within the trajectory of a unique lineage (where there may be considerable inﬂuence of intrinsic constraints). Much allotely is likely to be identiﬁed during 웁-anagenesis, since this is when parallelism is most likely to be manifest in extant faunas and in well preserved fossil lineages. Again, the structural attractor will probably have become tightly channeled by later anagenesis, so that paralleling ‘‘trends’’ will be more likely to follow much the same structural path in different lineages. The effect of a benign–hostile niche proﬁle differential as this affects lineage level evolutionary rate may thus frequently be manifested in allotelic evolutionary rates, whenever parallel evolution is expressed. Evidence in favor of the allotelic rates concept will perhaps be most manifest in living bradytele taxa (as well as being implicit in much of the paleontological data). The implications of allotely must also be considered for cladogenetic rates.

Adaptive Corridors The adaptive corridor of a lineage is the static niche proﬁle projection of the benign–hostile niche dichotomy, as this affects evolutionary rate. There are thus ‘‘wide’’ and ‘‘narrow’’ (or benign and hostile) adaptive corridors, linked to an isotropic lineage niche proﬁle. The adaptive corridor factor inﬂuences evolutionary rate directly, rather than through passive constraintive mechanisms (which latter are more likely to be implicated in evolutionary anachronism or in facultative endogenous factors causal to rapid evolutionary change during 움-anagenesis). The adaptive corridor is thus a reﬂection of the ongoing gap between inputs from structural as against logistic domains in the adaptive response, and as argued earlier (see Chapter 6) this is likely to mean a large dichotomy in the extent to which a selection interface is manifested in the benign versus hostile adaptive corridor (especially in sub- or hypoparametric niche space). Lineages with a long-term commitment to benign niche will therefore have a wide adaptive corridor and higher intrinsic evolutionary rate, while those existing in a hostile environment will have a narrow adaptive corridor and a lower adaptive index and average evolutionary rate. Following the above line of argument, bradytely is thus explicitly linked to the hostile, and tachytely to the benign adaptive corridor. In bradytely, stochastic mortality factors have a low probability of becoming linked to any selection driven structural adaptive response, tending thus to be met by logistic adjustment in the nonselective offset of fecundity. With the tachytely strategy, selection can operate at maximum level, and little or no stochastic override of (or sequestration from) selection occurs. Paradoxically, apparent niche stability thus promotes maximization of selectional drive, and hostility is causal to generation of the lowest base values of s. However, we must recall that the

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term ‘‘hostility’’ is an expression of the degree of tendency toward the evolution of a logistic rather than deterministic response in the structural component of the adaptive ensemble, and it can also be shown that high levels of selectional activity may be channeled toward adaptive equilibrium, rather than to evolutionary change! The longer term effect of the dichotomy between broadly benign and hostile niche types thus becomes evident when this differential enters the evolutionary scenario of anagenesis via the macroniche, and this is most noticeable where allotely occurs because of divergence in adaptive corridors for n paralleling lineages. Taking parametric niche space as the ‘‘master switch’’ in the adaptive cascade (see Chapter 2), then the primary adaptive shift must have determined both the occlusional and adaptive zones of a lineage (Chapter 17) and also its intrinsic evolutionary rate. Many traits actually affected by allotelic rates seem most likely to belong in the sub- or hypoparametric category of adaptive niche space, as these link to the larger dimensions of abiotic niche space: Stebbins (1949, 1950, partly following Schmalhausen, 1949) observed that the slowest evolving plants rely on high fecundity, whereas those with a more ‘‘ambient’’ evolutionary rate have resistant spores and seeds, the fastest evolving lineages tending to have animal carried seeds and pollen. This clearly exempliﬁes the link between the fecundity offset strategy and adaptive corridor. Similarly, many living monotrysian and lower ditrysian Lepidoptera such as the Hepialidae and Cossidae, are known to have high fecundity linked to a hostile niche (see below). Observations on extant bradytelic lineages suggest that many organisms expressing relative primitiveness also gravitate toward sequestered environments: In Lepidoptera, ‘‘aphagy’’ (loss of functional mouthparts in the adult stage, usually also linked to a brief, ephemeral adult existence) often typiﬁes a sequestered environment in the adult stage, and it is frequently associated with relative primitiveness in each lineage in which aphagy occurs (Lasiocampidae, Lymantriidae, Notodontidae, etc.). In the early developmental stages of primitive Lepidoptera, xylophagy (or detritivorism) is a frequent adaptive strategy. For example, the primitive taxa Tineoidea, Cossoidea, and Castnioidea show this, as do some monotrysian families. In these examples, it is possible that the adaptive corridor has been inﬂuenced jointly by sequestration and stochasticity in the lineage niche. In the micro–macro ditrysia dichotomy, many highly polyphyletic traits operating at the family and superfamily levels show a gradistic differential that can only be due in turn to allotelic expression of evolutionary rate (see Chapter 21), and this appears to be linked to a simple primary adaptive shift from a predominantly cryptophagous to exophagous larval habit, reﬂecting a move into a benign adaptive niche regime in the ‘‘macro’’ domain. Stanley (1974) considered that the greater evolutionary rates seen in mammals compared to bivalve molluscs were due to a differential

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in the characteristic intensity of competition in the two lineages. Mammals typically show a K-selection strategy in specialized feeding habits, highly developed behavior, and mobility and social interactions, whereas weaker competition is associated with primitive behavior patterns, generalized feeding habits, ability to endure long periods of starvation, etc., in molluscs. Stanley also argued that the high evolutionary rates of reef building rudist bivalves were due to competition for space. The above observations clearly offer good evidence for the view that the adaptive corridors scenario does in fact lie behind a low evolutionary rate of lineage. Allotelism in paralleling trends (such as those studied in Lepidoptera) can also be shown to seriously challenge the methodology of cladistics (Chapter 21). Hypotelic Rate in the Benign Adaptive Corridor Given that an intrinsic selection gradient has been shown to exist for anagenesis and that the adaptive corridor phenomenon must have some effect on the overall trend in evolutionary rate in a lineage, we must now ask, in what way can evolutionary rate vary around the fundamental selection gradient curve itself? There are, in fact, two ways in which the selection gradient can be diminished, the ﬁrst of which can be deemed to be almost universal. Firstly, we must examine the damping effect on evolutionary rate arising from adaptive equilibrium in the context of the benign adaptive corridor. Here, we can see that a more realistic derivation of the intrinsic selection gradient equation must also take account of factors that are not intrinsic to anagenesis, in that we must consider the essential inﬂuence of leading effect allomorphism (see Chapter 14). This problem can be approached using an artiﬁcial analogy in the form of a pair of interacting difference equations which separately reﬂect the contributions of anagenetic change (⌬WA/dt) and change in the domain of adaptive equilibrium (⌬Wa/dt) to selectional activity in the adaptive system.* Bearing in mind our earlier conclusion, that each selection interface has to be measured against the total one (⌺ W ), clearly a growing element in Wa must tend gradually to override the anagenetic contribution to overall ﬁtness. This can be simulated in the chosen equation set, one equation of which must be affected by accumulative change in the other, the second equation of the pair being inﬂuenced only by degree of change in each successive generation with respect to the ﬁrst (the ‘‘sigma–delta’’ equation set): ⌺ WAt⫹1 ⫽ ⌺ WAt ⫹ rA ⫻ WAt ⫻ (L ⫺ WAt ⫺ ⌺ Wat) ⌺ Wat⫹1 ⫽ ⌺ Wat ⫹ ra ⫻ Wat ⫻ (L ⫺ Wat ⫺ ⌬WAt) where L ⫽ adaptive limit and r ⫽ differential owing to developmental modularity, mutation rate, etc. In the above equation set, ⌬WA is depressed by ⌺ Wa, but ⌬Wa is only affected by the WAj increment per step. The effect is that the selective value of each anagenetic increment (⌬WAj) is depressed by expansive ingression of adap* That is, we are continuing to use the intrinsic selection gradient of anagenesis approximation introduced in Chapter 17.

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tive equilibrium, such that ⌺ WAj and ⌺ Waj gradually converge on 0 and 1.0, respectively. This is due to the dichotomy between ‘‘ﬁxation’’ (in anagenesis) and ‘‘perpetuation’’ (in allomorphism); that is to say, the allomorphic contribution to the active selection interface is gradually increasing with time, but anagenetic increments simply pass to ﬁxation from one time frame to the next, leading to a mutual ‘‘race’’ between adaptive equilibrium and anagenesis for dominance of the selection interface (Fig. 108). The effect of the above equations is most pronounced in terms of the extent to which ⌺ W differs in the ‘‘free’’ as against interaction situations in the anagenetic integral curve (see Fig. 109 and Chapter 17).

FIGURE 108 Hypotelic evolutionary rate in the intrinsic selection gradient of anagenesis: ⌺ WA

and ⌺ Wa (above) as components of the active selection interface. ⌺ Wa eventually becomes the only component of the selection interface, and potentially positive anagenetic increments fall to a near neutral value. (X ⫽ time; Y ⫽ L ⫽ adaptive limit.)

The above equations clearly describe a family of constrained curves which reﬂect greater and more rapid depression of anagenetic evolutionary rate as a function of increasing input to the domain of adaptive equilibrium, the latter tending to impinge on the system as time progresses. In this scenario, the ‘‘raw’’ intrinsic selection gradient is visible only when the input from the anagenetic component approaches 1.0, evolutionary rate being diminished with any lowering of that value in the face of expansion in allomorphism. The above of course constitutes only an approximation to reality, particularly since it is not the entire allomorphic component which affects anagenetic rate, but some restricted proportion thereof, as determined by the extent to which the ambient leading effect selection interface lies on chromosomes other than that carrying the anagenetic increment. There is therefore a coefﬁcient ␦ expressing this relationship: ⌺ WAt⫹1 ⫽ ⌺ WAt ⫹ rA ⫻ WAt ⫻ (L ⫺ WAt ⫺ ␦ ⫻ ⌺ Wat)

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FIGURE 109 Two anagenetic integral curves: with no inhibition (top) and as depressed by accumulated allomorphism in the context of hypotelic evolutionary rate (bottom). (X, Y are as Fig. 108.)

It is proposed here that hypotelic evolutionary rate constitutes that depression owing to gradual impingement of leading effect allomorphism, and that this factor tends to evolve in the speciﬁc context of a benign adaptive corridor. Hypotelic rate may thus be regarded as being that state toward which adaptive systems tend in a ‘‘benign’’ organism–environment relationship. Consequently, the hypotelic curve constitutes a more accurate representation of real (as against fundamental) evolutionary rate manifested by an anagenetic sequence, than does the raw intrinsic gradient model discussed earlier. Hypotelic Evolutionary Rate in the Context of the Anagenetic Phase As we have just seen, part of the essence of a revised model of the intrinsic selection gradient of anagenesis is that during periods of low evolutionary rate of lineage, much of the adaptive state is determined by adaptive equilibrium lying beyond the domain of our anagenetic point of interest, when the selection interface is dominated by leading effect allomorphism. Niche-diversifying activity will then tend to predominate over anagenetic change, particularly as the function shift component comes to play a greater role in 웁-anagenesis. At this juncture, the overall contribution to the ambient selection interface from anagenesis must diminish, the inﬂuence of extrinsic variational activity thus gradually assuming a dominant role in determination of the adaptive state as the leading factor comes to be largely controlled by allomorphic activity. In terms of anagenesis in general, we must therefore suppose that the ambient evolutionary rate ranges observed for many lineages are not raw intrinsic selection gradients, but are tending gradually toward a hypotelic one depressed by ingress of leading effect allomorphism in the benign adaptive corridor. This question will be examined in greater detail in the context of evolutionary stasis (see next chapter).

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The Hostile Adaptive Corridor and Bradytelic Evolutionary Rate In the hostile adaptive corridor, evolutionary rate is depressed by the J factor in the system equation set (see above). This circumstance describes the relative inputs to mortality from selectional as against nonselective factors, in the balance between stochastic and deterministic factors, namely, when selectional mortality is of rare occurrence. The J factor thus depresses ⌬WA/⌬t, so affecting evolutionary rate directly and thus potentially greatly extending the time taken to reach the anagenetic limit. This identiﬁes true Simpsonian bradytely as an apparent lowering of the adaptive limit itself, which can actually be seen more realistically as a residual potential that may, at least theoretically, ultimately be reached. The latter scenario is an important element in the hostile adaptive corridor, although it should also be borne in mind that, while some component of selection is affected by the ‘‘no encounter’’ element, other mortality factors may simply be sequestered out (the latter inﬂuence applying also to density independent factors). Predictions of the Adaptive Corridors Hypothesis What evolutionary phenomena would be expected from the existence of benign–hostile adaptive corridors? It is in fact possible to predict certain levels of activity both in speciation and in anagenesis, in terms of evolutionary rate and perhaps also in longevity of lineage. A benign adaptive corridor should support more species for a time, but it may be more prone to eventual catastrophe if its stability lies in complexity of the adaptive system. Conversely, a hostile adaptive corridor may support very few species for a much longer period of time. Low penetration of selection means low cladogenetic potential but greater vulnerability to stochastic mortality factors. Thus, the adaptive corridors scenario should affect, not only anagenetic rate, but also rate of speciation and longevity of lineage. In particular, the benign adaptive corridor should favor a high level of balanced polymorphism and structural allomorphism in dynamic equilibrium, the latter tending to build up toward the 웁 phase (see above):

Effect on adaptive equilibrium Effect on cladogenesis Effect on anagenesis

Benign adaptive corridor

Hostile adaptive corridor

High allomorphism High speciation rate High intrinsic rate

Low structural allomorphism Low speciation rate Low intrinsic rate

Bradytely, that evolutionary scenario in which a very low evolutionary rate is conferred on a lineage by virtue of invasion of a hostile adaptive corridor, leads to persistence of exceptionally primitive anagenetic states, the primary causality being the lowering of both inter- and intraspeciﬁc competition of the selectional kind. Some hostile adaptive corridors should thus contain ‘‘living fossil’’ taxa. Bradytely may also be linked to overspecialization in the hostile niche, and thus also to ultimate ‘‘extinction vulnerability’’ (see Chapter 20). Hence it may be that relatively few lineages of this kind actually do survive in the very long term: Simpson (1953) described four categories of ‘‘evolutionary relicts’’: numerical (‘‘rare survivors’’), geographic (limited distribution com-

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pared to ancestral lineage), phylogenetic (‘‘slow rate survivors’’), and taxonomic (taxa with less diversity than previously). Combinations of Simpson’s four categories also occur, especially since they may frequently be interlinked in a deterministic sense to bradytelic evolutionary rate, for example, the coelacanth Latimeria (all four simultaneously), also Sphenodon and ginkgo. Some of the most primitive families of Lepidoptera are also of restricted distribution (Agathiphagidae, Mnesarcheidae, and others). Limulus, on the other hand, is not rare, is fairly widely distributed, and was never an abundant group, and the same is at least partly true for the moth family Hepialidae. The latter examples are nevertheless relict taxa in the phylogenetic sense (and have a relatively small number of living species compared to other, related families). Clearly, not all of Simpson’s criteria can be presumed to demand an adaptive corridors explanation (for example, a numerical relict group may be on the decline owing to some factor other than primitiveness linked to a hostile environment). The value of bradytely (equivalent to the phylogenetic relict state) is that it is particularly instructive in underlining the fundamental causalities for the adaptive corridors theory in general, by virtue of being an exemplar of the extreme case. There seems to be no clear evidence that bradytely (as against relative hypotely within the context of the horotelic range) is affected by intrinsic factors in the very long term, and this tends to underline the probability that input from controlled inﬂuences in the adaptive niche do indeed constitute the overriding factor in determination of evolutionary rate. Simpson proposed that the reasons for bradytely lay in the relationship between organism and environment as this evolves in generalized rather than in specialized groups. Although there is no doubt that paleontological evidence exists for survival of generalized lineages during times of catastrophic extinction, it is nevertheless equally evident that many living fossils have at least one extreme specialization (which may of course not be structural ), and this again would be a predicted corollary of the adaptive corridors model: The extant lungﬁshes, for example, are not a generalized ‘annectant’ group evolving toward the terrestrial adaptive zone, but a ‘dead-end’ branch of an ancient lineage that has adopted a highly specialized mode of life which offers little or no further adaptive potential for advance toward a truly terrestrial mode of life. The links between bradytelic evolutionary rate and specialization will be examined more closely in the context of episodic evolution (see below).

EPISODIC EVOLUTION Various models explaining the observed variation in rate of evolutionary change have been proposed above. However, the benign–hostile adaptive corridors scenario does not explain movement from a state of relative stasis to one in which evolutionary change is occurring. How, then, does evolutionary rate

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vary within the trajectory of a lineage, given the likelihood of the existence of ‘‘periods of no change’’? In discussing this problem, we encounter the question of episodic evolution, that situation where evolutionary change occurs in periodic bursts rather than via more evenly spaced incremental steps (see Brown, 1987). Rensch (1959) stated that it had long been recognized that many lineages pass through an explosive phase of radiation manifesting an extraordinary acceleration of evolutionary rate, at around the time of origin in about half the groups analyzed and later in the remainder. Simpson (1953) was in fact the prime mover in arguing an effective case for ‘‘quantum change’’ in evolution. This episodic phase was generally thought to be followed by more or less ‘‘stationary phylogeny’’ in which many earlier types die out and others show slower adaptation to the environment. Extinction of apparently suboptimum types is common after the ‘‘explosive’’ phase: The carnassial teeth in certain primitive Eocene carnivores (Creodonta) were located too far forward to allow further improvement, and this group did not survive in the longer term. Similar ‘‘dead-end trends’’ have been widely reported in the fossil record (see Simpson, 1953). The question of episodic evolution is clearly closely linked to evolutionary rate (particularly in the context of the benign adaptive corridor), and it has recently become surrounded by considerable controversy concerning the punctuationist versus gradualist schools of thought: Fenster and Sorhannus (1991) stated that gradualism and punctuated equilibrium can be distinguished at least in part on different predictions regarding evolutionary rate. Reciprocal Effects of Speciation and Anagenesis on Evolutionary Rate of Lineage Quite apart from the question of rate change within a phyletic lineage, there is also an important question concerning the manner in which lineage rate affects (and is in turn affected by) the interaction between clado- and anagenetic modes of evolutionary change. Although cladogenesis and anagenesis are partially independent mechanisms, they clearly must also manifest a large interactive role in the sculpting of a phyletic lineage; however, the extent to which this interaction actually occurs has been the center of much controversy in recent times. This question clearly links to the dichotomy existing between 움and 웁-anagenesis where, as we have seen earlier, higher rates of speciation could well be deemed to occur during the latter phase. How are rates of speciation and anagenesis actually linked? High endogenously generated anagenetic rates seem probable, as, for example, with respect to the tachytelic phase associated with the occlusion zone or adaptive grid. Rates of speciation and anagenetic change cannot, however, be taken as causally independent events, nor can the selection interface for speciation be presumed invariably to exist in complete isolation from that for anagenesis, so that rates of speciation and phyletic evolution cannot be mutually autonomous. High levels of anagenetic change must at times accelerate speciation, and high levels of cladogenetic activity must similarly accelerate anagenesis:

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Wright thought that ‘‘a macroevolutionary step depends not only on establishment of a major character change but also on reproductive isolation.’’ However, the phyletic occlusion scenario shows that this is certainly not the case. Simpson conversely believed that tachytelic anagenesis could proceed via infraspeciﬁc evolution alone. Unless a lineage can be supposed to be able to manifest a high level of anagenetic change while exhibiting no particular acceleration with regard to speciation rate within the same time frame, anagenetic change in allopatric populations of a single parent gene reservoir must often lead to a greater probability of speciation in the eventual neosympatric situation. Anagenesis does indeed possess the capacity to occur independently of speciation (e.g., in the sense of continuing via parallel evolution when interrupted by cladogenesis), but clearly it must inevitably also affect rate of speciation to some extent. Similarly, speciation events can (and usually do) occur quite independently of anagenesis, but subsequent evolutionary change could well have an inﬂuence on the buildup of fresh anagenetic forces. A lineage could therefore be highly speciose while expressing little anagenetic change, while at the same time, the postspeciation cladogenesis scenario (see Chapter 6) may subsequently come to invoke changing selectional priorities (which might include increasing pressure to manifest anagenetic change). From an entirely different viewpoint, proliferation of species in a lineage could of course also slow down anagenesis: the greater the number of species sharing a niche, the less is the opportunity for niche-expanding adaptive change. As a general rule then, anagenetic and cladogenetic events must at the very least express reciprocal effects on evolutionary rate, some of them facilitative, others constraintive in nature. However, this need not imply that the one mode is necessarily always a function of the other (it must be clear by now that there is really no ‘‘general rule’’!). In conclusion, anagenesis must often tend to accelerate speciation, and speciation, anagenesis. However, there may well be periods when one or the other may tend to dominate evolutionary change. Is it possible to predict what circumstances permit either scenario to predominate?

Quantum Evolution and Punctuated Equilibrium The quantum evolution and punctuated equilibrium hypotheses constitute proposed models of episodic evolution centered around the anagenetic and cladogenetic mode, respectively. Simpson’s (1953) concept of quantum evolution stresses ‘‘phyletic evolution’’ as the mechanismic root of episodic evolution, whereas Eldredge and Gould’s (1972) punctuated equilibrium considers speciation as the key to understanding this phenomenon. Furthermore, in quantum evolution, lineage rate is presumed to drop back to lie somewhere within the horotelic range following the quantum phase itself, whereas in punctuated equilibrium, a tachytelic phase is followed by evolutionary stasis. In the present study, we have to consider also the role of phyletic occlusion (Chapter 17), and it is particularly necessary to ask (a) whether or not some anagenetic interpretations of quantum evolution could be regarded as constitut-

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ing speciation, and also (b) whether the apparent role of speciation in punctuated equilibrium might not in fact constitute phyletic occlusion with respect to an anagenetic selection interface. In fact, some of the evidence for quantum evolution can probably be quite readily interpreted as containing a likely cladogenetic element; similarly, much of the data promoting punctuated equilibrium could be interpreted as incorporating probable anagenetic change. Both quantum evolution and punctuated equilibrium can be additionally challenged on the basis of the incompleteness of the fossil record! However, circumstantial evidence for episodic evolution sensu lato is conclusive, and this existing body of evidence can also be shown to be strongly supported by theoretical considerations (as well as by paleontological studies in which the record is more or less continuous). The gradualist view of evolutionary change is seriously challenged in the ﬁrst place by clear evidence in the fossil record (as well as by implications of certain neontological data) for episodes of remarkable tachytelic anagenesis and/or speciation. As already stated, Simpson believed that tachytely is simply a normal factor surrounding the origin of higher categories, a fact which he thought helped explain systematic deﬁciencies in the fossil record (some part of his evidence thus constituting ‘‘inference from evolutionary gaps’’). Simpson stated that this kind of extrapolation usually locates incredibly remote dates for the origins of higher groups (see below). Simpson theorized that tachytelic evolution occurs while populations are shifting from one adaptive zone to another, and he also felt that this situation had to be clearly distinguished from rapid speciation: Wright (1982b) also believed that rapid evolution occurs under special circumstances: ‘‘The evolutionary potentialities of most species are probably restricted to very slow, gradual progress in adaptation to the single ecological niche which they occupy, by the occupancy of all related niches by other species.’’ This is overcome when new areas are invaded (as on islands) or when opportunity arises through extinction of other lineages, also by evolution of a new adaptive type like the echinoderm larva. Phases of extremely rapid evolutionary change have thus been very widely reported in the fossil record. Are intrinsic or extrinsic factors involved? And is massive species proliferation or tachytelic anagenesis implicated? There are obviously two possible scenarios for rapid macroevolutionary change of the above kind: tachytely could occur through either infraspeciﬁc or transspeciﬁc anagenesis. This problem in fact identiﬁes the fundamental dichotomy between punctuated equilibrium and quantum evolution. Model 1. Quantum Evolution: Quantum evolution describes macroevolutionary change occurring via apparent species proliferation owing to rapid intraspeciﬁc anagenesis occurring through the mechanism of phyletic occlusion in the context of 움-anagenesis, followed by lowered evolutionary rate as the 웁 phase is approached. Model 2. Punctuated Equilibrium: Punctuated equilibrium is evolutionary change through species proliferation, diagnostic of massive cladogenetic activity in the occlusion zone. Some versions of

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the punctuated equilibrium hypothesis also demand saltational evolution (as distinct from rapid iterative incremental change), this additionally being presumed to be non- or even maladaptive in nature as a result of the inﬂuence of stochastic factors. Additionally, anagenesis is usually relegated to the status of being a purely transspeciﬁc event only. A lineage may become prone to rapid speciation at certain periods owing to changes in the physical environment conducive to population isolation followed by neosympatric gene pool competition, or else through rapid evolution of prezygotic isolation factors in a multidimensional spatial zone. Such episodes may favor and facilitate accelerated evolutionary change, which may be linked to concurrent anagenetic progress manifested in the species-to-species interaction itself. Quantum Evolution and Punctuated Equilibrium Compared The above models of acceleration in evolutionary rate of lineage are clearly fundamentally different. Quantum evolution stresses anagenesis, while punctuated equilibrium highlights speciation. However, both clearly reject gradualism (in the sense of the incremental steps of evolutionary change being approximately the same at all points during the unraveling of a macroevolutionary anagenetic sequence). A large problem of interpretation clearly exists, however, in that it is often not possible in practice to distinguish between ‘‘true’’ and ‘‘phyletic’’ speciation, given the fragmentary data generally available in the fossil record. Both models of episodic evolution imply a state of relative stasis or of slow ambient change when the tachytelic phase is over, although here we must consider the whole horotelic range of evolutionary rates likely to be experienced by a lineage (hence, also, the likely heterogeneity of the term ‘‘stasis’’ itself; see next chapter). Episodic Evolution versus Phyletic Gradualism The third scenario, sometimes termed phyletic gradualism, makes no attempt to account for the paleontological data cited by Simpson and others (other than by making an unjustiﬁed claim concerning the universally fragmentary nature of the fossil record) and therefore cannot constitute a realistic alternative to the episodic model. However, much confusion has resulted from a lack of understanding of what gradualism actually is! The concept of ‘‘phyletic gradualism’’ criticized by Eldredge and Gould concerned ‘‘slow, steady change by degrees.’’ Another view of gradualism could be simply that evolutionary change occurs by means of incremental change. However, this must not be taken to imply that the rate at which these increments are added (in relation to periods of ‘‘nothing happening’’) is also uniform throughout the duration of a lineage. Indeed, it is now necessary to say that the latter interpretation is not supported either by theoretical considerations or by the fossil evidence and should thus be dismissed at the outset. Finally, it is necessary to add that the dichotomy between saltational and incremental change should not be allowed to cloud the issue concerning episodic

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evolution, since this is an altogether different dichotomy from that existing between episodism sensu lato and hard gradualism. Quantum Evolution in Theory Simpson believed that phyletic evolution generates a high evolutionary rate at the origins of new major groups, and indeed, as we have seen, the preponderance of niche-expanding adaptive shifts in 움-anagenesis clearly does indicate the likelihood of the highest evolutionary rate being manifested at this stage. Good supporting evidence for this scenario also lies in ‘‘missing annectent types’’ around the bases of many anagenetic lineages. Simpson also stated that within his view of quantum evolution, there are deﬁnite examples where a species (even a genus) has been transformed into another, and that it is ‘‘fairly well established that this happens with subfamilies—occasionally even families’’; also, he stated that the all-or-none element in quantum evolution arises from discontinuity in adaptive zones (see Chapter 17). In spite of gradualistic examples, most new species, genera, and families appear suddenly, and discontinuities are almost always present at the origin of higher taxonomic groups (especially orders and above). One possible corollary of the ‘‘evolutionary gaps’’ phenomenon is, indeed, that if speciational activity had been great during the early evolution of certain lineages, extant gaps might well have been fewer. However, the ‘‘missing link’’ scenario clearly does not necessarily exclude a transspeciﬁc interpretation, and Simpson’s somewhat extreme view did not accordingly ﬁnd widespread acceptance. A majority of contemporary workers would certainly doubt many of Simpson’s claims, given our present state of knowledge concerning the nature of species isolating mechanisms and the role of population movements in the generation of cladogenetic potential. The quantum evolution concept could nevertheless be valid for that situation where a changing adaptive response occurs in the immediate aftermath of transgression of the adaptive threshold surrounding the ﬁrst structural response to the primary adaptive shift of a lineage. Anagenesis may then predominate over rather than totally exclude speciation, as a function of evolutionary rate, particularly in the lack of opportunity for neosympatric cladogenetic forces to manifest any signiﬁcant inﬂuence. Simpson’s view of quantum evolution as ‘‘change of adaptive zone such that transitional forms cannot (or do not) persist’’ in terms of a process predominantly determined by infraspeciﬁc change also agrees in broad outline with the concepts of 움- and 웁-anagenesis, especially when considered along with the isopatric selection interface. Intraspeciﬁc anagenesis would be expected to predominate in 움-anagenesis, especially considering the ‘‘post-threshold’’ release of latent adaptive potential following the primary adaptive shift. However, a similar scenario could also apply to dynamic environments, if resolution of cladogenetic potential involves selectional substitution of many incipient species as species substitution, rather than major phyletic occlusion. Again, there is no reason to suppose that intraspeciﬁc anagenetic change occurs extensively in later anagenesis, nor indeed is there any theoretical construct that would in any case totally eliminate ambient speciational activity from 움-anagenesis either.

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The concept of 움-anagenesis thus clearly forms the principal theoretical support for quantum evolution, albeit with certain vital qualiﬁcations. Punctuated Equilibrium in Theory Owing to inherent weaknesses in Simpson’s concept of quantum evolution, Eldredge and Gould (1972) discounted the inﬂuence of phyletic evolution (including intraspeciﬁc anagenesis) during periods of rapid evolutionary change, maintaining that the latter must be linked to an increase in speciation. Their model would clearly be valid for that situation in which a changing adaptive response reﬂects migrational activity linked to a dynamic environment, and where genomic change does not involve iterative phyletic occlusion. Speciation will, in such circumstances, predominate over anagenesis in determining evolutionary rate, since there will have been ample opportunity for buildup of cladogenetic drive, either through multiple neosympatry or as a result of change in the prezygotic component (as with the speciﬁc mate recognition system, following Paterson; see Chapter 6). Eldredge (1985) also claimed that the punctuated equilibrium model is supported by the theory proposed by Mayr (1959 and elsewhere) that new species arising very rapidly in small, peripherally isolated populations could offer an explanation of ‘‘jumps’’ in the fossil record. Certain rather more controversial elements in the punctuated equilibrium hypothesis hold that ‘‘another consequence of the allopatric model is that morphological features distinguishing descendant species are present close after, if not actually before onset of genetic isolation.’’ Also, ‘‘Once established, a descendant species is unlikely to show gradual, progressive change as is the parental species. . . . We should not expect to ﬁnd gradual divergence between two species’’ (Eldredge, 1985). Eldredge and Gould (1972) thus proposed that new species evolve rapidly in allopatric situations from a small subpopulation of the original species, following the model ﬁrst proposed by Mayr (1959). In addition, and most signiﬁcantly, they also held that such periods of rapid change punctuate much longer periods of stasis, thus negating any real inﬂuence from either postspeciational divergence or infraspeciﬁc anagenesis. This is, however, a polarized viewpoint of a wider view that speciation may well be episodic, but with no good reason to exclude postspeciational divergence and anagenesis from the equation: We must therefore consider seriously the revised view proposed by Malmgren et al. (1983) that new traits probably evolve without regard to speciation, but may nevertheless show rapid transitions between longer term stable states in the context of ‘‘punctuated gradualism.’’* Supposed Random Factors in Speciation and Anagenesis Simpson’s original quantum evolution theory (1944) contained an initial ‘‘inadaptive phase’’ brought about by random factors, a view which he rapidly abandoned following criticism from Wright (1945). The theory of punctuated * Fenster and Sorhannus (1991) have also discussed the likelihood that other interpretations can be placed on the Malmgren data, namely, in view of the criteria by which evolutionary rate is measured (a criticism which of course applies equally to any punctuationist interpretation!).

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equilibrium also seeks to revive this aspect of the early Simpson hypothesis. Maynard Smith (1983) has, however, strongly criticized the punctuationist view that Mayr’s concept of speciation in peripherally isolated populations could imply a nonadaptive element (see also species sorting and effect hypothesis, Chapter 20). Similarly, he dismissed the view of Wright, that ‘‘direction of change in speciation is random in respect to large scale evolutionary trends, rather than being caused by within-population selection.’’ Arguments which have sometimes been raised against the actual existence of anagenesis have likewise been based on supposed random factors affecting ‘‘trends,’’ which latter term is clearly a heterogeny (in terms of including amphigenesis, vestigiation, anagenesis, and various other phenomena— sometimes apparently implying the additional presence of parallelism, sometimes not). Paradigm analysis (in the sense of Rudwick, 1964) is enough to dispel any suggestion that anagenesis is a random process in evolution, as is that related body of work inaugurated by Thompson (1917). Neontological demonstration through functional analysis with respect to the structure– function link also underlines the fundamental validity of the concept of anagenetic progress toward an essentially adaptive paradigm for structure. If the end points of anagenetic sequences are now seen to be adaptive, then they must have been so in the past also. Consequently, any hard structuralist interpretation used to dismiss the evolutionary role of anagenesis likewise holds no weight. The nonadaptationist claims, both of the early version of Simpson’s quantum evolution and of ‘‘strict punctuationalism,’’ cannot therefore be supported in any biosystematological analysis, for reasons already discussed in Chapter 15. This does not of course imply that suboptimal adaptive states (and transiently maladaptive ones carried by pleiotropic balance) cannot form some smaller part of the scenario of radical neomorphic change following a major adaptive shift (see previous chapter). The shifting balance hypothesis of Wright (see Chapter 13) has also been invoked as an explanation for punctuated equilibrium. However, this model is also decidedly lacking in support (see Chapter 15). Evidence for Quantum Evolution and Punctuated Equilibrium Eldredge and Gould (1972) deﬁned gradualism as the steady accumulation of microevolutionary change over signiﬁcant spans of geological time ‘‘as witnessed in generation-to-generation changes observed at the present time, as segments of a greater trend.’’ There is, in fact, very little doubt that some proponents of neo-Darwinism (at least up until the 1960s) ﬁrmly believed in this hypothesis. As stated by Fenster and Sorhannus (1991), the terms punctuation, gradualism, and stasis have not been deﬁned in a quantitative fashion (any more than have fast or slow with respect to evolutionary rate), and this naturally makes for difﬁculty in deciding what is implied in many interpretations. No evidence whatsoever exists for a universal application of ‘‘purist gradualism,’’ unless we conﬁne all evolutionary activity to ambient rate within adaptive equilibrium and microevolutionary change. However, good evidence exists for the reality of episodic evolution, partly following Simpson’s concept of

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quantum evolution, which remains valid at least in terms of a tachytelic phase followed by a subsequent lowering of evolutionary rate: In consideration of the slight difference between modern and Cretaceous opposums, Simpson stated that extrapolating backward from observed ambient rates in that lineage, the group itself would have arisen in the Precambrian. Similarly, the morphology of bats has also changed but little since the mid-Eocene, and following Simpson’s argument, backward extrapolation on the basis of observed ‘‘ambient’’ rates could here place the origin of the Chiroptera before that of the planet Earth! The oldest known bat Icaronycteris from the Eocene in fact scarcely differs from modern Microchiroptera (Rayner, 1989). More realistically, actual estimates for the apparent true origins of the mammalian orders suggest that the origin sequences occurred in about one-third of the time taken for subsequent diversiﬁcation, and as pointed out by Eldredge (1989), bats and whales could clearly not have arisen from terrestrial forms much more than 10 million years before the earliest known members of these groups appeared in the fossil record. Other evidence for rapid evolutionary change surrounding the origin of macroevolutionary lineages is widespread. For example, there are few indicators for the relationships of pterosaurs with other archosaurs, despite the fact that the pterosaur record is itself fairly comprehensive (Rayner, 1989). Of course, not all ‘‘gaps’’ automatically infer rapid periods of change as, for example, that between cephalochordates and craniates (see Carroll, 1997). In contradistinction to the above argument, we must of course also consider that, as Carroll (1997) points out, it is no longer necessary in the light of more recent discoveries to assume that the origin of major new structures invariably happens so rapidly that the transition is unlikely to appear in the fossil record. At the same time, however, where changes in such parameters as locomotor skeleton have been observed, this can indeed occur in as little as less than 1 My. The concept of an episodic adaptive substrate is clearly the only possible explanation of the extremely rapid, concerted changes seen in the origin of certain higher groups: The whale lineage appears to have acquired a whole suite of novel structural traits over a period of some 12 My, involving major transitions from terrestrial to aquatically specialized limbs and respiratory system. According to Carroll (1997), major locomotory transitions occurred over a 15 My period in the origin of birds, and only 5 My seems to separate ﬁshes from amphibians. It is also pertinent to add that, even if recent estimates of the adequacy of the fossil record are only approximately accurate (see Donovan and Paul, 1999), then these major transitions can only have occurred through episodism. It is clearly quite pointless to try to extrapolate from observed allelic frequency changes in polymorphism (or even in ambient speciation) in examples such as

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the cetacean lineage, since we are now clearly concerned with a series of nicheexpanding adaptive shifts that have invoked massive change in the morphogenetic landscape in the context of an entirely novel selectional regime. Nei (1987) offers perhaps the most obvious (and probably also the most overlooked!) argument in favor of episodic evolution in general, namely, that of the demonstrable rarity of mutations of the kind likely to invoke rapid, large scale change of the kind involved in the origin of new structural types. To this axiom, we must now add the parallel scarcity of external environmental conditions permitting a rapid adaptive response (as exempliﬁed, for example, by the observed rapid evolution of immigrant island biotas, where absence of the minor adaptive niche has apparently permitted acceleration of evolution). Although the above evidence clearly conﬁrms the reality of episodic evolution in general, the original Gould–Eldredge data for punctuated equilibrium have not, however, stood up to critical reexamination.* The Eldredge–Gould examples of punctuated equilibrium included Gould’s (1969) work on Poecilozonites, a pulmonate snail from the Bermudan Pleistocene which manifests an iterated paedomorphic trend, also the trilobite genus Phacops, which manifests a phyletic trend toward modulation in number of eye lens ﬁles. Subsequent reexamination of the same examples has in fact tended to seriously question the veracity of this evidence: According to Brown (1987), the four original stipulations of punctuated equilibrium following Eldredge and Gould are not supported by the examples used by these authors. Brown also held that the Poecilozonites and Phacops examples actually contradict the tenets of punctuated equilibrium, arguing, for example, that ecophenotypic variation and selection on local genotypic states linked to varying environmental parameters offer a perfectly acceptable explanation of the apparent ‘‘punctuational’’ relationships of supposed subspecies of the Phacops complex. Similarly, genetically determined traits cannot be distinguished from phenoplastic ones in Poecilozonites. Palmer (1985) examined one of the most discussed examples of punctuated speciational change in the molluscs from Turkana basin (Lewin, 1981). He showed that in the gastropod Thais, spiral sculpture is inherited as a major gene (presence of sculpture dominant to no sculpture), and that the phenotypic effect of genes controlling this can also be modiﬁed by environmental conditions. Certain ‘‘punctuational’’ events could thus be due to frequency changes within the existing genetic repertoire of adaptive capacity and/or to changing environmental conditions, as indeed one might expect from neontological studies of related species. The examples in question therefore may not actually be valid species units. In addition, Palmer also showed that the structural differentials between morphs had a clear adaptive signiﬁcance. The Gould–Eldredge examples could thus be interpreted as being changes in the domain of adaptive equilibrium, and the concern of these authors regarding * In discussing this problem, we shall leave deeper analysis of stasis until the next chapter and concentrate on punctuation in its links with the speciational mechanism.

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interpretation in terms of phyletic gradualism by lineage anagenesis appears to constitute something of an ‘‘Aunt Sally hypothesis.’’ Much of the argument surrounding punctuated equilibrium has tended naturally to dwell on the admitted imperfections in the fossil record. It is not unreasonable to suppose that events surrounding evolutionary change (rapid or otherwise) will rarely be encountered in the fossil record, since such occurrences are generally agreed to take place in small populations of restricted geographic distribution (see Chapter 14). Gingerich (1983) stated that the stratigraphic record is rarely complete enough on a scale of hundreds or even thousands of years to preserve rapid transitions. However, by the laws of chance, evolution cannot ‘‘always be happening some place else,’’ and there must be occasional snapshots of what actually takes place when there is morphogenetic change; some ‘‘ﬁne-grained’’ fossil series will therefore capture such events. Of even greater concern for the punctuated equilibrium hypothesis is the fact that where ﬁne-grained sediments have been examined, good evidence has been found which clearly supports gradualistic change: Sheldon (1987) studied Ordovician trilobites which apparently manifested speciational events linked to an anagenetic sequence for increase in number of pygidial ribs. However, closer examination of the strata in which the fossils were preserved revealed the existence of intermediate forms which ‘‘ﬁll in the gaps’’ between apparent species. This clearly does not support the punctuationist view that transitions between species are ‘‘instantaneous.’’ Barnosky (1987) also drew attention to several examples of signiﬁcant phyletic change occurring in mammalian lineages (see Carroll, 1997, for a discussion of these and other instances of proven gradualistic change). Sheldon (1987) also pointed out that a readiness to apply the Linnean binomial system to imperfectly representational fossil lineages constitutes a highly signiﬁcant factor behind some apparent examples of punctuation. As stated by Maynard Smith (1983), some of the evidence presented in favor of strict punctuational evolution may reﬂect the habits of taxonomists, rather than any real phenomenon. Eldredge (1995) has subsequently discussed Sheldon’s work from the standpoint of the punctuated equilibrium hypothesis. Despite disagreement with some details, it is agreed that Platycalymene and Nobiliasaphus do in fact show a gradual, more or less unidirectional trend with respect to increase in rib count over a period of some 3 My. It is thus agreed that Sheldon’s trilobite data do conﬁrm ‘‘phyletic gradualism’’ occurring over a period that is in fact 600 times longer than Eldredge and Gould’s original minimum estimate of ‘‘punctuational speciation time’’ and 60 times greater than the maximum. Quite apart from the discovery of data which clearly support phyletic gradualism, other problems have arisen which further question the validity of some of the data advanced in favor of punctuation. Sampling bias may also exist in the evidence for punctuated equilibrium, particularly in that observed patterns may simply be those of the most widespread species: Jablonski (1995) drew attention to the fact that the fossil record of shelly marine invertebrates is the most complete and reliable for global

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biodiversity analysis, and that taxa in paleontological databases are consequently skewed toward the more abundant, widespread, and geologically long-lived species; molluscan species durations are positively correlated with geographic ranges. In the above, we can see the difﬁculty of accepting that apparent examples of punctuated equilibrium are not also skewed toward a bias in the kind of phenomena most likely to be preserved (as with apparent stasis, manifested by the longest lived, most widespread, and thus most readily fossilized species). In the same way, punctuation must be at least partly a function of the extreme rarity of sediments capable of capturing evolutionary events that are both extremely localized in space and exceedingly infrequent in time. Discredited evidence aside, what other examples exist to support punctuated equilibrium? It has in fact been demonstrated that not all paleontological species criteria are typological, and similarly, not all ﬁne-grained sediments support gradualism: Jackson and Cheetham (1990) examined morphological species in Bryozoa from the standpoint of breeding experiments and protein electrophoresis, concluding that the ‘‘morphospecies’’ of paleontologists are most probably valid species units in this lineage. In contrast to the ﬁndings of Sheldon, they thought that their ﬁndings conﬁrmed punctuation. A rigorous reexamination of supposedly gradualistic transitions in the oyster genus Gryphaea through study of previously overlooked transitional fossil zones may also support a punctuationist interpretation (Hallam, 1982). The fact that evolutionary events here were paedomorphic trends may, however, indicate a more likely path toward episodic change than with more mainstream modes of evolutionary change. The same point applies to the ‘‘sudden’’ origin of angiosperms by neoteny (Takhtajan, 1954) as well as to plant speciation through polyploidy (Thomas and Spicer, 1986). Of rather more signiﬁcance is the fact that Gryphaea species durations were estimated to be as high as 14 My in some cases. Given that an episodic mechanism resembling punctuation is quite deﬁnitely happening in certain instances, what evidence is there that this phenomenon also reﬂects speciation? In the ﬁrst place, Simpson’s view of episodic evolution did not require species proliferation, and we must clearly question why this has been deemed necessary in punctuated equilibrium. We must now consider the questions of migration and cladogenetic substitution between species moving from allopatric to sympatric conditions as an important factor which cannot be addressed other than in the most exceptionally well-preserved fossil lineages. What appears as a punctuation may sometimes be nothing more than a species substitution between nonsister species, or even a phyletic occlusional event signifying anagenesis (see below). One very important question here is that, where apparent punctuation occurs, on what basis can we be sure that the criteria under investigation are actually valid species characteristics? If neontological data for very closely

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allied sibling species often actually show that continuous variation within a species is greater than that between species, then it is difﬁcult to see how the biological data needed to resolve such problems can always be extracted from paleontological data: In the species level taxonomy of Ophion wasps studied by Brock (1981a), certain decisions on species limits could not have been reached in the absence of adequate population samples plus information on behavior relative to such parameters as host choice and ﬂight period. This is, of course, merely the normal situation with a great many ‘‘difﬁcult’’ taxonomic groups. In actual fact, ‘‘good’’ data are more often unavailable even to the neontologist than not, and the question of speciation in its nontypological sense cannot always be resolved on the basis of molecular studies of extant species and fossil remnants of extinct ones (as, indeed, with the Trilobita!). In the argument over punctuated equilibrium, there clearly exists a real danger of misinterpretation, since neither speciﬁc status nor the distributional movement of substitutional gene pools can be expected to be fully evident in fossil data, nor can we fully exclude nonspeciational change from the interpretation of much of the data. Notwithstanding the fact that it is often some particular infra- or transspeciﬁc interpretation which seems to best ﬁt the information at hand, there may be no sensible way of distinguishing speciation from phenoplastic variation or cladogenetic substitution, or the latter from major phyletic occlusion (see Chapter 17). Another argument which favors quantum evolution over punctuated equilibrium is that there has not been enough time for thousands of ‘‘microspeciational’’ changes to have occurred, in order for small, iterated anagenetic steps to have been taken. Evolution under domestication shows what is possible in the absence of speciation, and transient pleiotropy may sometimes be all that is needed to support this in Nature: Consider the degree of change in the domestic dog under artiﬁcial selection. Could this happen in Nature? The answer lies in the extent to which selectional balance favors reproductive isolation between populations. The outcome may then be a ‘‘contract race’’ between anagenetic change and speciation. No rules concerning degree of phenotypic change can apply to such examples. If the mutational type is superior to the ‘‘wild’’ type, then the latter may simply pass to extinction, rather than become a separate species. This is the true basis for quantum evolution, and distribution and dispersal obviously play an important role in this. The migrational movements of nonsister species must also be considered in apparent punctuational events. If we look at the insect fauna of a single geographic region over a time period during which there has been much environmental ﬂuctuation (see Coope data, Chapter 19), an apparently punctuational pattern might emerge, in that different species would tend to move in or out of a given region according to prevalent conditions, yet with no real species substitution of any kind occurring. Whether this is interpreted as ‘‘punc-

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tuational speciation,’’ as migrational movement of continuing species units, or as substitution between nonsister species clearly depends on the degree of completeness of the subsequent fossil record and the degree of survivorship in the extant fauna. Eldredge (1995) actually suggests that the Sheldon data might be explained by species movements, to which comment we must add that some punctuations might not concern emergent species pairs derived from a single cladogenetic event. Some apparent punctuations may in fact even prove to be transient events: Bell et al. (1985) observed anagenetic-like change in Miocene Gasterosteus apparently causal to a punctuation event but followed by a return to the previous norm. Presumably this was a case of genomic anastomosis, whereas a ‘‘true’’ punctuation would involve genomic substitution (but how can we be certain which of these interpretations is the correct one, in the absence of genetic data of any kind?). Punctuated equilibrium (in the sense in which it has been widely discussed and contested) could clearly constitute a conceptual heterogeny. In particular, it must not simply be equated with ‘‘ambient speciation’’ following the conventional allopatric model. Why, then, does episodic evolution seem perfectly acceptable, yet punctuated equilibrium meet with so much difﬁculty? From the above discussion, the claimed links to the speciation process probably constitute the principal weakness with the latter hypothesis. In particular, attempts to invoke the Paterson recognition model and the Mayr peripheral isolation theory of speciation expose contradiction in certain of the tenets and data of punctuated equilibrium. Looking more closely at the question of the Mayr peripheral isolate model as an explanation of punctuation, we must clearly insist that the term ‘‘peripheral’’ should not be taken to automatically mean ‘‘outside the area within which fossilization is occurring.’’ Eldredge (1995) criticizes phyletic gradualism on the basis that ‘‘evolution is always happening some place else.’’ However, if this criticism is true for phyletic gradualism, then it must also be true for punctuated equilibrium. If evolution really is occurring beyond the limits of the fossilization zone, then it could be happening in some other, more distantly related gene reservoir, on the basis of cladogenetic substitution between nonsister species. Again, apparent punctuation via apparent cladogenetic substitution (as against binary resolution in speciation itself ) could actually be major phyletic occlusion. Given that punctuational species are probably not always true sister species, they could just as easily have evolved some place else via phyletic gradualism; even when the species do represent splits from a common parent gene reservoir, the observed substitutional event could be one increment within a phyletic occlusion sequence (see Thomas and Spicer, 1986, for a similar argument relating to patterns of speciation in plants). Occlusionary and substitutional interpretations in general are in fact supported by the view that punctuational species are frequently claimed to replace rather than coexist and compete with their ancestral gene pools. Therefore, while Eldredge’s insistence on the Paterson model of speciation clearly attempts to bypass the problem of the

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absence of coexisting species pairs in the punctuation model, it simultaneously opens up the question of a possible leading anagenetic selection interface. Owing to the admitted difﬁculties of interpretation with fossil data, neontological evidence is clearly needed in order objectively to conﬁrm several of the claims made by the punctuated equilibrium hypothesis. Some level of support has in fact been found with the cichlid ﬁshes of Lake Victoria: The Lake Victoria cichlids support punctuationism, to the extent that they exhibit noticeable speciational divergence that is clearly linked to rapid species proliferation in an isolated ecosystem. Furthermore, genetic analysis now conﬁrms that the species ﬂock of Lake Victoria cichlids is indeed monophyletic (Meyer et al., 1990), and around 300 endemic species have evolved in at most 200,000 years. Schubart et al. (1998) have provided molecular evidence that an adaptation of land crabs took place in Jamaica over the last 4 My. The species concerned have varying degrees of independence from the sea, and structural differences are often pronounced, tending to be linked closely to habitat type. Related marine species separated for the same length of time by the Isthmus of Panama have, in contrast, diverged but little in structure and adaptive niche. The above examples clearly conﬁrm the existence of an episodic substrate that is linked to dramatic species proliferation. However, it is not possible to extrapolate from this to conﬁrm all aspects of punctuation. In particular, one must guard against extrapolation from speciational events of the above kind to the question of major anagenetic change and Simpsonian quantum evolution. The view that punctuated equilibrium can be supported by extant ‘‘species explosions’’ is thus only partly correct, since this has not been fully conﬁrmed other than for more or less ‘‘ambient adaptive radiation,’’ excepting to some limited extent in the cichlids, where skull proportions and size and conﬁguration of teeth in the cranial and pharyngeal jaws have undergone noticeable (but not gross) change. This claim is thus true only within somewhat narrow limits: According to Greenwood (1981) the changes seen in cichlid ﬁshes could in fact be regarded as selectional sorting of quantitative genetic traits in the context of ‘‘phyletic gradualism.’’ Larger changes (some recognized as being of tribal value) have, however, occurred in Lake Tanganyika over a longer period of some 5 My (although these could clearly be evidence of postspeciational divergence from an original radiation not unlike that observed in Lake Victoria). The Gould–Eldredge criticism was particularly based on examples relevant to ambient cladogenesis, although with predictions extending into the macroevolutionary domain that were not actually linked to direct evidence concerning any signiﬁcant level of anagenetic progress. Punctuated equilibrium has thus been presented as a revised rationale for quantum evolution, despite the fact that its original base lay more with infraspeciﬁc change and ambient speciation than with major patterns of adaptive radiation. In the latter situation, the relevance of the cladogenetic input to punctuated equilibrium is likely to be determined by the balance existing between evolutionary rate and extrinsic

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factors such as geophysical dynamism in the external environment, distribution of the gene reservoir, and dispersal linked to propensity of development of a neosympatric selection interface. Furthermore, there seems no good reason to suppose that cladogenetic activity is always episodic in nature, especially in view of the fact that phyletic gradualism of the kind observed by Sheldon clearly does occur also (see p. 472). In reality, it would appear much more likely that quantum evolution and punctuation constitute the opposite ends of a spectrum of rare episodic events, while at the same time, gradualistic change is clearly happening in other zones of the adaptive substrate. There is thus ‘‘punctuation’’ as ambient speciation superimposed on stasis, and ‘‘quantum punctuation’’ linked to more dramatic macroevolutionary events. Neither quantum evolution nor the punctuated equilibrium hypothesis really contradicts Darwinian theory, although as stated by Brown (1987), the term punctuated equilibrium has had a life of its own, changing emphasis as positive data are removed. Apparent evidence supporting ‘‘strict’’ punctuation (especially in its supposed links with non-Darwinian evolution) therefore needs to be examined more assiduously, if it is to be construed as anything other than conﬁrmation of episodism in general. Even given acceptance of the episodic nature of much ambient speciation and of quantum punctuation, certain allegedly non-Darwinian elements in hard punctuationism must still be rejected. It will be argued here that tachytelic evolution in quantum punctuation does not require saltation, nor is a predominantly nonadaptive component acceptable. There has been a split between hard and soft views of the punctuation mechanism, and it would be unfair to criticize the hypothesis as a whole on the basis that it constitutes nothing more than a resurrection of Goldschmidtian saltation and wholesale nonadaptivity. However, although Eldredge (1995) does partly withdraw from a ‘‘hard saltationist’’ view, Stanley (1998) clearly continues to place too much emphasis on the question of macroevolutionary change via chromosomal mutation, and not enough weight on the obvious necessity of iterated change in the domain of mutation in strategic regulatory genes. Maynard Smith (1983) has also questioned the relevance of ‘‘speciational saltation’’ in the punctuationist argument, in view of data which show that differences between morphologically distinct species are generally polygenetic and not linked to single large effect mutations. He also pointed out the unlikelihood of suites of characters arising simultaneously (indeed, how could the secondary palate of vertebrates have evolved exactly concurrently with a breakdown in reproduction?).* Interestingly enough, Simpson (1953) actually held the view that evolution does involve almost exclusively gradational change in populations rather than saltation, even in the context of quantum evolution. From this standpoint, the fundamental rate of evolution may in some sense actually be the tachytelic * Some species differences may of course lie in nonviable ‘‘nonsense haplogenes,’’ which would not be available for analysis in such a study (the view that this cannot happen other than through postspeciational divergence would of course constitute a circular argument!).

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phase, and ‘‘ambient rate’’ could then be considered as being a depressed rate (see hypotelic rate, present chapter). In consideration of the view that, in the context of a benign adaptive corridor, tachytely could be thought of as constituting the base rate of evolution, we must of course also beware of the likelihood that many of the narrow basal phyletic gaps in major lineages must be partly due to sampling error in the fossil record. In support of this view, Hedges et al. (1996; see also Chapter 21) found good molecular evidence to show that the major radiations in birds and mammals had probably been underestimated by a factor of around 50%. In this situation, the adaptive grids (occlusion zones) visualized by Simpson are compressions of the true dimensions they represent, although they nevertheless remain short enough to indicate a dramatic phase of tachytelic evolution which contrasts strongly with subsequent patterns of diversiﬁcation in the same lineages. Given the right parameters in both extrinsic and endogenous environments (that is, in the absence of other constraints), this would indeed seem likely to constitute a base rate, at least for the earlier phase of a major adaptive shift (see Chapter 17). It is also a fact that ‘‘saltational gaps’’ tend to be reduced in terms of number of changes incurred, as transitional phases become better known: Carroll (1997) cites the example of Acanthostega, which retains some traits formerly thought to belong to the ﬁsh grade of organization, while Panderichthys had also already developed some characters that had been presumed to belong to tetrapods. Much evidence from the domain of developmental genetics also exists to support the view that saltation does not occur in the manner envisaged in hard punctuated equilibrium (see Chapter 12, 15, and 16), particularly in the obvious need for iteration of the kind of mutational activity likely to lie behind most modes of morphogenetic transformation. The arguments against nonadaptive evolution in punctuated equilibrium are no less strong than as with saltation. In this context, some of the evidence needs to be examined from the viewpoint of functionality: In the Phacops example (see above), the trend in question appears to be a vestigiational one. In general, with examples involving functional redundancy, saltation might not be a very surprising route, given the possibility of atrophy via major mutation (for example, a wingless moth could easily evolve through a single mutation preventing expansion of the pupal wings, but wings could not evolve de novo in the same way!). Evidence of nonadaptivity (even maladaptivity) is likewise not at all surprising in such circumstances. Neither of these observations is, however, of any importance in terms of establishing fundamental evolutionary laws. Eldredge (1995) rejected the criticism that punctuationism demands no selectional activity, while at the same time clearly accepting a lack of adaptive divergence in the recognition model of speciation. However, this constitutes a paradox, since selection must be deﬁned in terms of relative adaptive states (see Chapter 4). The confusion here seems to lie with the statement by Wright

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(1967) that speciation may be stochastic in relation to longer term ‘‘trends’’ (namely, with anagenesis). In fact, Eldredge (1985) gives a perfectly acceptable explanation of his view on this: the specializations of speciation may have only a ‘‘local’’ advantage in the shorter term. To this, we should now add that anagenesis survives a great many species proliferation events, by virtue of the isotropic nature of the anagenetic selection interface. The Paterson speciational model has nevertheless been linked to nonadaptive punctuated equilibrium by Eldredge (loc. cit.), who states, ‘‘There is no necessary connection between speciation and adaptive change. . . . If Paterson is right—we should expect to see closely related species with next to no discernible differences between them . . . and this is in fact found in sibling species.’’ However, actual studies of close sibling species generally do show pronounced behavioral and/or physiological divergences which reﬂect niche divergence, and Eldredge’s view seems to contradict that of the original punctuated equilibrium hypothesis, namely, that structural divergence (including saltational change) occurs exclusively at the time of speciation. In any case, the behavioral differences between sibling species are adaptive, whether or not they extend to the domain of actual morphogenetic change: Extremely closely related species in the parasitic wasp Ophion luteus complex in Europe show decisive niche differentiation, with particular regard to host preferences and ﬂight period (Brock, 1981a). Other examples are, of course, legion in the literature. Above all else, punctuated equilibrium does not, in the extrapolation from ambient to ‘‘quantum punctuation,’’ disprove the existence of infraspeciﬁc anagenesis, nor of anagenesis itself (as has been claimed). In this, the paleontological viewpoint seems to have swung from one extreme to another, all change being infraspeciﬁc in Simpsonian quantum evolution, and none at all in punctuationism! Clearly, the kind of changes observed by Sheldon and others are of the kind manifested by anagenesis, at least some component of which must be infraspeciﬁc. This may derive either from an element of postspeciational cladogenesis or from anagenetic factors arising after the original root speciation event. As we saw in Chapter 17, the greater the evolutionary rate associated with anagenesis, the more probable genomic substitution will be occlusional, rather than cladogenetic. Wright (1982b), in a critique of the punctuated equilibrium theory, states that while he agrees with punctuation in general (namely, as episodic evolution, a tenet by no means rejected by all neo-Darwinists), he would nevertheless chose to remove ‘‘speciation’’ and substitute ‘‘character change.’’ The alternative to this view seems to be to recognize every increment in each lineage as constituting a distinct species, which would clearly be a pointless exercise with such examples as the Sheldon trilobite data. If infraspeciational anagenetic change does not occur in Nature, does this mean that a biophysically advantageous morphogenetic trait will never be selected for, simply because there is no cladogenetic potential in the selection interface such as can be resolved in speciation, rather than by phyletic occlusion?

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One might also ask whether vestigiation cannot incur decremental change in the absence of a speciation event. Continuing with the same argument, how many human species were there between the prehuman ancestor and Homo sapiens? Were all of them sibling species, with nonadaptive differences less manifest than those between different geographic populations at the present time, or did whole suites of ‘‘quantum leap’’ characters arise with each of the few speciations that are known to have occurred, at the time of speciation? Why would many of the observed changes not have occurred within the postspeciational divergence scenario, or as independent events arising through a selection interface that is quite unconnected with cladogenesis? Simpson believed that European elephants exhibited phyletic evolution between two species on tooth structure, and in apparently continuous populations (see also Maglio, 1973). Indeed, why would species isolating mechanisms be deemed necessary in order that these changes can occur? Probing more deeply into the unlikely hypothesis of anagenesis as an increment occurring solely at the time of speciation, it is instructive to consider examples where much speciation has taken place, yet little or no anagenetic change has been expressed: Although MacFadden (1985) and Van Valen (1964) found only weak selection behind the most rapid change in Equidae, Hulbert and MacFadden (see MacFadden, 1988) observed that, despite lack of rapid anatomical change, there was explosive speciation. Thus species proliferation is conﬁrmed as having no necessary correlation with anagenetic change. The parasitic wasp family Ichneumonidae is presently at the peak of an immense species proliferation event in many parts of the world, but with little or no evidence that this is linked to the origin of radically new structural types. Most species (and even generic) characteristics are either minor amphigenetic traits or else slight vestigiational trends, whereas the wing venation (almost always a rich source of diagnostic characters in other Hymenoptera) is monotonously uniform virtually throughout the family. In any case, ‘‘quantum speciational events’’ would obviously themselves have to be due to iterative anagenesis of the gradualistic kind (as in the Simpson model), unless genetically impossible levels of saltation are accepted. Attempts to replace anagenesis with species selection (see Chapters 6 and 17) have perhaps proved to be the most counterproductive of all elements in the literature of punctuated equilibrium. Eldredge (1995) and Stanley (1998) have discussed species selection as an alternative to infraspeciﬁc anagenesis in order to explain large scale differentiation in phylogeny, a view that must now be rejected. This approach is essentially a way of trying to force speciation on anagenesis, with anagenetic increments invariably being exactly coincident with speciation events, and with species selection itself at times apparently converging on a group selection model. The view that evolution is directed by

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species interactions of this kind clearly stems from a fundamental misunderstanding of niche shift as always constituting divergence. As shown in Chapter 17, this is certainly not the case, since anagenetic progress toward the structural attractor can frequently involve change directed toward purely isotropic properties of the adaptive niche. Similarly, it is not possible to exclude the all-important role of infraspeciﬁc competition from evolutionary change.* Maynard Smith (1998) has further dismissed the role of species selection, as a concept that has arisen from a typological species concept welded to the Hennigian dogma that ‘‘species do not change except when they split.’’ Species selection, as a corollary of genic selection (see Chapter 6)—and not at all in the sense in which it has been used to demote anagenesis—may indeed play a large part in determining evolutionary rate and in inﬂuencing diversity patterns through differential extinction (Chapter 20). However, directionality in evolution is concerned with the orientation of anagenesis toward an adaptive paradigm (see Chapter 7), and not with the multiplicity of frequently transient tangential developments associated with an iterative bifurcational divergence scenario. The interplay between speciation and anagenesis is complex, and it cannot actually be resolved in favor of one mechanism over another in the context of any ‘‘general law.’’ Even where a dynamic environment is present (thus apparently favoring cladogenesis), it is still possible that anagenesis may at times predominate through mutual phyletic occlusion of incipient species. Conversely, of course, while the recombination impediment cannot impede anagenesis within the context of (plesiosympatric) phyletic evolution, it may also superimpose speciation on ‘‘lineage anagenesis’’ in the neosympatric situation. Therefore, the probability of speciation occurring is further conﬁrmed as being a complex function of rate of dispersal, geophysical dynamics, degree of niche diversiﬁcation, and rate of evolutionary change. In 움-anagenesis, the existence of pressure for multiple speciation may be of little consequence when there is rapid extinction of one emergent species of each pair on the basis of a leading effect in the anagenetic component of the selection interface, and this repeated unary resolution of anagenetic potential probably does often constitute the mechanism of anagenesis in the context of major phyletic occlusion (see Chapter 17). That this lies close to and may often be supplanted by cladogenetic substitution is, of course, a perfectly logical scenario that would also ﬁt the diagnosis of punctuated equilibrium—provided of course, that the latter explanation is not invoked purely in order to exclude all other interpretations. Additionally, the isopatric selection gradient of anagenesis concept (Chapter 17) implies that the intraspeciﬁc model invokes the higest possible evolutionary rates, and there is a further ‘‘facultative’’ aspect of this scenario in that ‘‘one step makes another easier.’’ This principle thus affords an acceptable mechanism for a re-formed concept of Simpsonian quantum evolution, namely, in terms of 움-anagenesis. Although Simpson’s model is obviously greatly over* As a further element in species selection theory, Stanley (1998) regards Simpsonian quantum evolution as constituting gradualism, on the grounds that infraspeciﬁc change is implicated (this is, of course, completely different from the Eldredge–Gould intepretation of gradualism; see above).

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simpliﬁed, it is nevertheless highly probable that intraspeciﬁc anagenesis does have a much larger role to play in 움- than in 웁-anagenesis, and this mechanism is, in turn, ultimately overshadowed by the preponderance of speciational activity during 웁-anagenesis (see Chapter 17). At the same time of course, we must not be blind to the fact that no perfect ‘‘snapshots’’ of quantum evolution have come to light, to the extent that species proliferation can be ﬁnally proved or disproved in the origins of a new higher group lineage. This statement remains true, despite the fact that gaps continue to be ﬁlled by spectacular annectent types such as those discovered in China in relation to avian phylogeny (Quiang et al., 1998). As stated by Eldredge (1995), Sheldon’s trilobite data do not in fact show remarkable evolutionary change, and Stanley (1998) likewise quite correctly dismisses evidence for gradualistic change as being in any way equivalent to quantum evolution. What conclusions can now be drawn concerning quantum evolution, punctuated equilibrium, and episodism in general, on the basis of the above discussions? The main proposals are as follows: • Above all else perhaps, arguments regarding the nonvalidity of particular examples, the role of speciation, criteria for measurement of evolutionary rate, and saltation must not be allowed to obscure the reality of episodism itself. • The term punctuation refers to a break in ambient stasis or of ambient rate of change, whether speciation and/or gross morphogenetic change is involved or not. • Quantum punctuation additionally involves tachytelic evolutionary rate linked to considerable morphogenetic change of the anagenetic kind (again, with or without species proliferation). • Punctuation should not be seen as being directly linked to speciation, but reﬂects a heterogeny of episodic events in both cladogenetic and occlusionary genomic substitution (as well as in speciation itself ). However, we must clearly seek to exclude substitution between nonsister species (as well as distributional events giving rise to ‘‘pseudopunctuational’’ patterns in the fossil record).* • Gradualism sensu Eldredge and Gould occurs in ambient evolutionary change. Again, this may or may not reﬂect speciational events, although it is probably often linked to infraspeciﬁc anagenetic change and other modes of neomorphic allelogenesis. • Saltation is tachytelic gradualism, irrespective of whether speciation is superimposed or not, with the exception of switch gene mechanisms which generally operate only at lower taxonomic levels. However, ‘‘concerted’’ change and certain manifestations of paramorphic transformation (Chapter 16) may act to create ‘‘pseudosaltational’’ bursts of evolutionary change of the episodic kind. • Iterative anagenetic change does not occur through niche divergence. Consequently, species selection does not ‘‘direct evolution,’’ other than in the sense of having an input to evolutionary rate differentials and extinctional patterns, as an emergent property of genic selection. * The foregoing terms will be used exclusively in the above context from this point on.

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• Maladaptivity and nonadaptivity are not signiﬁcant leading effects in evolution, although they may well be linked to anagenetic change in the context of pleiophorism and partial functional redundancy. In summing up, the remaining problems with both quantum evolution and punctuated equilibrium lie mainly with the utter impossibility of ﬁnal decisions being made on the presence or absence of cladogenetic events for a large proportion of the available paleontological data. Of even greater signiﬁcance is the fact that many neontologists (especially population geneticists) have completely failed to appreciate either the reality or the signiﬁcance of episodic evolution. An integrated model introduced below helps to explain the adaptive substrate responsible for episodic evolution, and this combines in turn with a comprehensive theory presented in the next chapter.

A General Model of Episodic Evolution Given that good evidence does apparently exist for the occurrence of episodic evolutionary events (and ignoring the controversy surrounding certain aspects of the punctuational model), how can this fact be reconciled with available knowledge concerning the adaptive process? The ‘‘episodic substrate’’ is clearly a bipartite structure. As we saw in Chapter 14, the exogenous substrate for evolutionary change is linked to changing competitional regimes. Second, the endogenous substrate is particularly associated with loss of heterozygote advantage, since included in that element of allomorphism impeding evolutionary change is that component which is linked to overdominance. As a whole then, the evolutionary substrate constitutes a contraction of the domain of adaptive equilibrium, and the root of this clearly lies with adaptive shifts causal to collapse of structurologistic interdigitation with a former adaptive niche: Good evidence in support of the above hypothesis lies with loss of the minor adaptive niche combined with dramatic change in other aspects of the external environment, in relation to invasive populations on remote islands, where evidence of rapid speciation and anagenesis has been widely reported. One important element in the substrate of evolutionary change can thus be seen to lie with removal of the minor niche and thus of interspeciﬁc competition and predation, thus allowing infraspeciﬁc competition to be relaxed intermittently.* The endogenous episodic substrate is not, however, restricted to changes in hybrid vigor, and an adaptive shift may also act to change the morphogenetic receptivity proﬁle of certain phenotype parameters in the context of redundant morphospace (see Chapter 14). This in turn will favor passive decanalization through loss of selection pressure acting to perpetuate the canalized state. Morphogenetic potential may then be realized, and pro- or neotropic mutational change (see Chapter 12) may appear in the context of a general expansion * It is evident from investigations by Jablonski (1986) that episodic evolution is not exclusively linked to opportunistic substrates such as the aftermath of mass extinction events.

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of pleiotropism. With relaxation of selection, many potentially positive changes that had been canalized may thus come to be expressed in realized morphogenetic potential for certain parameters of structure, so also raising the probability of realization of unexplored domains of adaptive potential. In this situation, negative elements in pleiotropy may lead to selective mortality linked to both extrinsic and endogenous selection interface structures, so that the domain of competition has effectively shifted from an extrinsic–anisotropic to a partially endogenous–isotropic selection interface. The term ‘‘episodic substrate’’ thus describes movement of the selection interface from ongoing anisotropic to intermittent isotropic status, the latter clearly favoring anagenesis over adaptive equilibrium. How then is episodism linked to rapid evolutionary change? That situation in which anagenetic change is favored should predictably facilitate both rapid iterative incremental change via gene duplication plus larger incremental steps, the latter occurring owing to the fact that pleiotropic balance may at times operate to permit more profound changes, where ‘‘anagenes’’ are not competing with leading effect allomorphs. Clearly the ideal requirement for temporospatial coexistence of extrinsic and endogenous substrates also implies a rarity factor for episodic evolution. A behavioral adaptive shift must therefore not be taken to constitute an automatic switch capable of catalyzing a macroevolutionary event, and the low probability of extrinsic and endogenous adaptive potential being realized simultaneously is surely conﬁrmed by the phenomenon of evolutionary anachronism (see previous chapter). The episodic substrate as described above clearly must have the highest level of potential for expression in the context of a benign adaptive corridor, since it is here that the highest levels of selectional activity are supported. The situation with a hostile adaptive corridor is quite different, since although competition may still be high, selection is not. Where decanalization occurs, negative phenotypes will obviously continue to be selected against in the hostile adaptive corridor, but potentially positive neotropes may not be selected for unless they are counteractive to the inﬂuence of stochastic override of selectional interactivity. It follows from the above argument that the architecture of the adaptive corridor must contain a highly signiﬁcant input to evolutionary rate of lineage. This premise also predicts that lineages occupying a hostile adaptive corridor should manifest bradytelic evolutionary rate, with the exception of certain specialized phenotype parameters linked to parametric niche space, this link between niche space hierarchy and adaptive corridor lying with the low probability of the K limit occurring in sub- or hypoparametric niche space in the hostile niche. The hostile adaptive corridor will thus tend to favor parametric niche space adaptations over other categories, as apparently conﬁrmed by the observation that living bradyteles generally do tend to display strong structural specializations in a few parameters of that kind, in association with general primitiveness in more sub- or hypoparametric niche linked traits (see p. 462). In the general overview, rapid evolutionary change seems paradoxically to originate in a substrate manifesting a pronounced ‘‘lack of struggle,’’ although only in the context of the axiom that any relaxation of the extrinsic

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selection interface automatically leads to an increase in the endogenous one. This situation is evidently poised on the edge of dramatic change, in that any lowering of competition will tend to invoke developmental events which in turn lead to powerful selective regimes linked to selective decanalization and expansion of morphogenetic potential. Thus, the selectional proﬁles of episodic evolution must be viewed in terms of both (a) the intercalary scenario (see below), and (b) the punctuational regime itself. The question of the behavior of the evolutionary substrate itself will be examined further in the next chapter.

EPISODIC EVOLUTION AND REAL EVOLUTIONARY RATE The concept of episodic evolution highlights clearly the fundamental distinction between real and apparent evolutionary rates. Given that there must be periods of intercalated stasis, it could (in an extreme view) even be held that lack of adaptive potential for change rather than lack of opportunity in the external environment holds the key to major variation in evolutionary rate. The simplest answer to the latter view would of course be that, since observed rates tend to begin high and gradually tail off toward an adaptive limit (and that adaptive potential is surely more likely to become more rather than less easily facilitated with time), intercalation through lack of endogenous adaptive potential cannot possibly serve to explain the overall trend in the variation of evolutionary rate of lineage. Nevertheless, the input from periods of inactivity must be taken into account in any realistic assessment of rate differentials, particularly when we move away from the domain of ﬁxation of a single gene allele to that of the unraveling of a complex anagenetic sequence in the context of macroevolution.

The Intercalation Model Following a discussion of episodic evolution, it must now be clear above all else that actual measures of evolutionary rate from the fossil record cannot, in view of periods of evolutionary stasis, be fed blindly into the Haldane equation without incurring a huge margin of error in the form of underestimation! Similarly, with further reference to the isopatric selection gradient of anagenesis and the adaptive corridors models of evolutionary rate, it is clear that theoretical rate curves will also not actually be observed directly in reality, owing to the existence of intermittent periods of evolutionary inactivity. The intercalation model takes into account the fact that periods of change are interspersed with periods of stasis and thus considers factors contributing to evolutionary rate of lineage that are only ‘‘apparent,’’ in the sense of their being nonselectional (as with the inﬂuence of a whole range of factors presenting impediments to evolutionary change; see Chapter 14). The intercalation model is an artifact, in that it ignores the question of actual step size in order to show with greater clarity how other factors are involved, and since it also largely bypasses the question of whether evolutionary change occurs by intra- or transspeciﬁc anagenesis.

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The model operates as follows. Let each 1 element in a time series represent an incremental step in an anagenetic sequence and each 0, a period of no change of the same duration. The progress of the sequence in question can be illustrated as shown below. We thus begin from the axiom that periods of anagenetic change are highly unlikely to occur end to end, this approach explaining why the intrinsic selection gradient of anagenesis is really drawn through a probability distribution:

FIGURE 110 Intercalation: periods of evolutionary change [1] interspersed with periods of stasis [0].

Gingerich (1983) produced good evidence for supposing that underestimation of evolutionary rates with respect to the larger time scales involved in the origins of higher groups may frequently occur, from the observation that ‘‘a period of rapid change followed by a period of stasis will yield a rate of intermediate value for the entire interval.’’ In other words, measurements of rate over lineage time ‘‘average out’’ periods of stasis and of evolutionary reversal, so that calculated evolutionary rates come to be negatively correlated with measurement interval. Following Gingerich’s conclusions, the criticism of Eldredge (1989) that ‘‘phyletic evolution is too slow’’ is frequently easily answered in reality. Where low coefﬁcients of selection have apparently been measured in relation to anagenesis, we must therefore obviously consider the intercalation problem (and also, of course, the real possibility that many anagenetic trends in the 웁 phase will actually have intrinsically low evolutionary rates!). Gould (1990) also pointed out the inadequacy of Haldane’s ‘‘darwin’’ unit of evolutionary rate, and here we must obviously avoid any tendency to equate anagenesis with random drift on the basis of an averaged-out rate: Eldredge, for example (1989), cited Lande (1976), who held that weak selection coefﬁcients could be interpreted as genetic drift. Fundamental evolutionary rate of lineage can now be deﬁned as being that component that is directly determined by selection, ignoring any averaging out over periods of stasis, while the latter approach identiﬁes real evolutionary rate. Gingerich (1993) has proposed a revised version of the Haldane equation, which takes these factors into account. The Intercalation Model and Tachytely Tachytely is probably not solely due to the 움-anagenesis scenario, since it could also involve crossing of a threshold in adaptive potential that could lead to so-called tight intercalation. With tachytely then, high intrinsic evolutionary rate may well be increasing at the same time as intercalation is becoming compressed, and these points must be borne in mind when considering the veracity of the intrinsic selection gradient model introduced in Chapter 17.

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Following the tenets of the intercalation model, bradytelic and tachytelic (anagenetic) evolution can now be represented as shown below.

FIGURE 111 The effect of intercalation on evolutionary rate: the same number (and size) of incremental steps is intercalated by low incidence of stasis (tachytely) and high incidence of stasis (bradytely).

The Intercalation Model and Gradualism Episodism has become a further ‘‘special’’ theory of evolution, in the sense that Darwin’s original thesis (1859) held that the evolutionary mechanism always proceeds via incremental change. However, the intercalation model shows that this disagreement is at least partly illusory. The intercalation model shows that apparent evolutionary rate of lineage differences may occur, not always owing to selectional differentials, but sometimes owing to ‘‘nothing happening,’’ even in a soft gradualist interpretation (while a hard gradualist view might hold that variation in evolutionary rate of lineage is nothing more than varied intercalation via stasis!). Purist gradualism might thus hold that intercalation is ‘‘even,’’ namely, that evolutionary steps are always small and of the same duration. However, both theoretical considerations and the fossil record clearly conﬁrm that this is not the case, and interpretations must then follow the re-formed view of episodic evolution already discussed. There is evidently an element of ‘‘Aunt Sally hypothesis’’ in purist gradualism, according to which theory a particular author has been trying to support or disprove. Intercalation alone will not, however, explain the broad shape of the intrinsic selection gradient of anagenesis, nor the evolutionary rate differentials arising from benign versus hostile adaptive corridors, nor does it offer any real explanation of those patterns of evolutionary change that have been equated with quantum evolution or punctuated equilibrium.

MAIN POINTS FROM CHAPTER 18 1. There are two principal criteria for measurement of evolutionary rate: rate of speciation and rate of anagenetic change. These criteria are neither mutually dependent nor entirely mutually autonomous.

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2. Anagenetic rate can be examined in terms of change within a single anagenetic sequence, or for the same sequence evolving at different rates in separate lineages. The former has been analyzed in terms of a horotelic range plus extreme fast or slow rates of tachytely and bradytely. The second criterion constitutes allotely, and here, alone, noncomparability problems are bypassed. 3. Tachytely has been associated with the adaptive isthmus surrounding the origins of a new lineage, whereas bradytely is often linked to ‘‘relict’’ groups. Allotely is linked to the benign–hostile macroniche dichotomy. 4. The causalities of cladogenetic and anagenetic evolutionary rate are fundamentally different, especially in that the former is more inﬂuenced by geophysical change and patterns of dispersal. 5. Evolutionary rate is linked in the ﬁrst instance to the intrinsic selection gradient of anagenesis, but it also contains a profoundly signiﬁcant input from qualitative differentials originating in the benign–hostile niche dichotomy. This is shown (for density dependent selection) in the equation set of the adaptive system, in terms of a J factor added to the Lotka–Volterra equations. The effect of a very long-term interface with benign or hostile macroniche is manifested in ‘‘wide’’ or ‘‘narrow’’ adaptive corridors. 6. Bradytelic evolutionary rate is determined by the above-mentioned J factor, in the context of a hostile (narrow) adaptive corridor, as a function of the level of nonselective mortality. 7. Ambient evolutionary rate should not be taken as being the ‘‘raw’’ anagenetic rate, but as a hypotelic rate affected by progressive ingress of the leading effect impediment arising from predominance of adaptive equilibrium in the selection interface. This relationship can be modeled using the sigma–delta equation set. Tachytely lies closer to the true base rate of lineage evolution (depending, of course, on the existence of a suitable endogenous substrate in adaptive potential). 8. In general, a wide adaptive corridor supports high evolutionary rate plus high levels of speciation and allomorphism, whereas a narrow adaptive corridor is linked to low evolutionary rate and less speciation, with logistic variation having a greater inﬂuence on the ambient selection interface than structural allomorphism. 9. Evolution may well be fundamentally episodic with respect to major adaptive shifts, but this should not be taken to exclude a gradualistic input at other levels. 10. The adaptive substrate for evolutionary change lies with lowering of competition and subsequent release of morphogenetic potential from its ambient state of canalization, which explains the observedly rare incidence of ‘‘episodism.’’ 11. Two main models of episodic evolution have been proposed: quantum evolution and punctuated equilibrium. The ﬁrst model emphasizes infraspeciﬁc evolution and phyletic occlusion, the second, speciation and cladogenetic substitution. Punctuated equilibrium also demands a predominance of evolutionary stasis in the ambient behavior of adaptive systems. Simpsonian quantum evolution excluded saltation, but this constitutes an important element in the punctuated equilibrium model.

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12. Only limited support exists either for strict Simpsonian quantum evolution or for punctuated equilibrium. Quantum evolution cannot be exclusively due to lineage anagenesis, and apparent ‘‘punctuation’’ can often be explained in other terms. The dichotomy between cladogenetic substitution and major phyletic occlusion constitutes the greatest barrier to interpretation of paleontological data, in the quest to separate cladogenesis from phyletic anagenesis in the context of episodic evolution. 13. Apparent punctuated equilibrium seems more relevant to ambient speciational events, whereas quantum evolution has been more frequently linked to the origin of new higher groups. 14. Gradualistic change also forms a signiﬁcant component of evolution. ‘‘Peripheralization’’ of gene pools (as a function of fragmentation of a gene reservoir) is not the only source of evolutionary opportunity, and slower change will presumably be more readily supported within the ambient sympatric adaptive substrate. 15. Saltation and maladaptivity should be seen as having a relatively low proﬁle in the general scheme of evolution. Apparent saltation is probably best interpreted in terms of tachytelic gradualism, plus a varying input from ‘‘concerted evolution.’’ Pleiophorism must be viewed in the context of changing pleiotropic balance, and suboptimality in general is usually a corollary of multiple functionality, rather than a leading effect in evolution. Neither randomicity nor maladaptivity can have leading effect status, nor can either constitute anything other than a transient state (although ‘‘transient’’ can nevertheless mean ‘‘greater than ambient speciation time’’). 16. The term ‘‘punctuation’’ should be considered to refer to a break in stasis or in ambient speciation rate (the latter by orders of magnitude). Quantum punctuation refers to rapid anagenetic movement involving neomorphic change, whether there is speciation or not. 17. The evolutionary substrate derives from an adaptive shift from an ambient anisotropic to an episodic–isotropic selection interface. This is diagnostic of a deep oscillation between ‘‘lack of struggle’’ and ‘‘high struggle’’ scenarios, in the context of collapse of adaptive equilibrium in a benign adaptive corridor. 18. Evolutionary rate of lineage can only be realistically understood in the context of an intercalation model reﬂecting the fundamentally episodic nature of the longer term adaptive substrate.

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STASIS AND THE ADAPTIVE SUBSTRATE

ANALYZING EVOLUTIONARY STASIS The concept of stasis has already been introduced in the context of punctuated equilibrium, and it may be loosely deﬁned as being that state within an evolving lineage which exhibits no structural change within a given time frame. However, much uncertainty remains as to the precise deﬁnition of the term, and indeed, reference to ‘‘ambient stasis’’ must now be qualiﬁed in terms of particular aspects of a rather wide heterogeny of evolutionary phenomena that can broadly be referred to as constituting stasis. Clearly, certain problems need to be resolved in order that the special theory of episodism can be seen in perspective with the general theory of evolution. As with episodism in its broadest sense (see previous chapter), it can be shown that stasis is (in at least one signiﬁcant sense), a further expected outcome in the evolution of adaptive systems.

Frames of Reference In reality, there are numerous frames of reference that might be presumed to contain a state of stasis in adaptive systems, some referring to infra gene pool criteria, others to a much wider zone. It is therefore necessary at the outset to examine a range of possible bench-marks in order to explore the nature of this heterogeny. The reference frames of evolutionary stasis can at once be seen to be similar to those for evolutionary rate (just as one question must center on whether

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apparent stasis might not often simply constitute a very low rate of change). Any criteria of evolutionary stasis must clearly be measured over an appropriately speciﬁed time scale and may also require to be referred to a particular structural locus. Within a very small time frame, many traits may seem to express stasis, whereas with a greater time scale, it may become apparent that this is not the case. Similarly, one structure unit may be manifesting evolutionary stasis while considerable mutational change is going on somewhere else in the genome. It follows that evolutionary stasis can only be deﬁned once a set of appropriate reference frames have ﬁrst been speciﬁed. Time Frame and Adaptive Equilibrium An extreme (and unrealistic!) view of evolutionary stasis might hold that this state only exists in that situation in which only passive logistic changes are occurring in the gene pool (see Chapter 1). However, even within the limited time frame of a generation, we would naturally expect to identify adaptive equilibrium in the structural component of the adaptive response as constituting the ambient state of adaptive systems. Clearly any element of structure undergoing bidirectional change within a narrowly deﬁned time frame must, however, be excluded from the deﬁnition of stasis, in that all species surely exhibit adaptive equilibrium with reference to a number of gene loci. In attempting to deﬁne the state of evolutionary stasis more explicitly then, we must seemingly ignore allomorphism, thus limiting our concept of what constitutes stasis to the evolutionary component of the adaptive response. Just as all lineages exist in a state of dynamic equilibrium in their adaptive system, most also exhibit long-term stasis with respect to certain major structural characteristics in the domain of anagenetic change, while some at times manifest unusual stability with regard to frequency of speciation. These phenomena clearly require investigation over an appropriately large time frame. Stasis and Evolutionary Mode: Cladostasis and Anastasis Speciation and anagenesis can be seen as ‘‘breaks in ambient adaptive equilibrium,’’ as also in stasis. Following the exclusion of adaptive equilibrium from the deﬁnition of evolutionary stasis, we must go on to consider the meaning of the term for truly evolutionary events in the two principal macroevolutionary modes: cladogenesis (and especially speciation) and anagenesis. In this context, the concept of stasis is clearly also linked to episodic evolution and (in particular) the punctuated equilibrium hypothesis (see previous chapter). Looking at this problem through the intercalation model, it is easy to see that the cladogenetic situation is quite different from the anagenetic one (Fig. 112). Some lineages may show much cladogenetic change but little or no anagenetic progress, as, for example, with many well-known ‘‘sibling species complexes.’’ Others may manifest considerable anagenetic differentiation without being particularly ‘‘speciose.’’ Each example thus shows evolutionary stasis in one respect, but not in the other. Again, some lineages may manifest stasis in both the clado- and anagenetic domains for long periods of time. Within the context of macroevolutionary change, we may thus chose to investigate evolutionary stasis on the basis either of cladostasis (and, in particu-

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FIGURE 112 Intercalation model, showing a period of anagenetic stasis punctuated by a speciational event, followed by a period of cladogenetic stasis in which anagenetic activity occurs.

lar, stasis in the major cladogenetic domain, as distinct from the lesser question concerning the evolution of dominance) or of anastasis (stasis in the anagenetic domain). The term stasis cannot therefore be limited to lack of change solely with reference to an anagenetic sequence, since we must also consider that evolution could alternatively be manifested in lack of cladogenetic activity, and the same is true in reverse. In the deeper analysis of mechanisms leading to evolutionary stasis, these two alternative applications of the term will therefore be subjected to closer examination. The Structural Locus of Anastasis In the analysis of anastasis, it is further necessary to understand that there are generally only one to a few loci of structure in which anagenetic stasis may constitute a point of interest over the time course of a lineage. Although it is axiomatic that all gene pools exist in a state of perpetual adaptive equilibrium via movement within the mobile genome sector, anastasis can only relate to larger structure units controlled by genetic factors lying beyond the domain of adaptive capacity, so that the term anastasis can therefore only be applied to speciﬁc structural parameters (e.g., stasis in the structure of the vertebrate eye does not imply stasis in hair color, etc!). Anastasis can thus be postulated to exist in relation to certain structure units, notwithstanding the fact that some other phenotype parameter might well be involved in neomorphic change at the same time. It should also be realized that the terminal phenotype may manifest stasis when there is much evolutionary change taking place at the level of phenogeny or ontogeny (see earlier remarks on direct development in some echinoderm species). The Locus of Cladostasis The question of species stasis is clearly of special interest in the search for causal mechanisms in general, and in particular with its links to the punctuated equilibrium hypothesis: Darwin’s critics included ﬁve paleontologists all of whom agreed that ‘‘once a species appears in the fossil record, it tends to persist with little appreciable change throughout the remainder of its existence’’ (see Eldredge, 1995).* * To that statement we must now add ‘‘within the range in which fossilization is occurring’’!

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We can clearly locate stasis in the balance of all antagonistic selectional forces in the cladogenetic selection interface. So far as major cladogenesis (speciation) is concerned, the ‘‘locus’’ of cladostasis is simply that of the time frame between two speciation nodes, and this may be readily diagnosed for species with an exceptionally long evolutionary history, in the absence of any further speciation events in the same lineage. However, a heterogeny of reasons for cladostasis exists, some of which are more apparent than real. In actual practice, the paleontological data of cladostasis often lack realistic test criteria (for example, where no evidence of population movements is apparent or where microspeciational events have been overlooked). In fact, much ambient speciation in the extant fauna cannot be traced readily (or at all) on the basis of morphological data alone: The Drosophila melanogaster and D. simulans species pair illustrates the ‘‘speciation without morphogenetic change’’ syndrome evident in many extant lineages, where a cladogenetic node dividing ‘‘sibling’’ species would clearly not be at all apparent in the fossil record. Similar examples are of course abundant in the neontological taxonomic literature. The dichotomy between the causal mechanisms of species isolation and postspeciational divergence as a manifestation of ongoing cladogenetic activity between species with a continuing niche intersect is clearly a crucial criterion. The proliferation of sibling biospecies in (for example) Ichneumonidae or Drosophilidae is not the same thing as the adaptive radiation of geospizine ﬁnches, and the former examples could indeed even be regarded as ‘‘stasis’’ in purely anagenetic terms! There thus exists a very wide gulf between ambient and Renschian cladogenesis and a wide area of potential confusion with regard to the domain of postspeciational evolution. As a general rule, it would be reasonable to accept any degree of observed speciational activity over lineage time as constituting ‘‘nonstasis’’ in the cladogenetic sense, while admitting some element of heterogeneity in the ‘‘stasis residue’’ at the same time, owing to much practical difﬁculty in applying theory to some examples of real data!

Endogenous Factors in Cladostasis Following on from earlier discussions, it will clearly be useful to divide endogenous factors in major cladogenesis into speciational versus postspeciational. In the former instance, there may be apparent factors in genetic constraints acting to impede speciation or to promote racial merging in the neosympatric scenario, as already illuminated with reference to the recombination impediment (Chapter 14). Adaptive capacity could also be versatile enough to allow expansive intraspeciﬁc polymorphic variation in the face of gene pool diversiﬁcation in a dynamic environment, as an alternative to speciational resolution of cladogenetic potential. Intrinsic constraints on postspeciational divergence (where structural change may supplement the behavioral–metabolic basis of many primary species isolating mechanisms) would be expected to be similar to those acting on anagenetic progress generally. That is to say, those endogenous factors which

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contribute to constraints on realization of adaptive potential and which manifest a depressive effect on evolutionary rate must also constitute constraining inﬂuences on postspeciational divergence. All of the above mechanisms clearly possess the capacity to inhibit binary resolution of cladogenetic potential and/or postspeciational divergence. In short, speciation may not occur when there is insufﬁcient demand in the cladogenetic balance between parent and hybrid genomes, or else it might be favored, but with no adaptive potential available such as would permit much divergence beyond the behavioral–substructural domain.

Extrinsic and Integrated Factors in Cladostasis External inﬂuences may act either to promote or to retard evolutionary change. The rate at which the neosympatric state develops within the geographic boundaries of the gene reservoir must clearly be one highly signiﬁcant factor in facilitation of the speciation process, since it is precisely spatial diversiﬁcation of the gene reservoir that is the crucial factor in the buildup of cladogenetic drive. In this scenario, adaptive capacity for dynamic equilibrium is not to be seen as constituting a perpetual impediment to speciation, but rather it creates the necessary background genetic diversity within which speciational activity may in fact evolve, given the appropriate external substrate. The macrodynamics of the geophysical environment must therefore form an important input to cladogenetic activity of the kind tending to be resolved in speciation, and the combination of a high selective offset of fecundity and dynamic environment with high cladogenetic potential in free adjacent niche space probably underlies the necessary combination of genetic casual factors acting to promote cladogenetic potential in the gene reservoir. The reverse equation for the above scenario may of course be that lack of geophysical dynamism and/or of genetic diversiﬁcation could lead to the opposite situation, thus favoring cladostasis owing to lack of capacity for any speciational divergence. Looking now at the postspeciational domain, it is possible to further examine the link between clado- and anastasis. The intensity of postspeciational cladogenetic drive between two emergent species will naturally be directly proportional to the degree of residual sympatry (and of niche intersect) in the gene reservoir, and hence character displacement is simply ‘‘the steep end of the postspeciational cladogenesis gradient’’ where there is incomplete overlap (see Chapter 6). Postspeciational cladogenesis may thus be manifested in anagenetic activity (notwithstanding the likelihood that many anagenetic trends must arise within the postspeciational domain, without necessarily demanding any further cladogenetic movement). The degree to which neosympatry between emergent species is realized is thus crucial to cladogenesis, and thus also to cladostasis, and there is an additional interaction with the genetic component of adaptive capacity in this. The Species as a Limit Cycle in Adaptive Systems Stasis in the species dimension has been well documented in the paleontological literature, albeit with frequent criticism from neontologists that ‘‘paleospecies’’ are not the equivalent of true biospecies. Nevertheless, good evidence

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exists for species stasis. Insect subfossils, for example, can be determined with exactly the same taxonomic characters as those utilized with the present-day fauna, and these ﬁndings are consequently not subject to the usual criticism leveled at paleotaxonomy. A good level of support for species stasis has in fact emerged from this work: Coope (1995) states that over 2000 insect species known from the British subfossil fauna are a perfect match with present-day species, ‘‘mystery species’’ constituting for fewer than 1% of the total. Stasis for individual species has lasted 1–2 my, during which time changing conditions were met, not by evolutionary change, but by distributional movement. Even more remarkably, Hallam considered that some Gryphaea species had durations of up to 14 my (see previous chapter). Given the quasi-cyclic nature of the interaction between gene pool and environment over long periods of lineage time (as seen in the Coope data), it could be suggested that the species genome contains a limit cycle that is bounded by the contours of adaptive equilibrium, in that the ambient leading effect may tend to lie more with adaptive capacity in dynamic equilibrium than with any element of directionalized change in the genome. The species unit would thus constitute a large element of stasis in the evolution of adaptive systems, as a corollary of factors actually promoting adaptive equilibrium. Paradoxically then, while adaptive equilibrium can safely be excluded from stasis, it may well also form the most signiﬁcant factor lying behind species stasis, provided of course that any parallel facility for allopatric diversiﬁcation of the gene reservoir does not come to outweigh the stabilizing inﬂuence in question. The capacity for a gene pool to diversify via leading effect allomorphism controlled by the mobile genome sector is therefore one signiﬁcant inﬂuence on cladostasis, since speciation is not the only resolution of cladogenetic drive. A species unit may thus express much change in the domain of allomorphism in the resolution of conﬂicting cladogenetic selectional forces without incurring further speciation. As already noted, there will be endogenous factors in the above scenario. However, other inﬂuences in the external environment will almost certainly be implicated. Here, we witness ‘‘containment of cladogenesis by adaptive equilibrium’’ as a corollary of the architecture of a complex anisotropic selection interface. We must now contrast the foregoing postulate with the point raised by Maynard Smith (1983), that species are unlikely to be static in time if they are obviously not so in space. The answer to this criticism may lie in the fact that paleontologists make value judgments on data derived mainly from the morphological domain, whereas much of the spatial variation seen in living species is predominantly substructural in nature. Again, much of the latter may merely constitute a higher dimension for adaptive equilibrium. Real evidence exists to support the view that species stasis is promoted by adaptive equilibrium: Coope (1995) observed that, paradoxically, it is climatic inconstancy that can be seen to be an important factor in the maintenance of

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speciﬁc constancy, querying the degree to which ‘‘stabilizing selection’’ could operate to maintain constancy over millions of generations. However, it would be more correct to say that the underlying factor here is, in fact, ‘‘diversifying selection,’’ as predicted by the theory of adaptive equilibrium. Much of the observed spatial variation may thus indeed constitute adaptive equilibrium, and it is this (largely substructural) repertoire of adaptive capacity that invokes morphogenetic stasis in the temporal dimension. The crucial difference between this interpretation and the strict gradualist one dismissed by Eldredge and Gould is simply that ambient variation of the kind manifested in adaptive equilibrium had been largely misinterpreted as being incremental to all modes of evolutionary change by many neo-Darwinian evolutionary biologists, up until at least the 1960s. If changing domains of allomorphism are contained without splitting the gene pool, then the fact that the species unit appears to be acting as a limit cycle (and thus apparently contributing to stasis directly) is simply an emergent corollary of the adaptive equilibrium mechanism (although it may of course be more accurate to describe the behavior of adaptive capacity in dynamic equilibrium as being no more than quasi-cyclic in the longer term). Whereas the work of Jackson and Cheetham on Bryozoa cannot prove the punctuationist hypothesis (see Chapter 18), it clearly does provide good evidence that some species in certain lineages may exist in a state of clado- and anagenetic stasis for long periods of time. However, any tendency of species to form limit cycles via adaptive equilibrium must nevertheless generally constitute a transient phenomenon in the perspective of longer term evolution, and we know nothing of the regimes of substructural allomorphism occuring at different time horizons in examples such as the Jackson and Cheetham data, nor of the effects of this in terms of promoting or impeding the evolution of species isolating mechanisms.

Anastasis Deﬁned Unlike the cladogenetic case, which must ultimately be judged entirely on the basis of the presence or absence of genome splitting, anastasis could be regarded as being a conceptual heterogeny that can be approached from several different angles. First, there may be apparent stasis owing to endogenous impediments in adaptive potential (see Chapter 14). Second, there may be real stasis, in that an anagenetic sequence has reached an adaptive limit in the biophysical paradigm. Third, the same factor causing species to behave as limit cycles could also be retarding anagenetic progress, namely, in the speciﬁc context of hypotelic evolutionary rate (see above and previous chapter). Within the aforementioned heterogeny, true anastasis might perhaps be most explicitly deﬁned as that structural state in which the anagenetic sequence has approached the adaptational paradigm state: Simpson, summarizing Westoll’s data on evolutionary rate in lungﬁshes (see Chapter 18), concluded that evolutionary rate had been ‘‘virtually nil’’ in this lineage for the last 150 my, about half the history of

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the group. This probably constitutes an adaptive limit for a highly specialized adaptive zone. The alternative criterion of ‘‘stasis via constraint’’ may clearly often be interpreted as anastasis, according to the chosen temporal reference frame (or through lack of any attempt at functional analysis of ‘‘evolutionary trends’’). However, this is less than satisfactory for a number of reasons. In particular, it has to be assumed that evolutionary change is ultimately possible, for any state of stasis to be construed as constituting ‘‘evolutionary anachronism.’’ Nevertheless, the ﬁrst deﬁnition of ‘‘stasis at the adaptive limit’’ is also open to the objection that adaptational paradigm states are probably never quite reached, owing partly to continued dynamism in the organism–environment interaction in the very long term of evolution, and also owing to that domain of suboptimality enforced by multiple functionality. Finally, bradytelic evolutionary rate (see Chapter 18) could also be considered to constitute a state of near stasis. This complex heterogeny of apparent versus real elements in anagenetic stasis clearly requires closer examination in the context of the architecture of the adaptive system.

Endogenous Factors in Anastasis Some factors seemingly invoking anagenetic stasis are clearly more apparent than real, and certain ‘‘real’’ factors that have been claimed to exist must only constitute temporary impediments (for example, the genetic homeostasis hypothesis of Lerner, 1954). Although endogenous factors tend often to be the focus of apparent stasis, we must work toward a more general understanding of this phenomenon. Apparent Endogenous Factors in Anastasis As stated earlier, one endogenous factor profoundly affecting apparent stasis lies with the fact there may be a very long time lapse between adaptive shift and structural adaptive response (and thus between primary adaptive shift and phyletic node), owing to the existence of a wide and complex topological gap between preadaptive and paradigmatic adaptive states. There is thus an ‘‘apparent factor’’ with respect to paradigm distance, where adaptive potential may itself lie in a state of sequestration from which it can only be dislodged following a long train of events leading to decanalization. The ‘‘canalization paradox’’ further illustrates how certain structural states may remain ﬁxed for very long periods of time, effectively ‘‘freezing’’ adaptive potential and depressing evolutionary rate of lineage, and the related pleiotropic impediment also has a constraining inﬂuence on realization of adaptive potential, thus affecting apparent stasis as an indirect adjunct of canalization (see Chapter 14). Evolutionary anachronism is thus a corollary of adaptive potential and paradigm distance, and canalization is also implicated in this scenario. We must therefore consider that the term stasis can simply refer to a lack of anagenetic progress owing to evolutionary anachronism. The above apparent factors for anastasis are clearly linked to constraints and impediments in adaptive potential (see Chapters 7 and 14), rather than

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being diagnostic of a ‘‘ﬁnal’’ state of adaptation, and a fundamental dichotomy clearly exists between the ‘‘potential changes that have not yet happened’’ and the ‘‘no further change necessary’’ scenarios. If an anagenetic sequence reaching an ultimate adaptive limit is equivalent to true stasis, then evolutionary anachronism cannot also constitute stasis! Real Endogenous Factors in Anastasis As already suggested above, true anastasis may be postulated to have been reached when an anagenetic sequence has reached the adaptational paradigm state. However, an observed state of supposed anagenetic stasis is not necessarily to be interpreted as ‘‘biophysical paradigm state attained,’’ but may be a transient state at which the selective pressure for stasis is greater than that for further anagenetic change, over a given time course. An obvious problem with the above view clearly lies with the existence of ‘‘living fossil’’ taxa, where an adaptive limit has not apparently been reached, but where there appears to have been no selection pressure for further advance toward the paradigm state (however, see extrinsic factors below). Coallometric transformation (Chapter 16) also constitutes a further problem for the adaptive limit deﬁnition of anastasis, in that very many ‘‘ﬁnal paradigm states’’ actually continue to change as a function of the relationship between absolute size and the gravitational force. Thus, even true stasis is subject to variance in the biophysical paradigm, owing (for example) to the gravitational input to biomechanical systems, and thus probably often constitutes an amphigenetic rather than stasigenetic state. Consequently, the diagnosis ‘‘adaptive limit reached’’ must be regarded with skepticism. A great many suboptimum states obviously exist in Nature, and here we must presume that something other than the anagenetic selection interface itself is holding up progress.

Extrinsic and Integrated Factors in Anastasis Linked to Adaptive Corridors If we now accept that anagenesis is impeded by some factor other than evolutionary anachronism or adaptive limit, then it seems most probable that the explanation in adaptive equilibrium already invoked with respect to species stasis might be operating here also. This hypothesis can be usefully examined in the context of the adaptive corridors hypothesis (see Chapter 18). Adaptive Equilibrium as Stasis in the Benign Adaptive Corridor Adaptive equilibrium has already been considered as an element in cladostasis, and also as an impediment to anagenetic change in the context of an input to depressed (hypotelic) evolutionary rate (see previous chapter). Accordingly, Wright’s adaptive topography model (as a special theory of evolution; see Chapter 13) must be viewed in the wider context of holding a potential function for evolutionary stasis, in the particular context of the benign adaptive corridor. Thus, where the structural component of the adaptive response is invoked, the benign adaptive corridor clearly constitutes that substrate necessary for evolution of ‘‘stasis in adaptive equilibrium’’ in relation to an expanding adaptive response in allomorphic variation linked to a dynamic selection interface.

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The differential between 움- and 웁-anagenesis also cannot be exclusively driven by that anagenetic trait which forms the leading factor in the intrinsic selection gradient itself. Other elements must also contribute to the adaptive state, and the evolutionary rate of an anagenetic sequence must derive from quite diverse inﬂuences in the adaptive system, including that of ambient allomorphism and minor cladogenesis (as indeed already proposed in the constrained model of hypotelic evolutionary rate). Any analysis must therefore look at the input from all components of the active selection interface, including those extrinsic to the anagenetic point of interest. It is obvious, at this point, that anastasis will be more apparent in the hostile adaptive corridor than in the benign. Although it may reasonably be supposed that there is a tendency to evolve toward the benign state via a predominantly structural response, any subsequent ingress of stochastic effects in the external environment may cause the system to gravitate toward the logistic response in the hostile environment. There will consequently be a tendency to adopt a compromise solution of ‘‘stability in adaptive equilibrium’’ within a long-term macroniche in any stable adaptive corridor conﬁguration, with a bias toward logistic equilibrium in the hostile and toward structural in the benign. This is why the orientation of the adaptive ensemble is continually falling back on the logistics led strategy, with any deterioration of the deterministic parameters of an adaptive system (as seen with progenesis in Chapter 16). A trend toward anastasis may thus be presumed to occur in any type of adaptive niche, owing to a tendency of gene pools to gravitate toward whichever mode of adaptive equilibrium is most readily attainable in the adaptive corridor present, this occurring as a gravitation of the gene reservoir toward either the major (structural) or minor (logistic) selectional attractor. Both clado- and anagenetic stasis in the benign adaptive corridor is thus often equivalent to the presence of leading effect structural allomorphism and thus really constitutes ‘‘adaptive equilibrium overriding realization of adaptive potential’’ owing to overall selectional balance favoring the selective over the nonselective offset strategy in adaptive capacity. The same is true with respect to the logistic adaptive response in the hostile adaptive corridor. In ‘‘anagenetic stasis through dynamic equilibrium’’ we are, of course, really looking at a special case corollary of that mechanism which affects hypotely in evolutionary rate of lineage, and it is thus correct to apply the term ‘‘apparent stasis’’ in this instance: Wake et al. (1983), summarizing the situation with stasis in plethodontid salamanders, observed that although much evolution had occurred at the molecular level, structure had been relatively static. They concluded that an important contributing factor appears to have been ‘‘plasticity—behavioural, physiological, and developmental—which allows organisms to compensate environmental, and even genetic, perturbations without having to change morphologically.’’ Sheldon (1987) similarly thought that the anagenetic evolution he observed in Ordovician trilobites could only occur through organisms tracking a slowly changing environment so that stasis ‘‘almost paradoxically,

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tends to prevail in more widely ﬂuctuating, rapidly changing environments.’’ Stasis and Competitive Coevolution The question of stasis in adaptive equilibrium cannot be held to be exclusively concerned with the dynamic balance between gene reservoir and abiotic environment, and reciprocal adaptivity clearly raises important questions of how competitive coevolution affects both dynamic equilibrium and stasis. Stensteth and Maynard Smith (1984) analyzed the effect of lag load, in which model each competing species evolves toward mutual dynamic equilibrium, the latter constantly changing, so that W always lags behind the optimum state: — lag load (L) ⫽ Wopt ⫺ W/Wopt Following the lag load model, there are four possible outcomes of competitive coevolution. Two are unstable: the ‘‘lag behind’’ and ‘‘pull ahead’’ options conform, respectively, to contractional and expansionary modes of evolutionary change. In this situation, as lag load increases, so too does the probability of extinction (see Chapter 20). In general, a species interacting with a stable natural adaptive system may be in one of two broader modes: in the ‘‘Red Queen state’’ or in evolutionary stasis. One outcome of the Maynard Smith–Stensteth model is evidently a stationary state in which competitors reach an optimum level and then stay there, there being thus one optimum form to compete with other species. This is clearly linked to the theory of adaptive equilibrium, although the latter is also strongly correlated with abiotic factors in which the leading effect is generally not directly involved in the reciprocity interaction. The adaptive equilibrium model thus encompasses this aspect of competitive coevolution as a subset. The fourth outcome of the lag load model is one manifesting dynamic equilibrium between species (the Red Queen hypothesis; van Valen, 1973), this mode demanding constant deterioration of the environment. This, however, need only constitute stasis with respect to the adaptive state (and not the structural adaptive response). Bradytely and Apparent Stasis in the Hostile Adaptive Corridor Bradytely (see Chapter 18) could perhaps be regarded as true stasis in the restricted sense that an anagenetic adaptive limit is depressed below that of the biophysical paradigm state by virtue of stochastic override of (or sequestration from) selection owing to a predominantly logistic adaptive response to stochastic mortality factors. Given that the true adaptive limit is probably rarely reached even in the benign adaptive corridor (and then only with respect to certain structure integrals), apparent ‘‘organismic stasis’’ as observed in Nature is thus probably most often due to the much more apert inﬂuence of bradytely. A third model for evolutionary stasis thus exists with this particular factor. The constraining inﬂuences of extrinsic adaptive potential arising in the hostile adaptive corridor must, in this way, have a large inﬂuence on apparent anastasis.

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The adaptive corridors concept shows clearly how extrinsic factors could underlie ‘‘stagnation’’ in a lineage, in that this interpretation would also equate with apparent stasis with very low (bradytelic) evolutionary rate, where the adaptive limit is effectively lowered. However, a larger time frame superimposed on supposed stasis of this kind might of course reveal a transient, apparent element! From this analysis, ‘living fossils’ exhibiting apparent evolutionary stasis need not be maintaining either evolutionary anachronism or true stasis, so much as inhabiting a hostile adaptive corridor. Once a lineage has entered such a macroniche, it will probably have evolved one or a few specializations which effectively lock it into that particular adaptive zone (see Chapter 17). In this scenario, it is not a unit structure that reaches an adaptive limit, but ultimately the whole organism, in its state of reciprocal adjustment within the adaptive system. The above view may appear at ﬁrst sight to clash with certain observations that have been made regarding the supposed ‘‘evolutionary plasticity’’ of some relict taxa: Simpson’s observations (1953) of variation in ‘‘modern primitives’’ such as Crocodilia uncovered evidence for as much intergroup variation as seen in more rapidly evolving lineages: ‘‘There is even evidence that conservative groups are sometimes exceptionally variable.’’ However, this variation is clearly not manifested in any ongoing evolutionary activity of the anagenetic kind. Simpson’s remarks above seem perhaps to indicate that anastasis is not equivalent to a ‘‘genetic dead end’’ scenario in relict taxa. However, quite apart from the possibility of confusion with phenotype plasticity, adaptive equilibrium is not the only source of intraspeciﬁc variation in a population, in that the inﬂuence of stochastic survivorship factors might lead to perpetuation of a large contingent of near neutral mutation. How can this be reconciled with the adaptive corridors hypothesis for low evolutionary rate? Polymorphism–allomorphism is certainly incompatible with a hostile adaptive corridor scenario, but stochastic mortality factors will nevertheless promote variation in the gene pool in a manner that is not exclusive to the state of adaptive equilibrium between organism and environment. Consequently, all evidence for variability needs to be subjected to closer scrutiny, and in particular, the neutrality hypothesis of molecular evolution (Chapter 12) must also be considered here.

Interpreting Evolutionary Stasis Evolutionary stasis now seems, in its broad deﬁnition, to be a heterogeneous corollary of several mechanisms, in that most (perhaps all) of these factors could be regarded as contributing only to apparent rather than real stasis, that is, given the counter arguments that have been cited against acceptance of any one them as an absolute deﬁnition of true stasis. In summary,

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Type of stasis

Interpretation

Problem

Cladostasis

Static adaptation interface in the external environment Lack of cladogenetic potential Species ⫽ limit cycle Evolutionary anachronism

Unlikely in larger time frame

Anastasis

Adaptive paradigm limit Adaptive corridors (stasis below adaptive limit)

Likely to be transient in longer term Corollary of adaptive equilibrium Apparent only, owing to action of developmental constraints and impediments Rarely fully valid Corollary of adaptive equilibrium

In actual practice then, the term stasis is usually a reference either to the existence of low adaptive potential or to a heterogeny of factors affecting stasis in speciation and anagenesis. Ultimately, it may more realistically be a reference to the corollary of adaptive equilibrium directing the active selection interface away from evolutionary activity in general, since this appears to constitute a common factor for both clado- and anastasis. The best general deﬁnition of stasis might then be that this condition generally lies with the effect of adaptive equilibrium in the context of intercalation (see Chapter 18). What seems to be a most useful overview, here, is that species stasis constitutes an evolutionary corollary of an unstable niche in which a chaoslike pattern (rather than random stochasticity) is implicated, and evolution appears to take place in an apparently stable niche only when there is no overriding input from the repertoire of adaptive equilibrium in the allelomorphic component of the genome (see Chapters 14 and 18). The proposed solution holds that adaptive systems passing through an episode of evolutionary change may subsequently tend to gravitate toward adaptive equilibrium in either the structural or logistic domain, with stasis constituting a corollary of (rather than being synonymous with) adaptive equilibrium. Anastasis, following the adaptive limit model, constitutes a further tendency of adaptive systems contributing to apparent stasis. However, this is also affected by leading effect allomorphism and is itself subject to an intrinsic residual dynamism. There is a sense, in fact, in which any conﬁguration in the adaptive corridors scenario can be said to ultimately contribute to stasis. In the benign adaptive corridor, we may encounter stasis in adaptive equilibrium in the structural component, whereas in the hostile adaptive corridor, apparent stasis may be evident owing to predominance of a logistic adaptive response. It is also important at this point not to confuse evolutionary stasis with selective removal of advantageous mutations as some have done. Stasis must (in this particular context) not be seen as the absence of dynamic change in the gene pool, but as ongoing depression of evolutionary innovation through a corollary of leading effect allomorphism invoked by the balance existing between different components of the allelomorphic genome. A danger clearly also exists in any assumption that species remain constant if the environment is constant. Any positive novel mutation that arises within the gene pool of a species will be selected for, whether the environment is constant or not (for example, an improvement in mechanical efﬁciency for ﬂight does not depend on changes occurring in the aerial environment). How-

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ever, such changes will only be selected if they are of high enough contribution to overall ﬁtness in terms of the active selection interface.

A COMPREHENSIVE VIEW OF THE ADAPTIVE SUBSTRATE Evolution is frequently shown to be episodic and the ambient state of adaptive systems to be one of stasis, with gradualism also ﬁtting in somewhere in the spectrum of evolutionary activity. How can we now contain this wide range of activity within the context of a single comprehensive model of the evolutionary process?

Episodic Evolution, Stasis, and the Evolutionary Substrate The evolutionary substrate model (Chapter 14) is not conﬁned to episodic evolution alone, since ambient microevolution does not imply any necessary dramatic change of a quantum kind. With gradualistic change, only small increments to ﬁtness occur. Again, the macroevolutionary substrate seen in episodic evolution of the quantum kind may be presumed to be linked to an adaptive isthmus passing from one adaptive zone to another via a large occlusion zone, whereas the microevolutionary model certainly does not. Adaptive zones may be seen as being essentially quasi-autonomous adaptive systems that are connected to the global system only by isthmuses in the temporal plane, but not all evolution is actually concerned with movement between bounded adaptive zones. A Comprehensive Substrate Model What is the probability of evolutionary change occurring in the face of ambient adaptive equilibrium and stochastic override of selection? We can begin by deﬁning the evolutionary substrate (see Chapter 14) in terms of selection space open to truly neomorphic allelogenesis. To examine this circumstance more closely, we shall return to the problem of anagenetic change in the context of varying levels of allomorphism in adaptive equilibrium (see Chapter 18). In this situation, the contribution of anagenetic change to the selection interface (⌺ WA/⌺ W ) clearly constitutes that particular adaptive substrate on which evolutionary change can actually occur. However, there will be many different levels at which this value exists in Nature, since ideally the adaptive substrate might be construed in terms of a continuous distribution, and only a limited sector of the entire substrate may actually be conducive to rapid evolutionary change. Evolutionary activity is thus obviously conﬁned to a relatively small proportion of a much wider substrate in terms of adaptive capacity and potential. There are in fact two main factors tending to depress the adaptive substrate, principally (1) the level of adaptive equilibrium in the selection interface itself (⌺ Wa) and (2) the level of stochastic mortality in populations, such as would tend to override selection. We can see, for example, that if ⌺ Wa ⬍ 1.0, then ⌺ WA ⫽ (1.0 ⫺ ⌺ Wa). However, since the value of ⌺ WA also depends on the degree to which stochastic mortality factors affect populations, a low level

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input of selectional mortality relative to total mortality (Ms) will act to further depress the adaptive substrate, in which case that component of population space in which anagenetic change is occurring is given by ⌺ WA ⫽ (1.0 ⫺ ⌺ Wa) ⫻ Ms It is possible to examine all conﬁgurations of the above equation in the context of a much simpliﬁed three-dimensional surface, where X ⫽ ⌺ Wa, Y ⫽ Ms, and Z ⫽ ⌺ WA ⫽ (1.0 ⫺ ⌺ Wa) ⫻ Ms ⫽ (1.0 ⫺ XY ), thus arriving at a working deﬁnition of the adaptive substrate (of which the evolutionary substrate forms one special subset). The ﬁrst observation to make here is clearly that ⌺ WA values on the XYZ matrix approach 1.0 (‘‘the ideal evolutionary substrate’’) only when X 씮 0 and Y 씮 1.0. We can choose arbitrary cutoff points for substrates which (subject to endogenous adaptive potential) would be conducive to stasis (ⱕ0.25), gradualism (⬎0.25, ⱕ0.75), and punctuation (⬎0.75), in order to examine the broad primary topography of the substrate equation. From the topography of the surface shown in Fig. 113, it is clear that even with an equal frequency distribution for all intercalary substrates, quantum punctuation will be a relatively uncommon event.

FIGURE 113 Distribution surface for the adaptive substrate (surface orientated to display the highest Z values). Substrates conducive to different levels of adaptive response are indicated.

What, then, is the ambient frequency distribution for the adaptive substrate surface in natural adaptive systems? All the evidence points to highest frequencies for peaks centered around leading effect allomorphism and stochastic

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override of selection, which circumstance makes punctuation a very rare event indeed. In a sketch surface for the frequency distribution of the adaptive substrate (see Fig. 114), most gene pools are thus visualized as having a very high component of adaptive equilibrium and/or a high input from the logistic adaptive response to stochastic mortality factors.*

FIGURE 114 Frequency distribution (freehand sketch) for the adaptive substrate. The orientation and X,Y axes are as in Fig. 113; Z ⫽ frequency XY.

In the diagram shown in Fig. 114, evolutionary stasis by adaptive equilibrium or stochastic override is shown as being the predominant state of adaptive systems. Gradualism occurs in the context of an ambient evolutionary substrate * Given the assumption that ‘‘endogenous adaptive potential is available’’ in the graph shown in Fig. 114, the heights of the stasis peaks would be very much greater in a four-dimensional surface, with adaptive potential forming a further axis!

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on the middle slopes, while that for quantum punctuational change is exceptionally rare. This ‘‘twin-peaks’’ model is perhaps the fundamental attractor for biotic adaptive systems, owing to a dual gravitation toward adaptive equilibrium linked to chaos and to purely stochastic domains, in terms of the structural and logistic components, respectively, of adaptive capacity. Evidence in support of the above broad topography (which of course can only be a rough approximation) comes from several sources, and can be summarized as follows: • Paleontological evidence exists for widespread species stasis (following Gould–Eldredge–Coope) in at least a signiﬁcant proportion of many biotas. • The origin of new higher group lineages is observed to be rare, both from paleontological evidence and by inference from extant taxonomic hierarchies. • Observed levels of genetic allomorphism in natural populations are demonstrably diagnostic of adaptive equilibrium and not evolutionary change. • The physical organization of the genome is also clearly structured around adaptive equilibrium, in its links with allelomorphism and recombination. • The known mechanisms of canalization and sequestration are demonstrably counteractive to evolutionary change in the ambient adaptive substrate. • The observed results of perturbations to ambient evolutionary stasis (as seen, for example, in remote island and other isolated biotas) clearly support the view that evolution only occurs when adaptive equilibrium and high stochasticity can be bypassed. • Major quantum events in evolution are generally associated with the aftermath of mass extinctions (see Chapter 20) or with other threshold events (as in the Precambrian radiation of advanced multicellular organisms). Evolutionary change thus only occurs in those regions of the adaptive substrate at which change to stasis and low ambient evolutionary rate is invoked. This can take place through ‘‘peripheralization’’ (as observed in isolated biotas), but the stimulus can also be endogenous: For example, a neomorphic gene for temperature regulation could remove a strong leading effect allomorphism decrement, where regulation had previously been due to n allelomorphic genes with different selective values at different temporospatial loci. Microevolution (particularly in the form of neomorphic allelogenesis adding to the repertoire of adaptive capacity) takes place within the gradualism domain. However, the quantum punctuational substrate is an essential component of the substrate topography, so far as many speciational and other macroevolutionary events are concerned. The greater the degree of shift toward the evolutionary substrate, the greater is the level of structural change which may be supported in the punctuational selection interface—paramorphy in lower,

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possibly neomorphy in higher. The effect of quantum punctuation can additionally be illustrated using the sigma–delta equation set approximation (see Chapter 18).

FIGURE 115 Punctuation in the sigma–delta equation set, through collapse of adaptive equilibrium (compare with Fig. 108).

Following the occurrence of an ‘‘evolutionary episode,’’ restoration of cladogenetic activity, re-expansion of the domain of adaptive equilibrium, or any ingress of competitors or predators will, of course, invoke increasing levels of infraspeciﬁc competition, so that there will be subsequent gravitation toward a state of renewed evolutionary stasis. This alternation between episodes of evolutionary change and stasis is, of course, the intercalation model already discussed in Chapter 18.

MAIN POINTS FROM CHAPTER 19 1. The concept of evolutionary stasis reﬂects a heterogeny of factors. Of particular signiﬁcance is the fact that evolutionary rate tends generally to be damped by inﬂuences tending to invoke adaptive equilibrium of one kind or another, and this has a very large input to species stasis. 2. Stasis must clearly embrace the concept of adaptive equilibrium, in which case ‘‘nonstasis’’ is simply equivalent to true evolutionary change. At the level of the phyletic lineage, special points of interest lie in cladostasis and anastasis. These are not, however, mutually independent phenomena. 3. Species tend to act as limit cycles in the evolution of adaptive systems, owing to a corollary of gravitation toward a state of adaptive equilibrium in the structural domain, with respect to the benign adaptive corridor—as also in the logistic domain, in the context of a hostile environment. Geophysical

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dynamics and dispersal patterns obviously form important inﬂuences affecting cladostasis. 4. Anastasis is evident in certain apparent factors linked to constraints on realization of adaptive potential, as well as in a tendency toward equilibration at a suboptimal adaptive limit. Real anastasis constitutes a corollary of adaptive equilibrium, being manifested in hypotely in the structural domain and bradytely in the logistic, for wide and narrow adaptive corridors, respectively. None of the foregoing interpretations of stasis is, however, fully valid in terms of relating to the whole organism. 5. A comprehensive theory of the adaptive substrate must combine the extremes of episodic evolution, gradualism, and stasis. This is illustrated in a frequency distribution reﬂecting the degree to which selection for evolutionary change penetrates the ambient adaptive state. 6. The ambient frequency distribution for the adaptive substrate surface must be doubly skewed toward stasis in adaptive equilibrium and in stochastic override of selection, with a minimal peak for the active evolutionary substrate. This view receives support from paleontological evidence, as well as from theoretical considerations in both population and developmental genetics. 7. The effect of quantum punctuation must be that of shifting the evolutionary substrate of a gene reservoir to a high level, as the corollary of a dramatic lowering of peaks in both adaptive equilibrium and stochastic override. Following punctuation, the adaptive system will tend to gravitate toward restoration of the ambient state of stasis. 8. The greater the shift toward the evolutionary substrate and away from the ambient state of adaptive equilibrium, the greater is the degree of morphogenetic change which can be supported in the punctuational selection interface.

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20

EXTINCTION—LINEAGE TO CLADE

THE NATURE OF EXTINCTION It is quite possible to discuss evolutionary activity as if all phyletic lineages remain complete for all time. This is, however, clearly completely unrealistic. In fact, the general theory of evolution is itself incomplete in the absence of an explanation of the causal factors of extinction. The latter can in fact be shown to be the result of a heterogeny of predictable behaviors of evolving adaptive systems. One very important reason to examine the extremely widespread inﬂuence of extinctional mechanisms in detail is to consider that, in the apparent dichotomy between close gradualistic differentials between extant taxa in speciesrich complexes and the wide phenotypic gulfs existing between many higher groups, valid explanations may often lie not so much in saltational evolution (or in the existence of unrealistically high evolutionary rates) as in the activity of extinction factors. What factors actually act to change the proﬁle of the anagenetic sequence with time, as lineage becomes clade? The evolutionary interest in this question clearly lies mainly with intrinsic factors, but stochastic inﬂuences must have a profound effect also. The latter is probably more true for extinction than for any other facet of activity associated with adaptive systems, despite the fact that some past workers actually considered that the conversion of lineage to clade is invariably a direct manifestation of the evolutionary process itself. Central to this problem is the observation that ‘‘extinction’’ seems almost at ﬁrst glance to be a heterogeny of effects.

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Mortality versus Extinction Not all mortality factors can be presumed to be potential extinction factors, and mortality and extinction will have different effects at the genotype and gene pool levels, according to causality in the adaptive system. For example, all gene pools within a gene reservoir must be lost in order to constitute species extinction, and similarly, all species within a genus must be lost to effect ‘‘generic extinction.’’ Above the level of gene pool in particular, categorization of extinction level clearly must depend on the subjective opinions of taxonomists! However, the view that extinction must therefore be deﬁned on the basis of species and above, rather than being concerned with mortality factors acting at a lower level, must be considered with care, especially bearing in mind the mechanism of phyletic occlusion. Direct and Indirect Causal Factors The primary causality of an extinction event must clearly lie at its ﬁrst temporospatial locus of activity within the adaptive system. We must then examine the complete trophic level hierarchy with respect to a possible trajectory of indirect causalities, since many apparent extinction agencies can be traceable to other mechanisms (for example, extinction of a gene pool owing to disappearance of its nutritional resource may really be due to loss of some other limiting factor acting on the latter). The causalities of extinction may thus frequently lie in a sequential chain of events rather than in a single factor, and this must be borne in mind wherever we are attempting to link cause and effect. Although proximal causalities are often the main point of interest, many of these may not be direct. Furthermore, seemingly diverse proximal causations may often have a common distal root in events lying beyond the domain of the adaptive system itself. These problems obviously create particular difﬁculty in the analysis of paleontological data, so that it is sometimes more instructive to extrapolate from our knowledge of living adaptive systems. Biotic versus Abiotic Extinction Factors Extinction factors may be biotic or abiotic. However, following the above maxim concerning proximal versus distal causes, the true primary cause of an extinction may be abiotic when the secondary mechanism is biotic. Very many extinction factors fall into this category. Deterministic versus Stochastic Extinction Factors By deﬁnition, deterministic extinction factors arise within, while stochastic ones originate beyond the boundary of the adaptive system. Thus, with the biotic–abiotic dichotomy, a primary abiotic cause may often be stochastic, while the secondary biotic effect appears deterministic. In all probability, very many extinction factors are at least indirectly stochastic in origin (see below). Some quasi-random mortality factors may of course manifest authentic links with the adaptive system via logistic strategies in adaptation, whereas others will be of entirely ‘‘exotic’’ origin. Stochastic mortality factors in the nonselective offset of fecundity (Chapter 4) thus really belong to the adaptive system, whereas true stochastic extinction factors lie outside the threshold band in adaptive capacity for adjustment in r, or else have simply had no previous

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encounter with the adaptive system. However, a stochastic extinction factor may begin as an integral part of the adaptive system and later transgress adaptive capacity for logistic adjustment in the nonselective offset of fecundity. The latter may, indeed, increase within the boundaries of a chaotic external inﬂuence (although clearly not if this leads to such formless randomness that a population zero line is reached throughout the gene reservoir). Similarly, some potential extinction factors of entirely exotic origin may prove to be ultimately adjustable within the context of the nonselective offset of fecundity.

EXTINCTION FACTORS AND THE ADAPTIVE SYSTEM As we have seen, extinction factors can often be readily traced to proximal processes and mechanisms in the structure of the adaptive system, although the latter in turn may ultimately prove to be far removed from the direct causality. The general heterogeny of these mechanisms can be analyzed with reference to two principal parameters, namely, whether a given extinction factor lies in the selection interface or solely in the adaptation interface. In the latter context, the trophic level forming the locus of the external extinctional mechanism will also be shown to be of interest, this second dichotomy being linked to that existing between factors arising in the major as against minor adaptive niche (see Chapter 2). The fact that extinction factors arising in the selection interface frequently relate to other equivalent trophic level genotypes is of special interest in the context of ‘‘pseudo-extinction’’ happening as a corollary of evolutionary change, a situation that does not arise in that circumstance in which the adaptation interface is simply broken. In this situation, ‘‘equivalent trophic level’’ can of course mean members of the same species or else members of different species occupying the same adaptive niche. The range of factors observable in the above extinctional scenarios and causal to change expressed at the genotype and gene pool levels links to the alternative scenarios of cladogenetic substitution and phyletic occlusion (see Chapter 6, 12, and 17) as components of selectional extinction, and also to the alternative concepts of minor and major adaptational dysgenesis (equivalent to the inability to adapt to change and loss of key resource, respectively). These phenomena can be outlined as shown in Fig. 116. The diagram reﬂects the important dichotomy between adaptation-rooted and selection-based extinctional factors, identifying cladogenetic substitution and phyletic occlusion as being selectional in origin, with minor and major dysgenesis constituting independent modes of extinction arising from direct dislocation of the adaptation interface. This dichotomy also reﬂects the fact that many supposed ‘‘selective agencies’’ have no connection with any real selection interface, this being due to a fundamental misunderstanding as to what selection actually is. Extinction in general can also be seen to underline the need for the adaptive capacity concept introduced in Chapter 1 (see also Chapters 3 and 5).

Selectional Extinction Mechanisms Selection-rooted extinction is that component of extinction sensu lato which arises through true selectional interactivity between genotypes or gene pools

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FIGURE 116 The heterogeny of extinction factors affecting the evolution of adaptive systems.

as a result of the coexistence of different relative adaptive states in the same niche. The simplest expression of selectional extinction lies with cladogenetic substitution, although phyletic occlusion has already been implicated as a potential source of phenotype ‘‘loss,’’ as a higher form of iterative substitution in the context of anagenesis (see Chapter 12). It is vital to see that selectional extinction factors are actually endogenous to the affected lineage gene pool and thus constitute a corollary of the evolutionary process itself. The Substitutional Mechanism and Speciation With genomic or species substitution, one species is replaced by another in the context of a cladogenetic selection interface. The essential extinctional mechanism lies here in competition for a coincident adaptive niche (one gene pool being adaptationally inferior to another), combined with lack of endogenous cladogenetic potential for binary resolution in speciation (Chapter 6). The effect of compound genetic differentiation in allopatric divergence being followed by two gene pools arriving at a neosympatric selection interface may thus lead to cladogenetic forces which cannot be resolved by genetic

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readjustment. This can mean substitution of one gene pool or else speciation, which latter is simply binary resolution of the same scenario such that the extinctional element is merely suppression of the hybrid state. Cladogenetic factors in general include the following extinctional corollaries of realized major cladogenesis: 1. Merging of gene pools (with ‘‘partial extinction’’ of each) in genomic anastomosis 2. Genomic or species substitution (no propensity for speciation in cladogenetic potential) 3. Elimination of the hybrid state through evolution of prezygotic species isolation Cladogenetic Substitution, Phyletic Occlusion, and Species Sorting In the past, much confusion has existed between ‘‘evolutionary trends’’ of various kinds and true anagenetic evolution, and this has resulted in some controversy concerning the supposed mechanisms of ‘‘species sorting.’’ This problem must now be reassessed in the light of substitutional and occlusional mechanisms. Stanley (1975) proposed the term species selection to embrace certain evolutionary patterns: ‘‘If most evolutionary change occurs during speciation events and if speciation events are largely random, natural selection, long viewed as the process of guiding evolutionary change, cannot play a signiﬁcant role in determining the overall course of evolution.’’ Eldredge (1989) adds that ‘‘species appear to be sorted . . . as well as being the product of selection and drift,’’ following Vrba, who proposed species sorting as a more neutral term than (sensu lato) species selection (see Vrba and Gould, 1986). The supposedly random and non- or maladaptive element in the evolution of adaptive systems has already been discussed at an earlier point (see Chapters 15 and 17), and Stanley’s original view of species selection has also been refuted (see Chapter 6). However, other problems clearly now have to be examined in relation to species sorting, which latter is obviously linked to a heterogeny of selectional and other extinction factors. In general, any discussion of species interactions must begin from the standpoint of the competitive exclusion principle. As already pointed out, the most signiﬁcant species interactions giving rise to a corollary in extinction will be cladogenetic substitution plus minor and major phyletic occlusion linked to anagenesis. This does not of course mean that all species of a lineage are necessarily involved in mutual competition, nor does it in any way exclude the existence of much nonanagenetic activity from being causal to speciational divergence. Most signiﬁcantly from the viewpoint of the present argument, however, is the observation that certain genuinely nonselectional species sorting events probably constitute adaptational extinction (see adaptational dysgenesis, below). Not only are these nonselectional events, but they are also noninstrumental to the generation of diversity patterns (i.e., other than in the much restricted sense of reducing diversity)! Species selection is also partially equivalent to postspeciational divergence (see Chapter 6). However, as we have now seen, a large element of extinctional activity is clearly also evident in the broader domain of species sorting.

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Phyletic Occlusion as a Corollary of Evolutionary Change We have already proposed that anagenesis can proceed in the infraspeciﬁc mode through phyletic occlusion, the natural corollary of which is the occurrence of much ‘‘pseudo-extinction’’ in the occlusion zone. Thus, change at the genotype level may also be expressed in some linear iterative aspect. Phyletic occlusion is therefore part of the evolutionary relationship between genotype and phenotype, involving change within the gene reservoir. In analyzing the phyletic occlusion of a given phenotype, reference must clearly be made, not to individual genes (as deﬁned by ‘‘point mutations’’), but to the architecture of the entire genetic module controlling the phenotype trait in question. As we saw in Chapter 12, occlusionary changes in a regulatory locus are linked to manifestation of linear, iterative change in a phenotypic parameter as expressed in the dynamics of anagenesis, whereas the gene substitution model may more nearly approximate to changes in variation in minor genetic traits linked to adaptive equilibrium. In iterative occlusion then, the phenotype becomes occluded predominantly through changing regulator activity in the epistatic system. In the above scheme, the ‘‘basal gaps’’ of many lineages must be presumed to be at least partly due to ‘‘morphospace lost due to phyletic occlusion’’ in the regulatory hierarchy of major epistatic systems. Examples are legion, and they include the autopod of terrestrial vertebrates as well as precursors to fully evolved ﬂying appendages in insects, bats, and birds (see Rayner and Wootton, 1991). Phyletic Occlusion and Atavism The concept of phyletic occlusion raises interesting questions concerning atavism and amphigenesis. The lost phenotypic traits of phyletic occlusion may be regarded as having been, in a sense, ‘‘absorbed into the modiﬁed genotype’’ rather than having been eliminated; that is to say, some component of the parent genome has evolved rather than having been lost, namely, by addition of new genes rather than through actual loss of old ones. Here, the ‘‘lost’’ genotype is, in some manner, sequestered within the extant epigenetic system. Occlusional extinction may therefore (in theory at least) be facilitative to both atavism and amphigenesis, on account of a hypothetical ‘‘retrievability factor’’ (see Chapter 12). Phyletic Occlusion, Morphogenetic Accommodation, and Recapitulation The lost traits of phyletic occlusion should also have the potential to remain, not only as potentially atavistic components in some sequestered region of the genotype, but sometimes also as actual precursor developmental states manifesting a topological relationship with the ﬁnal modiﬁed phenotype state, within the context of morphogenetic accommodation. Thus, a trait that has been removed from the ﬁnal phenotype state may continue to serve as an ontogenetic or phenogenetic state during development. Just as phyletic occlusion is a corollary of anagenetic change, so too is recapitulation a potential corollary of phyletic occlusion itself, although this may involve any level of

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adjustment to the geometric coordinates of a portion of a developmental trajectory (and, of course, many retrotranslative changes may simply devolve below the ﬁnal translation level ). In this context, the recapitulatory component of accommodation is now shown to be a function of the degree to which developmental modularity permits an epistatic system to simply ‘‘switch on’’ certain morphogenetic coordinates at an earlier stage with no change to former phenotypic coordinates and without invoking any large element of negative translational pleiotropy (see Chapter 16). ‘‘Recapitulative accommodation’’ thus occurs when a developmental phase retains ancestral adult form, so that atavism must then have a higher probability of occurring than when a more complex topological relationship occurs between ancestor and descendant. Consequently, recapitulation provides some developmental evidence in support of the phyletic occlusion concept, in the same way that atavism provides direct genetic data for this. From the link between phyletic occlusion and morphogenetic accommodation–recapitulation, we now approach the question of the directionalization function in anagenesis. It seems likely that occlusion actually becomes iterative owing to the fact that an evolving epistatic system is tending to organize a sequence of adjacent morphosystems in an accommodative manner, such that each successive stage in the sequence becomes a fabricational precursor to the next stage. This mechanism must in turn constitute an important element in directionalization of the anagenetic sequence. It is instructive to now compare and contrast the mechanisms of phyletic occlusion and compound substitution in terms of several signiﬁcant differentials that have emerged: Phyletic occlusion

Cladogenetic substitution

Iterative changes to regulatory hierarchy of an epistatic system; lost alleles submerged through addition of new members to system High probability of recovery of genotype and phenotype in amphigenesis Lost trait may be subject to atavism Lost trait may be involved in recapitulation via morphogenetic accommodation Major phyletic occlusion invokes false species substitution via the anagenetic selection interface Major link to basal gaps in extinction scenario of higher groups

Allelic substitution in n loci of diverse function

Major contribution to architecture of diversity patterns Forms a component of the directionalization function in anagenesis

Lower probability of recovery Lower probability of atavism No input to recapitulation possible for lost traits True species substitution occurs via a leading effect in the cladogenetic selection interface Minor link to extinction patterns, particularly concentrated at level of species sorting Lesser contribution to diversity patterns No (or only negative) contribution to directionalization function

Selectional Extinction and the Anagenetic Integral Curve The intrinsic selection gradient of anagenesis (see Chapters 17 and 18) can alternatively be interpreted as a survivorship curve, on the grounds that probability of survival must be approximately directly proportional to the

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selection gradient at any point in the trajectory, namely, as a function of the degree of anagenetic differentiation tending to develop in the gene reservoir. As we have already seen, only the steepest selection gradients may invoke direct phyletic occlusion. As selection pressure drops below this level, we may more frequently tend to encounter major phyletic occlusion or species substitution. At a later stage, as the anagenetic rate drops to ambient level, speciation will then tend to dominate the adaptive response (since cladogenetic potential will expand as a predominant force as anagenetic change drops to sequiform status in the joint cladoanagenetic selection interface). From the above argument, we arrive at a law of anagenetic survivorship which states that the hierarchy in the selection gradient intrinsic to a given anagenetic sequence invokes a complementary hierarchy in successive modes of extinction, manifested in temporal sequence: minor phyletic occlusion ⬎ major phyletic occlusion ⬎ species substitution ⬎ speciation ⬎ genomic anastomosis. There is thus a predictable trend in the way basal gaps expand in the domain of phyletic occlusion or cladogenetic substitution. In contrast, the Simpsonian horotelic range of evolutionary rates constitutes that sector of the anagenetic sequence in which ambient speciation is a dominant activity, with selectional extinction ultimately being manifested mainly in the domain of hybrid substitution or genomic anastomosis.

FIGURE 117 The extinctional trend relative to the anagenetic integral curve, with predominance of different modes of extinction indicated at different stages of the anagenetic sequence (freehand).

In the above scenario, it is furthermore evident that bradytelic lineages must not only manifest apparent stasis through an effective lowering of the adaptive limit in anagenesis, but should also contain the narrowest basal gaps (as indeed seems to be the case with ‘living fossil’ taxa).

Nonselectional Extinction in Adaptational Dysgenesis Adaptational dysgenesis occurs in the absence of any selection interface, owing to breaks in the fundamental adaptation interface between organism and envi-

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ronment. This mode of extinction is thus due to factors external to the lineage gene pool itself and, unlike selectional extinction, does not form a corollary of any real evolutionary change in the affected lineage. Selectional extinction is thus linked to deterministic, and adaptational, to stochastic factors operating in adaptive systems. Adaptational dysgenesis clearly always acts as a negative input to diversity pattern in that it can never maintain or add to the latter, whereas true selectional activity can (and frequently does) also maintain or increase diversity. It must now also be made clear that much apparent ‘‘selection acting against species and higher groups’’ is not group selection (see species sorting, p. 515), since it is either a corollary of individual selection or else (as in the present case) is not in fact selection of any kind. This is a distinction that has almost universally been overlooked in the analysis of extinction. A further element in the heterogeny of species sorting also comes from changes in the adaptation interface. However, these factors contribute little to evolutionary patterns other than lineage gaps. Factors in adaptational dysgenesis have, of course, previously been recognized in earlier studies. Simberloff (1986) deﬁned ultimate and proximate causes of extinction: ‘‘processes that make populations rare in the ﬁrst place’’ versus ‘‘those which may ﬁnally cause extinction, once populations are small.’’ Simberloff’s four commonest causes of extinctions below the minimum viable population were as follows: • Demographic stochasticity, or ‘‘gambler’s ruin’’ • Genetic deterioration, or not enough genetic variability to adapt to changing conditions • Social dysfunction, or males not ﬁnding females, etc. • Extrinsic forces, or ﬁre, disease, and so on Many of Simberloff’s factors probably link in one way or another to adaptational dysgenesis. Lawton (1995) considered phylogenetic effects on extinction: In birds, large bodied species are commoner than small bodied in the more ancient tribes (see Cotgreave and Harvey, 1991), and rare North American plants are signiﬁcantly overrepresented in certain families (Schwartz, 1993). In such situations, change seems to have been rendered impossible, other than in minor coordinates of form (Raup, 1991). Many of the above examples probably constitute ‘‘overspecialization’’ in relatively senescent lineages, and again, adaptational dysgenesis seems likely to be frequently invoked whenever such factors actually do lead to extinction. It follows that macroevolution (by the deﬁnition adopted here) is, under certain conditions, ‘‘its own worst enemy’’ (see also evolutionary progress, Chapter 8). In this context, we might well extend the widely known ‘‘Peter Principle’’ to encompass organic evolution: ‘‘Every lineage rises to its own level of incompetence, then falls back on logistic adaptation, ﬁnally tending to extinction unless some new structural advance is made and phyletic divergence occurs.’’

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Major Adaptational Dysgenesis Adaptational dysgenesis can be conveniently subdivided according to whether the external agency lies in the major or minor adaptive niche, thus giving major or minor adaptational dysgenesis. Major adaptational dysgenesis occurs because of loss of one or more key positive niche parameters, speciﬁcally in the domain of the major adaptive niche (bearing in mind the fact that any possible loss of minor niche will most probably be compensated rapidly by the logistic component of adaptation). In this scenario, there is no differential survivorship, either within or between competing gene pools, hence no selection interface.* Major adaptational dysgenesis is noncompetitional in origin, and it does not form part of the evolutionary relationship between lineage and clade. An essential major niche resource disappears, either permanently or as the result of periodicity greater than that permitting evolutionary reversal through amphigenesis. Major dysgenesis results in loss of a gene reservoir in its entirety, and immediate extinctional mechanisms lie in the interface with inferior trophic levels or with abiotic factors. It should also be stated at this juncture that extinction is not necessarily an automatic corollary of even quite dramatic environmental change, but may occur at the end point of some cascade leading ultimately to a dysgenetic event: Coope (1995) studied Quaternary insect subfossils during glacial transitions, some of which were very rapid. The mass extinctions of large vertebrates that occurred during the last 2 My (many presumably owing to major adaptational dysgenesis) were not reﬂected in the insect fauna from the same period. Many common subfossil insect species of Great Britain are now restricted to Siberia or even to the Asiatic region. In the above examples, it can be seen that the probability of extinction through changing physical (and especially climatic) conditions depends on the distribution and dispersal of species, and on whether niche conditions do or do not remain stable in at least part of the range of a mobile species unit. Lawton (1995) discussed the question as to whether vulnerability to local extinction is independent of where species ﬁt into food chains, following the suggestion that higher trophic levels ought to incur greater probability of extinction. An analysis by Mikkelson (1993) suggests that this is in fact not the case but that, conversely, proportions of species in different trophic levels remain constant as diversity falls. It should therefore not be assumed that major adaptational dysgenesis is an automatic corollary of changes in the middle and lower trophic levels of an ecosystem. The most likely explanation of these ﬁndings may simply be due to the capacity of gene pools to manifest a ﬂexible logistic adjustment in the face of such changes. Certain catastrophic events seem likely to lie at the causal root of many examples of abiotic dysgenesis (see below). * In biotic dysgenesis linked to mechanisms apparently operating from a superior trophic level, causality could hypothetically lie in loss of predation acting as a ‘‘population check loss.’’ However, this seems an inherently unlikely scenario!

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Biotic and Abiotic Factors in Major Adaptational Dysgenesis Major adaptational dysgenesis divides naturally into biotic versus abiotic components, whereas in cladogenetic substitution and phyletic occlusion, the (immediate) causality is invariably biotic. Whereas the latter are clearly restricted to interactions between gene pools of equivalent trophic level, biotic dysgenesis principally involves factors from inferior trophic levels (loss of limiting resources, etc.). With major biotic dysgenesis arising from changes at inferior trophic level, structure may have moved far from any morphosystem which could lie adjacent to some unpredicted, dramatic change in the adaptive paradigm, so that any required structural transformation becomes impossibly remote (for example, ‘‘loss of limiting resource,’’ leading to a discontinuity at the niche interface in the adaptive ensemble). Progressive increase in the constraint inherent to canalization of highly specialized structural states can therefore mean that poised systems have little probability of being adjacent to adaptational paradigms when rapid changes occur in the external environment (see Chapter 15): Huxley (1942) voiced a concern that was quite widely expressed by the synthetic school of evolutionary biologists, namely, that a supposedly ‘‘orthogenetic’’ input to evolution could not be adequately explained on a selectionist basis. One apparent example of this lay in the shell coiling trait of Gryphaea which was said to have become ‘‘overextrapolated,’’ such that a number of lineages eventually became extinct through ‘‘overcoiling,’’ seemingly in lack of adaptive potential for amphigenetic change. It is only necessary to see that any irreversible anagenetic change which later meets a sudden reversal in some key environmental variable will naturally tend to incur extinction. Consequently, anagenesis may often contain a source of latent adaptational dysgenesis, and certain cases of apparent orthogenesis may constitute real examples of this. This phenomenon could be correctly identiﬁed as nonselectional (in the lack of any differential survivorship between gene pools), but it is clearly neither non-Darwinian nor orthogenetic in nature. As we have seen above, niche changes can occur because of misalignments in tertiary adaptive equilibrium or in the context of much larger time frames. There exists every intergrade between dynamic and static selection proﬁle in the selection interface, and periodicity may sometimes be great enough to permit anagenetic change yet be subject at the same time to longer term reversal, so resulting in extinction. Tertiary adaptive equilibrium may thus form a signiﬁcant input to major biotic dysgenesis, owing to the presence of a precarious adaptive response that cannot be rapidly reversed within existing adaptive capacity, a situation which essentially constitutes collapse of adaptive equilibrium itself. Major dysgenesis may occur in the structure–niche link by virtue even of such simple misalignments as those relating to absolute size differentials, and with Cope’s law, both ‘‘too big’’ and ‘‘too small’’ may at times be placed in this category. Here again, the causal mechanism derives from sudden reversals

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in the adaptation interface of unpredictably long period (in which respect, Cope’s law is really, in its allometric role, only a subset of overspecialization). Abiotic factors in the above scenario include any extinction factor other than those involving organismic agency, and which also belong to the adaptive system itself (mortality factors from climate, geomorphology, etc.): Biotic

Abiotic

Inferior trophic levels: limiting resource ‘‘dries up’’

Abiotic forces that belong to adaptive system, for example, soil conditions or essential mineral resources

Many supposed biotic factors can, in reality, be traced to primary causalities in the abiotic domain, namely, in that a lost biotic resource may in turn have disappeared owing to loss of its own abiotic resource. However, major adaptational dysgenesis is probably also one focus of directly acting abiotic factors in extinction. Partial Dysgenesis and Vestigiation Adaptational dysgenesis may affect some structure units and not others, resulting in functional redundancy leading to vestigiation, rather than to extinction. Different structure units have adaptation interfaces that can be separated in time and space (see Chapter 1), and change of habit can render one facet of the total interface redundant, this constituting the primary adaptive shift for vestigiation. Vestigiation thus derives from partial dysgenesis, owing to loss of an adaptation interface for a single structure unit or integral that is unessential for survival of the gene pool as a whole. Vestigiation thus occurs when functional redundancy affects some structure which cannot be removed in a single step, and this may often be the corollary of a pivotal adaptive shift expressed in some novel anagenetic sequence: In ﬂightless insects with winged ancestry, it is often easy to detect comparatively recent wing loss, in that large vestiges (or even complete wings) are found in some ﬂightless species. In the same way, many ﬂightless insects with a longer term interface to that state show but little trace of wing rudiments. In ﬂightless birds and insects, the presence of a large redundant vestige of the ﬂight apparatus clearly does not depress ﬁtness such that extinction is threatened. Clearly, there was some advantage in loss of ﬂight that outweighed any disadvantage in carrying the ‘‘phenotypic load’’ of a useless structure. Vestigiation follows a ‘‘negative anagenetic sequence’’ trend that is subject to the same anachronism law as ‘‘positive’’ anagenesis. However, this is clearly not true negative anagenesis, so much as ‘‘negative rationalization’’, in the sense of ontogenetic reorganization around an iterative, endogenous selection interface. Unlike ontogenetic recapitulation, however, a vestigial structure may often serve little or even no function even as a pheno- or pheno-ontogenetic precursor state, and its ultimate fate will then be atrophy and eventual loss. Minor Adaptational Dysgenesis Minor adaptational dysgenesis arises through addition of a negative minor niche parameter to which there can be only a limited adaptive response (com-

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pare and contrast with major dysgenesis above). Minor adaptational dysgenesis constitutes that component of density independent mortality that is nonselectional, and in fact, this mode of extinction may be readily confused with selectional mortality when causality is unclear from the available evidence. For a mortality factor to constitute true selectional activity, there must be some shared limiting factor, even if the factor in question does not actually reside in the latter; that is to say, the dysgenetic agency could lie in shared sub- or hypoparametric niche space that is in turn contiguous with shared parametric niche space. Selection may act anywhere within the sub 씮 hypo 씮 parametric niche space trajectory, which is in fact why it has the capacity to be either density dependent (usually within parametric niche space) or density independent (usually in sub- or hypoparametric niche space). No direct or indirect selection interface exists in adaptational dysgenesis, so that in this situation there exists no niche overlap with regard to any limiting resource: If two herbivorous species share and compete for the same food plant, and one species is eradicated because of intolerance to temperature change, while the other survives, this is clearly selection in the form of cladogenetic substitution. However, adaptational dysgenesis would be deemed to have occurred, had there been no shared limiting resource. As with major dysgenesis, the causality of minor adaptational dysgenesis may be biotic or abiotic. However, its biotic element lies mainly with superior and equivalent trophic levels, rather than with the limiting resource. Minor dysgenesis also includes that manifestation of apparent species substitution where two gene pools sharing a resource are remotely related and of total niche intersect, one having a W value of 1.0 relative to 0 in the other, and where no element of direct individual-to-individual competition is implicated (e.g., a large mammalian herbivore may simply eliminate the limiting resource of a phytophagous insect species by trampling, as a stochastic corollary of partial niche coincidence). Geomorphological Inputs to Major and Minor Adaptational Dysgenesis Abiotic dysgenesis may include signiﬁcant stochastic factors in parameters such as climatic change, volcanism, and cosmic radiation, inasmuch as adaptive capacity may already have existed in the gene reservoir with respect to purely ambient levels of such factors. Biotic dysgenesis may also occur through appearance of a new predator or superior competitor that is causal to a contractional response. Biotic bridges must therefore hold a large inﬂuence on adaptational extinction, where biota that have evolved in separate geographic regions suddenly come into contact (this phenomenon serving to underline the fact that adaptive systems are not global in extent): Raup (1991) discussed the role of competition in extinction patterns in connection with the effects of land bridges such as the Isthmus of Panama, an effect that has been well documented for land mammals with respect to the latter example. Marsupials originally dominated

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the south, and placentals, the north of the American continent. About 3 My ago, the land bridge emerged, following which event a greater number of northern species migrated south than vice versa. The interchange at ﬁrst increased the numbers of species in each area, following which numbers then dropped. Today, about 50% of South American genera are of North American origin, and about 20% of northern species originated in South America. Other widely documented examples of extinction owing to distributional displacement include the arrival of rats and domestic animals in isolated endemic island faunas, and the introduction of placentals in Australia. Jablonski (1995) also observed that, under background extinction, larval ecology is a better predictor of gastropod species survivorship than phylogenetic afﬁnity or adult trophic group (namely, for planktotrophic versus nonplanktotrophic forms; the former have broader geographic range and survive better). Both major and minor dysgenesis may have differential effects according to geomorphological change and other factors affecting dispersal, so that, predictably, adaptational extinction is not indiscriminate in its effects, some lineages being more prone than others. Many examples of adaptational extinction may, or course, be difﬁcult to place in major or minor dysgenesis in actual reality, and this obviously applies to many of the factors just discussed. The Role of Competitive Coevolution in Adaptational Dysgenesis The direct biological factor thought most likely to be causing extinction is competitive coevolution. Most minor coevolutionary selection pressure is probably simply absorbed by logistic adjustment, which will not show in the fossil record. The logistic solution is, however, unstable in the longer term, and there may then be a reciprocal structural response reﬂected in coevolutionary change, which may in turn link to different extinction factors. The contractional and expansional outcomes of competitive coevolution (see Chapter 19) need to be understood in terms of the architecture of the adaptive niche, and of distribution and dispersal. These strategies are both unstable in the longer term and could eventually lead to extinction through the intermediary of populations approaching their minimum viable size, presumably through adaptational dysgenesis. Conversely, the Red Queen option (van Valen, 1973) could clearly be presumed to operate in the context of intraspeciﬁc anagenesis, in which case we would witness phyletic occlusion and not true extinction. The ‘‘strong’’ version of the Red Queen hypothesis is exclusively biotic in nature, whereas the ‘‘weak’’ version includes interaction with abiotic factors (showing that extinction factors of the biotic or abiotic kind need not interact in a linear hierarchy). Evidence for the strong version is, however, scant (see Ridley, 1993). Consequently, the coevolutionary model of extinction is probably concerned with adaptational–stochastic rather than with selectional– deterministic factors. In the analysis of actual data in relation to the Red Queen hypothesis, it should also be understood that quantiﬁcation of extinctional intensity has pitfalls, in that each of the standard means of measurement has drawbacks ( Jablonski, 1995).

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A problem thus exists in that situation where long-term evolutionary change is expressed in species speciﬁc, reciprocal adaptational change, in that reciprocal specialization must give rise to a high vulnerability factor in adaptive potential of the gene pools involved. Any negative change in the adaptive system may then result in reciprocal extinction, appearing as a dysgenetic effect. Certain lineages may thus be shunted toward a state of poised dysgenesis through reciprocal adaptational specialization in the structural component of the adaptive ensemble: If moths with long probosces became extinct, then so too would those ﬂowering plants which rely on them for pollination (and vice versa). Williams (1975) described a case of adaptational dysgenesis with respect to a hypothetical ﬂea speciﬁc to the passenger pigeon. As the bird becomes rarer, the ﬂea would have to become a more efﬁcient parasite. Stensteth and Maynard Smith (1984) also assumed that extinction would increase with coevolutionary lag, but for a different reason: a species could ‘‘fall behind in the evolutionary race.’’ Evidence for this lies with the apparently short-lived durations of pathogenic species, in that they cannot evolve as quickly as their sexually reproducing hosts. However, Maynard Smith and Stensteth concluded that this factor is less important than disappearance of the adaptive niche. It must also be understood that the Red Queen mechanism does not remove the effect of the adaptive limit from an adaptive system. For example, if a prey species has reached an adaptive limit in terms of biophysical capacity for escape from a given predator, then the latter must adopt a behavioral strategy such that the continued survival of prey is assured. Similarly, the coevolutionary paradigm does not apply at all to a great many anagenetic sequences for traits linked to supra- or hypoparametric niche space. Nevertheless, an element of fragility must evolve in adaptive systems, according to the degree of reciprocal specialization, and this constitutes an openness to extrinsic extinction factors, that is to say, to those arising external to the reciprocally adapted gene pools in question, as in the weak version of the Red Queen hypothesis. The competitive coevolution model clearly has implications for both major and minor dysgenesis. Status within the latter dichotomy depends, of course, on choice of reference frame within a framework of adaptational reciprocity!

Environmental Catastrophe and Indirect Causality in Extinction Some extinctions could be taken to be both nonselectional and nonadaptational, being due to proximal catastrophic factors originating beyond the boundaries of the adaptive system itself. Environmental catastrophes of this kind may also be the ultimate cause of much adaptational dysgenesis, rather than being a direct cause of extinction: Possibly as many as 96% of the world’s species became extinct at the end of the Permian period. The terrestrial vertebrates and plants also exhibited perturbations similar to the oceanic mass extinctions, although the magnitude and timing of land relative to marine extinction events are still controversial issues ( Jablonski, 1995).

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Raup (1991) states that the extinction of widespread species is favored by stresses not normally experienced. For this to occur simultaneously to many species, stress must cut across ecological lines, meteor strike being favored as one viable candidate for catastrophe of this level. Massive volcanism is also thought to lie at the root of catastrophic events of this kind. Patterson and Smith (1987) have conversely argued that the supposed periodicities of extinction in marine organisms of approximately 26 My ago (Raup and Sepkoski, 1986) are an artifact due to ‘noise’, owing in part to the ‘noncladistic’ approach of some investigators. Sepkoski (in Patterson and Smith, 1987) points out, however, that a cladistic approach in fact fails to recognize even the great K–T extinction! (as with paraphyletic groups such as the dinosaurs). Jablonski (1995) holds that probably more than 90% of species extinctions in the fossil record actually occurred outside the ﬁve major events (Raup, 1986, 1991) and that mass extinctions have such profound biological consequences owing to the fact that they disrupt background selection regimes, not because they account directly for most species terminations. From this standpoint, we must therefore always be ready to question whether a supposed ‘‘environmental catastrophe’’ is not really a prime mover in a chain of subsequent events in which adaptational dysgenetic factors are widely mobilized. In this view, environmental catastrophe may be the stochastic–abiotic root of much adaptational (and ultimately also selectional) extinction. Apparently periodic patterns of this kind cannot, however, be viewed in terms of endogenous cycles of evolutionary expansion and contraction, and clearly it is not possible to extrapolate from local dysgenetic events to mass extinction. Contrary to some claims, the latter does not in fact exhibit fractal behavior (Kirchner and Weil, 1998). Pathways through the Extinctional Mosaic As we have seen, extinction involves a heterogeny of mechanisms in the adaptive system, some of which are the corollary of evolutionary change, and some not. Some extinction factors also reﬂect ‘‘evolutionary gain’’ elsewhere in the adaptive system, and some do not. Major and minor adaptational dysgenesis are the loci of potential ‘‘no gain,’’ whereas phyletic occlusion and cladogenetic substitution actually reﬂect positive evolutionary change within the contours of a lineage. The root causalities of extinction clearly need to be traced back to the locus of ‘‘ﬁrst strike’’ in the adaptive system. In general, many extinction factors may ultimately prove to be indirect abiotic–stochastic in nature: Mechanism

Direct deterministic

Species Competitor evolved substitution superiority or change in niche (cladogenetic selection interface)

Indirect deterministic Competitor’s superiority arose owing to some change in limiting resource

Direct stochastic

Indirect stochastic

Competitor appeared via change in distribution

Competitor arrived via new land bridge

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Phyletic occlusion

Major dysgenesis

Minor dysgenesis

Competitor evolved superiority or change in niche (anagenetic selection interface) Limiting resource changed its distribution

Competitor’s superiority arose owing to some change in limiting resource (Cause of change in limiting resource distribution)

Predator changed prey

Predator changed prey owing to changed distribution of new prey species

Competitor appeared via change in distribution

Not applicable

Volcanism, meteor strike, etc., affecting limiting resource

Volcanism, etc., may have affected limiting resource, not consumer species Tectonic activity was causal to origin of land bridge

New predator arrived via land bridge

Thus, although it is possible to erect various plausible hypotheses concerning the manner in which a given extinction event has occurred, it may often be difﬁcult or even impossible to conclusively prove any one solution in actual practice.

Extinction, the Adaptive Substrate, and Major Macroevolutionary Events Although adaptational (and catastrophic) extinction do not constitute ‘‘evolution,’’ they nevertheless contribute to the substrate within which fresh evolutionary change can occur in adaptive systems, in the sense that extinction may remove much competitional and selection pressure from the adaptive system: McGhee (1989, following Sepkoski, 1985, and Jablonski, 1986) discusses the view that ‘‘Repeated periods of diversity loss may have prevented life from ever reaching a state of equilibrium or saturation.’’ Jablonski (1995) observed that recovery after mass extinctions is very rapid by the geological time scale (although according to Crane, 1989, the fossil history of plants does not show clearly the same mass extinctions as those thought to ‘‘reset the evolutionary clock’’ in many animal lineages). Raup (1991) adds the interesting observation that although, without extinction, adaptive systems would evolve to a steady state, bacteria may be exceptional because they have been immune from mass extinction agencies. Without doubt, ‘‘renewal of the evolutionary substrate’’ must constitute a large factor following any mass extinction event, since this can only provide an opportunity for the origination of new adaptive zones from the best adapted residue of the old. That this is not in fact restricted to the effects of agencies such as vulcanism and strike by extraterrestrial bodies is, however, evident from the fact that the data of Hedges et al. (1996) strongly support the importance of continental breakup in the renewed diversiﬁcation of land vertebrates toward the K–T boundary. In this situation, an adaptive system is greatly reduced in overall species diversity, presumably as a result of the massive inﬂuence of invasive species on extinction rates (no doubt aided by vulcanism, etc.).

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We can now render the earlier adaptive substrate model (Chapter 19) a dynamic one, by considering that, in the aftermath of mass extinction, the modal values for the adaptive substrate will be skewed toward higher levels, thus allowing wholesale evolutionary innovation in the context of a revitalized substrate. In attempting to illustrate this, I have imagined a situation (see Fig. 118) in which a single peak occurs through convergence of the two original maxima in adaptive equilibrium and stochastic override (see Fig. 114 in Chapter 19) toward a system dominated by a low X and high Y value (namely, with little input to the selection interface from either allomorphism or raw logistic adaptation).

FIGURE 118 Modiﬁed adaptive substrate surface following a mass extinction event (compare with Fig. 114).

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The greatest quantum events must therefore occur only when the global substrate frequency distribution is shifted away, not only from leading effect allomorphism, but also from the inﬂuence of stochastic override of selection (the latter presumably having an even lower probability of occurrence than the former in the aftermath of mass extinction). In the context of a quantum punctuational event, the adaptive response also has to occur in an iterative fashion in order to pass through the adaptive isthmus of a bounded adaptive zone, whereas a lower substrate will merely pass to a more or less apert zone (see Chapter 17). Relatively small evolutionary events such as those surrounding ambient speciational activity should thus be interpreted as occurring through local perturbations in the evolutionary substrate, as seen, for example, in the aftermath of fresh colonization of remote islands. In contrast, the origination of higher level group lineages must be associated with widespread (even global) disturbances to the equilibrium of the evolutionary substrate. It is also again evident that the attractor for the distribution of adaptive substrate is that of stasis, and that ‘‘revitalized’’ systems should therefore ultimately return to that state (see Chapter 18).

MAIN POINTS FROM CHAPTER 20 1. Extinction can be due to direct/indirect, biotic/abiotic, or deterministic/ stochastic factors. However, the most important dichotomy is that between selectional extinction factors (species substitution and phyletic occlusion) and adaptational dysgenesis (nonselectional extinction). 2. Selectional extinction is an important corollary of evolutionary change, manifested in cladogenetic substitution and phyletic occlusion, the latter additionally constituting ‘‘pseudo-extinction’’ as a corollary of evolutionary change. Phyletic occlusion also has signiﬁcant mechanismic links with atavism, amphigenesis, and recapitulation. 3. Bounded adaptive zones are isolated by phyletic occlusion, and the occlusion zone thus reﬂects the ‘‘pseudo-extinction’’ gap in a higher group lineage. 4. The concept of species sorting contains a heterogeny of effects, including the inﬂuence of both selectional and nonselectional modes of extinction. 5. The law of anagenetic survivorship states that the intrinsic selection gradient for an anagenetic sequence will tend also to be reﬂected in the degree to which different increments in the sequence pass to extinction. Extinctional mechanisms affecting the form of the anagenetic survivorship curve follow the trend minor occlusion 씮 major occlusion 씮 species substitution 씮 speciation 씮 genomic anastomosis over the course of lineage time. 6. Many manifestations of extinction form no part of the evolutionary process in any direct sense, reﬂecting adaptational dysgenesis rather than selection-driven events. Major adaptational dysgenesis constitutes loss of a key positive survivorship factor in the major adaptive niche, whereas minor adaptational dysgenesis involves addition of a key negative survivorship factor in the minor niche.

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7. Adaptational dysgenesis is often linked to geomorphological change and other factors affecting dispersal and ‘‘peripheralization’’ of populations. Competitive coevolution also contains a corollary in vulnerability to dysgenesis, speciﬁcally in the domain of parametric niche space. 8. Both selectional and adaptational extinction may link to indirect causalities arising from stochastic activity originating beyond the domain of the adaptive niche itself. Factors arising beyond the boundary of the adaptive system are very often the common ‘‘distal root’’ for a heterogeny of apparent ‘‘proximal’’ causes of extinction. 9. Extinction may at times have a profound effect on the frequency distribution of the evolutionary substrate, a situation which has a reciprocal inﬂuence on facilitation of evolutionary innovation. With mass extinction, we may envisage the rare convergence of ambient peaks in adaptive equilibrium and stochastic override on a single peak lying close to the optimum evolutionary substrate. This circumstance is that most likely to support movement into novel adaptive zones.

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The objective of this chapter is to look at major theoretical aspects of the evolutionary process in the way in which they relate to phylogeny, not so much as a prescription for phylogeny reconstruction, but rather in terms of the manner in which evolutionary theory affects the validity of the criteria of cladistic analysis. The question as to what genuine deductions can actually be made concerning mechanisms of evolution will also be given a high proﬁle in the ensuing discussion. In this, we shall draw on all special aspects of the general theory in order to fully understand the causal factors behind systematic hierarchies. Here we can see the effects of a great heterogeny of mechanisms operating in evolving adaptive systems on the architecture of the phyletic lineage.

THE ADAPTIVE CASCADE, FROM LINEAGE TO TAXON Following the ﬁndings of earlier chapters, the mechanismic basis for the generation of a taxonomic hierarchy must clearly lie in the rarity of genuinely neomorphic mutations acting at higher translation levels (e.g., in Hox genes). Following on from this, we must proceed to examine the manner in which a set of secondary and tertiary mechanisms interact in sculpturing clade from lineage, and taxon from clade. The behavior of the adaptive cascade (see Chapter 15), extended to encompass the entire set of interactive mechanisms leading to determination of the adaptive paradigm itself, ultimately lies behind all evolutionary activity in the

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development of a phyletic lineage. The overall pattern emerging for origins of new higher groups and evolution of structural landmarks within the lineage can be summarized thus, in terms of cause and effect: Cause

Effect on clade

Primary adaptive shift Adaptational paradigm

Establishes new adaptational paradigm, via new niche interface Determines what form a structural anagenetic sequence must ideally take in order for a realized adaptive response to be expressed in relation to niche, thus also determining the form of the adaptive zone with respect to any subsequent anagenetic activity May play a large part in directionalization of diversity patterns, in the context of endogenously driven (Thompsonian) transformation factors Degrees of freedom therein affect capacity for an adaptive response to change occurring in the external environment; the limits of adaptive potential also affect the probability of occurrence of parallel evolution The intersect between degrees of freedom in the biophysical paradigm (for structure in relation to a given function) and adaptive potential determines directionalization of the anagenetic sequence Affects the domain of evolutionary anachronism between primary adaptive shift and adaptive response Determined by the interaction between exo- and endogenous adaptive potential, with special reference to major features of the abiotic environment, absolute size range, and trophic level Ratiﬁcation of directionality (plus possible eclipse of a previous adaptation interface) Controllant to evolutionary rate of lineage, as a function of the type of long-term adaptive niche occupied by a lineage Determines state-to-state relationships of structural traits, from preadaptive to biophysical paradigm state, as expressed in the trajectory of an anagenetic sequence One gene reservoir becomes two and a lineage splits: a major Renschian cladogenetic node may be formed between diverging higher group lineages, or else there may simply be an ambient speciation event

Facultative adaptive differential Adaptive potential

Structural attractor

Paradigm distance Adaptive zone

Pivotal adaptive shift Adaptive corridor Anagenesis

Speciation

Despite the apparent complexity of interacting factors involved in higher group origins, there is an underlying axiom from the analysis of adaptive systems that each higher group lineage will have some causality that is neither necessarily its ‘‘essential feature’’ nor even a uniquely derived trait. This function is always rooted in the primary adaptive shift. However, the probability of identiﬁcation of the primary shift may be low, and subsequent phyletic nodes may thus tend often to be the main focus of attention in taxonomy. Much of this difﬁculty arises from the maxim that there is no reason why a lineage should develop a structural trait that is not subsequently modiﬁed or lost. Above all else, the adaptive cascade obviously emphasizes the role of functional analysis as a guiding principle for the unraveling of phylogeny, and this is a criterion that has been all but lost in the context of much cladistic analysis.

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From Lineage to Clade Although it is easy to speculate on the architecture of an evolutionary lineage in terms of adaptive shifts and phyletic nodes, it must be clear from the outset that the true lineage is in reality a four-dimensional structure that is never entire at any one time horizon. Within any given time frame, a lineage will be represented by a clade, which is merely some (often quite arbitrary) subset of the total lineage. Classiﬁcations which attempt to incorporate extinct groups on the basis of fossil evidence are also looking at fragments of a larger reality, since even true clades can really only relate to their own ‘‘horizontal dimension’’ within any one time frame. A clade is thus deﬁnable as the extant representation of a lineage (or of any subset of a lineage) within any chosen time frame: Aves is a clade, but it is only the extant representation of a formerly, much more diverse assemblage completely connecting reptilian and avian grades in the context of a single evolutionary lineage. The relationship between lineage and clade is clearly a highly complex one, and in this we begin to ﬁnd some means of understanding the typology of taxonomy in practice, with respect to causality in the dynamic behavior of adaptive systems. Ambient and Renschian Clades Ambient clades are formed simply by repeated speciation (expressing no signiﬁcant anagenetic change), whereas the major processes of macroevolution really only become fully manifest in that situation where Renschian cladogenesis plays a signiﬁcant role in phylogeny. Primary adaptive shifts and associated Renschian phyletic nodes thus constitute those criteria through which to analyze macroevolutionary clade structure. It will also be convenient to refer to an individual clade as being either ambient (nonanagenetic) or Renschian (derived from a lineage manifesting Renschian cladogenesis at its origin; see Chapter 6). The dichotomy between ambient and Renschian clades obviously underlies a highly signiﬁcant differential existing between lower and higher level taxonomic categories. The Primary Adaptive Shift and Boundaries of the Renschian Clade What are the fundamental boundaries of a Renschian clade? In any given macroevolutionary lineage, there will be a locus of qualitative change in the form of a primary adaptive shift, which in turn will have been followed by a Renschian phyletic node (see Chapter 17). Some understanding of the nature of the primary and pivotal adaptive shifts of a lineage is thus crucial in interpretation of functional input to phylogeny, since this knowledge may, through functional analysis, afford evidence as to the nature of constraints operating on the adaptational paradigm, such as could in turn offer predictions as to expected levels of polyphyly of an anagenetic sequence. The time gap between primary adaptive shift and phyletic node in evolutionary anachronism may be short or long. This is a fundamental concept, when we come to consider functional analysis in relation to phylogeny reconstruction, in the sense of offering a rationale to explain the topological gap

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between lineage and clade in activation of the occlusion zone effect (see Chapter 17).

From Clade to Taxon Many well-established taxonomic groups are clearly not true clades, and there is obviously a heterogeny of reasons why this should be so. Among the most signiﬁcant inﬂuences are those of extinction, ‘‘gradism,’’ and tangential evolutionary change following origination of a higher group lineage. The Inﬂuence of Extinction in Determination of Clade What information can be gleaned concerning such theoretical entities as the primary adaptive shift and pivotal phyletic node of an evolutionary lineage? In answering this question, the ﬁrst reality to encounter is that a clade is essentially equivalent to a phyletic lineage minus the heterogeneous effects of extinction. The true sequence of phyletic nodes may or may not remain in evidence, according to the degree to which extinction has affected the architecture of a lineage, and this will affect the probability of a ‘‘natural’’ taxon being a true clade. How do extinction factors actually affect the architecture of a lineage, and what are the differential inﬂuences of ‘‘pseudo’’ as against true extinction? These questions must clearly be linked not only to the nature of the adaptive strategy, but also to the supplementary inﬂuence of stochastic extinction factors: Extinction factor

Iterative effect on architecture of lineage

‘‘Pseudo-extinction’’ in 움-anagenesis, thus at least partially deﬁning distance between ancestral and descendant lineages and greatly inﬂuencing size of occlusion zone; hence causal to ‘‘basal gaps’’ Species substitution Parts of a clade sequence may be removed at any point in a lineage, through interspeciﬁc competition and species substitution Major Extinction with a larger stochastic input, often manifesting a ‘‘terminal’’ adaptational effect on the architecture of a clade, rather than being causal to basal dysgenesis gaps (namely, where overspecialization is implicated) Minor More random extinction of various systematic categories adaptational dysgenesis Phyletic occlusion

Phyletic occlusion and species substitution must be particularly important causal factors with respect to gradistic differentials of the kind linked to the adaptive zone in taxonomic hierarchies, and thus to a rapidly evolving differential between clade and lineage. The taxonomic gap between two clades descended from a common lineage is thus in large part a function of the differential in ﬁtness between ancestral and descendant forms in the transition between adaptive zones. Earlier (움-) anagenetic states will tend to pass rapidly into phyletic occlusion, where the largest selectional differentials are developing. Morphosystems close to that expressed by the primary phyletic node will thus have a low probability of survival as progression toward the adaptational paradigm state occurs, and extant sequence fragments will in time tend to express much lower ﬁtness differentials. Cladogenetic substitution may also create areas of ‘‘lost morphospace,’’ at times with profound effects on lineage

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structure, and it should be noted also that adaptational and stochastic extinction sensu stricto both have the capacity to create quite random (and sometimes large) modiﬁcations to the form of the extant lineage. In summary, the combined effects of adaptational dysgenesis and phyletic occlusion must be to greatly modify the relationship existing between lineage and clade, partly as a function of time lapse since the primary adaptive shift. The dichotomy between lineage and clade (and also that between clade and taxon) is thus primarily a function of the input from a heterogeny of extinction factors. Although the phyletic occlusion element in this must be of fundamental importance with respect to the evolutionary mechanism itself, we must also realize, however, that this relationship may also be greatly obscured by other, more random factors. The outcome of the foregoing scenario is simply that our knowledge of the key adaptive shifts causal to the originating anagenetic and cladogenetic events of a given lineage will usually have to be obtained by deduction (namely, through functional analysis) rather than through direct observation. Clearly, this fact underlines the absolute necessity of incorporating functional analysis into the study of phylogeny if the latter is to have any bearing on evolution, rather than being a futile exercise in mere classiﬁcatory topology. Evolutionary Grade, Adaptive Zone, and Zonal Separation Huxley (1958) proposed the term grade for units of anagenetic advance, also stressing that such entities need not be monophyletic. The term grade has in fact been used to mean three entirely different things in the past. First, it has been said that ‘‘gradistic differences’’ exist between (for example) aquatic and terrestrial organisms, in which instance we are really referring to the gap between two different adaptive zones, as deﬁned by a greater or lesser phyletic occlusion zone. All adaptive zones are phyletically ‘‘contiguous’’; however, if they are also separated by large paradigm distance correlated with a steep selection gradient, then zonal separation will evolve through phyletic occlusion as a function of time. This tends to happen when an adaptive shift in certain niche parameters manifests an abrupt, qualitative differential (as in the aquatic to terrestrial and terrestrial to aerial environment transitions). This corresponds to the differential between bounded and apert adaptive zones (see Chapter 17). A further input to the expression of an isolated adaptive zone must be that of reciprocal specialization, this being a further mechanism by means of which transitional forms can no longer occupy the adaptive isthmus. Following the criticism of Maynard Smith (see Chapter 17) we should, however, be skeptical of the universality of any ‘‘adaptive zone law’’: The carnivorous water beetle family Dytiscidae shows a typical occlusion zone effect corresponding to a terrestrial–aquatic zonal ‘‘discontinuity,’’ but many transitional forms exist in the extant fauna in the unrelated (and herbivorous) family Hydrophilidae, which includes species with quite limited locomotory and respiratory specializations, presumably of a kind which existed also in the ancestral dytiscid (namely, in the occlusion zone of the latter lineage). Of course, we must also consider the possible inﬂuence of evolutionary anachronism

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as an explanation of this apparent anomaly (and also the differential in trophic level between the lineages in question as a possible indicator of the nature of the dichotomy in architecture of the respective adaptive zones of these two lineages). A second usage of the term ‘‘evolutionary grade’’ lies in that circumstance in which two Baupla¨ne may be said to be of ‘‘different grades of organization’’ according to the degree of complexity in superstructure (‘‘mammals are of a higher grade than Porifera,’’ etc.). This is a more colloquial usage, and one which need not enter into further discussions. Third, ‘‘gradistic’’ has been used to signify differentials between lineages that are based on evolutionary rate alone. In allotelism (see Chapter 18), we are looking at false patterns of afﬁnity manifested in anagenetic sequences that are evolving in parallel, but at different rates in different lineages, according to bifurcation in the domain of the adaptive corridor. In this situation, certain taxonomic landmarks come to be a function not of relationships so much as of evolutionary rate itself. Several of the anagenetic sequences that have been described for ditrysian Lepidoptera are quite certainly parallel trends that have evolved slowly in Microditrysia and rapidly in so-called macros, probably as a function of a differential in adaptive corridors (see Chapter 18). The latter understanding of gradism lies at the root of many problems with cladistic methodology, although serious questions are also raised by the dichotomy existing between bounded and apert adaptive zones. Owing to the frequently large gap between lineage and clade, Linnean taxa are quite commonly gradistic (at least in the sense of zonal separation), rather than being genuinely cladistic. In reality, a taxon need not have any interpretative input from biological criteria, so that in actual practice it may even be an entirely artiﬁcial construct. However, it should be accepted that both clade and grade are evolutionary phenomena, and gradistic classiﬁcation is in no way ‘‘artiﬁcial’’! In many ways, it is in fact the practical difﬁculty of distinguishing cladistic and gradistic from one another that demands the concept of the ‘‘artiﬁcial taxon’’: Aves is both a taxon and a clade, but it leaves Reptilia ‘‘paraphyletic.’’ The latter concept, however, ignores the zonal separation criterion, since Reptilia and Aves are perfectly valid gradistic units in that sense (namely, through manifestation of a very high level of zonal separation, and looking solely at the extant representation of these lineages). In the same way, whales are rather obviously gradistically distinct (and zonally separated) from artiodactyls. One major input to the problem of natural classiﬁcation thus clearly lies in the disparity between cladistic criteria and the taxon sculpting inﬂuence of the adaptive zone (as well as of more random factors in extinction). The occlusion zone is essentially that extinctional zone expressing 움-anagenesis, and most signiﬁcantly, phyletic occlusion may contribute to ‘‘lineage gaps,’’ which latter are in turn partially causal to the reality of gradistic taxonomic

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hierarchies on the basis of the vacant morphospace scenario often linked to quantum evolution. A major difﬁculty is of course that it may be impossible to decide whether a given gap is in fact due to phyletic occlusion, or to some dysgenetic or purely stochastic extinctional event. A higher group taxon is ideally the extant representation (clade) of an evolutionary lineage, as manifested at any given time horizon. In reality, however, many taxa tend to be naturally gradistic rather than cladistic in nature, owing not only to the existence of wide occlusion zones, but also to the effect of extinctional phenomena in general. In this context, the lineage (rather than the grade) is the objective reality, but the degree to which various extinctional factors have affected the lineage–clade relationship must determine the likelihood as to whether only gradistic information is retrievable in a cladistic analysis of the available fragmentary data. The further clade is removed from lineage, the less likely taxon can be equated with clade, owing to the greater inﬂuence of true extinction and the frequent stochastic root factors in this (see Chapter 20): Insistence on the removal of paraphyly where many very large occlusion zones exist in the trajectory of a phyletic lineage has resulted in such anomalies as Hominidae being regarded as a subgroup of the supposed clade Crossopterygii (Long, 1995). In Sheldon’s vitally important work with Ordovician trilobites (1987; see Chapter 18), the point was made that ‘‘to unite all the components of each lineage into single species, as a strict cladist might, would be to submerge the observed evolutionary trends under one taxon.’’ Sheldon’s remarks are all the more relevant to the phylogeny of higher groups. The gradistic view of classiﬁcation has also proved extremely valuable in the context of analysis of evolutionary events in the fossil record: Van Valen (1985) concluded that cladistic classiﬁcation would completely preclude certain analyses of extinctional trends: ‘‘Families are comparable to each other adaptively and are parts of phylogenies delimited adaptively. . . . They are thus natural taxa.’’ Similarly, Jablonski (1995) stated that paraphyletic taxa are probably not a problem in this context: loss of a paraphyletic taxon often reﬂects disappearance of a distinctive mode of life or an ecologically meaningful suite of traits, and even quite arbitrary Linnean taxa may provide a robust portrait of biodiversity changes. (N.B. See also Chapter 20 concerning the fact that the extinction of the theropods at the K–T boundary would go unnoticed with a strict cladistic analysis.) Zonal separation is perhaps an obvious source of confusion in the clash between cladism and gradism. However, this situation may at times be further complicated by the much more subtle inﬂuence of differential evolutionary rates linked to parallel evolution, and the latter situation will need closer analysis within the concept of cladistic parsimony (see below). Endocladic and Exocladic Phyletic Nodes It is useful in the context of terms of reference to denote some phyletic nodes as endocladic (coincident with or subsequent to the Renschian phyletic

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node of a chosen clade) or exocladic (preceding to the Renschian node), within the conﬁnes of a larger lineage. The terms exo- and endocladic carry only a relative status with reference to the parent lineage. A phyletic node is exocladic when it was precedent in relation to some larger lineage of which it is a subset, and endocladic when it occurred after the causal adaptive shift (or when it is the latter). Looking at the structure of a lineage, it is easy to see that phyletic nodes are those elements of the adaptive response which provide taxonomic landmarks, while the causal adaptive shifts (including the primary) may often remain unrecognized through having been behavioral rather than structural. The latter, however (and not taxonomic characters), contain the true causality in any functional analysis. Consequently, many apparent diagnostic features of higher groups often turn out to be endocladic in origin, with deeper analysis: Several of the apparently diagnostic traits of the butterﬂy lineage are in fact absent in the most primitive taxa, indicating an endocladic origin in that lineage (Brock, 1990a) rather than bearing special status as ‘‘autapomorphies’’ of the higher group. The thoracic tympanum is probably a primary phyletic node for noctuiform moths, although the abdominal tympanum is apparently endocladic in geometriform and pyraliform moths, since in the latter lineages there are primitive taxa lacking these organs (Brock, 1971). Some cladistic systematists, of course, ‘‘solve’’ this problem by erecting typological boundaries around the presence or absence of the tympanum, to the exclusion of other data, and in the guise of unsubstantiated autapomorphy! (See, e.g., Kiriakoff, 1953; also Minet, 1991.) It is also self-evident that neither endo- nor exocladic nodes need manifest structural constancy within a lineage, given the possibility of subsequent functional redundancy and/or tangential adaptive shift occurring (see the noncongruence principle of Crowson, 1970). Many endocladic nodes will represent function shifts rather than true adaptive shifts (see Chapter 17), and these will generally correspond to those phyletic nodes comprising the anagenetic sequence.

FUNCTIONAL ANALYSIS AND PHYLOGENY RECONSTRUCTION Given the knowledge we possess on how taxon relates to clade, and clade to lineage, what objective information can we now expect to retrieve concerning phylogeny? In addition, what positive steps can be taken to avoid misinterpretation in cladistic analysis, bearing in mind the various impediments that have arisen from the analysis of adaptive systems? Cladistics looks at the incidence of cladogenesis in the structure of a lineage, usually with reference to some (perhaps fragmentary) subset of the same, at least so far as the higher group case is concerned. However, the exclusion of implicit anagenesis from cladistic analysis frequently removes much signiﬁcant data. It is, in fact, possible to arrive at good objective explanations of the anagenetic process without the need to precisely determine the placing of

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cladogenetic nodes, solutions to which latter often have to be based on parsimony rules. From the adaptive cascade (see above) we can see that functional analysis (or ‘‘teleonomy’’: the means by which morphological data are analyzed with reference to supposed and/or observed functional interpretations) provides essential objective data on the architecture of the anagenetic sequence, even in lack of direct knowledge concerning the exact phylogeny: We know precisely how (for example) adaptational progress has been manifested in skeletal structure in the horse ancestry, although the exact branching nature of the equid lineage remains to some extent conjectural. The latter is also arguably of much less intrinsic interest than a knowledge of functional relationships of anatomy in the context of an objectively determined anagenetic sequence. Similarly, the overall directionality of a number of major anagenetic and vestigiational sequences is now known for Lepidoptera, despite the fact that even the monophyly–polyphyly question surrounding the dichotomy between Microditrysia and Macroditrysia remains unresolved. Given that phylogeny reconstruction is the goal of cladistics, could it not be that much of the data of such analyses actually holds more important information concerning the evolutionary process, than does the target cladogram?

The Role of Functional Analysis Around the middle of the twentieth century, the phenetic school proposed that objectivity could be brought to classiﬁcation by requiring characters not to be logically subdivisible. From a biological (i.e., adaptational ) standpoint, we should clearly in fact be looking for functional relationships between unit characters, taxonomic correlations between which might very frequently imply not phyletic afﬁnity, but functional interdependence. The homogeneity (or otherwise) of the function integral containing all structural parameters manifesting a common selectional modularity (Chapter 7) is of no importance whatsoever for phenetics but is clearly fundamental to any understanding of evolutionary perspectives, following the premise that functionally linked structure units carrying a constrained adaptational paradigm may frequently tend to follow a common phyletic path quite independently of cladistic events. Thus, if a character is seen to manifest parallelism, any other character that is both structurally and functionally linked to it may well do so also, given only limited degrees of freedom in the relevant structural paradigm. An appreciation of this concept is fundamental to any understanding of the link between functional analysis and phylogenetic interpretation, and this has immense implications for the validity of such cladistic criteria as parsimony and compatibility analysis. The term functional must relate to activity at the adaptation interface, which is not the same as the classic usage of ‘‘function,’’ since it is possible to describe functional morphology purely in terms of the biomechanical capacity of integrated structural complexes, quite independently of any consideration of behavior in relation to the adaptive niche. The classic approach to function

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may seem an adequate way of understanding causality; however, analysis of the entire adaptive ensemble is essential for identiﬁcation of the true function integral, and this clearly brings function into the domain of a wider biosystematological view: The larval proleg crochets of ditrysian Lepidoptera show progressive change from early to last instar in many macroditrysian families, where complete circlets of hooks are gradually reduced to a single longitudinal band. This has often been interpreted in terms of recapitulation, since mature larvae in primitive lineages tend to have complete circlets of crochets. However, functional analysis based on direct observation of locomotor behavior shows that the complete circlets are already partially functionally redundant in many ﬁrst instar larvae of advanced arboreal families; therefore, they have simply tended to become vestigiated more rapidly in more mature larvae, where they would constitute some disadvantage in the climbing activity often utilized at that stage of development in the macro lineages (Brock, in prep.). Past authors (and some recent ones) have used the presence or absence of a complete circlet of crochets to subdivide the Ditrysia into two supposedly monophyletic groups. However, taxonomic distribution of proleg crochets in caterpillars must be at least partly a function of lineage evolutionary rate linked to the presence or absence of climbing behavior in mature larvae (see also Hinton, 1955). The distribution of character states for this trait seems thus likely to carry very little phylogenetic weight, and the fact that an approximate ‘‘compatibility’’ exists between this and a few other attributes of macro grade is likewise of no real cladistic signiﬁcance. These data in fact provide good evidence of allotelic evolutionary rates (see Chapter 18), not of phyletic afﬁnity. From our analysis of the biophysical paradigm concept (which must clearly constitute the key to functional analysis, see chapters 7 and 15), we have also learned that many individual traits may be parts of a superstructure which evolves as a unity toward a tightly constrained paradigm, often one structure unit at a time in temporal sequence. More than one structure integral may be also be adapted to the same end, and conversely, a single structure integral may belong to more than one function integral. Given a high input from parallel evolution (that is to say, where a tightly constrained selectional attractor exists), identiﬁcation of the domain of a function integral may then often uncover the correct explanation of character correlation, and this may not necessarily be ‘‘compatibility/parsimony ⫽ phyletic afﬁnity.’’ Structural divergence is, of course, a possible option also; however, the actual levels of homoplasy discovered in a great many cladistic analyses imply that a great many adaptational paradigms are sufﬁciently constrained so as to frequently confer a high degree of parallelism on anagenesis: Examples of parallel evolution are legion but perhaps best exempliﬁed by the studies of Sheldon (1987) on Ordovician trilobites, and by the Cichlidae of the African Great Lakes (see Greenwood, 1981 and elsewhere). In fact, whenever anagenesis has been examined from the

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standpoint of exceptionally well preserved fossil lineages or through genetic analysis, the most prominent feature of evolutionary topology has been parallelism. Similarly, where neontological data have been examined from a supposedly cladistic viewpoint, ‘‘homoplasy’’ (rather than monophyly) has generally been the rule, for example, as with most of the data on higher groups of ditrysian Lepidoptera (Brock, 1971, 1990a). As noted in earlier chapters, the developmental basis for the scenario of homoplasy is so large that this might be considered almost as an expected behavior of adaptive systems, rather than constituting some morphopathological phenomenon. Character weighting in the absence of any assessment of functional relationships is thus of no value for phylogenetic reconstruction, nor indeed for extraction of evolutionary or biological data of any kind, and functional analysis should in fact be regarded as the sole criterion for this endeavor. Functional analysis also forms an objective basis for reconstruction of former anagenetic sequences, given that progress in the biophysical sense can often be postulated from the standpoint of comparative morphology alone, and this approach can also be used to support and amplify the outgroup comparison method (over which it may sometimes hold precedence, by virtue of having an empirical basis). In this, we must of course also guard against false premises made on the basis of guesswork and casual observation: Williams (1966) states that for a given biological mechanism there are no established principles and procedures for answering, ‘‘What is function? . . . Teleonomy is a suitable name for this special ﬁeld of study’’ (after Pittendrigh, 1958). Williams (1966, 1992) has also very sensibly advocated the approach that adaptations be recognized as such by the criterion of design speciﬁcation (as with Rudwick’s paradigm concept, 1964). There may thus be areas where the Rudwick paradigm approach is absolutely clear. It is difﬁcult, for example, to misidentify the functions of appendages of ﬂight or organs of vision, although of course it may be less easy to arrive at functional explanations of structures in certain fossil forms that have no living descendants! Nevertheless, functional analysis must always be the ideal, and in the extant fauna and ﬂora at least, there will always be some empirical approach that will provide answers to questions of this kind, even if sometimes only in the shape of a working hypothesis: One of the most puzzling traits of ditrysian Lepidoptera larvae is the tendency for certain body setae to become associated in pairs in a manner that appears to cut across conventional classiﬁcatory units. However, actual observation shows that the behavioral response to touch stimuli is signiﬁcantly greater for paired than for unpaired setae, suggesting that the probable function of ‘‘setal pairing’’ is linked to improved tactile response in lineages that are adapted to a more or less concealed adaptive niche. Given that the paired setae are in fact concentrated at the front and rear ends and in the neighborhood of

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the spiracles, any improvement in the tactile sense in these domains may assist in such activities as construction of the larval refugium and protection from fecal contamination and predator–parasite attack. In addition, lineages with a relatively short-term adaptation to the endophagous habit tend to show only restricted (or no) setal pairing. A reasonable working hypothesis to explain this would therefore be that paired setae constitute a polyphyletic character state, the taxonomic distribution of which is linked to choice of adaptive niche, having little or nothing to do with phylogeny via any manipulation of parsimony rules (Brock, in prep.). Functional analysis has, however, become unpopular with many cladists, presumably on the grounds that it interferes with fundamental dogma in the Hennigian methodology. Is it really necessary to question, for example, whether photosynthesis is a ﬁtness enhancing trait in plants (see Niklas, 1988), or whether possession of wings carries adaptational advantage in birds, bats, and insects? Too often claims against ‘‘adaptationist storytelling’’ seem to be moving too far into the domain of postmodernism to be taken seriously, especially when this argument is used to promote ‘‘non-Darwinian evolution’’ or to bolster unsound cladistic methodology. Of course difﬁculty will be experienced with functional interpretation of certain traits, but this should not lead one to discard the majority of sensible deductions that can be based on known biomechanical principles. In fact, much of the doubt that is sometimes expressed concerning adaptivity really stems from confusion between adaptation and selection. The simplest way of looking at this problem is to consider that as selection constitutes ‘‘survival of the ﬁttest,’’ so too adaptation is simply ‘‘survival of the ﬁt’’ (see Chapters 1 and 4). The presence of an adaptation interface therefore does not necessarily imply simultaneous presence of a selection interface, and capacity for photosynthesis may indeed have no selective advantage, if all members of a gene pool have approximately equal functional capacity in this respect. This does not mean ‘‘no adaptive value’’ (nor can arguments of this kind be used to cast doubt on the very real need for functional interpretation in phylogenetic analysis). Characters, Function Traits, and Nonadaptivity In the analysis of causality, it is essential to see that a taxonomic character (as any feature used in a diagnostic sense in taxonomy) need not necessarily correspond in any direct way with the form of a structure unit or integral, nor need it even be a real entity in terms of functional analysis. Thus, it is much easier to identify examples of ‘‘nonfunctional characters’’ than it is to specify nonadaptive function traits: A numerical index which incorporates two noncorrelated variables (perhaps antennal segment number against position on some pigmental scale) is a character, and not a function trait, and examples of this kind cannot be used to promote the view of nonadaptivity in evolution. It may sometimes be a simple matter to deﬁne a set of arbitrary characters for any taxonomic group, on the basis of which any claim of

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‘‘nonadaptive evolution’’ would be quite correct (relative to the characters so deﬁned ). Clearly then, there is a need to get away from the typological way of thinking inherent to taxonomy and classical morphology. In the following treatment, I use function trait to mean a structural unit deﬁned in relation to its known functional–adaptational perspective, rather than in the potentially artiﬁcial sense of ‘‘character.’’ The term trait therefore carries an element of causality for evolutionary interpretation, whereas character is seen as a derivative, which may at times lie beyond the domain of any worthwhile biological interpretation. Classiﬁcation procedure has no real need to discriminate between function trait and character, but phylogeny reconstruction cannot proceed other than through functional analysis, and therefore has to be exclusively concerned with function traits in the strict sense adopted here. A function trait is capable of functional analysis, whereas a character may not be. Many extremely useful taxonomic characters may also in fact be truly maladaptive or near neutral traits, such as those associated with functional redundancy: Huxley (1942) stated that there will be ‘‘useless or deleterious characters due to chance.’’ He also stated, ‘‘It may be presumed . . . that ‘useless’ nonadaptive differences . . . may be enlarged . . . to give generic distinction, though it seems probable that differences of family or higher rank are always or almost always essentially adaptive in nature.’’ We can perhaps observe Huxley’s view most clearly in those genuinely useful taxonomic characters based on vestigation trends which just happen to provide useful markers for supraspeciﬁc categories (as, for example, in the loss of certain wing veins in many insect groups). However, these features tell us nothing of the causal factors underlying evolution (and we must also beware of any wholesale extension of Huxley’s hypothesis; see Chapters 15 and 16): At the time of writing, it is still normal practice for the taxonomic characters of insect groups such as Lepidoptera to be fed into cladistic algorithms with no regard whatsoever for the difference between actively evolving and vestigiating trends; an alarmingly large proportion of such traits do in fact belong in the latter category (see Brock, 1990a).

Evolutionary Mode and the Data of Cladistics A major problem exists for phylogeny reconstruction in the nonhomogeneity of the kind of raw data used, speciﬁcally in terms of evolutionary mode. The data of infraspeciﬁc variation are obviously automatically excluded from consideration in the phylogeny of higher categories, and even much of that surrounding ambient speciation should generally be excluded from higher group phylogeny analysis, since any input from amphigenetic activity will lead to inherently nonlinear patterns of relationships:

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Simpson (1953) understood that higher groups originate in a speciation, but he also introduced the adaptive grid and zone concepts into the equation (see Chapter 17). Higher group traits clearly do originate in hierarchic sequence, owing to the differential between ambient and Renschian cladogenesis. The latter must both be centered on speciation but have a quite different respective selection interface, leading to a much larger differential in longer term postspeciational anagenetic divergence. Certainly, speciation is fundamental to the divergence of higher groups. However, the profound dichotomy between the ambient and Renschian cladogenetic selection interface gives rise to many fundamental differences in the way lineage relates to clade, and clade to taxon. We therefore must be wary of data linked to ambient cladogenesis, in the analysis of evolutionary change at the level of the higher domains in macroevolution. A further signiﬁcant axiom of cladistic analysis must also be that the ‘‘retrievability’’ of cladistic information must often be fundamentally different for species as against higher level scenarios. Parametric niche space will tend often to dominate speciational change, since niche intersect is a major factor in cladogenetic potential, and emergent species will generally tend to differ primarily on parametric niche linked traits. Furthermore, much speciational change will occur with behavioral activity forming the leading factor. The problem here is that many parametric niche space changes will be linked to a highly dynamic selection interface, and as a consequence much speciational change will be amphigenetic in nature, thus appearing nonlinear in cladistic terms. In contrast, the iterated function shifts of anagenesis arising from a Renschian phyletic node will tend to manifest long-term, linear change continued over a protracted sequence of subsequent cladogenetic radiations (both ambient and Renschian), and such anagenetic trajectories will often tend more to concern sub- and hypoparametric niche space carrying a very long-term stability factor. In addition, extinctional events may tend be dominated by cladogenetic substitution and adaptational dysgenesis in speciation, whereas occlusional changes will tend to be associated with rapid anagenesis and thus with midlevel to higher categories. The outcome will then be a mosaic pattern dominated by amphigenesis for speciation, and larger, more linear patterns in anagenesis, the latter tending to be bounded by ‘‘basal gaps’’ via implementation of zonal separation: Ambient cladogenesis

Anagenesis

Parametric niche space predominates

Sub- and hypoparametric niche space are more signiﬁcant in the very long term Iterative adaptive response manifests linearity

Iterative adaptive response tends to express amphigenesis Extinction dominated by selectional substitution Usually little or no zonal separation

Much occlusional extinction Zonal separation can be profound

A fundamental difference thus clearly exists between the required methodology for species level as against higher level phylogenetic analysis, owing to

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profound qualitative differences existing between those evolutionary mechanisms underlying ambient and Renschian cladogenesis and anagenesis. Most speciational data will thus be excluded from higher group lineage analysis on an a priori basis, as being amphigenetic or otherwise nonlinear. Conversely, characteristics directly related to species isolation mechanisms are intrinsically likely to have a greater role to play in species diagnosis than in unraveling the phylogeny of a compound anagenetic sequence. In this context, chromosomal data (for example) will link closely to speciational change, yet have little or no input to macroevolutionary patterns. In general, it will often be easier to align genetic data with micro- than with macroevolutionary events (given our better knowledge of simple substitutional change in structural genes, than of complex restructuring strategies for epistatic regulatory gene sets). Given the above situation, it is clear that ‘‘nonlinear data’’ must inevitably contaminate cladistic analysis, whenever macroevolutionary events are the target of phylogeny reconstruction. In the present study, both situations are, of course, points of interest. However, it is with the latter that the most complex and difﬁcult questions arise. Phyletic Orientation in the Context of Evolutionary Mode The most fundamental axiom to be derived from functional analysis of structural traits is that the temporal orientation of an evolutionary sequence can frequently be deduced on an a priori basis. This may be ‘‘linear’’ (as in anagenesis), but it can also be bidirectional, as with amphigenesis. The cascade of changing adaptational mechanisms manifested in an anagenetic sequence may be expressed in purely temporal terms or else through functional propensities, and each of these categories constitutes an orientation for the sequence in question. Orientation in the exclusively temporal perspective is described by the terms plesiomorph and apomorph (quite simply ‘‘older’’ and ‘‘newer,’’ following Hennig), with no adaptationally interpretative implications being implicit. It is, however, often not possible to say whether a trait is apomorph or not unless the phylogeny is at least partly known or until functional analysis has been carried out, a fact which must be particularly true where amphigenetic traits are concerned: Here, we may (for example) consider changing ovipositor length in parasitic Hymenoptera as being an amphigenetic trait, being apomorph for short ovipositor in some lineages and plesiomorph for the same condition in others. Only when a consensus view of broad relationships is available can we then assign any particular state in such traits to any particular phyletic orientation. The purely functional perspective in directionality is described by the terms primitive and advanced in the strict biophysical sense. An advanced structural state corresponds to a biophysical design improvement over some precursor (primitive) state from which it evolved through anagenesis, and this mode of orientation clearly expresses a true linear progression in terms of functional efﬁciency. A primitive state can be determined by its relative sequential position in a lineage; however, it also has an absolute value in relation to the link with

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biophysical efﬁciency, in the advance from ‘preadaptive’ to adaptive paradigm state (even although the genetic system for a given trait sequence may itself have no intrinsically obvious primitive–advanced orientation in the sense that its structural parameters do): The anagenetic sequence involving strengthening of the leading edge of the forewing in ditrysian Lepidoptera (Brock, 1990a) has clear directionality on the basis of biophysical efﬁciency alone (wing structure cannot be moving toward a less aerodynamically efﬁcient structure, excepting when ﬂight itself has become a redundant trait!). Consequently, the time arrow is given by the anagenetic sequence for wing venation as this relates to biophysical properties of the wing, on the basis of functional analysis alone. In this situation, it is also clear that the epithets primitive and advanced become appropriate in the context of an isotropic adaptation interface, while amphigenesis relates to temporal dynamism in the selection interface (in which case, plesiomorph and apomorph are more appropriate terms). The primitive– advanced terminology thus represents an objective polarity for functional analysis and must always be used in that role, whereas plesiomorph–apomorph should likewise be used with amphigenetic data, being more appropriate where there is no linear pattern. Consequently, the Hennigian terminology does not form an alternative dialectic to the ‘‘classical,’’ but forms a special subset of the latter (as well as constituting a more a posteriori rather than a priori designation). It is also essential to recall that application of the terms primitive and advanced has no implications for the adaptive state, which is always a function of the entire organism–environment interaction, to which a given structural trait may offer a large or small contribution, depending on the totality of the adaptive system in question (see Chapter 8). In addition, reference must also be made to usage of certain other terms that are sometimes used incorrectly as synonyms of primitive and advanced, namely, in the niche linked perspective, generalized and specialized. Generalized is equivalent to ‘‘wide spread of K in the adaptive niche,’’ whereas specialized describes an adaptive response expressing links with a highly constrained niche interface. It is important to realize that generalized is not exactly synonymous with primitive. A generalized adaptation may even precede a Renschian adaptive shift then survive it, conferring a tripartite pattern of relationships. This form of adaptive radiation may then be followed by establishment of descendent lineages expressing structure states reﬂecting an apparent ‘‘trichotomy.’’ Consider a hypothetical radiation in beak structure, with three Renschian cladogenetic events expressing nonlinear topology of change, superimposed on ambient speciational events (Fig. 119). Two major problems are evident in the phyletic scenario shown in Fig. 119. First, there is no obvious linear progression between the four Renschian cladogenetic states (generalized, seed eater, insect eater, and scavenger), and second, each of the specialized branches actually carries a sequestered component of ancestral (generalized) structure. At a glance, it is evident that a blind application of the terms plesiomorph and apomorph in the above scheme readily identiﬁes an entirely false paraphyletic

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FIGURE 119 Hypothetical cladogram for adaptive radiation from generalized to specialized states, showing potential for ‘‘nonparaphyletic’’ survivorship of the generalized condition in three descendant lineages (i.e., where synapomorphy is not reﬂected in the trait under analysis).

group that is actually made up of several discrete lineages with closer phyletic links to the specialized types! There may be little or nothing in a fragmentary extant sequence which offers any information concerning the true bifurcational architecture of a lineage, and indeed, this ‘‘bushiness’’ (radiation ‘‘from an apparent common point’’) is characteristic of many known adaptive radiations: In Lepidoptera, an apparently cryptophagous ancestral larval form has led to an iterated, polyphyletic radiation of larval types entering either a specialized endophage or exophage adaptive niche (Fig. 120). Genetic data may or may not ultimately serve to solve such problems (see below), and we have to consider the possibility that single tree answers may not be obtainable in the face of such difﬁculty. Continuing with the above theme, the term specialized also does not mean advanced in relation to the whole organism, since bradytelism (Chapter 18) is frequently linked to specialization within a hostile adaptive corridor, with respect to at least one function integral: Thus, several endophagous lineages of Lepidoptera show larval structures that are as specialized as the exophagous groups (sometimes

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FIGURE 120 Adaptive radiation and phylogeny. In this apparent ‘‘Renschian trichotomy,’’ primitiveness is distributed according to evolutionary rate of lineage, particularly appearing in endophagous (hostile adaptive corridor) lineages, whereas the generalized cryptophage state is preserved in some extant groups.

much more so), despite the fact that most traits of adults and pupae tend to be primitive for endophage lineages and advanced for exophage ones. Total confusion has existed in the past, concerning the correct application of the above terms. As already indicated above, anagenesis must clearly be approached via functional analysis; hence the primitive–advanced dichotomy for structure additionally has an a priori meaning outside of cladistic analysis, and also must not be confused with the generalized–specialized dichotomy. The latter nomenclature is nevertheless vital in linking functional analysis to the wider adaptive system, in that the dynamic structure of adaptive shifts is often readily understood through the generalized–specialized dichotomy linked to Renschian cladogenesis. In conclusion then, functional analysis may often show whether a linear or amphigenetic pattern is to be expected, since at least some traits will usually have a dynamic selection interface met by evolutionary reversal (at the same time, however, amphigenetic status may often be implied a posteriori on the basis of statistical correlation with linear data).

Anagenesis and the Function Integral Sequence It will already be clear that a phylogenetic sequence is made up of the descendants of an ambient or Renschian phyletic node, from which we may identify the existence of certain characteristic lineage structures. A clade is the representation of a lineage at any point in time (‘‘lineage minus extinction’’), whereas

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an anagenetic sequence describes the trajectory of a given structure integral over any portion of a lineage or clade. In this view, an anagenetic sequence is essentially a temporally orientated sector of lineage architecture in which some part of the progression preadaptive state 씮 biophysical paradigm form is reﬂected. It is necessary at this juncture to realize also that a given anagenetic sequence may be monophyletic for extant taxa, yet polyphyletic in terms of the true antecedent lineage. So far as the postulated anagenetic sequence is concerned, however, the question of monophyly cannot be approached at this stage. The term anagenetic sequence can thus be used generically to include any fragment of a supposed clade sequence made up of linearly orientated data that is supported by functional analysis. The taxa used as raw data for the analysis of phylogeny will no doubt have been recognized on the basis of apparently uniquely derived traits, which is acceptable within the limitation that the validity of such an assumption will, of course, have to be questioned later, in that an element of circular reasoning obviously appertains to this: The tympanal organs are useful ‘‘static’’ diagnostic traits (apparent autapomorphies) for certain families and superfamilies of Lepidoptera, but this does not mean that our assumption of ‘‘probable monophyly’’ for complex structures expressing basal lineage gaps constitutes anything more than a preliminary hypothesis (indeed, quite similar abdominal tympanum elements have now been found in remotely related lineages of ditrysian moths, and this can only reﬂect some element of polyphyly and convergence). The anagenetic sequence is the equivalent of a morphocline (see Maslin, 1952; and elsewhere)*, except that it can be designed to carry an a priori temporal orientation by virtue of functional analysis, provided that no assumptions concerning monophyly are made at the outset, such as are not subject to later adjustment. Function Integral Sequence Analysis Clearly we must now distinguish between the anagenetic sequence for a series of taxonomic groups and that simply describing the trajectory of evolutionary change within an isolated structure unit or integral. Adopting the categorization of structural architecture introduced earlier (Chapter 7), an anagenetic sequence could in effect be most usefully reﬂected in the topology of a structure integral sequence. It is often possible to arrange structure states in linear order on the basis of a single structure unit. A structure integral sequence reﬂects the topological progression between dynamic character states of a compound set of linked function traits temporally orientated with respect to the time arrow of evolution following the tenets of the biophysical paradigm concept, from interpretation through functional analysis. This approach can generally be further supported through concordance testing (on the basis of rank correlation) between different * The Maslin approach was nontypological and also contained a dynamic perspective that was absent in the original Hennig method.

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structure unit sequences of the same structure integral (Brock, 1981b). From this mode of analysis, we may be presented with a range of different degrees of concordance among functionally correlated dynamic traits, the evolutionary interpretation of which clearly becomes a focus of interest. The only really valid approach from the standpoint of functional analysis must, however, clearly be to go on to examine a larger holistic assemblage, namely, that of the links between different structure integrals of a larger adaptive complex. The basis for analysis of the function integral sequence then lies with the axiom that selection interactions are functionally correlated for n structure integrals of a single function integral but tend to be autonomous for discrete function integrals. A function integral sequence would then be based on concordance analysis between n structure integrals of the same function integral, thus moving one step closer to acceptance of functional analysis as a route to the objective interpretation of ‘‘nonrandom character correlation,’’ either in terms of phylogeny or in view of possible parallelism among n trait sequences. The statistically viable function integral sequence may then constitute a probable anagenetic sequence. In this approach, possible parallelism between discrete lineages should really be accepted as the ideal preliminary hypothesis, since functional correlation is a likely explanation of much nonrandomness in the distribution of taxonomic characters, particularly in that frequently encountered situation in which directionalization (in terms of restricted degrees of freedom in the structural attractor) implicates a uniform adaptive response in anagenesis. Similarly, the huge manifestation of homoplasy in the results of a majority of cladistic analyses clearly supports the same viewpoint. The eventual goal in these investigations should clearly be that of ﬁnding the consensual sequence for n function integrals. The latter would then be acceptable as a valid topological description of the parent anagenetic sequence. However, given that there may be a degree of internal disagreement concealed by consensual rank order, it may or may not approximate to the phyletic sequence also. The concordance approach can be illustrated as follows. We commence with, say, six taxa (A to F) that are displayed in any sequential order in a K ⫻ N table (K ⫽ rank values of a and b sequences, N ⫽ number of taxa being ranked), in the usual manner of the Kendal concordance technique: Taxa

A

E

D

C

B

F

Rank (sequence a) Rank (sequence b)

4 2

4 4

1 1

3 1

2 1

4 3

Summed (Rj) ranks

6

8

2

4

3

7

We can see that the tied ranks at A, F, E (a sequence) and C, B, D (b sequence) are dealt with following a reordering according to the consensual (Rj) sequence, the latter forming a preliminary phyletic sequence: Rj rank order Possible phyletic sequence

2. ⬍ 3 ⬍ 4 D 씮 B 씮 C

⬍ 6 씮 A

⬍ 7 씮 F

⬍ 8 씮 E

Statistical signiﬁcance of the consensual sequence is then conventionally assessed following computation of W, the coefﬁcient of concordance:

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w⫽

s 1/12 ⭈ K (N3 ⫺ N ) 2

where s ⫽ sum of squares of deviations of each raw rank value from that of the mean Rj (consensual) value. Given a valid functional analysis program and a statistically acceptable level of concordance, the consensual sequence for n function integrals correctly describes the topology of the anagenetic sequence, but not necessarily phylogeny, since the sequence in question might well be evolving in parallel. The largest conceptual problem here is clearly that when ‘‘statistically signiﬁcant’’ concordance is achieved by the data set in question, this could mean simply that there has been parallel evolution affecting a tightly constrained anagenetic sequence, such that the same structure units always appear in functional correlation, no matter what the true phylogeny is! It is possible, for example, that absolute size alone could account for at least some of the traits typifying micro and macro lineages in Ditrysia (Brock, 1990a), given the usual correlation between size and biophysical design (see Chapter 7). In this situation, even the autonomy between apparently discrete function integrals may be no barrier to correlated pattern of change. Similarly, a number of traits associated with exophagous behavior are ‘‘highly correlated’’ in the larval stage (not only with regard to vestiture of the integument, but also in relation to detailed structure and musculature of the prolegs; see Hinton, 1955), yet are thought to have no bearing on phylogeny. A larger consensual sequence for data derived from all developmental stages would of course represent a more robust input to phylogenetic analysis, and thus might arrive at a ﬁnal, correctly orientated function integral sequence. However, there is no reason to suppose that the combined effects of multiple polyphyly, zonal separation, and differential evolutionary rates would not continue to create considerable problems with the view that such analyses automatically equate with the true phyletic sequence for inclusive taxa! Static and Dynamic Data Static traits express disjunct state-to-state relationships, whereas dynamic ones are those with an intrinsically continuous sequence form, deﬁned both by topological and functional relationships. Obviously, static traits must have had a dynamic origin. However, it is assumed that extinction factors will have impinged to such an extent that such relationships are not evident in the extant clade sequence (indeed the best absolute diagnostic traits or autapomorphies are derived from complex structures for which there is no direct evidence in the extant fauna of how such form evolved from the ancestral state). The raw data of a function integral sequence will no doubt be based on static traits carrying no a priori evidence of actual monophyletic origin, a fact which serves further to underline the ‘straw man’ status of the consensual sequence! A combination of bounded adaptive zones, parallelism, and extinction may often create an illusion of monophyly where none exists, and obviously the more incomplete the extant representation of a lineage is, the more likely

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monophyly will tend to be diagnosed. False diagnostic characters may well then come to be utilized in cladistics. Paradoxically then, the ‘‘best evidence of monophyly’’ scenario for static traits may sometimes be the worst for determination of ‘‘vertical’’ relationships, given that direct evidence of the anagenetic sequence structure is absent. The absolute diagnostic characters scenario clearly lies close to the basal gaps problem associated with quantum evolution (Chapter 18) and is probably frequently derived from 움-anagenesis via a large input from the mechanism of phyletic occlusion. Thus, although static data may often give acceptable evidence of taxon monophyly, it is often only with dynamic data that we can explore vertical as against horizontal relationships. Bearing in mind the frequently simple nature of many dynamic traits, rank order analyses may therefore tend to focus on traits that are intrinsically likely to carry a high likelihood of polyphyletic status, which would of course explain why parsimony is generally invoked as a solution to such problems. Owing to the variable inﬂuence of the above factors in different lineages, it may be that different higher groups are deﬁned either by the pivotal phyletic node or by some subsequent but more practical endocladic node. This circumstance creates a fundamental heterogeny in the concept of the clade itself, in that recent clades will lie closer to the true lineage sequence (with much prima facie evidence of polyphyly), whereas older clades represent senescent lineages in which conventional cladistic analysis will appear to readily identify ‘‘monophyly by parsimony’’: This can be seen in the apparently ‘‘mosaic’’ relationships apparent in Ditrysian as against monotrysian lepidopteran families and superfamilies, in that more nearly linear patterns of similarity have been found in the fragmentary extant representation of the monotreme groups (Brock, 1971, 1990a; Kristensen, 1984 and elsewhere). One great difﬁculty for cladistic analysis is thus that the more representative data sets will probably uncover much higher levels of ‘‘nonparsimonious’’ evolutionary activity, while the more ‘‘workable’’ data from fragmentary clades will tend to lie beyond the domain of meaningful concordance analysis! Static traits therefore help to diagnose probable monophyly of whole lineages, but may be of little value for cladistic relationships between different lineages. Similarly, dynamic traits offer criteria for an understanding of phylogenetic direction, but not necessarily of phylogeny itself. Absolute diagnostic characters tend of course to form the basis of conventional classiﬁcations in that they probably often do reﬂect unique solutions to highly complex functional problems that confer high ﬁtness values, such that a steep intrinsic selection gradient in 움-anagenesis acts to contour the adaptive zone in a highly pronounced manner, with most or all of the anagenetic sequence leading to annectent states passing to extinction. Such data often provide highly convincing evidence of monophyly of a proposed clade, while frequently appearing to afford little or no evidence of phylogenetic relationships with other clades of the same rank. However, it may happen that the polythetic distribution of several static traits in the endocladic situation offers some evidence of cladistic relationships, by virtue of the nested sets criterion.

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In any attempted analysis of the dynamic relationships of function traits, the foregoing comments on the absolute diagnostic character concept should be borne in mind, as should the preliminary hypothesis status of phylogenies drawn from concordance of dynamic trait sequences.

Interpreting the Function Integral Sequence The importance of function integral sequence analysis is that it clearly constitutes the conceptual nucleus of any cladistic methodology which purports to transcend the domain of ambient speciation and to enter that of complex anagenetic change. The most biologically robust basis for analysis of the anagenetic sequence must involve rank testing over n function integrals following the Kendal concordance coefﬁcient. Given an optimistic view that the topological sequences described by anagenetic increments in different structure and function integrals ought to reﬂect monophyletic trends, one might then expect to ﬁnd complete concordance between all input data to such an analysis. In that situation where functional autonomy between structure integrals is certain (for example, larval chaetotaxy against morphology of adult reproductive organs), we could indeed ascertain a fundamental truth in relation to observed correlations, namely, that common phyletic origin is the simplest explanation, when concordance ⫽ 1.0 whenever there is demonstrable functional autonomy between two or more function integral sequences. The above concept can be demonstrated following the tenets of a probability model which shows that rank order correlation between even quite small functional unit integral sequence arrays can be a surprisingly rare event, given only random sampling (Brock, 1981b). However, examples in real phylogeny do not concern inﬁnite populations of sequence terms combining in a purely stochastic manner in the context of taxon diagnostic character sets, nor are the forces determining rank order correlation in any way limited to the effect of phylogenetic afﬁnity or even functional correlation (in that varied evolutionary rate linked to parallel evolution may, for example, play havoc with predicted patterns). Thus, even a probability value approaching 1.0 cannot be presumed to constitute proof of an underlying cladistic sequence. In reality, it appears in fact to be a common outcome of the concordance approach that the results constitute nothing more than ‘‘high rank correlation,’’ combined with some element of internal disagreement between unit sequences and the consensual (Rj) sequence, suggesting that polyphyly is manifesting some unknown input to the dynamic class of data: Actual application of concordance analysis to real data sets derived from all developmental stages of Lepidoptera (Brock, 1981b) gives no indication of any general ‘‘internal agreement’’ with the consensual sequence, despite the fact that the latter is ‘‘highly signiﬁcant’’ in terms of concordance. This, of course, merely conﬁrms (from a more rigorous model) the observation that homoplasy is usually manifest whenever cladistic analysis is applied to real data.

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The preceding observation is a crucial one, since it is obvious that total rank correlation across all constituent function integral sequences comprises the minimum requirement for a proven phylogeny, in that any nonconcordance within the K ⫻ N matrix for a concordance test must imply some element of parallel evolution. The probability model thus ‘‘solves phylogeny’’ only at the P 씮 1.0 point (namely, for total rank order agreement between all inclusive function integral sequences). Consequently, if homoplasy did not exist, it would not be necessary to invoke the question of evolutionary parsimony. With regard to that situation where parsimony must be taken into account (as is probably generally the case!), the situation is, however, clearly quite different from the P 씮 1.0 scenario. There will clearly be topological parsimony solutions to such problems, but there is no reason to suppose that such solutions necessarily carry any degree of objectivity in terms of expressing true lineage relationships. The fundamental problem with interpretation of dynamic data on the basis of supposed evolutionary parsimony is of course that, if one sequence is deemed to be polyphyletic, then others could be also (and we cannot in any case be certain that parallelism is always minimized in evolution). Phylogeny should thus be seen here as having the status of hypothesis, rather than theory, since more than one solution may be reached on the basis of a single data set. What category of information do we actually then obtain from the concordance analysis approach? Positive Findings of Function Integral Sequence Analysis Signiﬁcant positive ﬁndings in function integral sequence analysis can be identiﬁed in the areas of anagenetic directionality, temporal orientation, and reconstruction of phyletic progenitor groups of a lineage. 1. Directionality in the Consensual Sequence The concordance approach constitutes a rationalization of compatibility analysis, with incorporation of the objective methodology of functional analysis, and this scheme may act to reduce (but not entirely remove) the number of possible phyletic pathways for a given data set. In general, the robustness of a consensual function integral sequence depends on its degree of concordance with n other similar data sets, and in that context, it does at least constitute an objective statement of the broad directionality of all constituent anagenetic sequences. 2. Time Arrow and Orientation Another deduction to be made from the consensual sequence of a concordance analysis will be that of an objective temporal orientation for all constituent data, including any portion for which functional analysis itself has been unable to reach any deﬁnite a priori conclusion. A function integral sequence data set expressing signiﬁcant concordance must therefore at least reﬂect the geometric progression between dynamic character states in the consensual sequence, orientated with respect to the time arrow of evolution. One primary goal of function integral sequence analysis should therefore be that of attainment of a potential for some degree of ‘‘reciprocal illumination’’ on understand-

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ing of functional correlation and temporal orientation, which may often serve in turn to identify evolutionary reversal (namely, for those sequences showing bidirectionality against consensual rank). Where structural divergence has occurred at a Renschian phyletic node, the topology of nodal structure itself gives further objective evidence on the direction of time arrow, from the simple axiom that ‘‘two branches cannot become one,’’ and in view of demonstrable functional relationships (namely, that the sequence has not in fact been ‘‘inverted’’ in the analysis). Temporal orientation may also be possible in genetic analysis, if the functional code for a redundant gene locus is also known or if the ancestral functional gene state is identiﬁable. Here again, the molecular clock hypothesis may often provide vital information, following the maxim that for any given macromolecule, evolutionary rate is approximately constant over time in all lineages (Zuckerkandl and Pauling, 1965): Lewin (1996) has provided a useful summary for the basis of the molecular clock hypothesis as follows: ‘‘As species diverge from a common ancestor, they accumulate mutations at a regular rate, progressively becoming more different from each other genetically. . . . Different genes within the same organism mutate at different rates, depending on how much of the coded protein can be modiﬁed and still perform its function.’’ It is believed that ribosomal genes are particularly slow in mutation, thus providing a better reference frame for longer term measures. Gillespie (1994), however, takes the view that the molecular clock does not exist, since there is signiﬁcant variation in the rate of substitution. There is, of course, no ‘‘molecular clock’’ problem with actively selected gene changes. Only when DNA is redundant (and there is no residual control over mutability) can the concept of a molecular clock be completely valid, and even here, there may be some element of differential sequestration acting to obscure the random mutation time correlation in very long-term evolution. Nevertheless, a general time orientation can be elucidated in cladistic analysis, given valid data on mutational change in functionally redundant DNA, and this must form part of the data set feeding into the analysis of the function integral sequence set. 3. Phyletic Progenitors, the Principle of Amphiphyly, and the Adaptive Isthmus Although the P ⬍ 1.0 result of a concordance analysis may frequently arrive at nothing more than several approximately equally probable phylogenetic hypotheses, it must at least reach a correct judgment of time arrow, and there are certain related derivatives of the latter maxim that can also be said to be equally objective. Chief among these is the concept of a phyletic progenitor for the lineage in question. Capacity to deduce the progenitor state of a lineage derives from the observation that the distribution of primitive states among bifurcating lineages is often amphiphyletic, that is, the most primitive states are not all located at the root of one branch of the lineage, but are differentially distributed between

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two or more branches. The progenitor state may thus be implicit in a taxonomic hierarchy, even though it is absent in the extant representation of a lineage, thus being partially diagnosed from the ‘‘root’’ (zero) points of all structure integral sequences of its descendent taxa:

FIGURE 121 Amphiphyletic distribution of derived traits in a lineage, allowing deduction of the progenitor state (a and b being two anagenetic sequences).

Following the above concept, it is possible to predict some of the characteristics of the butterﬂy progenitor which actually occur in the related but more primitive Hesperiidae (skippers), on the basis of primitive traits preserved in different lineages of papilionoid families (pupa with active genomandibular and epicranial cleavage lines in head, limited degree of ‘‘splitting-back’’ of radial branches in venation of forewing, larva with complete circlet of proleg crochets, etc.). Similarly, the progenitor of the bombycoid like macro moth groups must have possessed circlets of abdominal spines linked to pupal motility, since three separate lineages within this complex contain a few species displaying these traits (see Brock, 1990b). With regard to dynamic data of the kind discussed above for lepidopteran traits, derivation of the phyletic progenitor state is often the only way of actually scoring sequence values in a function integral sequence in terms of a realistic evolutionary parsimony: Basal anagenetic states for ditrysian pupae are really those of the progenitors, since the family and subfamily groupings are based on characters mainly of adults and larvae, with only chains of endocladic traits being found in the pupal stage in most instances (Brock, in prep.). The origin of amphiphyly may often lie in the axial or tangential resolution of Renschian cladogenetic potential, where evolutionary rate of lineage is unevenly distributed between two descendent lineages, with some traits evolving more rapidly in one lineage relative to another. In this way, the ‘‘phenotype load’’ for relatively primitive states has been distributed in such a manner that

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no one gene pool carries the entire negative selective force appertaining to the suboptimum all-primitive state. The phyletic progenitor clearly holds high status as a valuable and valid deduction which can be made from function integral sequence analysis, particularly since it is not dependent on deduction of a single phylogeny. It also affords vital information on the nature of the occlusion zone of a lineage (Chapter 17), additionally forming a logical basis from which to explore evolutionary parsimony. The adaptive niche parameters of the progenitor of a higher group may well also help identify the probable primary adaptive shift of a lineage and thus also the causal boundaries of a clade. The primary adaptive shift constitutes the causal factor, both for evolution of higher group function traits and for determination of evolutionary rate of lineage. The adaptive zone is then reﬂected in that set of structure integrals which is functionally linked to the pivotal phyletic node, and the occlusion zone may likewise be implicit in terms of basal gaps for this same set of structure integrals. In this way, deduction of the phyletic progenitor state may assist in reconstruction of the adaptive isthmus which led to a novel, bounded adaptive zone: Data from early stages of ditrysian Lepidoptera converge on a suite of progenitor traits which clearly lie at the boundary between the cryptophage and exo- or endophage larval adaptive niches, thus identifying transition between these adaptive zones as being the most probable primary adaptive shift underlying the radiation of different macro- and microditrysian lineages. Acquisition of a correlated suite of adaptational specializations in these adaptive zones likewise constitutes a pivotal adaptive shift in the structural adaptive response. The phyletic progenitor for a given higher group must have existed at the root of its anagenetic sequence, the probability thus being high that its extinction may be largely due to the inﬂuence of phyletic occlusion. Problems in Application of Function Integral Sequence Analysis No mode of cladistic methodology should be blind to the many problems encountered with reconstruction of phylogeny from fragmentary data. Not all phyletic nodes need be apert, nor are all ‘‘good’’ diagnostic traits necessarily genuinely monophyletic. There are also considerable problems with reconstruction of ancestral states (as against mere progenitors), and the specter of gradism is never far away in cladistics. 1. Cryptic Nodes Phyletic nodes of an anagenetic sequence may be established on an a priori basis where there has been topological divergence of the Renschian cladogenetic kind with respect to structure, but this does not mean that there are no cryptic nodes obscured by parallelism in some apparently linear sequences. Phyletic nodes can in fact be identiﬁed in two different ways: the topological node is explicit in the geometric topology of the function integral sequence itself (from a priori evidence in anatomy), and the analytic node is a lineage node evident only from taxonomic correlations with a topological node in

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some other structure unit or integral. The existence of a topological node in one structure integral sequence thus may provide evidence for the existence of an analytic node in other, apparently nonbranching data, via incongruity with a consensual sequence in function integral sequence analysis. This constitutes a real problem, when the key node lies in some unstudied area of anatomy: The phyletic divergence between certain macroditrysian superfamilies was not at all apparent on the basis of early studies of wing venation and ‘‘general facies,’’ only becoming apparent when the tympanal organs were ﬁrst discovered in the 1930s. Renschian phyletic nodes evident in the latter structures afforded the ﬁrst clear evidence that certain major nodes were not reﬂected in any form of divergence with respect to most other traits. That statement is still more or less true, even following the more recent analyses of many additional anatomical traits by Hinton (1946), Ehrlich (1958), Yagi and Koyama (1963), Brock (1971), and Hessel (1969). The above scenario naturally raises the question of whether cryptic nodes conforming to a major lineage split can at times also be presumed to exist when there is low rank order correlation among a set of apparently nonbranching sequences which, in reality, might mask concealed Renschian cladogenesis where the locus of the node on the lineage sequence is unknown and, in all probability, is not in fact reﬂected in any single (known) anagenetic sequence: There are several families of lower ditrysian Lepidoptera, the systematic position of which is very difﬁcult to ascertain, owing to the absence of any traits that could connect them deﬁnitively to any other lineage (Immidae, Hyblaeidae, etc.). The relationships of these taxa are presumably concealed in cryptic nodes (so far as the known repertoire of morphological data is concerned). Although an explicit view of the topology of anagenetic nodes may be expressed in a single functional unit sequence, only the minimum totality of cladogenetic nodes is diagnosed in a consensual sequence over n functional integral sequences, so that the nodes of the consensual sequence are thus not necessarily to be equated with the totality of the true phylogeny. The cryptic node may ultimately be identiﬁed on the basis of genetic analysis (or perhaps even not at all), since if an unsuspected cladogenetic node can be implied on the basis of just one of many structural anagenetic sequences, then there is no reason why other such nodes should not also exist: Something of this nature is evident from work on DNA hybridization on the Australian avifauna, which appears to have cleared up a longstanding controversy over the relationships of lineages manifesting an extremely high level of evolutionary convergence with Old World passerine families, but which are now found to have evolved from corvida stock (Sibley and Ahlquist, 1990; see also Lewin, 1996). Solutions to the low concordance problem are also generally sought in topological parsimony (see below). However, we cannot assume that other cryptic nodes do not lie concealed, even in the ‘‘best ﬁt’’ system:

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Analysis of all known larval and pupal traits of ditrysian Lepidoptera would quite fail to identify those nodes indicated by tympanal organs and certain other traits of the adult stage. In addition, there are no explicit nodes in any of the data so far analyzed (for all developmental stages) such as could determine phyletic relationships of the superfamilies, other than those suggested by applications of more or less arbitrary parsimony rules. 2. Monophyly and the Problem of Stenophyletic and Euryphyletic Traits Following the implementation of concordance analysis to a data set, it will usually have become evident that some constituent anagenetic sequences must be subject to greater or lesser levels of parallelism than others. Anagenetic traits may thus be of mono-, steno-, or euryphyletic distribution (Brock, 1990a), depending on their tendency toward polyphyly. Euryphyletic traits are those for which cladistic analysis diagnoses high levels of parallel evolution, and stenophyletic traits are those shown by taxonomic distribution to have had an apparently much lower incidence of polyphyly. How valid are the criteria for determining eury- as against stenophyly? From the ‘‘phylogeny paradox,’’ the nearer the extant clade is to true lineage form, the more likely paralleling sequences will be recognized as such, but as the clade diminishes through extinction, the more probable it will be that parsimony will appear to diagnose monophyly. Consequently, both monoand stenophyletic traits may only be apparent in clade sequences that are the surviving remnants of lineages in which the same anagenetic sequences had originally expressed greater levels of polyphyly. Thus, the role of such traits in cladistics is often difﬁcult to assess objectively, despite a likelihood that this class of data should play a signiﬁcant role in the parsimony criterion. A majority of dynamic traits will in fact tend to be steno- or euryphyletic (rather than being strictly monophyletic), owing to constraints imposed by the structural attractor, since anagenetic change will have a much higher probability of discovering functional solutions in adjacent morphosystems than in remote ones. In general, movement ‘‘in and around the domain of adjacent morphosystems’’ appears to be the usual mode of anagenetic progress, and this probably explains the relative universality of parallelism. True monophylies seem thus to be static traits for which there had been extremely rapid occlusionary loss during early anagenesis. Such unique events most probably carry a very high contribution to ﬁtness, such as would preclude any likelihood of cosurvival between n paralleling lineages manifesting the same trend, and many established monophylies also seem to have invoked exceptionally complex structural transformations such as would simply have had a low probability of being realized independently in different lineages. Owing to the probability that a majority of dynamic traits probably express at least some degree of parallelism, only stenophyletic traits seem likely to help in the interpretation of phylogenetic relationships, so far as that class of data is concerned. This of course raises the question of how we can meaningfully judge certain classes of diagnostic traits as raw material for phylogenetic analysis, if there remains a question as to whether they are stenophyletic trends

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manifesting an unknown level of polyphyly. Once nonconcordance has identiﬁed evidence of parallelism, many traits may be recognized as being intrinsically steno- or euryphyletic; however, the distinction between the two may be largely a function of the (unknown) degree to which extinction has affected differential survival of paralleling sequences. 3. Reconstructing Ancestors The true ancestor of a lineage clearly lies ‘‘deeper than the phyletic progenitor,’’ in that at least one of its constituent traits is carried to the ⫺1 point (that is to say, it incorporates at least one trait lying outside the domain of all extant taxa). The ancestor for a lineage is thus similar to the progenitor, but also contains an unknown combination of ‘‘⬍0’’ gradistic states. The ancestral form may thus only be postulated from outgroup data. Thus, although a given lineage can be ascribed a single ‘‘gradistic root’’ (phyletic progenitor), it will have a number of possible ‘‘gradistic ancestors,’’ differing only slightly from one another in terms of topological parsimony. This fact inevitably connects with the view that several phylogenetic pathways may be deduced as being approximately equally likely, for a great many real data sets. Phyletic progenitors derived from function integral sequence analysis are clearly objective structures. However, they express only those traits identiﬁed as anagenetic, and they hopefully exclude amphigenetic data and any variation belonging to the broad deﬁnition of adaptive equilibrium. Ancestors ‘‘suggested by’’ progenitor states deduced from the same data sets can, however, carry only the status of hypothesis, their true identity being dependent in particular on unknown evolutionary rates acting differentially for different structure units. Furthermore, it is not always the case that the true ancestor does actually constitute a topological step in the usual sense of a conventional ‘‘afﬁne transformation’’ of form (see Chapter 16): As stated by Raff (1996), the discovery of the early amphibious tetrapod Acanthostega (Coates and Clack, 1990) showed that inference of ancestral traits cannot be based on parsimony from cladistic analysis of extant lineages. The tetrapod ancestor had eight digits, not ﬁve (and was aquatic, also against predictions). Similarly, there is no way that the extraordinary autapomorphies of zeuglopteran and dacnonyphan Lepidoptera could possibly be predicted by any form of extrapolation from our knowledge, either of other extant monotrysian moths or from outgroup comparison with Trichoptera! Goodwin and Trainor (1983) discussed luxate mutants in the mouse in which mesenchyme is shifted from making tibia into making enlarged or additional preaxial digits, concluding, ‘‘There is no reason why the pattern of condensations should not have been repeatedly remodelled during the adaptive radiation of the pentadactyl limb.’’ Following the conclusions drawn by these authors, there is no real ‘‘archetypal’’ system, and ‘‘deduced’’ ancestors based on comparative morphology may sometimes be virtually meaningless. Would it have been possible, for example, to deduce the morphology of the ﬁns of ﬁshes, given only a knowledge of the comparative morphology of tetrapod limbs? (The answer is probably no.)

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Some data may then be retrieved in the category of possible ancestors, but it must be understood that this is also that point at which lack of any means of understanding evolutionary rate of lineage differentials of different anagenetic sequences and uncertainty as to what constitutes a logical step in an anagenetic sequence leads to the multiple solutions problem reﬂected in evolutionary parsimony! 4. Clade or Grade? A realistic view of information retrievable from concordance analysis of function integral sequences is that the consensual rank order sequence is often a grade sequence, rather than constituting a true clade sequence (that is to say, it is probably an anagenetic sequence concealing unknown levels of cladogenetic divergence). While still holding that the consensual sequence may not be a true phyletic one, the grade sequence does nevertheless objectively express anagenetic directionality for the constituent function integral sequences. Only in senescent lineages, however, does the grade sequence of a lineage manifesting a bifurcation heavily inﬂuenced by adaptive corridor differentials have a high probability of also being a cladistic sequence, not because of actual monophyly but, rather, because of extinction factors having removed parallelism from the extant representation of the lineage in question. The minimum interpretation for a set of function integrals with high rank correlation might therefore constitute recognition of a grade sequence. The grade sequence thus represents both topological and functional relationships of sequential states, and it also has some (unknown) relationship with phylogeny, with establishment of the phyletic progenitor state perhaps helping to further elucidate the latter. The grade sequence thus probably generally constitutes a relevant preliminary hypothesis for phylogenetic analysis, and this may or may not be accepted (a posteriori) as a clade sequence also: A highly convincing grade sequence can be drawn up for anagenetic sequences in larval and pupal Lepidoptera, but this is entirely inconsistent with phylogeny as suggested by adult traits. This structure nevertheless serves to clarify the trajectory of certain anagenetic sequences as well to conﬁrm the inﬂuence of parallelism as a highly signiﬁcant input to diversity patterns. The grade sequence can now be seen to include a large quota of objective evolutionary information, without incurring any need at this stage to invoke parsimony rules. However, it may give much less than the true phylogeny. The greatest danger here is, of course, that even a highly signiﬁcant level of concordance may only reﬂect a combination of functional correlation, parallelism, and differentials in the evolutionary rate of lineage.

GRADISM AND EVOLUTIONARY PARSIMONY It was shown above that much objective data on phylogeny can be gleaned from certain analytical techniques, but that some components of phylogeny

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clearly still remain within the domain of speculative data manipulation. This viewpoint can be expounded as follows. Looking at trait sequence patterns over n functional units, if only one phylogeny can be ‘‘true’’ (all others being nonconcordant with the ﬁrst), then logically, it is probable that none of them is correct. For example, individual sequences in the morphology of the lepidopteran thorax, abdominal base, wing venation, compound eye, dorsal vessel, along with larval chaetotaxy and proleg structure plus pupal obtection are all in disagreement, not only mutually but also with a consensual sequence for the data in question (Brock, 1981b). There is thus no logical reason for the assumption that any one of these sequences constitutes a ‘‘good character set’’ capable of resolving the phylogeny. Can the inﬂuences of convergence and parallelism be completely excluded from phylogenetic reconstruction, or is the ‘‘n solutions’’ answer to the phylogeny question in fact the maximum approximation that can be achieved in cladistic analysis? It should already have become clear that, as we emerge from the domain of total concordance of all function integral sequence data, we also automatically enter that of evolutionary parsimony, that description of parsimony described in evolutionary rather than in purely topological terms. Since the straw man hypothesis that the consensual sequence is a gradistic one seems generally to be upheld rather than rejected, this means that further phylogenetic analysis must unfortunately be concerned with less objective criteria. At this point, we must return to certain primary axioms concerning the origins of clade from lineage and taxon from clade, in order to see how a number of factors render topological parsimony a highly precarious criterion, particularly when such solutions are claimed to lie with a single best ﬁt, minimum tree. It should by now be evident that both deterministic and stochastic mechanisms are causal to lineage architecture. Furthermore, a variety of factors indicate that false monophyly may arise, some of which elements have a deterministic nature, and some not. Extinction, parallel evolution, and evolutionary reversal will act to create extant diversity patterns which may or may not preserve evidence of past sequences of change in structure. Furthermore, these are simply expected attributes of evolving adaptive systems, rather than rare events acting to obscure phylogeny. These observations are not just hypothetical predictions, but large areas of impasse that are regularly encountered at many levels in the actual practice of phylogeny reconstruction.

Gradistic Factors Affecting Evolutionary Parsimony in Cladistics According to our analysis of adaptive systems, evolutionary parsimony cannot be presumed to be exactly the same thing as topological parsimony. Above all else, it must be held that there is no reason whatsoever to believe that evolutionary parsimony must inevitably be reﬂected in the minimum number of steps criterion. The single best ﬁt tree is a topological solution, not an evolutionary one: That multiple parallelism occurs even with highly complex organs in which monophyly seems intuitively likely has already been quite clear

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from many comparative morphological studies, for example, with the compound eye of annelids and arthropods (see Nilsson and Osorio, 1998). As stated by Eldredge (1989) parallelism is more common ‘‘than even its most ardent, grade minded earlier champions ever thought.’’ Similarly, Brundin (1968) argues that parallelism should be regarded as being the rule rather than the exception. The Inﬂuence of Parallel Evolution The true domain of cladistic parsimony lies with the biophysical paradigm and adaptive potential concepts, which in fact predict that evolutionary parsimony may often be expressed by parallelism, rather than by monophyly. This clearly constitutes a major problem, particularly when evolutionary rate differentials have had a large input to taxon differentiation. Topological parsimony can really only examine ‘‘departure from random assortment,’’ which is relevant solely in terms of molecular level variation expressed in random mutation in redundant DNA, and sometimes in certain highly complex superstructural systems where degrees of freedom in adaptive potential must be presumed to be extremely low (however, see above remarks on the arthropod eye!). Such problems cannot be resolved by arbitrary parsimony rules in the guise of such criteria as consensual rank order, minimum steps, or ‘‘compatibility’’: Traits of ditrysian Lepidoptera that can only have followed a course of parallel evolution include movements of radial and medial branches of the mesothoracic wing veins, closing of certain membranous ‘‘sutures’’ in the meso- and metathorax, strengthening of lamellae of the metathoracic furca, loss of frontal apodemes of abdominal sternite 2, and tendency for the anterior angles of sternite 2 to connect to tergite 1. Also the following: ‘‘pairing’’ of certain tactile setae in endophage larvae, development of secondary vestiture (warts, scoli, spines, etc.) in exophage larvae; fusion of thoracic appendages in ‘‘obtect’’ pupae, loss of habit of pupal emergence from cocoon before eclosion of adult, and many more euryphyletic trends. Even if the Macroditrysia does ultimately prove to be monophyletic, this will not be because of monophyly expressed by any of the foregoing traits—there is no sensible conﬁguration of phylogeny in which any one of them could be uniquely derived! Long (1990) similarly found that two independent lineages of lungﬁshes underwent parallel changes to skull roof and cheekbone patterns during the Devonian, and Simpson (1953) likewise documented very many examples of parallelism in the evolution of the Equidae (as well as in many other mammalian lineages). Sheldon (1987) discussed direct evidence of multiple parallelism and varied evolutionary rate in changes to the mean number of pygidial ribs (a species diagnostic character) that occurred during the Ordovician period in eight lineages of trilobites. Parallelism and Genetic Analysis Can parallel evolution be regarded as being irrelevant in the context of genetic analysis? With regard to molecular evolution in general, evidence for

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convergence in molecular structure has been observed in the stomach enzymes of unrelated herbivorous animals which ferment food in their fore stomachs (Stewart et al., 1987); thus, there is no reason to suppose that the parallelism problem does not arise with genes also. The functionally important unit of proteins lies in their three-dimensional structure, and the same form may result from very different amino acid sequences. Nevertheless, genuinely homologous enzymes seem to appear in different lineages. Although the difﬁculties of phylogenetic reconstruction on the basis of comparative morphology are well enough known, it should now be realized also that genetic analysis contains its own inherent problems. Some of these actually arise from the theoretical approach used by some molecular biologists. For example, the term ‘‘homology’’ has been used in quite a different context by many. Again, genetic homology cannot always be equated with evolutionary homology, as exempliﬁed by the similar expression of hedgehog family genes in vertebrates and invertebrates, which can in fact be explained in terms of homoplasy (following Arthur, 1997). In this same context, it is interesting to reﬂect also that the genetic homology between thoracic and abdominal legs in the larvae of Lepidoptera (see Chapter 16) has no implications whatsoever for so-called phyletic homology. The Hox genes apparently suggest also that at least some morphogenetic gene complexes have tightly constrained architecture. Not only are certain homologous high-level regulatory genes conserved between very remotely related lineages, but also parts of regulatory cascades are maintained almost intact, as in the example of the reciprocal interactions between hedgehog and wingless genes concerned with limb formation in insects and vertebrates (see Gilbert, 1997, for a review). Some apparent genetic homologies do not therefore signify nearness of phyletic relationship (or even parallelism–convergence), but might better be regarded as being due to genetic conservation. Is this tendency for ‘‘genetic conservation’’ likely also to cause problems in resolution of parallelism and convergence? If complex gene clusters of the Hox type have retained their fundamental architecture in taxa as widely separated phylogenetically as Insecta and Mammalia, then many other morphogenetic gene complexes may well tend to evolve within tightly constrained architectural paradigms, in the same way as many organic superstructures clearly do. These facts clearly contain implications for the capacity of genetic analysis to analyze problems where convergence, parallelism, and reversal have been manifested in structural evolution: Raff and others (see Raff, 1996) concluded that strong parallel trends were involved in the independent origins of direct development in various lineages. Gilbert (1997) lists examples of homologous genetic pathways in widely different higher groups, such as control of the alcohol dehydrogenase gene (Drosophila fat body and human liver cells, following Abel et al., 1992), also the widely used RTK-ras signal transduction pathway. Similarly, the existence of paralogous (cross-locus homology within a species) as against orthologous genes (cross-species gene homology) where there have been duplications also creates problems of actual analysis in phylogeny reconstruction.

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Gerhart and Kirschner (1997) reasoned that optimality lies behind the conservation of mechanism, not only with respect to signaling proteins responsible for generation of spatial organization, but in terms of entire intercellular translation systems. In contradistinction to the above ruling, Powell and De Salle (1995) analyzed changes in dipteran segmentation at the superfamily level, concluding that these characters are highly consistent phylogenetically, with no convergences or reversals. However, a more universal application of this relationship depends on the belief that convergence in structure will invariably be reﬂected in divergent gene systems, which may not necessarily be the case, other than for certain high-level morphogenetic modiﬁcations or for relatively trivial substructural traits (see, for example, Gilbert’s criticism of Dobzhansky’s assumption that similar structural traits generally conceal quite different genetic factors). A recurrent feature in the genetic dimension seems to be that likely potential for reversal and parallelism is implicit in certain fundamental mechanisms, for example, in the occlusion–atavism scenario, which could well underlie much amphigenetic activity (Chapter 17). Parallelism thus may or may not also be reﬂected in the structure of changing genetic systems. Similarly, we do not in fact know whether ‘‘reverse evolution’’ in the form of amphigenesis is generally purely phenotypic or involves genetic reversal also. In general, with functional DNA, it is by no means likely that parallel morphogenetic changes will automatically be resolved on the basis of nonidentical genetic modiﬁcations. From what is known regarding the structure of epistatic gene systems, this may or may not be the case. And although we must also consider the implications of the polytropism law (Chapters 12 and 16) in terms of the possibility that certain manifestations of structural parallelism may indeed conceal quite divergent genetic systems, there is no intrinsic reason to suppose that genetic parallelism does not often underlie structural parallelism. In summary then, there seems to be no special reason why convergence, parallelism, and evolutionary reversal should not at times affect the validity of genetic data in the same way as they do for morphological data. However, this is not to say that there are not certain circumstances where genetic analysis has apparently solved problems which could not be reliably interpreted through morphology alone. Some important examples of the latter are listed below: • The Bobbed (bb) gene causes altered bristles in Drosophila. De Salle and Grimaldi (1992) showed that phenotypic relationships between certain species based on this character are in fact produced by two quite different mutations (on the other hand, they also showed that the absence of interfacial setae used to divide the genus Drosophila can arise easily through a common mutation in the Hairless gene!). • Recent morphological studies based on cladistic analysis separated many genera in the African cichlid ﬁshes, some of which taxa inhabit different lakes. Molecular analysis shows, however, that the ﬂock in Lake Victoria is monophyletic, despite remarkable convergencies with species found in other lakes. The range of nucleotide variation is very slight in mitochondrial DNA, notwithstanding the existence of great morphological divergence.

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• In his review of the molecular evidence for phylogeny, Lewin (1996) draws special attention to the example of the Megachiroptera, which show very strong convergence with primates in eye morphology. Recent molecular evidence by Goodman nevertheless conﬁrms a relationship of the fruit bats with other Chiroptera. • Molecular data largely support the morphological with respect to the phylogenetic relationships of ‘‘Darwin’s ﬁnches’’ (although conversely the position is less clear for the Hawaiian honeycreepers): see Givnish and Sytsma (1997) for a discussion. • Genetic evidence on the origins of mammals suggests divergences had already taken place before the demise of the dinosaurs, in contrast to the usual assumption that this occurred at a later juncture (Hedges et al., 1996). Quite apart from the successes listed above, several unanswered questions obviously still remain. In this context, analysis of random change in redundant DNA may seem to offer the best chance of resolving residual problems. Owing to the probably wide discrepancy between functional and redundant DNA analyses in terms of capacity to resolve phylogeny, it is important not to introduce any element of pheneticism into the interpretation of ‘‘distance’’ data. Differentials will tend to be within the bounds of probability analysis for redundant DNA (hence the importance of knowing what genetic differences actually mean in functional terms). Tests on the randomness of mutational change may, however, be irrelevant unless the DNA under analysis is truly ‘‘redundant’’: MacLean (1989) stated that the large amount of redundant DNA means that great code sequence differences can mean little or nothing in terms of functionality, and a possible reason for the discrepancy between genetic and morphodistance has been suggested by Wilson et al. (1974), in that anatomical and reproductive incompatibilities are primarily affected by changes in a small number of regulatory genes. Reviewing the work of Donoghue and Sanderson on the levels of convergent evolution found in 42 morphological studies and 18 molecular ones (which were in fact found to be similar in the two categories), Lewin (1996) also pointed out that most molecular phylogenies actually agree with morphological data (see Sanderson and Hufford, 1996, for an overview). Lewin (1996) also draws attention to the fact that not all genetic data have equivalent information content for phylogeny, citing recent work carried out on the entire protein coding region of mitochondrial DNA in Amphioxus. Only DNA sequences involved in maintaining the three-dimensional structure of proteins reﬂected the true (known) phylogeny. The conclusion drawn was that morphology is better for resolving short bursts of evolution which occurred a very long time ago. In the same way, changes in chromosome structure will tend to be of paramount importance in species isolation mechanisms, but must be of little signiﬁcance for the higher level categories, owing to the link between the mobile

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genome sector and a dynamic selection interface (see Chapter 13). The primacy of genetic (including chromosomal) data in the analysis of species level phylogeny is, however, beyond any question of doubt: Maynard Smith (1998) discusses phylogenies of the genus Drosophila based on genetic distance that are almost identical to those based on inversions (Dobzhansky, 1951), inversion traits being unique events, hence exceptionally reliable for phylogeny reconstruction. In general terms then, genetic analysis will be of greatest value at and around species level, owing to the highly amphigenetic nature of much morphological data, possibly also to an intrinsically greater probability of divergence in many nonmorphogenetic traits. However, there have nevertheless been several spectacular successes at a higher level, as (for example) with Sibley and Alquist’s analysis of the Australian perching birds, and Lewin’s view was not of course intended to diminish the validity of this or any of the other ﬁndings listed above. As stated by Givnish and Sytsma (1997), ‘‘any rigorous noncircular study of adaptive radiation has to be based on phylogeny from traits other than those involved in the radiation.’’ This agrees with the view put forward in the present work, namely, that morphology may often reﬂect habit and function rather than phylogeny, whenever the structural selectional attractor is a highly constrained one. Of course, we must also expect convergence and parallelism in the genetic domain as well, and here the criticisms of Lewin and others must be taken seriously. However, even if genetic data constitute nothing more than a further set of data to analyze, this alone makes the exercise entirely worthwhile, especially considering the point raised by Givnish and Sytsma. We should not therefore conclude that good cladistic data do not exist in the architecture of certain gene complexes, only that the same critical approach to the question of parallel evolution should be applied to genetic as for morphological data! Extinction and False Parsimony As stated at the outset, the nearer the clade sequence is to true lineage form, the more likely paralleling sequences will be recognized as such. Conversely, as the inﬂuence of a range of extinction factors expands, the more ‘‘good ﬁt statistical evidence’’ will be found for neontological data and the more probable a purely topological deﬁnition of parsimony will appear to diagnose monophyly: With regard to homoplasy, Sanderson and Donohughe (1989) state that ‘‘as number of taxa in a tree increases, consistency decreases in a characteristic way.’’ Convergence on a best ﬁt tree may thus often be due to the fragmentary nature of the data available, especially when (true) gradistic differentials are involved: Earlier studies of lower monotrysian Lepidoptera arrived at a quite simple phylogenetic pattern, but as additional relict families were discovered (and as previously known taxa came to be examined more closely), the pattern became progressively more complex and a greater

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degree of homoplasy emerged among what were originally thought to be simple ladderlike anagenetic sequences of structure (see Kristensen, 1984, and earlier papers cited therein). In ditrysian Lepidoptera (to which grade the vast majority of living lepidopterans belong), multiple parallelism for nearly all known higher level characters was put forward as an interpretation in the ﬁrst attempt at a broadly comparative morphological analysis carried out by Brock (1971). Subsequent work has tended, not in fact to ratify possible mono- or stenophyletic status for seemingly ‘‘good’’ characters, but rather to reduce some apparently stenophyletic ones to even lower status! Similar adjustments have had to be made even in lineages where the fossil record is very much better than it is for Lepidoptera. The ﬁsh genus Psarolepis mixes supposedly diagnostic features of sarcopterygian and actinopterygian lineages (Zhu et al., 1999), and the earliest known mammal ( Ji et al., 1999) demands upward adjustment in terms of levels of homoplasy found in that lineage. Here, we witness once more the familiar problem that the raw data of phylogeny may itself be subject to the objection that unjustiﬁable assumptions on evolutionary parsimony may have been made on an a priori basis, frequently on the basis of missing data alone. Amphigenesis and Evolutionary Reversal An evolutionary reversal is any evolutionary change involving recurrence of a previous phenotype state that had passed into extinction. Functional analysis followed by concordance testing in function integral sequence analysis may result in the discovery of unexpected evolutionary reversals, and this again greatly alters our conceptions of parsimony as applied to evolution. The closer data lie to ambient cladogenesis, the greater the inﬂuence of evolutionary reversal will tend to be, owing to the large inﬂuence of amphigenesis on many speciation patterns (see Chapter 8). Much amphigenetic change will not, however, be identiﬁed on an a priori basis, but must be discovered a posteriori from function integral sequence analysis itself. In a functional analysis of amphigenetic trends then, the term parsimony cannot be limited to the view that linear change is ‘‘more parsimonious’’ than the reversal condition. The relevance of nonreversibility as an axiom of parsimony will in fact be very low for many speciational traits, and the extent of euryphyly in ambient cladogenesis will often be much greater than for anagenesis. The greater proportion of data derived from functional analysis (or from conventional cladistic analysis) often proves to be fundamentally nonlinear for all but the highest taxonomic categories, and this is clearly not diagnostic of anagenesis: Raff (1996) holds that short-term reversals may form a large part of the homoplasy emerging from cladistic analyses, also arguing that in groups undergoing rapid speciation, morphological innovations will not necessarily form a nested pattern.

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Data shown to be nonlinear in the absence of an identiﬁable vestigiating (functionally redundant) trait sequence are thus diagnostic of amphigenesis, and have to be excluded from analysis of higher group phylogeny. And the greater the input from amphigenesis, the less correlation there will be between probability levels for nonordered partitions and true cladistic events. As we have seen, realization of adaptive capacity and potential is intrinsically likely to create both multiple parallelisms and evolutionary reversals, and thus also to generate homoplasy. The effect of amphigenesis is therefore to greatly diminish the validity of parsimony being based on the best ﬁt tree, especially for species traits, but not excluding a very considerable input to supraspeciﬁc evolution also: There is no evidence of ‘‘linearity’’ in certain changes in the head structure of ditrysian pupae, bearing in mind functional interpretations that have been suggested for the genomandibular cleavage line often associated with head dehiscence in some pupae (Brock, 1990a, in prep.). The probable solution suggested here on the basis of apparent concordance among other, better understood anagenetic sequences is one of double evolutionary reversal, namely, the reopening of a primitive segmental interstice was associated with improvement of the adult–pupa escape mechanism, as pupal egress from the cocoon was suppressed in favor of direct adult cocoon escape. This adaptive shift may in turn have invoked a neotenous development of the larval mandibular state, as a pleiophoric state linked to the general mode of fusion of head appendages found at a slightly earlier stage of development, and it was evidently followed by a reclosing of the interstitial cleavage line in question once full obtection had been attained. The phenomenon of progenesis (see Chapter 16) also affords good evidence for partial or complete reversal in the niche interface and in correlated structural modiﬁcation. True genetic reversals (atavism) might also occur. However, the same structural reversal may well be ordered alternately by different modes of genetic change. In such instances, we need not expect anatomical and genetic analyses to necessarily show much congruence in cladistic analysis: The insect abdomen has apparently retained developmental potential for generation of limbs, as seen in the larval prolegs of Lepidoptera, for example. Although this is not in fact a true phenotype reversal, we nevertheless witness evidence of the degree to which recovery could be expected to occur in less distantly placed developmental systems! Functional Redundancy and Vestigation Little phylogenetic value can be placed on the topology of structure integral sequences which represent pathways of functional redundancy and vestigiation, notwithstanding the fact that many trends of this kind actually form useful diagnostic characters. Parallelism is an expected behavior of vestigiation, to a greater extent even than for progressive anagenesis, so that any question of parsimony or compatibility will frequently be of little intrinsic value for phylogeny here:

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Very many butterﬂy (and other lepidopteran) vestigiation trends have been treated as evidence of ‘‘synapomorphy’’ (Scott, 1985 and elsewhere, as in many other recent pseudocladistic studies). Dollo’s Law, Reversal, and Complexity Dollo’s law held that evolution is irreversible. However, evolutionary reversal becomes an unacceptable interpretation only in relation to certain highly complex structures. Here alone, topological parsimony may indeed be equivalent to true evolutionary parsimony, in that phyletic sequences involving loss and regain for such traits clearly belong in the realm of the extremely improbable. Amphigenesis could then be seen as being essentially anagenetic change of the kind that is not constrained by Dollo’s law, in the event of functional reversal in the adaptation interface.* Dollo’s law is, in fact, better understood as a subset of a larger axiom: ‘‘Evolutionary changes should not be assumed reversible, unless there is adaptive potential in the epigenetic system for this, and empirical evidence for adaptational reversal also exists.’’ The latter condition is obviously an easily attained situation in amphigenesis (where, however, the maxim ‘‘complex’’ may be presumed to be absent). Vestigiation of complex organs (see below) fully conﬁrms the reality of a restricted Dollo’s law and of the larger principle to which it lies inferior (as does the link between amphigenesis and adjacent morphosystems, with respect to the latter). Redundant structures do not truly ‘‘revert’’ unless they are structurally simple in nature. Reversal can often be identiﬁed through discordance with the consensual rank in a concordance test, plus empirical demonstration in supportive functional data. Evolutionary reversal is thus excluded from anagenesis only in the absence of any evidence for functional redundancy or with special reference to highly complex superstructures where vestigiation is observed. In terms of genetic causality, the traits of higher groups derive from sequestered differentials in the static genome sector, just as those of varieties derive from visible alleles of the mobile genome (Chapter 13), and this in turn must affect the probability of reversion: Mobile genome sector Labile genome sector

Allelomorphic genes Continuous variation in species

Static genome sector

Stable, complex anagenetic traits controlled by genes affecting morphogenesis

Reversibility common Easily reversed traits and microanagenesis Probability of reversal depends on complexity of epistatic systems involved

Characteristics of the genome mobility hierarchy thus also play a large part in determining the probabilities of evolutionary reversal. True genetic reversal may tend to be commoner in the mobile and rare in the static genome sector, and it will most probably lie in the relationship between regulator and structural genes of morphogenesis, so far as lineage phylogeny is concerned. * Dollo’s law may sometimes also be contravenable in artiﬁcial selection (as with so-called atavic mutations). However, such mechanisms cannot be regarded as being analogous to the evolutionary process, nor should they be used to support phylogenetic hypotheses in the absence of other evidence.

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The Inﬂuence of Gradism in Phylogeny Gradism, as the corollary of a dialogue between polyphyly and evolutionary rate differentials, was distinguished from zonal separation at an earlier point. It is now necessary to examine the respective problems created by gradism for evolutionary (as distinct from topological) parsimony. A Structure Equation for Gradistic Relationships As should by now be apparent, the complexity of gradistic–cladistic relationships is wholly predicted from the behavior of adaptive systems, following the tenets of the adaptive cascade, almost to the extent that a ‘‘structure equation’’ could describe the extent to which realization of a given gradistic anagenetic sequence will occur as a function of niche potential plus the product of time lapse since primary adaptive shift and evolutionary rate of lineage: Expanding this slightly, Anagenetic state ⫽ function of [(paradigm distance) ⫹ (adaptive potential) ⫹ (adaptive corridor)] Probability of parallelism ⫽ function of (degrees of freedom in structural attractor) Many ditrysian Lepidoptera larvae have adapted to exophagy, and the longer this habit seems to have been established, the more we observe the customary array of predictable structural specializations associated with it, with special reference to chaetotaxy and proleg structure. Similarly, many ‘‘reverters’’ to a concealed habit show little or no structural modiﬁcation to a more endophagous existence (as in some Noctuidae, for example). All of the traits concerned are clearly polyphyletic. Bigradism and Zonal Separation Simple bigradism evolves when a lineage enters a new adaptive zone to which there exists a long adaptive isthmus and thus also a large occlusion zone between ‘‘lower’’ and ‘‘higher’’ grades (as with the transition between aquatic and terrestrial, or terrestrial and aerial adaptive zones). This is ‘‘gradism by zonal separation’’ (Fig. 122). If the adaptive isthmus is smaller, then it may prove difﬁcult to decide whether some taxa are ‘‘lower members of advanced grade’’ or ‘‘higher members of primitive grade.’’ In a wide occlusion zone, inhabitants of the adaptive isthmus (A4 and A5 in Fig. 122) may in fact have passed into extinction, giving good zonal separation, but in a narrow occlusion zone, it may be that some small proportion of A4 states have survived as a late development in the lower grade and that a few remnants of A5 also occur around the base of the higher grade, leaving doubt as to the true position of certain transitional grade taxa and thus reﬂecting an ‘‘uncertain paraphyly.’’ This problem becomes much more complicated when polygradism is considered, and it is then that problems with cladistic methodology become most overt (see below). Polygradism as Mosaic Evolution Zonal separation or bigradism usually causes no great problems with phylogeny reconstruction, other than in creation of a dilemma between choice

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FIGURE 122 Zonal separation: A1–A8 are phases of an anagenetic sequence that is linked directly to the adaptive shift responsible for the zonal transition (with states A4 and A5 lying in the occlusion zone).

of gradistic versus cladistic classiﬁcatory solutions with respect to apparently paraphyletic taxa. Simple bigradism derives from adaptive shifts, whereas polygradism, on the other hand, more probably emerges from function shifts. Polygradism occurs when n branches of a lineage enter the same adaptive zone, the latter carrying an adaptive corridor-derived differential manifested in variable evolutionary rates, with no structural divergence occurring between paralleling lineages, owing to the presence of a tightly constrained structural attractor. The polygradism scenario (Fig. 123) can in fact be understood from certain aspects of evolutionary rate of lineage, in that the same anagenetic sequence may evolve at different rates in independent lineages owing to a differential in adaptive corridors, in the context of allotely (see Chapter 18). In the diagram shown in Fig. 123, the taxonomic distribution of sequence B is determined indirectly by the zonal transition to which A is functionally linked, as a function of evolutionary rate, and owing to the zonal transition in question also deriving from a differential in adaptive corridors. In this scenario, some residue of primitive A1–A3 states may persist in the neighborhood of the adaptive isthmus of the ‘‘higher’’ adaptive zone, and there may also be a tendency for overlap into the A3–A4 area in terminal members of ‘‘lower’’ grade. At a cursory glance then, it may not be clear whether a given taxon belongs to the beginning of one lineage or to the end of another. The evolutionary rate of lineage determined by a dichotomy in adaptive corridors

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FIGURE 123 Polygradism as a result of iterated zonal separation with respect to two paralleling lineages. A ⫽ anagenetic sequence linked to the zonal transition itself, B ⫽ a second anagenetic sequence having no functional links with the zonal transition. A and B are both evolving in parallel. There may then be differential survivorship in the two lineages (see Fig. 124).

may thus be responsible for the existence of confusing patterns of relationships among function integral sequences. Most signiﬁcantly, this factor may often override the criterion of modularity in function integral sequence analysis, in that some apparently autonomous function integrals may be affected to a similar degree by virtue of conformity in evolutionary rate alone, whether they are closely functionally correlated or not. The probability of apparent concordance appearing in the context of function integral sequence analysis may thus be profoundly affected by differential evolutionary rates interacting with a complex of euryphyletic anagenetic sequences, the result being that phylogeny becomes some (unknown) function of concordance, so that cladistic methodology then has to rely on criteria of parsimony that are unrealistic in evolutionary terms. Thus, while anagenetic sequences clearly do not of course evolve exactly synchronously when in polyphyletic mode, polygradism can nevertheless create a broad character correlation akin to positive rank correlation, owing to the effect of the adaptive corridors scenario: In ditrysian Lepidoptera, zonal transition is observed with traits that are separately linked to the exophage and endophage adaptive niche of the larval stage (particularly vestiture, habits, and proleg structure), but many other traits that are not functionally linked (wing venation, movements of thoracic sutures, pupal obtection, etc.) show strong taxonomic correlation with the same traits, most probably as a result of differentials in evolutionary rate and in absolute size (see Brock, 1971, 1990a, in prep.). This appears in turn to be due to the adaptive corridor effect arising from the macroniche divergence in question. Simpson (1953), studying the fossil horse genera Merychippus and Hypohippus, showed that most differences arose through differential

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rates of change, from which observation he deduced that evolutionary rate may change markedly at any time, and that the rates of two or more characters may change independently. Also, and most signiﬁcantly of all, two lineages may become differentiated by rates of evolution alone. The most problematic gradistic traits are thus those components of an anagenetic sequence following a course of parallel evolution, the taxonomic distribution of which is often partially, and sometimes predominantly, a function of evolutionary rate rather than of phyletic afﬁnity. The existence of ‘‘grades’’ in higher level classiﬁcatory systems may in fact also provide good evidence of evolutionary rate in action, particularly in that scenario in which a major group appears to resolve into brady- and tachytelic subgroups on the basis of traits which, on closer analysis, present clear evidence of widespread polyphyletic activity. Evolutionary grade at the lineage level may then derive from the adaptive corridor scenario, thus reﬂecting those causal factors underlying the observation that members of advanced grade clades will manifest tachytelic, and of primitive grade, bradytelic evolutionary rate. A primary adaptive shift may thus act to determine evolutionary rate of lineage. Furthermore, although evolutionary rate will be speciﬁc to each function integral of structure, there is nevertheless a tendency for a leading effect pivotal adaptive shift to affect uniform evolutionary rate over other function integrals, and especially over those which hold a generalized input to ﬁtness (mechanical efﬁciency, etc.). This is polygradistic evolution, where a Renschian node is resolved into several brady- and tachytelic lineages, some lineages sharing a suite of tachytelic or bradytelic traits, not due to community of descent, but to nature of adaptive corridor. This scenario has been confused with the concept of mosaic evolution (see below). The greatest problem with ‘‘evolutionary parsimony’’ thus lies with the inﬂuence of zonal separation, namely, where there are many euryphyletic trends and where an adaptive corridor differential is also implicit. This situation certainly requires both functional analysis and concordance testing, rather than blind application of cladistic methodology to n characters of no known interrelationship or evolutionary status. Mosaic Evolution The typologically based term ‘‘mosaic evolution’’ has been used in the past to describe such scenarios as the mixture of primitive and advanced traits found in Archaeopteryx and in early whales (cf. Raff, 1996). The functional basis for all so-called mosaicism probably lies with the structure integral concept (see Chapter 17), namely, in terms of selectional as against purely developmental domains of modularity. Alongside this concept lies the all-important inﬂuence of differential evolutionary rates affecting different function integrals of phenotype structure, as the main causal factor behind polygradism in living lineage fragments. In that situation where the occlusion zone is a narrow one, one important source of evidence for possible polygradism clearly comes from a characteristic distribution of gradistic data. To look more deeply into this relationship, it is necessary to devise a system through which various possible evolutionary scenarios can be clearly depicted.

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Frequencies of taxa bearing each state in an anagenetic sequence can usefully be designated faj, where f ⫽ frequency and aj ⫽ the jth term of a, a given anagenetic sequence. There will tend to be an ascending numerical trend in surviving sequence term frequencies, from primitive to advanced (assuming that functional analysis correctly identiﬁes a progressive adaptational paradigm sequence of that kind, and that the evolutionary component in the extinction heterogeny increases as a function, both of time and of ﬁtness): fa1 ⬍ fa2 ⬍ fa3 ⬍ fa4. . . Term frequencies will therefore tend to 0 for the roots of such lineages, where high levels of selectional extinction exist in the phyletic occlusion zone. Evidence for probable polygradism comes from a ‘‘pyramid-inverse distribution’’ of gradistic data as expressed in the frequency sequence described above: true members of bradytelic grade should show higher term frequencies for primitive states and lower for advanced states (the latter for a few ‘‘terminal’’ taxa only), while members of tachytelic lineages should show high frequencies for advanced states and lower for primitive (the latter for ‘‘residual traits of basal taxa only’’). The polygradism scenario is reﬂected in the diagram shown in Fig. 124, according to the form of the ‘‘frequency pyramids’’:

FIGURE 124 Frequency pyramids for a sequence of anagenetic states undergoing parallelism in a bradytele and tachytele lineage pair (frequency on vertical axis).

Bradytele: fa1 ⬎ fa2 ⬎ fa3 Tachytele: fa1 ⬍ fa2 ⬍ fa3 (. . . ⬍ fai) In other words, there might be expected to be a few residual primitives in the tachytelic grade, and a few terminal advanced forms in the bradytelic grade: This is exactly the position with the Microditrysia and Macroditrysia divisions of Lepidoptera. A few of the micro lineages (Pyraloidea, Cossoidea, Zygaenoidea, Castnioidea) clearly overlap with the macroditrysian grade with regard to certain traits, and a small element

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of ‘‘macros’’ likewise retain a few micro traits (Endromididae, Mimallonidae, Lasiocampidae, Epiplemidae, Callidulidae, Hesperiidae). The above scheme may then reﬂect polygradism, where the advanced grade is truly polyphyletic in terms of more than one primitive grade ancestor, or else it could in fact be derived from simple ‘‘bigradism’’ (zonal separation). In either case, we again meet the problem of deciding which grade certain transitional taxa belong to. Mosaic evolution is simply an early interpretation of polygradism in terms of hopefully monophyletic solutions. This scenario can be illuminated using the earlier adaptive cascade diagram, suitably modiﬁed to include the inﬂuence of a middle range of values corresponding to generalized adaptation: Adaptive Corridor

Adaptive response Evolutionary rate

Benign

Eurytopic

Hostile

Specialized High

Generalized Middle

Specialized Low

The result is that relatively generalized forms in a polyphyletic assemblage will tend to express a mixture of primitive and advanced states, which if taken to be monophylies, will lead to highly conﬂicting patterns of relationship with both bradytelic and tachytelic lineages. This may lead, in turn, to total confusion between ‘‘characters polyphyletic’’ and ‘‘higher groups themselves polyphyletic’’: Even with a monophyletic Macroditrysia (see above), the traits that have been used to deﬁne that category in taxonomic terms would nevertheless be polyphyletic, and the scheme would merely change from polygradism to bigradism of the mosaic kind. This has already been mentioned in connection with larval traits, and the same is also true for pupal obtection. Recent attempts to reestablish an Obtectomera ‘‘clade’’ in Ditrysia (Minet, 1992; see also Kristensen, 1999) clearly ignore wider implications of the fact that pupal obtection has obviously evolved independently in female psychid moths, as in the yponomeutoid–gelechioid lineage also. Larval proleg and pupal obtection classiﬁcations are also incongruent with one another (as one would expect if either or both were polyphyletic!). The reemergence of these modes of classiﬁcation in the guise of cladism really amounts to nothing more than a juggling of ‘‘rule of thumb’’ classiﬁcation. A particularly clear example of the scenario discussed above is found with the problem of monophyly of the Arthropoda. Fryer (1998), following the Manton school of thought, claims that ‘‘arthropodization’’ occurred more than once, on the basis of evidence that the compound eyes of sabellid polychaetes show remarkable convergence to those of Arthropods, and also owing to the fact that the jointed limb probably evolved elsewhere as well. However, the consensus opinion on this question now seems to be that, while very many of the diagnostic traits of Arthropoda did in fact arise in a polyphyletic manner, the arthropodan lineage is itself nevertheless genuinely monophyletic. Cladistic

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parsimony probably does resolve the latter problem, but it has not yet done so for the ditrysian Lepidoptera. In the present work, the term mosaic evolution is reserved for examples where a demonstrably monophyletic group is deﬁned on the basis of traits that are themselves predominantly of polyphyletic origin. This probably applies to the Arthropoda example (and it could also for the macroditrysian Lepidoptera, given more conﬁrmatory data than are at present available!). Vertical versus Horizontal Interpretations of Polygradism By far the greatest problem facing phylogeny reconstruction lies in distinguishing bigradism from polygradism, particularly in the context of possible mosaic evolution, as deﬁned above. Parsimony rules will often ﬁnd one or a few solutions to such problems; however, such answers will most probably gravitate toward a bigradism model, even where a polygradistic solution might have been equally (or even more) acceptable in evolutionary terms. The inﬂuence of polygradism thus creates a horizontal (stressing within-grade relationships) versus vertical (stressing between-grades relationships) dilemma for phylogeny reconstruction, which is most overt with mosaic evolution, in that gradistic clusters could be interpreted either as polyphylies or as pseudogrades, depending on slight differences in our concept of evolutionary parsimony or of functional interpretation: Looking ‘‘horizontally’’ at butterﬂy origins, it is easy to ﬁnd traits in common with other advanced Ditrysia. However, most of these can be readily diagnosed as euryphyletic anagenetic or vestigiation sequences. It is much more difﬁcult to assess the validity of apparent ‘‘vertical’’ relationships between butterﬂies and certain advanced micro moths which display a few apparently stenophyletic traits in common with the butterﬂies. Solutions to this (and related) problems on the basis of all-characters analysis can only be based on subjective opinion at the present time. The vertical–horizontal problem is clearly the focus of the clash between cladistic and gradistic approaches to phylogeny reconstruction. However, this is in every way an expected outcome of the evolutionary behavior of complex adaptive systems. In gradistic systems generally, tachytelic groups will probably tend to be deﬁned by absolute diagnostic traits, while bradytelic ones will tend more to be characterized by polythetically distributed relative diagnostic traits, owing to the likelihood of greater selection pressure for structural change in tachyteles and greater evolutionary rate linked to realization of adaptive potential. One other solution that has been proposed with regard to the polygradism dilemma is that of relationships based on the principle that parallelism is likely to be more frequent between closely than distantly related lineages. This view was reﬂected in the writings of Simpson (1953, etc.), and it was discussed by Brock (1971; also Crampton, 1929, and Tuomikoski, 1967). As with the usual ‘‘n solutions to parsimony’’ problem, however, no deﬁnitive solutions are likely to be reached on this line of reasoning (as in fact stated by Crowson, 1970).

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Gradistic Distance Information for determination of vertical ancestor–descendent relationships may perhaps be sought on the basis of gradistic distance, the topological distance between taxa on the basis of purely gradistic data, and this may form a signiﬁcant bias with respect to some parsimony solutions. To assess the value of gradistic distance between suspected ancestor and descendant lineages, it is clearly ﬁrst of all necessary to assess what this term really means. We may only scale for degree of difference on gradistic differentials on the basis of simple quantitative topological relationships lacking large extant gaps, since it is clearly not possible to scale for qualitative traits, owing to there being many topological solutions to complex transformations (the most parsimonious of which may not be the most probable solution in realization of adaptive potential). Gradistic distance can be measured fairly objectively in terms of the number of ‘‘grade steps’’ between phyletic progenitor and descendant. A gradistic map can then be drawn up to illustrate the gradistic distance between lineages having a postulated ancestor–descendant relationship. However, this may or may not have any direct bearing on genetic distance, since distance in terms of developmental topology and underlying genotypic change will usually be unknown: Apart from the close phenetic relationship of different superfamily lineages of Macroditrysia to one another, there are several superfamily groups in Microditrysia which have a relatively short gradistic distance to Macroditrysia (Cossoidea, Castnioidea, Pyraliformia, Zygaeniformia). Evolutionary parsimony could, however, be taken to be either vertical or horizontal in resolving this phylogeny. Here again, solutions to such problems do not consist of a single ultimate answer, but constitute a number of possibly viable hypotheses, and the question of gradistic distance indicates that both horizontal and vertical solutions may often have to be drawn from cladistic analysis. Again, the validity of any such analysis depends on unknown effects caused by differential evolutionary rates. Polygradism and Genetic Analysis Genetic analysis may afford the best means of solving the ‘‘horizontal versus vertical’’ relationships problem in parsimony analysis of function integral sequence data. The main concern here is, of course, whether or not genetic data from clades situated at the apices and bases of polygradistic pyramids can carry evidence of divergence that is not also obscured by the combined effects of parallelism and evolutionary rate of lineage. This, in turn, depends on the answers to questions concerning the relationship between change in functional genes and the morphogenetic parameters they control, and in interpretation of random mutation in redundant loci. The answer to these questions may lie in the relative inﬂuence of occlusive forces in the history of a lineage, as against those creating irretrievable gaps such as those arising from the effect of adaptational dysgenesis (see Chapter 20). To what extent can we expect genetic and developmental data (e.g., from analysis of atavism) to help close these gaps? At the present time, the answer to this perplexing question can only be based on speculation.

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Following our earlier analysis of genetic parallelism (pp. 563–564), it must be argued that although at least some parallelism in structural traits may well be penetrated through genetic analysis, at other times homologous genetic mutations will probably lie behind certain categories of structural parallelism. Rather worrying from this point of view is the likelihood that purely paramorphic mutations which extrapolate some neomorphic change that was already present at the root of a phyletic lineage seem intrinsically likely (a) to lie behind euryphyletic structural trends and (b) to involve homologous genetic changes: De Salle and Carew (1992) found that many of the most spectacular modiﬁcations of Hawaiian Drosophila species resemble well-known mutations in D. melanogaster to some extent. Here, we are probably witnessing direct evidence of the maxim that the relaxation of selectional regimes on remote oceanic islands permits the evolution of a wider expression of certain mutations than is normally possible. From the standpoint of the present discussion, it is also signiﬁcant that adaptive potential seems here to lie adjacent to a preexisting adaptive capacity held by certain recurrent mutations. Remarkable divergences may clearly occur in the context of species diversiﬁcation in such instances. However, this might not be the case where simple allometric or duplicational modes of morphogenetic change are involved (as seems often to be the case with simpler paramorphic modes of change of the kind frequently involved in examples of parallel evolution!). Evidence of genetic conservation in higher translation level regulatory genes must also give cause for concern for the genetic resolution of parallelism. If false structural homologs are also genetic parallelisms, then taxon differentials that are due to evolutionary rate are unlikely to be resolved. In this instance, it may be that mutations in redundant DNA might give good data; however, as has already been suggested, if a basal adaptive radiation has occurred (as seems in fact to be the case with the superfamily lineages of ditrysian Lepidoptera), then time since divergence is unlikely to offer much help: The best known example of ‘‘suspect polygradism’’ is probably that concerning ‘‘arthropodization.’’ Despite the fact that the Arthropoda now seems proven to be of monophyletic origin, the interrelationships of the different arthropodan classes are still confused by conﬂicting evidence, not only from morphological data, but also from molecular analyses (see Raff, 1996, for an extended discussion). Recent work on ribosomal RNA in Lepidoptera (Weller et al., 1992) uncovers both horizontal and vertical patterns of relationships, and some of the genetic evidence thus seems to be pointing to similar mosaic patterns of relationships as those observed in morphological analyses. These ﬁndings are, in fact, no more conﬁrmatory of a monophyletic than of a polyphyletic origin for Macroditrysia. Despite the fact that ribosomal RNA was chosen on the grounds that this class of data is thought to be particularly well suited for lineages in which morphological characters provide little resolution, the authors concluded that both anatomical and genetical methods experienced difﬁculty in resolving multiple, short, ancient divergences of this kind.

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Sometimes major decisions can be made where the function of an active gene complex is more widely known, as (for example) in evidence for the ‘‘inversion’’ theory of chordate origins. However, the question as to whether such revelations should always be transmitted as modiﬁcations to gradistic Linnean classiﬁcations is an entirely different matter!

Pitfalls in the Methodology of Cladistics The failure of several supposed cladistic criteria is due to their origins in a philosophy that has generally been more or less divorced from evolutionary principles, and chief among these are a number of weak hypotheses proposed by Hennig (1950, 1966) that received wide acceptance during the 1960s and 1970s (many of which have already been at least partially superseded by modiﬁed versions). Several of the early premises of phylogenetic analysis can now be seen to be based on fallacies concerning the nature of organic evolution. From the foregoing analysis, it is possible to arrive at a list of conceptual criteria that have been (or should be) critically reassessed in the context of any serious evolutionary analysis. Synapomorphy and Functional Analysis The Hennigian deﬁnition of monophyly was, without doubt, by far the most signiﬁcant development in the ﬁeld of phylogeny reconstruction in the ﬁrst half of the twentieth century. However, the methodology for determination of (true) monophyly is a much more complex and difﬁcult issue than originally envisaged by Hennig. The concepts of apomorphy and plesiomorphy are clearly important for amphigenetic diversity patterns. However, they have less value for the analysis of anagenesis and with macroevolution in general. The term synapomorphy (as a synonym of ‘‘shared-derived traits’’) as a measure of phyletic afﬁnity is demonstrably a heterogeny, consisting of so-called syn-functional, syngradistic, syn-vestigiational, and syn-phyletic traits. a. Syn-Functional Traits Many apparently positive character correlations will be suites of structural traits belonging to a single function integral holding a tightly constrained biophysical paradigm which invokes a polyphyletic evolutionary pathway. Compatibility analysis (as with character correlation in general) is not a relevant solution here, unless functional autonomy is also diagnosed for traits entering into the analysis. Probability levels from cladistic analysis will thus tend frequently to confuse functional correlation linked to parallelism with community of form based on common phyletic origin: Many lepidopteran traits associated with diurnal habit are exemplars of this problem, including not only butterﬂy-like color patterns and wing shape, but also resting position and probably even certain anatomical traits such as the migration of the parepisternal suture on the mesothorax (see Brock, 1990a).

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b. Syn-Gradistic Traits Very many endocladic adaptive trends involve relatively trivial structural transformations of a kind manifesting euryphyletic distribution. Where differentials in evolutionary rate occur owing to a divergence in adaptive corridors, it may appear that strong character correlations exist between such traits, even where functional autonomy is evident. Similarly, when some substructural adaptive shift forms the pivotal one for a higher group and also confers bradytely on that lineage, the result may be a retention of ‘‘symplesiomorphies’’ that are not necessarily evidence of paraphyly (in the same way, independent tachytelic lineages will also tend to accumulate apparent synapomorphies in euryphyletic trends via allotelism, for which an apparently parsimonious solution may have little bearing on real phyletic relationships): Very many ditrysian larval traits are obviously associated with endophagy, and this clearly links to a narrow adaptive corridor expressing low evolutionary rate of lineage (see Chapter 18). As already stated, various other euryphyletic traits of Lepidoptera (including vestigiational trends) have been used quite uncritically as synapomorphies or shared-derived traits by a number of authors. c. Syn-Vestigiational Traits Traits that are seen to be subject to functional redundancy should be treated with great caution in cladistic analysis, since they will often take a similar degenerative path, leading to secondary loss in a manner differing from lineage to lineage, mainly owing to the inﬂuence of evolutionary rate. This clearly must not be interpreted as character correlation or synapomorphy under any deﬁnition of parsimony: Many reductions in the complexity of wing venation in Lepidoptera fall into this category, as do larval setae reductions and some pupal traits associated with obtection, yet these and other vestigiation trends are regularly used as synapomorphies equivalent to anagenetic change by many so-called phylogenetic systematists following the Hennig school of thought. d. Syn-Phyletic Traits Only when the above criteria have been negated do we ﬁnd true synapomorphies which could be taken as good evidence for phylogenetic afﬁnity. These will lie in functionally autonomous sets of anagenetic sequences of a kind intrinsically unlikely to express parallelism, in that their biophysical paradigms will not be tightly constrained in nature. The greatest problem with the Hennig method is simply that, to be fully valid, the operational hierarchy between different categories of cladistic data should ideally be of the form monophyly Ⰷ stenophyly Ⰷ euryphyly, whereas in actual practice, it generally proves to be quite the opposite! The corollary of this is that, for certain higher systematic categories, the particular mosaic of character states typifying a taxon may tend to be a function of evolutionary rate of lineage plus steepness of selection gradient in the adaptive isthmus. Intrinsic evolutionary rate of lineage is in turn a function of adaptive zone, as

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determined by the lineage niche. In this situation, ‘‘easy’’ phylogeny generally occurs when there is only a fragmentary extant representation of a higher group lineage (as with the monotrysian versus ditrysian Lepidoptera example already mentioned). All of the foregoing ‘‘problems’’ appear to be natural corollaries of (a) the rarity of viable neomorphic mutations operating at higher translation levels (i.e., those affecting morphogenetic traits) and (b) the high probability that similar paramorphic changes will tend to evolve in different lineages, as a function of the tight constrainment expressed by the great majority of adaptive paradigms for structure. Homoplasy: Unwanted Data or Valuable Information? Homoplasy is considered to constitute the ‘‘unwanted data’’ of cladistics, in its purely classiﬁcatory role. However, in evolutionary terms, homoplasy clearly constitutes a heterogeny (parallel evolution, functional redundancy and vestigiation, reversal as a function of amphigenesis). Rather more worrying is the fact that these same factors clearly contain much vital information on fundamental evolutionary phenomena (the effect of factors linked to evolutionary rate of lineage, and so on). Consequently, the term homoplasy has no useful meaning in any biological context. Indeed, the waste products of cladistic analysis could in fact form the basis for more realistic phylogenetic investigations that are entirely divorced from the goal of classiﬁcation. Most signiﬁcantly of all, homoplasy also proves the reality of the inﬂuence of attractors in the similar adaptive zones of unrelated lineages, through the phenomenon of parallelism. In this view, no element in homoplasy constitutes ‘‘useless information’’ (other than in the context of classiﬁcation). Cladistic versus Evolutionary Parsimony Cladistic parsimony has been used to prop up weaknesses inherent in Hennig’s original conception of phylogeny reconstruction. However, it should by now be clear that topological and evolutionary parsimony can often be two entirely different things. Parallelism and reversal are expected behaviors in the evolution of adaptive systems, and evolutionary rates have a crucial role to play in the dynamic structure of evolutionary topology. Evolutionary parsimony is very frequently manifested in gradism, parallelism, and reversal, rather than in monophyly via synapomorphy. Farris (1994) defends the concept of parsimony, which he claims (using a confused set of double negative axioms) does not presume ‘‘that evolution is not irreversible, rates of evolution are not constant, that all characters do not evolve according to identical stochastic processes, that one conclusion of homoplasy does not imply another—only that these possibilities are not established’’. The problem with this view is that the last mentioned of the foregoing presumptions constitutes a fundamental weakness, in view of the vast amount of evidence for multiple parallelism (in addition, several other criteria can clearly be taken as established, on an a priori basis!): Raup (1991) gave a prime exemplar of inappropriate application of statistical methodology that could well apply to some overzealous claims concerning cladistic parsimony, namely, that good statistical

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evidence exists to support the hypothesis that people are attracted to cities with names starting with letters in the second half of the alphabet. In cladistic analysis, a similar skepticism to that engendered by this example would go a long way to improving the situation. The study of evolution (as against ‘‘phylogeny by parsimony’’) should not be misled by apparently ‘‘sophisticated’’ mathematical methodologies of the kind which led to the largely dead-end discipline of phenetics in the 1960s and 1970s! Above all else, what many exponents of cladistic analysis seem unable to accept is the fact that parsimony solutions do not in fact arrive at a single ‘correct’ phylogeny but at a choice between several approximately equally viable interpretations. Even such a well studied area as the origins of the terrestrial vertebrates is not without disagreement: Lewin (1996) pointed out that although mitochondrial DNA favors a lungﬁsh–tetrapod lineage, support is not overwhelmingly strong for this, and Long (1995) is equally certain that the coelacanth origin theory is the correct interpretation. Wake (1996) states that in molecular systematics, it is not unusual to encounter hundreds of equally parsimonious trees for a large data set, and Sanderson and Donohughe (1989) came to the same conclusion with reference to morphological data! Indirect Ancestors, Evolution, and Classiﬁcation The ‘‘indirect ancestors’’ principle is not in fact a criterion for phylogeny reconstruction as such, but for classiﬁcation of extant to the exclusion of extinct taxa (namely, following the assumption that successful cladistic analysis can actually always be attained!). In fact, no theoretical foundation exists for this criterion, other than an extrapolation from the frequently observed state of amphiphyly manifested in Renschian cladogenesis. The latter scenario has in fact been used by Hennig to introduce dogma into the clade–taxon relationship. Truly cladistic relationships between extant higher groups certainly do often tend to be of the indirect ancestor kind. However, the true phylogeny of all extant organisms can only have been via direct ancestry, and criteria based on indirect as against direct ancestry cannot logically be used as a basis for converting phylogenetic hypotheses into a classiﬁcatory hierarchy on the grounds that ‘‘direct ancestry is impossible’’: The class Aves is a frequently cited example of a widely recognized ‘‘cladistically incorrect’’ higher group directly derived from an extant ancestor, the paraphyletic group Reptilia. However, all higher groups must be directly derived from some extinct ancestor (the only difference being that most ancestors have not been discovered in the fossil record!). Recognition of the class Aves in fact reﬂects a zonal separation. Similarly, the problem of paraphyly only emerges owing to the fact that the reptilian grade of organization lay at the root of a signiﬁcant zonal transition (a fact that is also true with respect to the Mammalia). The ‘‘cladistically correct’’ placing of Homo sapiens in the same taxo-

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nomic group as the coelacanth has been mentioned as an example of the same kind of reasoning. No one doubts that the trajectories of phyletic lineages cut across gradistic criteria of classiﬁcation, but what has been lost sight of is the simple fact that classiﬁcation itself can only be a utilitarian concept built around the extant remnants of most lineages, the ‘‘roots’’ of which have been greatly transformed by zonal separation, as by the totally unrelated inﬂuences of stochastic extinction. The causality for indirect ancestry lies with the dual resolution architecture of Renschian cladogenesis and with the subsequent effect of phyletic occlusion in particular, not with any law underlying how taxonomic rank should be bestowed. The adaptive zone concept in fact entirely precludes the need for cladism in the construction of classiﬁcation from phylogenetic information and is an acceptable biological rationale for understanding the causality behind the origins of higher groups, both mono- and paraphyletic. A descendant clade may thus be clearly separated from its ancestral lineage by virtue of one or more occlusion zones (as Aves from Reptilia, or Hominidae from coelacanth ﬁshes!) quite irrespective of the criterion of indirect ancestry. Identiﬁcation of the true phyletic trajectory for a set of taxa neither reﬂects nor explains the evolutionary mechanisms underlying the origin of a higher group, which may often be better mirrored in a gradistic classiﬁcation (as in that scheme which separates Aves and recognizes Reptilia, or which views Hominidae as an entity other than a subgroup of the coelacanth dynasty). Causality of formation of a discrete adaptive zone lies in many factors, including the essential establishment of a new adaptational paradigm, which can only emerge after very many anagenetic changes have occurred as part of a larger, compound set of evolutionary events. Again, a new higher group has not been deﬁned until some structural discontinuity also appears, and the latter requires deeper understanding of the occlusion zone assemblage, as of a larger and more complex heterogeny of extinction factors (see Chapter 20). The Sister Group Concept There are really two possible kinds of ‘‘sister groups’’ in relation to any given lineage: (1) the nearest known higher group (extinct or otherwise) in terms of a Renschian cladogenetic event and (2) the nearest extant higher group lineage. In practice, (2) is the customary usage by neontologists, whereas (1) is that favored by paleontologists. These are very often two entirely different things, especially in higher groups with only a fragmentary extant representation: This situation appertains to the concept of sharks as the sister group of Osteichthyes, in that extinct forms completely confuse the issue. The sister group concept can sometimes be seen as an attempt to graft features of Renschian cladogenetic branching onto all other subsequent evolutionary events, but it can have no real relevance other than for those circumstances surrounding the initial divergence of two or more higher group lineages. This can be demonstrated simply by removing randomly chosen sections of a multiple branching lineage, whereby any chosen pair of sister groups can have

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any real phyletic interrelationship relative to the true lineage, irrespective of the degree to which extinction processes have acted: In the lower monotrysian Lepidoptera, one sister group pair replaced another, as more extant families were discovered. What happened to those pairs of taxa previously termed sister groups? And will discovery of further new taxa show that the present ‘‘true sister groups’’ are also false? A more reasonable conclusion might be that the sister group concept is itself a semantic illusion (unless a complete fossil record of all descendant lineages representing a series of Renschian cladogenetic events exists). The only really clear exception to this objection should be that of extant sibling species (where the issue of complex phylogeny is perhaps less likely to arise in practice). Another reason for rejection of the sister group concept lies in tri- or multipartite Renschian cladogenesis (adaptive radiation) (see Chapter 17), the actual (bipartite) speciational events behind which may be totally obscured by postspeciational divergence of the mosaic kind. Typology in Cladistics Certain tenets of cladistic analysis which relate to the speciation process have been widely dismissed by evolutionary biologists, as dogma that has been designed to support hypotheses which attempt to merge typological taxonomic concepts with phylogeny: Nixon and Wheeler (1992) have expounded several doctrines of this kind: ‘‘Extinction of plesiomorph character states results in speciation. . . . From a cladistic perspective, these changes are irreversible. . . . ‘‘Apparent anagenesis can be an artefact of extinction, in that the species bearing ‘transitional’ character states . . . have disappeared through extinction.’’ Also, ‘‘methodologically, character transformations occur only at the time of species genesis, and only arbitrary or process based deﬁnitions of species recognise anagenetic change (involving ﬁxation) within species,’’ and, ‘‘New perspective emerging from ascension of phylogenetic systematics is that evolutionary processes that occur within a single species are microevolution—while those that occur at slower rates such that their effects are manifested in among-species patterns constitute macroevolution.’’ With reference to the above statements, it is only necessary to say that cladistic methodology must not be used to modify evolutionary theory in such a way as to justify taxonomic procedures which in reality may well have no relevance whatsoever to the mechanisms of evolutionary change. Conversely, we should apply the known tenets of evolutionary theory to seriously question the validity of many of the accepted doctrines of cladistics. Much cladistic work may in fact be deﬁning a hybrid construct between cladistic and gradistic schemes, which we may choose perhaps to refer to as ‘‘gladistic.’’ A glade would seem to constitute a taxon that has the following properties:

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• A glade is deemed monophyletic in terms of purely topological parsimony, but conceals crucial questions concerning discarded homoplasy. • A glade has nearly equivalent status to other units that have been removed from the analysis on the basis of a largely subjective a posteriori tampering with the raw data, perhaps in the guise of socalled character weighting. • Little or no functional analysis has been carried out in order to assess noncladistic inﬂuences on character correlation or to derive objective criteria for character weighting. • The glade is either highly impractical and unstable from the viewpoint of Linnean classiﬁcation, or else it simply constitutes a rewriting of a purely typological classiﬁcation thinly disguised as cladistic analysis. In summary, it might be said that some cladists are now in the process of rediscovering phenetics when they use parsimony or manufactured synapomorphies to resolve the problem of euryphyletic traits ordered by differential evolutionary rates!

The Relationship between Cladistics and Evolution What conclusions have been drawn from evolutionary theory as this affects the principles of phylogeny reconstruction? In general, we can conclude the following: 1. If n taxonomically correlated characters are also functionally correlated, then their taxonomic distribution will tend to be a function of degrees of freedom in the structural attractor, in terms of the extent to which the latter acts to invoke parallel evolution. Actual experience conﬁrms that parallel evolution in fact forms a highly signiﬁcant input to a majority of diversity patterns. 2. If n taxonomically correlated characters are not functionally correlated, then their taxonomic distribution may nevertheless frequently be partly due to evolutionary rate of lineage differentials arising from divergence with respect to the adaptive corridor. 3. Evolutionary reversals are abundant for much amphigenetic evolution and may often predominate at the species level. 4. Topological parsimony and evolutionary parsimony are not one and the same thing. In actual reality, character weighting often has to be applied on the basis of intuitive estimation of degrees of freedom in the structural attractor. From this, it may be possible to arrive at approximate estimates of taxon monophyly, but it may be that much intertaxon phylogeny at certain levels in the hierarchy remains some unknown function of topological parsimony. In general, however, character correlation is more likely to be derived from functional interrelationships, than to constitute a direct indicator of phylogenetic relationships. We have ultimately to ask, what is more important in cladistic analysis, classiﬁcation, or feedback concerning fundamental evolutionary principles? Overem-

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phasis on the former has led to total confusion concerning the real theoretical value of interpretative work on comparative morphology and genetics. Given that cladistic analysis is often seen to have no practical function whatsoever in taxonomy, its objectives should move away from classiﬁcation and concentrate on evolutionary analysis. Why, indeed, do we want to reconstruct phylogeny: to investigate the evolutionary process, or merely to classify organisms in a manner that is actually much less comprehensible than the classical method? Phylogeny is seen here as having the status of hypothesis rather than theory, and more than a single hypothesis may be reached on the basis of one set of data. There may well be topological parsimony solutions to such problems, but there is no reason to suppose that these solutions carry any degree of objectivity in terms of expressing true lineage relationships. There will thus be an ‘‘unknown fraction,’’ especially in that a number of major problems may arise with regard to application of functional analysis in practice. Concordance correlation may sometimes provide good evidence of unexpected functional correlation between two or more traits which appear to have mutual interdependence in a functional sense. However, lack of taxonomic correlation cannot conversely be taken as evidence of lack of functional interdependence. All adaptationally linked traits must in reality evolve in sequence; however, the time lag between adaptive shift and phyletic node may be either short or long. Hence, where empirical evidence of functional autonomy is lacking, taxonomic data cannot be used to conﬁrm apparent noncorrelation. Therefore, although random correlation between traits can indeed imply that there is no functional correlation between them (Crowson, 1970), it can also mean that some functional link is obscured by the time gap between function and adaptive response, and this means that empirical demonstration of function must ultimately take precedence over interpretation through taxonomic correlation. Relationships of the sequiadaptive kind may indeed become immediately apparent through function integral sequence analysis, either obtaining through implicit sequiadaptive functional correlation or, conversely, raising doubts on a hypothetical functional interpretation that has already been made. Functional autonomy itself may be dissipated within the architecture of anatomy. Parametric niche-correlated traits should certainly display functional autonomy, but sub- and hypoparametric niche related traits need not necessarily do so (a rationale for such an interpretation would be that the latter probably contain several parametric niche functions, and will thus tend to belong to that suite of function traits expressing an allotelic evolutionary rate of lineage). Only functions with no external adaptation interface remain overtly autonomous with respect to those with an external interface. The main problem with use of function integral sequence analysis to sidestep the false compatibility issue is therefore that unknown functional correlations may exist where they are thought not to, this becoming a major problem if complementary biophysical paradigms are highly constrained: This could be a problem with apparently paraphyletic taxa which are, in reality, true monophyletic lineages that have evolved little in the way of adaptive response to a causal adaptive shift. Paramorphic (and simple neomorphic) differentials (Chapter 16) are more likely to be polyphyletic than almost any other category of structural change,

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and nonuniformity of trend structure may be apparent when the interplay between absolute size and paradigm structure is not understood, so that ‘‘false divergence’’ may then enter the equations of cladistic analysis. Phyletic reversibility is also a predictable factor with certain coallometric factors, more than for almost any other category of dynamic data. Unfortunately, the allometry problem displays a facet of functional correlation that may not be apparent, since the complex interrelationship between allometry and the biophysical paradigm is but little known with respect to most complex superstructural traits. Above all else, it should be realized that monogradistic solutions to the above problems will tend to form the basis of utilitarian classiﬁcation. It is interesting at this point to recall the words of D’Arcy Thompson: ‘‘To look upon the hereditary or evolutionary factor as the guiding principle [in morphology] is to give that science a one sided and fallacious simplicity.’’ This point had been made previously by Howes, and indeed it might be ventured that this revelation has a recurrent cycle in the development of taxonomic thought in biological circles! To this, we should reiterate Simpson’s comments (see preface) concerning the harm done to evolutionary theory when one part of the whole is artiﬁcially isolated and given false priority! Phylogenetic systematists should also seriously consider the criticism of Maynard Smith (1983) who, despite such claims as that of Eldredge that ‘‘cladistics has done much to take the guessing, the ‘just so story’ scenario out of studies of adaptation,’’ states that there is no relevance whatsoever in the supposed link between cladistic taxonomy and Darwinism. It is only with the hard Hennigian line that we can exclude functional analysis (and thus, biology itself ) from the study of evolution. However, given a severely critical reexamination of the criteria of phylogenetic reconstruction, there is no reason why Eldredge’s claim should not contain some measure of truth. Nevertheless, the substitution of ‘hard’ cladistic dogma for sound evolutionary analysis can never be acceptable. Bland statements such as ‘‘birds are living dinosaurs’’ (why not ‘‘mammals are living therapsids’’?) do nothing to resolve fundamental problems of functional morphology (for example, why is the reductional transformation in forelimb digits different in birds and dinosaurs?), nor do they reﬂect the considerable degree of zonal separation between living members of cladistically related lineages. Where ‘‘hundreds of characters’’ seem to support a phylogeny that also contains problematic contradictions, we should also be concerned with the proportion of these data which refer to traits that are known to undergo functionally linked programs of parallel evolution in other lineages, as well as with the question as to how many characters are really only vestigiation or even amphigenetic traits. Perhaps the most realistic assessment of cladistic analysis is to conclude that its contributions to classiﬁcation and taxonomy too often converge on the negative, but also to accept that much valuable data can be gained from phylogenetic studies in which a single tree leading to a new Linnean classiﬁcation is not the ﬁnal goal. In that connection, a great many valuable insights may be gained for a whole range of topics in general biology (many of which are discussed in Harvey et al., 1996).

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The general conclusion that is now drawn from the preceding discussion is that some taxa are bounded by selectional gradients creating a deterministic input in zonal separation, while others are generated by adaptational extinction factors and other inﬂuences commanding a signiﬁcant stochastic input to diversity pattern. That is why it is not possible to have a universal system of ‘‘natural’’ classiﬁcation, whether cladistic or gradistic. Secondary to that, it should be said that the predictable frequency of parallel evolution, convergence, and evolutionary reversal in the evolution of adaptive systems clearly advocates extreme skepticism in the face of claims for (perfect) phylogeny reconstruction, in the form of simple answers to extremely complex questions. In the same way, one must obviously criticize the damage done to the fundamentally utilitarian Linnean nomenclature system, in attempts to impose ‘‘ﬁnal’’ cladistic decisions on practically useful classiﬁcations!

MAIN POINTS OF CHAPTER 21 1. The relationship between lineage and clade is much more complex than has often been supposed. The lineage is sculptured by diverse forces, most signiﬁcantly by adaptive shift, structural attractor, and adaptive corridor, and through the inﬂuence of both clado- and anagenetic selection interface structures. The clade is additionally affected by phyletic occlusion, cladogenetic substitution, and adaptational dysgenesis; hence, the older the lineage, the more fragmentary the clade, and the less apert the relationship between the two. 2. The cascade of causal factors underlying the architecture of a higher group clade does not predict the necessary presence of any one absolute diagnostic character for the lineage in question. 3. The complex interrelationship between lineage and clade leads in turn to the ‘‘cladism versus gradism’’ problem in classiﬁcation. Either approach can be valid in the appropriate circumstances. 4. Zonal separation, as a function of remoteness of the biophysical paradigm state for a given adaptive function and steepness of the anagenetic selection gradient between two adaptive zones, is a key element in the deﬁnition of both clade and grade. 5. Functional analysis is fundamental to any attempt at phylogeny reconstruction. In the study of morphology in particular, identiﬁcation of the domain of both the structure and function integral is essential, owing to the high incidence of parallel evolution occurring in a great many anagenetic sequences. 6. The function trait must be deﬁned separately from the conventional ‘‘character.’’ Apparent nonadaptive characters may not be true function traits, and this may lead to false claims of ‘‘non-Darwinian evolution’’ (as well as to unjustiﬁed phylogenetic speculation). 7. The retrievability of phyletic information is fundamentally different for different evolutionary modes (as also for different lineages). For example, amphigenesis presents a common problem at the species and other lower levels, while zonal separation is more likely to lead to problems of interpretation with macroevolutionary anagenesis.

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8. In discussion of evolutionary directionality, the terms ‘‘plesiomorph’’ and ‘‘apomorph’’ do not replace ‘‘primitive’’ and ‘‘advanced,’’ nor indeed must the latter be confused with ‘‘generalized’’ and ‘‘specialized.’’ Attempts to apply any one of these terms to phylogeny, without consideration of the others, may result in anomaly and confusion. 9. The anagenetic sequence is of prime importance in the analysis of macroevolutionary patterns, and must be approached through statistical concordance between structure integral sequences. Total rank correlation in the consensual function integral sequence constitutes the minimum requirement for deduction of phylogeny. 10. The consensual function integral sequence at least identiﬁes the directionality and temporal orientation of constituent anagenetic sequences, and an objective phyletic progenitor state may also be deduced from the same data. However, there may be additional ‘‘cryptic’’ nodes in a lineage, and predominance of euryphyletic and stenophyletic (as against truly monophyletic) traits may lead to the scenario of ‘‘high correlation, but P ⬍ 1.0’’ in cladistic analysis. Truly ancestral states may not be at all objectively identiﬁable in function integral sequence analysis, and the combined effect of this plus the preceding problems means that a supposed clade may really be a grade. 11. Owing to confusion between clade and grade, a consensual sequence generally has to be interpreted in terms of parsimony. However, topological and evolutionary parsimony are not necessarily the same thing, as proven by the very high incidence of parallel evolution and amphigenesis that has been found to exist in a majority of known phylogenies. 12. A combination of weak zonal separation and multiple parallelism in the context of a wide–narrow adaptive corridor dichotomy leads to the highly complex problem of polygradism. In the context of evolutionary parsimony, there may be several approximately equally viable ‘‘horizontal’’ and ‘‘vertical’’ interpretations of such scenarios. 13. Many gradistic taxa are bounded by steep selection gradients, whereas others are circumscribed mainly by stochastic and other nonselectional extinction factors. Some appear not to be at all ‘‘taxonomically differentiated’’ in a manner such as would permit either a clear gradistic or cladistic solution. Many supposedly cladistic units thus seem likely to be ‘‘glades’’ (that is to say, they are neither practically useful gradistic units nor true clades). 14. The original Hennigian view of synapomorphy has already been reformed in view of the observed widespread occurrence of ‘‘homoplasy.’’ However, cladistic solutions often place too much emphasis on single solutions via topological parsimony, and too little on the question of functional analysis in the context of true evolutionary parsimony.

EPILOGUE: AN OVERVIEW OF THE GENERAL THEORY

In this study, the essential goal of formulating a valid interdisciplinary approach to evolutionary theory has centered on the behavior of biotic adaptive systems, from which standpoint we witness the emergence of several key conceptual structures that serve to unify diverse inputs to evolutionary topology. In particular, the concept of an attractor toward which dynamic systems tend to gravitate facilitates the investigation of previously unexplored links between environmental and behavioral science, as well as from developmental biology, functional morphology, and population genetics. The two structural and logistic attractors of biotic adaptive systems are linked to selectional activity and must not be construed as being emergent properties either of random interactivity or of spontaneous order. In particular, the structural selectional attractor is formed through an explicit relationship between degrees of freedom in endogenous adaptive potential and in the external biophysical paradigm for a given adaptation interface. Structural paradigms have furthermore been shown to fall into two distinct categories, adaptive and fabricational, and development must consequently be understood in the context of three interlocking paradigms of ontogeny (fabricational paradigm), phenogeny (extrinsic adaptive paradigm), and embryogeny (endogenous adaptive paradigm). Anagenetic evolution accordingly also has onto- and phenogenetic domains. Adaptive capacity (existing propensity for survival) and adaptive potential (developmentally ‘‘adjacent’’ regimes of adaptability) have been proposed as central structures for analysis of the dynamic behavior of natural adaptive systems, and a revised concept of the spatial architecture and temporal dyna-

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mism of the adaptive niche cannot be separated from these fundamental concepts. Recent advances in our knowledge of developmental genetics have obviously contributed greatly to the analysis of adaptive capacity and potential, and this in turn has lead to a deeper understanding of the longer term role of natural selection in the dynamic behavior of adaptive systems. The ongoing adaptive response of gene pool to external environment is centered on formation of a mutual selection interface, and the dichotomy between fundamentally dynamic versus static structures of that kind reﬂects a deep division between the state of ongoing adaptive equilibrium and the true evolutionary behavior of adaptive systems. Evolution may frequently manifest iterative behavior in gravitation toward a distant selectional attractor, alternatively manifesting cladogenetic, anagenetic, or amphigenetic modes of change, according to the architecture of the long-term selection interface. In this analysis, cladogenesis has been found to have a wider domain of expression than had hitherto been supposed, being manifested in both intraspeciﬁc (gene-homeostatic) and speciational modes. In addition, a radically re-formed view of anagenesis has been linked to the concept of a structural selectional attractor rather than to either ‘‘random trends’’ or ‘‘programmed orthogenesis,’’ and amphigenesis has been deﬁned as a new and signiﬁcant evolutionary mode. Any general theory of evolution must of course imply the existence of at least two ‘‘special’’ theories, and identifying what these latter actually are clearly constitutes the ﬁrst step in deriving a uniﬁed concept. The broader aspect of the Thompsonian input to evolution certainly forms the most signiﬁcant missing element in the original formulation of the Darwin– Wallace theory (1858), although the present interpretation is very different from that of Thompson himself (as indeed also from the hard structuralist program). The approach from the standpoint of the adaptive system is fundamental to any attempt at bridging the gap between Darwinian ‘‘selectionist’’ and structuralist viewpoints in the context of a general theory of evolution. The Darwinian input to the structural attractor (niche interface and degrees of freedom in the biophysical paradigm) and the intrinsic Thompsonian element (degrees of freedom in endogenous adaptive potential) are shown to be exclusively interactive, although the Darwinian input may tend to lead in phenogeny, and the Thompsonian in ontogeny. The general theory of evolution accordingly encompasses both paradigms, and in this fusion of concepts we have to envisage the way in which the outcome of many fundamental mechanisms of a uniﬁed adaptive process can follow a path of gravitation toward speciﬁc selectional attractors. Within the limits of generation time, we can best analyze what is happening in an adaptive system in the context of the adaptive capacity of a gene pool, while in the greater perspective of lineage time frame we may also observe realization of adaptive potential in generation of the complex architecture of a phyletic lineage. In the latter context, accommodation of the episodic theory advanced by Simpson (as well as of the much extended and modiﬁed model proposed by Gould and Eldredge) perhaps follows on naturally from a fusing of the Darwin–Wallace and Thompsonian schools of thought, taking account

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of both extrinsic selectional and endogenous fabricational elements as these affect evolutionary rate. Many factors may inﬂuence the rate of evolutionary change in a phyletic lineage—limits of endogenous adaptive potential, the intrinsic selection gradient of anagenesis, ingress of adaptive equilibrium, and the benign versus hostile niche dichotomy in the context of the longer term adaptive corridor being the most important. The search for minimum models describing the foregoing phenomena has led to equations which provide fresh insights into the mechanisms underlying evolutionary rate. Key elements can be found in linked equations of population dynamics and population genetics, and particular equations of evolutionary rate may also be derived either by homology or by analogy, these models serving in turn to merge episodic and gradualist strategies into the uniﬁed theory. In general, the combined inﬂuences of adaptive equilibrium and stochastic override of selection act to determine the conditions under which evolutionary change can occur in the context of an adaptive substrate, the ambient frequency distribution for which is predictably doubly skewed toward stasis. Collapse of adaptive equilibrium in the context of an adaptive shift, combined with the presence of an endogenous substrate in developmental lability and morphogenetic receptivity, are the necessary prerequisites for dramatic evolutionary change to take place. Major evolutionary change thus tends to be episodic in terms of lineage rate, and mass extinction creates the most volatile evolutionary substrate. A further signiﬁcant input to the general theory stems from the loosely articulated special theory centered around the Wright–Fisher–Haldane synthesis in population genetics, the relationships to both evolution and stasis of which have been unclear in the past. Any solution of this problem requires a ﬁrm understanding of the dichotomy between adaptive capacity and potential. Gravitation toward the structural attractor links to the behavior of genetic systems via mutation in epistatically ordered supergenes, either as the phenotype moves toward a distant structure integral of phenotype form via anagenesis, or when new allelomorphs join the repertoire of adaptive capacity in dynamic equilibrium. Separate components of the genome thus express a differential ‘‘mobility’’ in gravitation toward different selectional domains (a fact partly concealed by the convergent effects of independent forces affecting regulatory versus recombinational positional assignment of gene loci on the chromosome). In this context, the original adaptive topography and shifting balance models of Wright largely reﬂect adaptive equilibrium, in their links with the mobile genome sector and ongoing adaptive capacity, rather than evolution in realization of adaptive potential. Novel mutation (and especially that linked to allotropic genes which control more than a single trait) is clearly of special signiﬁcance for the generation of neomorphic states in the context of adaptive shifts leading to true evolutionary change, and this mechanism is in turn greatly facilitated by the occurrence of gene duplication and divergence. Genic substitution may then ascend to phyletic occlusion in the context of an iterative anagenetic sequence as new and modiﬁed gene loci are added to epistatic systems, and this clearly constitutes that route to true evolutionary change which is largely absent in Wright’s adaptive topog-

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raphy model. Nevertheless, the behavior of allomorphic genes of a selection interface in adaptive equilibrium remains crucial to the question of evolutionary stasis, and the adaptive topography model thus forms an important component of the episodic model. The Darwinian, Thompsonian, and population genetics models are thus closely interwoven in the context of the adaptive substrate hypothesis. Earlier descriptive biology frequently looked at morphology in terms of emergent properties, rather than through direct examination of process or mechanism. The so-called ultra-Darwinist approach has been especially concerned with removing damaging typological thinking from the residue of past misdemeanors of this kind. In order to see how the ultra-Darwinist special theory links with the general, we must accordingly examine the question of emergent properties of adaptive systems more closely. In the changing dialectic of evolutionary biology, it has been vital to separate emergent corollary from mechanism and process. However, emergent properties must not be confused in any way with the concept of ‘‘effect’’ (in its wider and more heterogeneous application). There are two fundamental kinds of emergent ‘‘essentiae’’ in adaptive systems as they especially concern architecture of the selection interface: (1) anisotropic essentiae, in which a common mechanism interdigitates with a temporospatially dynamic interface with the external environment (as with the highly signiﬁcant gene pool selection interface); (2) isotropic essentiae, which link diverse mechanisms to a static point (as with multiple functionality in a structural trait). Certain emergent essentiae in both the anisotropic and isotropic domains are clearly of major signiﬁcance in directing (or in preventing) evolutionary change. These facts clearly override certain ultra-Darwinist claims (although they do not contradict the basic thesis that the fundamental focus of selectional activity lies at the individual level). The outcome of the anisotropic essentia concept is that gene pool and species level selection interface structures can and do evolve as a whole (with no need for any input from ‘‘group selection’’). With the isotropic scenario, we also observe the origin of a force balancing against that apparently ‘‘selﬁsh’’ domain in evolution which operates at the level of individual selection, these two elements clearly being complementary in this context. Many of the ‘‘taboos’’ visualized by the ultra-Darwinists are thus linked to earlier misconceptions concerning emergent properties of adaptive systems. However, not all contributions from ultra-Darwinism are concerned with the refutation of wrongdoing on the behalf of supposedly ‘‘holistic’’ evolutionary theory, as witnessed by the great advances that have been made in our understanding of genetic aspects of social behavior in this ﬁeld. In fact, the process of understanding higher emergent properties on the basis of fundamental mechanisms such as that of genic selection can be seen to constitute the central core of that methodology through which classical Mendelian and population genetics can be connected to adaptive systems theory. With the emergent properties approach, we can see also that evolution is, in some sense, itself a corollary of the adaptive process, arising from imperfection and ongoing adjustment in the adaptation interface. In the same context, suboptimality in anagenesis is a consequence of multiple functionality in the

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phenotype and of epigenetic noise in development, and not a source of direct ‘‘non-Darwinian’’ evolution (in any case, a ‘‘suboptimal’’ state carries no real disadvantage other than in the context of a selection interface with a better designed competitor). Evolutionary progress can also be reexamined in the context of an emergent property of anagenesis in its links with the structural attractor, as well as of complexity in global biotic systems. Not all emergent properties are linked to the ultra-Darwinist critique, but all are certainly counteractive to typological thinking. Extinction is also to be seen as a heterogeneous corollary of several mechanisms, and the frequently anomalous relationship between lineage and clade is a corollary of a great many inﬂuences. These include both stochastic and deterministic extinction, including an outcome in phyletic occlusion arising from the presence of steep selection gradients leading to adaptive zones. The domain of emergent properties can also extend beyond that of the external adaptation interface to encompass purely ‘‘internal’’ events in the way complex morphogenesis may emerge from a few interacting factors affecting growth. However, this concept does not extend to encompass directional control over anagenetic evolution as a direct function of the action of developmental constraints, despite the inﬂuence of the latter on degrees of freedom intrinsic to endogenous adaptive potential. Certain other supposed ‘‘constraints’’ actually do act as impediments to evolutionary change, having no inﬂuence whatsoever on directionalization. It is at this point that we should perhaps pause in order to enquire more deeply into the true nature of the phenomenon of emergent properties. In reality, ‘‘emergent properties’’ and ‘‘self-organization’’ are not to be construed as being special attributes of complex systems, so much as indicators of the limits of the reductionist approach to the scientiﬁc method in the study of such systems. In this view, emergent properties are simply those properties which cannot be ascertained following the conventional reductionist method, and it is little more than parody to construe this as being self-organization. Following on from the foregoing conclusions, we can now add that no ‘‘emergent property’’ in evolution constitutes either a candidate for the epithet ‘‘nonadaptive self-organization’’ or a negation of the fact that natural selection constitutes the leading mechanism underlying any propensity which may appear superﬁcially to imply the existence of a leading role for ‘‘nonadaptive evolution’’. In the overall scheme, fusion of a re-formed Thompsonian element constitutes the main link between apparent self-organization and the general theory of evolution (Fig. 125). In this view, the Darwinian component still remains ‘‘the master theory’’ in relation to the Thompsonian and other inputs, yet even this element must ultimately be encapsulated within adaptive systems theory. In this context, natural selection is observedly concerned with both evolution and adaptive equilibrium, and the key feature of this analysis lies with the fundamental dichotomy existing between adaptive capacity and adaptive potential, and thus also between adaptive equilibrium and evolution per se. As has hopefully been made plain above, the conﬂict between special theories cannot be resolved following the methodology speciﬁc to any one

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FIGURE 125 An overview of the hierarchy of special theories making up the general theory of evolution.

domain, but must be sought via the adaptive systems approach. The integrated view emerging from this synthesis is clearly not just neo-Darwinism in new clothes, which epithet can only be held to encompass two or three special theories within the whole construct (certainly not including the neo-Thompsonian or re-formed structuralist components). Additionally, it has to be said that the general theory must also be ‘‘general’’ by virtue of being to some extent pluralistic. As pointed out by G. L. Stebbins (1988), much of the new data entering evolutionary biology indicate that many evolutionary parameters differ from one major group to another. While those axioms which do provide a more or less universal structure for a majority of multicellular organisms form the central core of the present study, it must also be realized that there are relatively few which equally ﬁt unicells and multicells. While the broad relationships of the general theory are more plainly visible in the light of the adaptive systems approach, we must not be blind to the many gaps which still exist in our knowledge. The link between classical and molecular genetics is still quite unclear in certain signiﬁcant areas (for example, in the way in which ‘‘polygenes’’ relate to morphogenesis). However, no factor can be dismissed simply because we do not yet know precisely how one body of knowledge connects to another. With real data on the genetics of populations, we do not even know for sure which apparent ‘‘exemplars of evolution’’ are really only time frames drawn from a broader spectrum of recurrent variation in the context of tertiary adaptive equilibrium. Likewise, comparatively little is known concerning the relationship between genotype and phenotype with respect to morphogenetic traits—a problem which needs to be investigated in terms of complex emergent properties arising from a heterogeny of primary mechanisms. How this will eventually explain such anomalies as the apparently extremely rapid transition between terrestrial mammals and cetaceans is still a matter of pure conjecture at present. Similarly, we have hardly begun to investigate the behavior of the linked equations of population genetics and

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population dynamics in terms of structural attractors of adaptive systems. Existing criteria for measurement of evolutionary rate also remain inadequate, equations of rate being either ‘‘provisional’’ structures or even mere analogs of straw man status at present. It is also true to say that behavioral science appears to lack a central conceptual foundation of the kind seen in other branches of biology, a problem which needs to be resolved through deeper analysis of the links between mechanisms of behavior, adaptive capacity, and the niche concept. Paleontological data clearly also constitute a signiﬁcant problem, in that it is very often impossible to avoid subjective judgment in interpretation. The above anomalies serve to illustrate the fact that a great deal remains to be learned concerning many fundamental mechanisms involved in the evolutionary behavior of adaptive systems.

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GLOSSARY

N.B.: Some deﬁnitions emerge gradually over the course of several chapters. The full deﬁnitions will be found below. Although widely known terms are excluded, many ‘‘old’’ terms that have been slightly modiﬁed are incorporated.

Accommodation, morphogenetic, Any change in the coordinates of morphogenesis must be topologically accommodated over a certain temporal sequence, rather than occurring at any single time horizon (phenotype or otherwise). This applies both to developmental and to evolutionary change. Active adaptive response, Any change in population structure that is due to heritable differentials between genotypes, as distinct from passive logistic change. Active morphospace, Any component of phenotype structure with a high level of structural differentiation and which either directly or indirectly manifests active functionality plus a high level of developmental canalization. Adaptation, That process through which mechanisms of the function ensemble (behavior, metabolism, structure, logistics) facilitate survi-

vorship in the interaction between organism and external environment. Adaptation interface, The actual loci in time and space of all direct adaptive organism– environment interactions of a gene pool, including those arising in reciprocal interactivity with equivalent and superior trophic levels. Adaptational dysgenesis, Extinction due to a discontinuity in the adaptation interface, where no heritable differential exists between survivors and nonsurvivors. Adaptational extinction, See adaptational dysgenesis. Adaptational paradigm of development, The biophysical paradigm state which relates to manifestation of adaptation at the interface with the external environment (q.v. fabricational paradigm). Adaptationally equivalent states, A hypothesis that two or more alternative structural states may express adaptivity, yet manifest no mutual adaptational differential.

599

600 Adaptive capacity, That capacity residing in the mechanisms of the function ensemble (behavior, structure, metabolism, logistics) for realization of the process of adaptation (endogenous component), plus a complementary set of niche parameters existing in the external environment (exogenous component). Adaptive cascade, The hierarchy of causal factors acting to determine directionality of evolutionary change. Adaptive corridor, The longer term manifestation of a dichotomy between benign and hostile niche (q.v.), as this affects evolutionary rate of lineage. Adaptive ensemble, That set of mechanisms (behavior, structure, metabolism, logistics) comprising the function ensemble in the role of realized adaptation. Adaptive equilibrium, That component of allelomorphic variation that is due to existence of dynamic selectional forces acting to perpetuate adaptive capacity. Adaptive grid, See occlusion zone. Adaptive index (Ai), The ratio of fundamental to real adaptive state (q.v.); more accurately, the ratio of selective offset to nonselective offset of fecundity (q.v.). Adaptive isthmus, Deﬁned by dimensions of the occlusion zone (q.v.) at the early part of an anagenetic sequence. Adaptive niche, That subset of temporospatial loci of the external environment in which adaptation is directly expressed by a gene pool, inclusive of the loci of reciprocal adaptive activity from equivalent and superior trophic levels. Adaptive orientation strategy hierarchy, The hierarchic trajectory through kinesis 씮 taxis 씮 processive behavior in realization of adaptive capacity. Adaptive potential, The relationship between existing adaptive capacity and a higher adaptive state in the biophysical paradigm for a given function, as determined by the probability of appropriate neomorph mutational change occurring. Adaptive radiation, Differentiation of form in a rapid succession of Renschian cladogenetic nodes (q.v.) manifested in a phyletic lineage.

GLOSSARY

Adaptive response, The changed expression of adaptive capacity following interactivity between gene pool and environment in respect of active or passive differential mortality, but excluding stochastic factors. Adaptive shift, A qualitative change in the adaptation interface occurring through neomorphic change in the phenotype. Adaptive state, A quantiﬁcation of capacity for adaptation in terms of probability of survival of a genotype or gene pool over a given time interval. Adaptive substrate, A three-dimensional surface reﬂecting the inputs to adaptive capacity and potential from adaptive equilibrium and stochastic override of selection, in terms of selection space available for neomorphic change in the anagenetic domain. Adaptive system, The adaptive system of a given gene pool incorporates all parameters of the direct adaptive niche of that gene pool plus all indirect links to other trophic levels and to the abiotic component of the external environment, inclusive of the adaptive capacity of all constituent gene pools but excluding stochastic interactions (q.v. environment). Adaptive topography model, Following Wright, a graph of mean ﬁtness of a gene pool in terms of frequency of its genotypes. Adaptive zone, That complement of morphospace deﬁned by major coordinates of the structural selectional attractor with respect to a given adaptation interface, and incorporating important inputs from the relationship between absolute size and gravity, position in trophic level hierarchy and larger dimensions of the adaptive niche. Generally bounded by an occlusion zone (q.v.) of greater or lesser dimensions. Adjacent morphosystems, That complement of morphosystems within morphogenetic potential (q.v.) lying both genetically and topologically close to the parent one. Advanced, A structural state corresponding to a biophysical design improvement over some preexisting state from which it evolved (or could evolve) through the mechanism of evolution.

GLOSSARY

Afﬁne morphogenetic transformation, Any change in a morphogenetic state in which the transformation factors involved do not alter the straight-line relationship of geometric coordinate(s). Allelogenesis, Evolution of neomorphic components added to the preexisting genome through genetic mutation, irrespective of selectional value. Allometric transformation factors, Any morphogenetic transformation which involves only scalar transformation to developmental coordinates. Allomorphism, That component of genetic and phenotypic variation that is actively controlled by selectional activity due to presence of a temporally and/or spatially dynamic selection interface operating in the context of adaptive capacity. Alloparametric (determination) factors, A set of determination factors controllant to qualitatively different parameters of a given structure unit. Allopatric speciation, Any mechanism whereby speciation occurs in geographically isolated gene pools, in the absence of any inﬂuence of hybrid depression arising in the sympatric state. Allotely, That situation in which evolutionary rate differs between two or more lineages for the same anagenetic sequence evolving in parallel. Allotropic gene, A gene that is expressed at more than one temporospatial locus during development: 움-allotropic ⫽ same gene, different temporospatial loci of expression; 웁allotropic ⫽ same gene, different splicing morph (same or different loci of expression); 웂-allotropic ⫽ same gene locus, different temporospatial sites of expression plus different epigenetic substrate.

601 domain as that expressed by the nonmutant gene (cf. 웁-allotropism). Alternative morphosystem, A morphosystem lying within the domain of adaptive potential that may be genetically, but is not topologically close to the parent morphosystem. Ambient cladogenesis, Any speciational activity that does not include novel anagenetic change (cf. Renschian cladogenesis). Ambient cladogenetic node, A speciation node that is not linked to Renschian cladogenesis (q.v). Amphigenesis, Evolutionary change involving phenotype reversal beyond the conﬁnes of adaptive capacity, thus expressed only through actual manifestation of reversible realization of adaptive potential. Amphiphyly, That situation in which the primitive states of an anagenetic sequence are distributed differentially between more than one descendant lineage in a branching phylogeny. Anachronism, evolutionary, The temporal gap between a behavioral adaptive shift and appearance of the ﬁrst structural adaptive response to same. Anagenesis, An iterative adaptive response to a long-term isotropic selection interface, involving realization of adaptive potential and manifesting linear structural progression toward a more or less distant selectional attractor. Generally also linked to phyletic occlusion (q.v.). Anagenetic integral curve, A curve reﬂecting the number of accumulated steps taken over the time course of an anagenetic sequence. Anagenetic node, Any ‘visible’ structural increment in an anagenetic sequence (generally presumed to have been coincident with a cladogenetic node or with chronopatric speciation).

␣-anagenesis, That phase of anagenesis for which change in the adaptive state due to qualitative modulation in real niche space is greater than that due to quantitative change linked to functional efﬁciency in niche hyperspace (cf. 웁anagenesis).

Anagenetic sequence, The topological sequence in structure between the preadaptive state preceding a qualitative adaptive shift and a distant paradigm state, reached through the mechanism of anagenetic evolution toward an isotropic selectional attractor.

␣-pleiotropism, Pleiotropism arising through mutational effects within the same allotropic

Anagenetic survivorship curve, An interpretation of the intrinsic selection gradient of anagene-

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GLOSSARY

sis (q.v.) in terms of a probability curve for survivorship.

coordinates of morphogenesis that had passed into a state of phyletic occlusion (q.v.).

Anagenetic survivorship law, The law which states that the selection gradient intrinsic to an anagenetic sequence invokes a complementary hierarchy in successive modes of extinction: minor phyletic occlusion 씮 major phylletic occlusion 씮 cladogenetic substitution 씮 (hybrid substitution in) speciation 씮 genetic anastomosis.

Autogenesis, That model of determination of form in which structure manifests ‘‘spontaneous order’’ through activity of determination factors that supposedly arise directly from chemical or physical factors affecting development.

Anastasis, Stasis expressed in the anagenetic domain. Anisotopic niche interface, A niche interface manifesting spatial dynamism over gene reservoir niche space. Anisotopic niche proﬁle, A niche proﬁle (q.v.) manifesting spatial but not temporal dynamism. Anisotopic selection interface, A selection interface which expresses dynamism in the spatial domain over gene reservoir niche space. Anisotopic selection proﬁle, A selection proﬁle (q.v.) manifesting spatial but not temporal dynamism. Anisotopic transformation factor, A transformation factor which affects different coordinates of a morphogenetic object in a different manner. Anisotropic niche proﬁle, A niche proﬁle (q.v.) manifesting both temporal and spatial dynamism. Anisotropic selection proﬁle, A selection proﬁle (q.v.) manifesting both temporal and spatial dynamism. Apomorph, A purely temporal measure of lineage orientation, here regarded as being relevant only to adaptive equilibrium and amphigenesis. Apomorph ﬁeld (apomorphosis), Any expression of morphogenetic change which transcends the domain of preexisting morphogenetic coordinates by virtue of neomorphic mutation in realization of adaptive potential (cf. plesiomorph ﬁeld). Assembly model of development, See regulative development. Atavism, A genetic mutation (or group of linked mutations) causal to recovery of one or more

Axial cladogenetic force, The axial component of binary resolution (q.v.) of the centrifugal cladogenetic force in which an adaptive shift tends to maximize niche realization through competition in a benign niche (cf. tangential cladogenetic force). Behavior, That strategy of integrated activity in the function ensemble (q.v.) through which movement is translated into realization of adaptive capacity. Benign adaptive corridor, The benign niche (q.v.) in its manifestation over a period greater than ambient speciation time in the context of isotropic selection proﬁle. Benign niche, An adaptive niche in which there is a high level of selectional activity as a result of propensity for competition based on a heritable differential in the structural component of adaptive capacity.

␤-anagenesis, That phase of anagenesis for which qualitative change in real niche space is less than that due to quantitative change linked to expansion of niche hyperspace (cf. 움anagenesis). ␤-pleiotropism, Pleiotropism which extends the domain of expression of a given gene mutation beyond its original allotropic domain (cf. 움-pleiotropism). Bigradism, That situation where a lineage enters a new adaptive zone separated from an earlier one by a large occlusion zone, thus giving bipartite ‘‘zonal separation’’ (q.v.). Binary resolution, The outcome of genomic change due to major cladogenesis (speciation), in which the genome is split two ways (1:1) (cf. unary resolution). Biophysical paradigm concept, That biophysical design serving the purpose of fulﬁlling a speciﬁc functional demand in the adaptation interface, as determined by some subset of the fundamental physical laws as these relate to

GLOSSARY

the intrinsic limits of existing structure and function (see fundamental structural attractor). Biosystematology, The study of the behavior of biotic adaptive systems. Boolean network model (of epistasis), Application of the Boolean network model to describe the hierarchic temporal train of interactivity of regulatory genes in an epistatic cascade (see epistatic array). Boolean periodicity, Periodicity in which a given parameter ﬂuctuates between 0 and 1 (cf. oscillatory periodicity). ‘‘Bottom-up’’ model, That model of morphogenetic change in which a genetic control system is altered incrementally from the lowest members of the epistatic hierarchy upward. Bradytely, Low evolutionary rate of lineage as determined by the effect of stochastic mortality factors holding precedence over selectional mortality in the context of a hostile adaptive corridor (q.v.). Caenophenogeny, A phenogenetic sequence in which there are large qualitative differentials between successive stages. Canalization, That complex of homeostatic mechanisms which sequesters complex morphogenetic determination systems from penetrance of pleiotropy arising from ambient mutational activity, and in which a stabilized output thus results from a varied range of inputs. Canalization paradox, That situation whereby canalization against exogenous pleiotropy may be presumed also to constrain realization of adaptive potential. Centrifugal cladogenetic force, That component of an anisotopic selection interface tending to favor splitting of the genome due to the existence of hybrid depression resulting from a niche intersect between emergent gene pools. Centrifugal polymorphism, Allelomorphism due to an anisotopic selection interface affecting two allelic classes of a gene locus in which hybrid depression is manifested, usually resolved through evolution of dominance for one allele.

603 Centripetal cladogenetic force, The ‘‘anticladogenetic’’ component of the anisotopic selection interface tending to favor homogeneity of the genome as a result of hybrid vigor. Centripetal polymorphism, Allelomorphism perpetuated by existence of a higher ﬁtness value for the heterozygote than for either homozygote class. Character, Any feature of structure used in a diagnostic sense in taxonomy, irrespective of the domain of the functional unit or function integral (q.v.). Character displacement, The steep end of a postspeciational cladogenetic selection interface gradient, manifested in local evolutionary change to sibling species that are only partly contiguous in distribution. Chronomorphism, Allelomorphic variation due exclusively to temporal periodicity of the selection interface. Chronopatric speciation, The hypothetical situation in which genomic change in a lineage may be presumed to have occurred to such an extent that species isolation could be taken to have passively evolved over an extended period of sympatric evolution. cis-acting genes, Cis-acting regulatory genes are those which control another gene locus lying (usually adjacent) on the same DNA molecule (cf. trans-acting genes). CIS-acting genes, CIS-acting regulatory genes are those having a function beyond the boundaries of the cell, but only in the domain of adjacent cells or tissues (cf. TRANS-acting genes). Clade, The extant representation of an evolutionary lineage at any one time horizon. Cladogenesis, Evolutionary differentiation of the genome relative to an anisotopic selection interface in which some degree of hybrid depression and niche intersect (or allopatric divergence) is expressed, such that the adaptive state of the genome is raised—either via dominance or else through genome splitting in speciation. In postspeciational cladogenesis, only the niche intersect factor operates. Cladogenetic capacity, That component of adaptive capacity relating to resolution of conﬂict in the cladogenetic selection interface as ex-

604 pressed in the balance between centripetal and centrifugal cladogenetic forces. Cladogenetic cascade, That cascade of evolutionary events tending to give rise to axial versus tangential cladogenetic forces (q.v.) in realization of major cladogenetic potential. Cladogenetic drive, A measure of the degree to which centrifugal selective forces favor occlusion of the hybrid state in a cladogenetic selection interface (q.v.). Cladogenetic node, A phyletic node reﬂecting speciation. Cladogenetic potential, That component of adaptive potential relating to resolution of conﬂict in the cladogenetic selection interface as expressed in the balance between centripetal and centrifugal cladogenetic forces. Cladogenetic selection interface, An anisotopic selection interface manifesting hybrid depression or allopatric divergence, such that differentiation of the genome through endogenous homeostasis or speciation is favored or facilitated. Cladogenetic substitution, That resolution of cladogenetic drive in which one emergent species is eliminated by another. Cladostasis, Stasis in the speciational domain. Complex heterokaryosis, Any difference in chromosome structure existing between members of a homologous pair and which results in meiotic failure in the zygote. Complex isotropic selection interface, Isotropic selection interface in which directionally antagonistic selection pressures act simultaneously on a single phenotype trait. Complex transformation factor, Any morphogenetic change which involves simultaneous action of more than a single mode of transformation (scalar, temporal, positional). Concerted evolution, See translational allotropism. Condensate model, That model of genome organization in which the members of a gene set are approximated on a single chromosome due to any combination of causal factors. Constraints, evolutionary, See directionalization function.

GLOSSARY

Convex epistatic system, An epistatic system with an approximately linear temporal hierarchy between many regulatory genes controllant to complex epigenetic interactivity, and especially to morphogenesis (cf. ﬂat epistatic system). Corollary (of mechanism or process), Any emergent outcome of a mechanism or process that is not actually part of the primary mechanism or process itself, while at the same time manifesting some higher function in the adaptive process (cf. effect). Coselectional equilibrium, That circumstance in which n gene loci are inherited as a unit due to possession of a common selection interface. Cryptic node, Any node in an anagenetic sequence which only becomes apparent through concordance analysis with other data. Darwinian transformation factors, Any morphogenetic transformation factor which constitutes an advance toward the adaptational (as against fabricational) biophysical paradigm (thus being ‘‘niche-driven’’). Decanalization, The process of passive randomization of regulatory genetic interactions resulting in epigenetic noise, probably partly due to a proliferation of ‘‘off’’ switch mechanisms in functionally redundant epistatic systems, as well as to ingress of pleiotropic gene activity. Depressor, Any gene pool which has the effect of lowering the adaptive capacity of another member gene pool belonging to the same adaptive system (i.e., predator, parasite, or competitor). Dimensional spectrum (of biophysical paradigm), Range of conﬁgurations of the structural selectional attractor due to dynamism in absolute size. Directionalization function, The corollary in topology of evolutionary change of a heterogeny of mechanisms constraining degrees of freedom in the selectional attractor with respect to anagenesis. Dispersive model (of chromosome organization), That model of genome organization in which the distribution of gene loci over n chromosomes is either independent of the inﬂuence of demand for regulatory linkage or else fa-

GLOSSARY

vored by requirement for recombination of alleles (see condensate model). Dynamic (niche, selection interface, etc.), Temporal periodicity in the ⬍t 씮 ⬍Tc range (cf. temporal reference frames). Dynamic trait or character, A trait or character expressing a sequence of change within the extant representation of a given lineage (q.v. static). Ecliptic adaptive shift, An adaptive shift which eventually completely supplants some preexisting function. Eclosion line, That temporal point during development at which the embryo becomes the free-living phenotype. Eclosion line shift, That mechanism through which the temporal locus of the eclosion line changes. Effect, Any incidental outcome of the adaptive process that has no adaptive function and no input to evolutionary change. Embryogeny, That developmental paradigm for structure that is linked to energy exchange via parent metabolism at the endogenous adaptation interface, rather than directly with the external environment. Endocladic (node, etc.): A phyletic node arising from an adaptive or function shift located subsequent to the primary adaptive shift of a clade. Endogenous adaptation interface, The adaptation interface of the embryo in its links with parent metabolism. Endogenous adaptive substrate, Equivalent to morphogenetic receptivity to neomorphic mutation, with special reference to the state of canalization in ‘‘vacant’’ or ‘‘redundant’’ morphospace. Endogenous component of adaptive capacity, That component of adaptive capacity that is endogenous to the function ensemble of the organism itself (behavior, structure, metabolism, logistics). Endogenous component of adaptive potential, That component of adaptive potential that is endogenous to the developmental program of the organism itself, as contained within morphogenetic potential (q.v.).

605 Endogenous component of cladogenetic drive, The inﬂuence of hybrid viability in the cladogenetic selection interface. Endogenous selection interface, Any selection interface not lying directly at the interface between organism and external environment (as with fabricational parsimony in development). Enhancer, Any gene pool which has the effect of raising the adaptive capacity of another member gene pool belonging to the same adaptive system (cf. coadaptation, mutualism, etc.). Environment, Incorporates that part of an adaptive system containing all interactive resources external to a given gene reservoir plus any stochastic inﬂuences impinging on that system. Epigenetic, Term given to any higher translational signal passing from cell to cell or tissue to tissue during development, whether of genetic or nongenetic origin. Epigenetic noise, Complex epigenetic interactivity resulting from expansion of allotropic gene expression and from passive decanalization, instrumental in invoking the pleiotropic threshold (q.v.) as well as in initiation of neomorphic change. Episodic evolution, That situation in which evolution occurs in periodic bursts of high evolutionary rate, rather than at a constant pace. Epistasis, The approximately linear–hierarchic pattern of interactivity between regulatory genes affecting development. Epistatic array, A Boolean function model of epistatic gene interactivity. Epistatic feedback, Pleiotropy resulting from epigenetic interactivity following a single transcriptional event, and emerging ‘‘downstream’’ of the mutation in question. Epistatic system, That complex of gene units jointly forming a supergene manifesting a complex, linear–hierarchic regulatory architecture. Essentia, Any emergent corollary of the fundamental mechanisms of adaptation which affects the architecture of the selection interface (q.v.).

606

GLOSSARY

Euryphyletic, Any trait for which cladistic analysis diagnoses very frequent parallel evolution (a subset of ‘‘polyphyletic’’; see also stenophyletic).

Extrinsic determination factor, Any determination factor arising in the external environment and affecting development by means of interactivity with the epigenetic system.

Eurytropic gene, A gene with n temporospatial loci of activation common to a wide range of cells and tissues, and where transcription and translation are both homologous at all sites.

Extrinsic selection interface, The selection interface between organism and external environment.

Evolution, That manifestation of the adaptive response that is manifested through realization of adaptive potential alone. Evolutionary competence, See prospective adaptation. Evolutionary impediment, Any factor which prevents evolutionary change from actually occurring. Evolutionary mode, Any conﬁguration in the topology of evolutionary change, expressed in terms of linearity and directionality in realization of adaptive potential. Evolutionary substrate, That component of the total adaptive substrate (q.v.) within which evolutionary change is facilitated. Exocladic (node, etc.), An adaptive or function shift lying prior to the primary adaptive shift of a clade.

Fabricational paradigm of development, That biophysical paradigm which is concerned with the problem of ‘‘how to make something in an energy-efﬁcient manner,’’ as distinct from direct concern with phenotypic coordinates linked to the external adaptation interface. Facultative adaptive differential, That model of evolutionary change in which differentials in the realized structural component of adaptive potential are directly facultative to changes in the niche, thus in turn expanding the adaptational paradigm itself. Facultative structuralism, A reformed view of structuralism in which true adaptive differentials arise through structure-driven transformation factors (q.v.).

Extinction, The outcome of any factor causal to the elimination of a species or higher group lineage from its adaptive system.

Fecundity offset strategy, That adaptational strategy whereby fecundity is increased in order to offset mortality due to the inﬂuence of stochastic mortality factors arising in either the internal or external environment.

Extrinsic adaptation interface, Formed by those temporospatial loci in the adaptive system at which behavior manifests realization of adaptive capacity.

Flat epistatic system, An epistatic system with one or a few ‘‘upstream’’ regulatory genes controlling n additive minor gene alleles (cf. convex epistatic system).

Extrinsic component of adaptive capacity, The capacity of some subset of the external environment to be adapted to, with respect to the endogenous adaptive capacity of a given gene pool (thus equivalent to the adaptive niche).

Free adjacent niche space, That component of ‘‘almost available niche space’’ lying adjacent to existing niche parameters, but only reachable in the context of realization of adaptive potential.

Extrinsic component of adaptive potential, That set of parameters in the external environment comprising free, adjacent niche space and presenting potential for raising of the adaptive state, but for which no complementary adaptive capacity exists in the genotype (other than through positive neomorphic mutational change).

Function, A propensity for realization of adaptive capacity expressed by integrated interactivity between behavior, metabolism, and structure.

Extrinsic component of cladogenetic drive, Those factors in cladogenetic drive arising from niche intersect and niche intensity (q.v.).

Function ensemble, The assemblage of mechanisms (behavior, structure, metabolism, logistic capacity) by means of which biotic function is manifested. Function integral, A set of structure integrals (q.v.) expressing adaptational homogeneity

GLOSSARY

607

regardless of degree of direct structural integration.

maintained (or positively altered) with respect to changes in the external environment.

Function integral sequence, Sequence of structural states for a set of function integrals, having a possible relationship with the terms of an underlying anagenetic sequence as suggested by consensual rank order over all inclusive sequences.

Gene pool niche, The niche space occupied by an entire gene pool over the course of a single generation.

Function integral sequence analysis, Application of concordance testing to a set of function integral sequences in derivation of the consensual sequence, following the premise that selectional interactions are correlated for members of a common function integral, but not for discrete function integrals.

Gene reservoir, The total complement of gene pools constituting a species, within the time frame of a single generation. Gene reservoir niche, The niche space occupied by an entire gene reservoir over the course of a single generation. Generalized, A structural state linked to a wide spread of qualitative parameters in the adaptive niche (cf. specialized).

Function shift, Any change in the adaptive state due to a quantitative change in niche hyperspace in the context of gravitation toward the selectional attractor.

Genetic assimilation, That phenomenon whereby a trait affected by determination factors arising in the external environment subsequently comes under direct genetic control.

Functional analysis, The means by which morphological data are analyzed with reference to supposed and observed functional relationships.

Genome mobility hierarchy, That hierarchy within the genome expressing relative propensity of different components of the total genotype for the perpetuated expression of allelomorphism (see mobile, labile, and static genome sectors).

Fundamental adaptive niche, All niche space for which adaptive capacity exists in the gene pool (see real adaptive niche). Fundamental adaptive state (Af), The probability of survival of a genotype or gene pool, ignoring the logistic component of adaptive capacity. Fundamental evolutionary rate, Evolutionary rate as determined directly by selection acting on available variation, thus ignoring ‘‘averaging-out’’ over periods of stasis (cf. real evolutionary rate). Fundamental structural attractor, The biophysical paradigm state (q.v.). Gene, A gene is a nucleic acid molecule that is both transcribed and translated, and in which the translative product also has some functional role to play in metabolism or development. Gene pool, That minimum subset of the total gene reservoir that is necessary for perpetuation of adaptive capacity and within which negative components of short-term selectional activity retain the capacity to be balanced by forces positive to longer term survival, thus permitting the adaptive state to be

Genomic anastomosis, That mechanism by means of which two emergent gene pools reform as a single coherent gene reservoir (racial merging). Grade, (1) A differential between two lineages that is based on zonal separation (see bigradism). (2) A differential between two or more lineages that is at least partly based on paralleling anagenetic sequences evolving at different rates due to a differential between benign and hostile adaptive corridors (see polygradism). Gradistic, Any systematic differential based on euryphyletic traits evolving at different evolutionary rates or involved in zonal separation (see grade). Gradistic distance, Topological distance between taxa in terms of measurements based exclusively on euryphyletic data (q.v.). Gradualism, (1) The view that evolutionary steps are always incremental. (2) The view that evolutionary rate is approximately uniform throughout the evolution of an anagenetic sequence.

608 Growth, Change in cell size or mitotic activity organized around simple coordinates. Heterochrony, Classical term given to speciﬁc temporal translation of somatic modules of phenotype form, in relation to the ancestral topography. Heterokaryosis, Any differential between homologous chromosomes other than that expressed by allelomorphism of gene loci alone and which leads to a positive or negative change in the adaptive state. Heterotopy, Classical term given to speciﬁc positional translation of morphogenetic coordinates through mutational change. Heterozygosis, Differential between homologous chromosomes as expressed by allelomorphism alone, and leading to a (positive or negative) change in the adaptive state. Homoplasy, A heterogeny of data excluded from conventional cladistic analysis and incorporating euryphyletic states manifesting parallelism plus evolutionary reversals linked to amphigenesis and vestigation. Horizontal relationships, That aspect of evolutionary parsimony which stresses withingrade (as against between-grades) relationships (cf. vertical relationships). Horotelic range, The ambient range of evolutionary rates expressed in a lineage, excluding the extreme ends of the spectrum. Hostile adaptive corridor, The hostile niche (q.v.) as this affects the phyletic lineage over a period greater than or equal to ambient speciation time. Hostile niche, Any adaptive niche structure in which penetration of competition/selection is low in the structural component of adaptive capacity, either through a logistic-led adaptive ensemble correlated with high stochastic mortality or else via direct sequestration. Hybrid depression, The negative aspect of recombination resulting from hybridization of gene pools (⫽ negative heterozygosis or heterokaryosis). Hybrid substitution, Elimination of the hybrid genome state through evolution of species isolation between gene pools of a gene reservoir competing in the neosympatric state.

GLOSSARY

Hybrid vigor, Any advantage contained in the heterozygote or heterokaryote, usually as a result of overdominance (or of sexual differentiation). Hypoparametric niche space, That component of niche space that is linked to kinetic behavior (cf. kinesis) and which holds a relatively low probability for realization of adaptive capacity (cf. parametric and subparametric). Hypotely, That scenario in which low evolutionary rate is conferred on a lineage by virtue of progressive ingress of leading effect allomorphism. Incremental change, That circumstance in which positively selected neomorph mutations correspond to small morphogenetic changes only. Infraparametric niche space, Collective term for sub- and hypoparametric niche space (q.v.). Infratranslational genes, Genes with a role in synthesis of metabolic products or in lower translation level differentiation of cells but with no role in growth or morphogenesis. Intercalation model, A model of evolutionary rate which takes into account the fact that periods of change are always interspersed with periods of stasis. Intrinsic selection gradient of anagenesis, The curve for changing evolutionary rate along the temporal trajectory of an anagenetic sequence, reﬂecting gradual decrease in intensity of selectional activity as niche-expanding adaptive shifts of early anagenesis are gradually replaced by smaller function shifts at a later stage. Isopatric selection interface, A hypothetical selection interface structure in which contemporaneous stages in the evolution of an anagenetic sequence are in direct mutual competition. Isotopic niche interface, A spatially uniform niche interface (gene reservoir niche space). Isotopic niche proﬁle, A niche proﬁle (q.v.) which manifests spatial but not temporal uniformity. Isotopic selection interface, A spatially uniform selection interface (gene reservoir niche space).

GLOSSARY

Isotopic selection proﬁle, A selection proﬁle which manifests spatial but not temporal uniformity. Isotopic transformation factor, A transformation factor having an equal effect on all dimensional coordinates of a morphogenetic parameter. Isotropic niche proﬁle, A proﬁle (q.v.) niche that is constant in both time and space. Isotropic selection proﬁle, A temporospatially uniform selection proﬁle (q.v.). Isotropic selection vector, A vector model of the complex isotropic selection interface (q.v.) in which quantity and directionality are seen in the context of the resultant of two components acting with respect to opposing selectional attractors linked to a single phenotype parameter. J factor, A factor added to the Lotka–Volterra equation set which reﬂects the probability of competitional encounter between individuals expressing a heritable differential, as a function of the level of stochastic mortality and/ or of sequestration from mortality in general. K-selection, That situation in which mortality is linked to an active, deterministic, heritable differential. Kinesis, A behavioral response to stimuli linked to niche realization, and which involves no change in orientation (cf. taxis). Labile genome sector, That component of the total genome which expresses minor allelomorphism of near neutral status, such that the frequencies of genes concerned tend to depend on proximity on the chromosome to leading mobile loci (q.v.). Leading effect allomorphism, That situation in which the allomorphic component of the selection interface (q.v.) is instrumental in directing the adaptive response, often via just one or a few gene loci. Leading effect impediment, Leading effect allomorphism impeding evolutionary change by virtue of the suppression of ingress of neomorphic change. Leading effect phenon, That phenon (q.v.) holding the highest contribution to ﬁtness in the selection interface at any one point in time, thereby tending to lead the adaptive response.

609 Lineage, phyletic, The descendants of a single species, following evolutionary change over a sequence of speciational and/or anagenetic events, excluding any effect of extinction. Lineage niche, That component of the adaptive niche that is constant over greater than ambient speciation time. Lineage time, See temporal reference frames. Linkage, Convergent corollary of regulatory and recombinatory positional assignment (q.v.) of gene loci on the chromosome. Linkage disequilibrium, See coselectional equilibrium. Loci of translation, The temporospatial loci of determination, differentiation, growth, and morphogenesis during development. Logistic attractor, The selectional attractor for the logistic component of adaptation. Logistic component of adaptive capacity, That component of adaptive capacity which is concerned with matching fecundity with the level of nonselective mortality factors in the external environment. Macroevolution, Evolutionary change incurring a nonreversibility factor due to loss of endogenous adaptive potential arising through progressive increase in developmental complexity (cf. microevolution). Macroniche, That complement of the adaptive niche that is static over a period greater than or equal to ambient speciation time. Major adaptational dysgenesis, Extinction due to loss of one or more key positive parameters of the major adaptive niche. Major adaptive niche, That component of the adaptive niche of a gene pool that is linked directly or indirectly to the domain of the limiting resource. Major allometric transformation factor, An anisotropic scalar transformation factor having a different effect on different dimensions of a given phenotypic structure unit. Major cladogenesis, That manifestation of cladogenesis encompassing speciation to postspeciational cladogenesis. Major phyletic occlusion, An occlusion event (q.v.) in an anagenetic sequence in which gene

610 ﬂow is no longer present between competing gene pools. Major selectional attractor, The selectional attractor for the structural component of adaptation (cf. minor selectional attractor). Mechanism, The means by which a process is either directly or indirectly carried out in terms of integrated activity in the function ensemble (q.v.). Metabolism, That component of the function ensemble that is concerned with cycling and utilization of energy in the adaptive system. Microevolution, That component of evolutionary change which retains adaptive potential for reversibility (cf. macroevolution). Microniche, Niche parameters having a transient existence with respect to ambient speciation time of a lineage. Minor adaptational dysgenesis, Extinction through addition of a key negative minor niche parameter to the adaptive system. Minor adaptive niche, That component of the adaptive niche of a gene pool containing the reciprocal adaptation interface with equivalent and superior trophic levels. Minor allometric transformation factor, A speciﬁc isotropic scalar transformation factor that affects all dimensions of a structure unit equally. Minor cladogenesis, That manifestation of cladogenesis incorporating subspeciational microevolutionary change alone, usually in the form of acquired dominance. Minor phyletic occlusion, An occlusion event (q.v.) in an anagenetic sequence in which gene ﬂow is still present between competing gene pools but the leading effect still lies with an anagenetic rather than cladogenetic selection interface. Minor selectional attractor, The selectional attractor for the logistic component of adaptation (cf. major selectional attractor). Mobile genome sector, That component of the total genotype expressing major gene allelomorphism in response to a dynamic selection interface with the external environment, thus forming the genetic component of adaptive capacity.

GLOSSARY

Modularity (in development), An expression of the degree of mutual developmental autonomy manifested by the morphogenetic trajectories of different structure integrals of the phenotype. Monotropic gene, A gene with a single, sitespeciﬁc temporospatial locus of expression. Morphogenesis, Growth and/or developmental movement organized around complex coordinates. Morphogenetic potential, That set of morphosystems generated by the entire range of possible conﬁgurations in the equation describing a set of morphogenetic coordinates, assuming the existence of intrinsic potential for realization of same, but irrespective of the positive or negative nature of the ensuing selection interface. Morphogenetic receptivity, A manifestation of the degree to which a given spatial locus of development can tolerate neotropic mutational change, as a function of its level of tolerance of morphogenetic perturbation. Morphology, The study of structure (q.v.) in terms of homology and analogy. Mosaic development, That model of development in which morphogenesis is generated largely by genetic programming endogenous to the cell lineage, thus maximizing modularity for each morphogenetic trajectory. Mosaic evolution, A typological view of the mutual autonomy existing between anagenetic sequences occurring in different structure units of the phenotype, in terms of differential evolutionary rates in each structure unit (cf. polygradism). Multiple functionality principle, The law which states that many structure units/integrals belong to more than a single function integral. Narrow adaptive corridor, See hostile adaptive corridor. Neomorph mutation, A neomorph mutation carries a (positive or negative) effect that was absent in preexisting adaptive capacity, even in the sense of recurrence. Neomorphic transformation, Any form of morphogenetic transformation other than universal factors (q.v.) or ‘‘reshufﬂing’’ of unaltered

GLOSSARY

parental modules (cf. paramorphic transformation). Neosympatry, The rejoining in sympatry of formerly allopatric gene pools of a species. Neosympatric speciation, That model of speciation in which reproductive isolation occurs partly as an adaptive response to hybrid depression between gene pools that have differentiated in allopatry, then rejoined in sympatry (⫽ reinforcement model). Neotropic (gene mutation), Any positively selected neomorph mutational effect which extends the domain of allotropic expression of the nonmutant locus (cf. protropic). Newtonian morphogenetic factors, Morphogenetic determination factors derived from interaction of physical forces resulting from morphogenetic movement. Niche, See adaptive niche. Niche-contracting adaptive shift, Any adaptive shift in which the niche is diminished in terms of qualitative dimensions. Niche-diluting function shift, An adaptive shift in which the niche contracts within the hyperspatial domain alone. Niche-driven transformation factor, Any morphogenetic transformation factor which constitutes an adaptive response to some parameter in the adaptive niche (cf. Darwinian transformation factor). Niche-expanding adaptive shift, Any adaptive shift in which the niche is enlarged in terms of qualitative dimensions.

611 Niche intersect, That component of the cladogenetic selection interface affected by niche overlap between competing gene pools and forming the exogenous component of cladogenetic drive (q.v.). Niche potential, The extrinsic component of adaptive potential residing in niche resources (cf. free adjacent niche space). Niche proﬁle, Behavior of adaptive niche parameters on a temporospatial plane over a period greater than or equal to ambient speciation time. Nonadaptive (character), Any character in which there is no direct or indirect function. Nonadaptive differential, A hypothetical differential between two structural states which differ, not because of any differential in relative adaptive states, but because of degrees of freedom in the selectional attractor alone. Nongenetic determination factor, Any determination factor affecting the developmental system, while arising beyond the domain of the genome itself. Nonselective offset of fecundity, That component of the fecundity offset strategy (q.v.) that is directed toward compensation for purely stochastic mortality (cf. selective offset). Occlusion, genic, Evolutionary change in which the phenotype state of an unaltered gene changes through addition of an extra member gene to the same epistatic system. Occlusion, phyletic, The phenotypic effect of iterated genic occlusion (q.v.).

Niche hyperspace, A temporal summation of adaptive niche space arising from repetitive, recurrent behavioral activity within generation time.

Occlusion zone, That zone of ‘‘lost’’ phenotypic morphospace arising through phyletic occlusion, commonly deﬁning the boundary of an adaptive zone (q.v.).

Niche intensity, A function of the degree to which niche hyperspace (q.v.) is expressed in a given parameter of the adaptive niche.

Ontoanagenesis, Anagenesis expressed with respect to the endogenous fabricational biophysical paradigm of ontogeny (q.v.).

Niche-intensifying function shift, A function shift having the facility of enlarging the domain of niche hyperspace (q.v.).

Ontogeny, That sequence of development during which morphogenesis is structured around the fabricational paradigm (q.v.).

Niche interface, That subset of the adaptation interface containing the loci of deterministic interactions between organism and environment, but excluding the subject gene pool itself.

Optimization, law of, The state of optimization of a structure integral is a function of time lapse since occurrence of an adaptive shift and degree of both functional and developmental autonomy from other structure integrals.

612 Orientation of adaptive ensemble, The leading effect phenon (q.v.) may lie in any component of the adaptive ensemble. ‘‘Orientation’’ may thus be behavior-led, structure-led, and so on. Orthogenesis, An early interpretation of anagenetic evolution in which directionality was presumed to emerge from some form of ‘‘internal program.’’ Oscillatory periodicity, Periodicity in which a value ﬂuctuates bidirectionally, but never reaches zero (cf. Boolean periodicity). Paedomorphosis, The convergent morphological corollary of either progenesis or neoteny, where the adult manifests features of the ancestral juvenile through apparent speciﬁc temporal translation and/or truncation of development. Panadaptationist model, That view of the evolutionary cascade (cf. evolution) which holds that all perpetuated mutational changes constitute an adaptive response to some preexisting demand in the exogenous adaptive paradigm, thus excluding any signiﬁcant input from endogenous adaptive potential. Panstatic (gene) system, That widest domain of genetic interactivity incorporating n epistatic systems displaying a limited element of modular interactivity. Paradigm distance, The evolutionary distance between preadaptive state and biophysical paradigm form for a given adaptive function. Parallelism, Continuation of an anagenetic sequence beyond one or more cladogenetic nodes, due to gravitation toward a tightly constrained structural selectional attractor. Parametric niche space, That component of niche space linked directly to processive behavior in realization of adaptive capacity, thus linked to limiting resources. Paramorphic transformation, Morphogenetic transformation in which no element of true neomorphic change is involved, due to operation of exclusively universal or of isotropicspeciﬁc transformation factors, plus certain other ‘‘special’’ manifestations of developmental afﬁne transformation (cf. neomorphic transformation). Parastatic system, A ﬂat epistatic system in which a set of genes has an approximately additive

GLOSSARY

effect on phenotype form, presumably linked to continuous variation by polygenic inheritance (cf. ﬂat epistatic system). Parsimony, evolutionary, That description of parsimony described in evolutionary (rather than purely topological) terms. Partial adaptive shift, An adaptive shift which does not subsequently come to eclipse an original function. Passive (adaptive) response, Any mechanism affecting change in N, for which no heritable differential exists between competitors. Peramorphosis, Any morphological corollary of apparent temporal developmental translation or prolongation of development, in which one or more somatic traits appear earlier in development than in the ancestral form. Phenoanagenesis, Anagenesis expressed with respect to the exogenous adaptational biophysical paradigm (q.v.). Phenocopy, That phenomenon in which the phenotypic effect of a gene mutation may be ‘‘mimicked’’ by the effect of a nongenetic determination factor. Phenogeny, The sequence of developmental events for those coordinates of morphogenesis for which an active exogenous adaptation interface is ultimately manifested. Phenogenetic convergence, That process through which there is apparent speciﬁc temporal translation of one or more somatic morphogenetic modules from adult to juvenile or vice versa, and where the causality lies in convergence of the adaptation interface itself. Phenogenetic recapitulation, A speciﬁc temporal translation which occurs entirely within the domain of phenogeny. Phenon, Any trait in the phenotype which corresponds to allelomorphism at a single gene locus. Pheno-ontogenetic recapitulation or translation, A speciﬁc temporal translation of morphogenetic coordinates which passes from phenogeny to ontogeny. Phenoplasticity, That component of development that is linked to dialogue between determinative factors arising in the external environment and those emerging from the genetic

GLOSSARY

program, so as to facilitate primary adaptive equilibrium (q.v.). Phenotypic pleiotrope hierarchy, That hierarchy among gene pleiotropes which reﬂects ascending degree of phenotypic effect alone. Phyletic evolution, An evolutionary mode recognized by Simpson and consisting of a heterogeny of anagenesis, postspeciational cladogenesis or divergence (q.v.).

613 Plesiomorph, ‘‘Older,’’ in the purely temporal aspect of orientation of an evolutionary trait or anagenetic sequence. Plesiomorph ﬁeld, That domain in which morphogenetic change lies within the probability domain of adaptive capacity (cf. apomorph ﬁeld).

Phyletic node, Collective category for Renschian cladogenetic plus anagenetic nodes (q.v.).

Plesiosympatry, A temporally and spatially contiguous state of sympatry of a gene reservoir that is not due to rejoin of formerly allopatric gene pools.

Phyletic orientation, The temporal orientation of an anagenetic sequence, reﬂecting also the primitive 씮 advanced proﬁle.

Poised morphosystems, That complement of morphogenetic potential (q.v.) holding the highest probability of actual realization.

Phyletic senescence, That phase in which an evolutionary lineage loses adaptive potential for reversal in the face of change in the external adaptation interface.

Polygradism, That situation in which two or more anagenetic sequences are evolving in parallel in related lineages, while at the same time expressing gradistic differentiation on the basis of evolutionary rate differentials.

Phylogeny, The interaction between anagenesis and cladogenesis in determination of the architecture of a phyletic lineage. Pivotal adaptive shift, That point in which an anagenetic sequence linked to a selection interface manifesting multiple functionality becomes decisively oriented in favor of the most recent adaptive shift. Pleiophore, Any pleiotropic effect that is perpetuated due to the inﬂuence of net positive pleiotropic balance. Pleiotrope hierarchy, The hierarchy among pleiotropes due to differentials in the selection interface or to degree of phenotypic change. Pleiotropic balance, principle of, The hypothesis that a negative pleiotropic load may be supported if there is an overall increase in the adaptive state due to ﬁtness of the leading effect of the same mutation. Pleiotropic impediment, The hypothesis that pleiotropic activity arising from positively selected mutations may carry deleterious effects tending to retard evolutionary change through negative pleiotropic balance. Pleiotropic threshold, That point in the buildup of pleiotropism at which the pleiotropic impediment (q.v.) is invoked. Pleiotropy, Any allotropic gene effect giving rise to a depression of ﬁtness relative to the wild type and resulting from mutation.

Polytropism law, The principle which states that underlying developmental mechanisms can be both mathematically and developmentally diverse with respect to a given morphogenetic transformation. Population, Any subset of the gene pool existing in the natural state. Population niche, That component of niche space occupied by a given population within the time frame of a single generation. Positional transformation factor, A morphogenetic transformation factor involving change in the spatial locus of some structural parameter. Postspeciational cladogenesis, That component of postspeciational divergence (sensu lato) that is due to a residual cladogenetic force. Postspeciational divergence, That component of evolutionary change following a species isolation event, but exclusive of any residual cladogenetic force. Postspeciational selection interface, That component of a cladogenetic selection interface which continues to act beyond the point of reproductive isolation between emergent species. Primary adaptive equilibrium, Adaptive equilibrium manifested within the time frame of a

614 single generation, generally expressed in phenoplasticity (q.v.). Primary adaptive shift, A qualitative adaptive shift that is causal to the origin of a new phyletic lineage manifested in anagenesis. Primitive, A functionally suboptimal state lying more or less remote from the biophysical paradigm state. Process, Goal of a mechanism (or chain of mechanisms), in the context of realization of adaptive capacity or potential. Processive behavior, Behavioral activity directly involved in realization of adaptive capacity. Progenitor, The sum of all primitive states in a consensual rank for function integral sequence analysis (q.v.), excluding known amphiphyletic states and any ⬍0 state. Prospective adaptation (ⴝ evolutionary competence), That component of adaptive potential that is contained in existing structure, while remaining latent in the behavioral component. Protropic (gene mutation), Any positive effect of a gene mutation which arises within the preexisting domain of allotropic activity for the gene in question (cf. neotropic). Punctuated equilibrium, The view which holds that evolutionary change occurs through rapid speciation followed by much longer periods of evolutionary stasis. The ‘‘hard’’ version implicates saltational change at the speciation node, together with some element of non- or maladaptivity, and excludes intraspeciﬁc anagenesis. Punctuation, Any break in stasis or in ambient evolutionary rate, whether speciation and/or gross structural change is involved or not. Quantum evolution, The view which holds that macroevolutionary change occurs largely through rapid infraspeciﬁc anagenesis, excluding all but chronopatric speciation, this being followed by a much longer period of low evolutionary rate. In the ‘‘soft’’ version nonadaptive differentiation is excluded. Quantum punctuation, Punctuation (q.v.) linked to major anagenetic change (with or without species proliferation). r-selection, That situation in which mortality is passive–logistic, with no heritable differential

GLOSSARY

existing between survivors and nonsurvivors, other than in the logistic component of adaptive capacity. Racial merging, See genomic anastomosis. Reagent–substrate hypothesis, That view which sees allotropic gene expression in terms of transcription (⫽ ‘‘reagent’’) in interaction with different ‘‘substrates’’ in the epigenetic environment. Real adaptive niche, That component of the fundamental adaptive niche (q.v.) which actually attains realization during the course of a single generation. Real adaptive state (Ar), The adaptive state inclusive of the logistic component of adaptive capacity (cf. fundamental adaptive state). Real evolutionary rate (of lineage), Evolutionary rate of lineage as averaged out over periods of change and intercalated periods of evolutionary stasis (cf. fundamental rate). Real structural attractor, That subset of the fundamental structural attractor (q.v.) that is constrained through limited degrees of freedom in endogenous adaptive potential. Realization (of adaptive capacity or potential), The act by which some innate capacity or potential in a functional mechanism becomes manifested in the context of direct adaptational function. Realization of cladogenetic capacity or potential, That situation in which cladogenetic drive is resolved via preexisting adaptive capacity or potential (usually in minor versus major cladogenesis, respectively). Recapitulation, Classical view of speciﬁc temporal translation of somatic traits from later to earlier developmental horizons. Recapitulation is now viewed as a corollary of several mechanisms, including that component of morphogenetic accommodation (q.v.) in which developmental modularity permits epistatic systems to simply switch on certain major structural coordinates at an earlier stage without invoking translational allotropy. Reciprocity principle, The concept that there is generally a reciprocal adaptive response between gene pools which interact at a mutual adaptation interface.

GLOSSARY

615

Recombination cluster, A group of tightly linked genes organized through positional assignment of gene loci on the chromosome in response to a shared selection interface in the external environment (part of classical linkage).

Reversal, evolutionary, Any evolutionary change that involves recurrence of an earlier phenotypic state that had passed into extinction.

Recombination impediment, That impediment to evolutionary change which arises in allomorphic gene loci through negative developmental viability in the hybrid state, as a corollary of degree of divergence between parent classes.

Scalar (ⴝ allometric) transformation factors, Transformation factors affecting Cartesian scalar coordinates of morphogenesis.

Saltation, That mechanism which supposedly allows evolutionary change to occur in large steps as the result of a macromutational event.

Recombinatory assignment, That aspect of classical linkage in which gene locus position on the chromosome is inﬂuenced by demand for recombination.

Secondary adaptive equilibrium, Dynamic equilibrium manifested in the gene pool within a time frame greater than or equal to generation time but less than ambient speciation time (q.v.), as generally manifested in genetic allomorphism (cf. primary and tertiary adaptive equilibrium).

Redundant morphospace, Any morphogenetic locus in development for which a formerly active adaptation interface has ceased to exist and in which a low level of developmental canalization can accordingly be tolerated.

Selection, That mechanism by means of which differential survivorship is conferred on genotypes as a result of mortality in which a heritable differential between competitors is manifested.

Regulation cluster, A set of genes lying adjacent on the chromosome as a function of regulatory interactivity between members of the set (part of classical linkage).

Selection interface, That locus in time and space within which the genetic variance of a gene pool interacts with mortality factors linked to a heritable differential between competitors.

Regulative development, That model of development in which a high level of regulatory interactivity occurs between different cell lineages.

Selection proﬁle, The manifestation of temporal and spatial dynamism in the selection interface over the course of a period greater than or equal to ambient speciation time.

Regulatory assignment, That mechanism through which gene locus position on the chromosome is inﬂuenced by demand for regulatory interactivity. Reinforcement model of speciation, See neosympatric speciation. Relative adaptive states, The ratio of two adaptive states appertaining to separate genotypes forming a mutual selection interface. Renschian clade, The extant component of a phyletic lineage at a given time horizon, the primary adaptive shift for which was a Renschian cladogenetic event. Renschian cladogenesis, That manifestation of cladogenesis in which two diverging phyletic lineages have come to occupy qualitatively different adaptive zones (q.v.) linked to anagenetic change. Renschian cladogenetic node, A cladogenetic node which reﬂects a Renschian cladogenetic event (q.v.).

Selectional extinction, That component of extinction arising from selectional interactivity between genotypes, gene pools, or species. Selectional pleiotropic hierarchy, That hierarchy among pleiotropes that is due to differentials in the selection interface. Selective offset of fecundity, That component of the fecundity offset strategy (q.v.) which facilitates adaptive capacity linked to dynamism in the selection interface, with respect to the allomorphic component of the adaptive response. Sequiadaptive correlation, That form of adaptive correlation between different traits in which one trait cannot evolve until some other trait has come into existence. Sequiform phenon, Any phenon, the ﬁtness of which has a lower contribution to the adaptive state than that which forms the leading effect (q.v.).

616 Shifting balance model, Hypothetical model of evolution in which signiﬁcant genetic changes occur due to chance selection of non- or maladaptive genotypes in the context of a small population. Simple heterokaryosis, That level of heterokaryosis giving rise to hybrid depression through ‘‘nonsense haplogenes’’ rather than to actual meiotic failure in the zygote. Simple transformation factor, Any morphogenetic transformation factor involving only one mode of modulation to parent form (scalar, temporal, or positional).

GLOSSARY

phogenetic coordinates and not others (cf. universal transformation factor). Stasis, evolutionary, That adaptive state exhibiting no change within a given time frame, other than that manifested in adaptive equilibrium and stochastic variation. Static genome sector, That complement of genes expressing no allelomorphism in the phenotype and generally linked to epistatic systems controllant to canalized morphogenetic parameters of development. Static niche selection interface, Temporal stasis in the niche interface at greater than or equal to ambient speciation time.

Spatial reference frames (of the adaptive niche), (s) The adaptive niche space of a gene pool. (S ) the adaptive niche space of a gene reservoir.

Static trait or character, Any trait or character existing in a single state in all extant members of a lineage.

Specialized, A state of adaptive capacity expressing a link between structure and a highly constrained niche interface.

Stenophyletic, A trait or character sequence shown by function integral sequence analysis to have had a low incidence of polyphyly.

Speciation, That mechanism by means of which reproductive isolation between gene pools is either actively or passively established.

Structural attractor, The selectional attractor which lies in the intersect between degrees of freedom residing in the biophysical paradigm and (q.v.) endogenous adaptive potential (q.v.).

Speciation, general model of, A model of speciation which encompasses sympatric, allopatric, and neosympatric theories. Species, A limit cycle in the adaptive system that is jointly bounded by reproductive isolation between lineages and by the contours of adaptive equilibrium. Species niche, The niche occupied by a species for the duration of its existence. Species selection, A reference to that higher level selection interface between species which emerges from individual selection in the context of partial or complete sympatry between competitor species. Species sorting, Heterogeny of factors affecting species interactivity and changing species diversity in a lineage, including species selection (q.v.) and a heterogeny of extinction factors. Species substitution, See cladogenetic substitution.

Structuralism: (1) Hard, The view that morphogenetic differentiation in evolution can be driven by endogenous propensities of the developmental system determining the direction of evolutionary change, to the exclusion of adaptation and selection; (2) Soft: the view that endogenous adaptive potential can ‘‘bias’’ directionality in evolution, but only in the restricted sense of adaptation and selection having a major controlling role to play in this. Structure, Organization of organic form for a range of functions linked directly or indirectly to adaptation. Structure-driven transformation factors, That model which considers the inﬂuence of degrees of freedom in the developmental program to be the leading factor in directionalization of morphogenetic transformation.

Speciﬁc mate recognition system model of speciation, See allopatric speciation.

Structure integral, A set of structure units (q.v.) expressing physical (although not necessarily functional) integration.

Speciﬁc transformation factors, Any set of transformation factors which affects some mor-

Structure-led (adaptive ensemble), That orientation of the adaptive ensemble in which the

GLOSSARY

leading factor lies in the structural component of adaptive capacity. Structure potential, See endogenous component of adaptive potential. Structure unit, Any unit of structure that is morphologically discrete from other units, irrespective of functional correlations. Subject and object, The ‘‘subject’’population or gene pool is that chosen point of reference in the adaptive system for which the limiting resource is the ‘‘object’’ reference frame. Subparametric niche space, That component of niche space corresponding to positive taxic behavior in the niche realization function and linked to a relatively high probability of realization of adaptive capacity. Substitution, genomic, The outcome of a major cladogenetic event in which one sub gene pool is eliminated by another. Supergene, That complex of gene units having a linked function in determination during development, generally comprising an interacting set of regulatory and structural genes, irrespective of chromosomal positional assignment. Supratranslational gene, A gene having a translational effect above differentiation, namely, in growth and/or in morphogenesis. Synparametric (determination) factors, A set of determination factors jointly controllant to development of a single parameter of morphogenesis. Tachytely, Highest evolutionary rate of lineage, especially that centered in 움-anagenesis (q.v.). Tangential cladogenetic force, That mode of resolution of the centrifugal force in the cladogenetic selection interface leading to an adaptive shift toward a hostile niche (q.v.). Taxis, Behavioral response involving change in direction to or from a stimulus that is linked to niche realization. Temporal reference frames, Reference time frames for analysis of the dynamic behavior of adaptive systems: t ⫽ life span of an individual; T ⫽ time for ﬁxation/equilibration of a new mutant allele of W ⫽ 1.0 throughout a sympatric gene pool; Tc ⫽ ‘‘ambient speciation time’’ ⫽ approximate average time for

617 accumulated genetic changes in allopatric gene pools of a gene reservoir to reach that point at which neosympatry leads to major cladogenesis. Temporal transformation factor, A morphogenetic transformation factor in which some developmental object changes relative position within the temporal domain. Tertiary adaptive equilibrium, Dynamic equilibrium in a gene pool with respect to adaptive capacity for recurrent mutation linked to periodicity of the selection interface of ⬎ T 씮 ⬍ Tc (cf. temporal reference frames). Thompsonian transformation factor, Any structure-driven transformation factor that is predominantly directionalized by degrees of freedom in morphogenetic potential (q.v.). ‘‘Top-down’’ model, That model of morphogenetic change in which a genetic control system is altered incrementally from the highest members of the epistatic hierarchy downward. Trait, function, Any structure unit delineated with reference to its domain of function, rather than in terms of a morphological unit. Trajectory, morphogenetic, The sequence of events in morphogenesis in the development of a single structural unit from embryo to phenotype. trans-acting genes, Trans-acting regulatory genes lie within the same cell but on a different DNA molecule from the regulated locus (cf. cis-acting genes). TRANS-acting genes, TRANS-acting regulatory genes are those having a function beyond the boundaries of the cell, and also beyond that of adjacent cells and tissues (cf. CIS-acting genes). Transcriptional allotropism, Any manifestation of allotropic gene expression that is due to multiple transcription or to differentials in gene product (cf. translational allotropism). Transformation factor, The effect of mutation with reference to the actual geometric parameters of change occurring in the coordinates of morphogenesis. Transgressive translation, Speciﬁc temporal translation of a morphogenetic object, which

618 latter crosses the eclosion line independently of the effect of actual eclosion line shift (q.v.). Translation level, The level at which gene expression occurs within the following spectrum: primary translation 씮 determination 씮 differentiation 씮 growth 씮 morphogenesis. Translational allotropism, Any manifestation of allotropic gene expression that is due to the multiple translational effects arising from a single transcriptional event (cf. transcriptional allotropism).

GLOSSARY

Vacant morphospace, Any morphogenetic locus manifesting a low degree of structural differentiation in combination with limited contribution to overall ﬁtness and low level of canalization. Variation, The range of phenotypes expressed in a species within any chosen temporospatial reference frame as the result of a heterogeny of causal factors in the organism–environment interaction.

Turing model, Reaction–diffusion model for generation of complex developmental coordinates.

Vertical relationships, That aspect of evolutionary parsimony which considers the status of between-grades relationships (cf. horizontal relationships).

Unary resolution, Anagenetic change in which only a single incipient gene pool survives as a result of major phyletic occlusion (q.v.).

Wide adaptive corridor, See benign adaptive corridor.

Universal transformation factor, Any morphogenetic transformation factor that affects all coordinates of development equally (cf. speciﬁc transformation factors).

Zonal separation, That component of differentiation between taxa that is due to width of the occlusion zone between two adaptive zones (q.v.).

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INDEX

Italicized numbers denote pages with definitions of terms.

Abiotic niche, environment, 29, 31, 32, 34, 37, 38, 448, 457, 501, 532 Absolute diagnostic characters, 551-553 Acanthostega, 478, 560 Active morphospace, 319-321 Activator genes, gene products, 183 Adaptation, 1-5, 329, 331,542 adaptation ensemble, 6 Adaptation interface, 2-3, 4-6, 269, 319, 513, 522, 532, 542 adaptive niche and, 32 endogenous, and embryogeny, 169-170 reciprocity principle and, 22 Adaptational divergence, 89, 137, 438 Adaptational paradigm of development. See biophysical paradigm Adaptive capacity, 2-8, 25, 446, 450, 494, 504, 507, 512-513, 521, 523 defined, 4 adaptive equilibrium and, 67, 72, 290 development and, 175-197 developmental modularity and, 194 dynamic aspects of, 9-10, 49, 300 endogenous and exogenous (extrinsic) domains in, 8-10, 18-21, 124

evolution and, 68, 121-122, 300, 579 evolutionary theory and, 591-597 genetic basis for, !99, 220-222 human, 159 limits of, 122 logistic component of, 6, 10, 11, 18, 24, 74-83, 124, 127, 378, 519,, 520 mechanisms of, 4-6 phenoplasticity and, 72 recombination and, 275, 284, 290 morphogenetic trajectory and, 191-197 realization of, 14, 231 speciation, links to, 113, 340, 495 structural component of, 4, 74-83, 124 Adaptive cascade, 326, 414 evolutionary rate and, 449 phylogeny and, 531-539, 576 Adaptive corridor. See evolutionary rate Adaptive equilibrium, 67-84, 442, 446, 471,560, 594 adaptive index and, 158 amphigenesis and, 146, 148-150 chromosomes and, 276, 278, 280 evolved dominance and, 105-106 gene pool concept and, 83 as leading effect. See Leading-effect allomorphism

minor cladogenesis and, 106, 500 neomorph mutation and, 294, 295, 300 phenoplasticity and, 72-73, 255, 257, 353 population genetics and, 67-71 primary, 71-72 recurrent mutation and, 73, 232, 234, 295 secondary, 71-72 stasis and, 153, 340, 492, 493, 501, 528 temporal domains in, 70-73, 504, 507, 508 tertiary, 72, 339, 521 Adaptive grid. See Occlusion zone Adaptive index, 79-83, 102, 157-158, 456 Adaptive isthmus, 433-434, 504, 529, 535, 557, 571,572, 581 Adaptive landscape, 293 Adaptive niche, 27-52 defined, 27-31,435 adaptive system and, 28 axiom of inequality, 28 evolutionary theory and, 591-597 fundamental versus real niche, 31-32 hierarchic structure of, 33-40 history of concept, 27-31 major niche, 29-31,520 minor niche, 29-31,483, 513, 520, 522

631

632 Adaptive niche (continued) spatial architecture of, 27-42 spatial reference frames of, 43-45 temporal reference frames of, 43-45 'vacant' niche, 27, 314 Verhulst equation and, 32 Adaptive orientation strategy, 33-34 Adaptive paradigm. See Biophysical paradigm Adaptive peaks, 292-298, 338 Adaptive potential, 121-128 adaptive zone and, 435 allometric change and, 165 behavior and, 123-124 in CIS- and TRANS-acting determination factors, 182-185, 187 degrees of freedom in, 127-128, 131, 178, 197, 301, 310, 326-327, 334, 343, 344, 347, 397, 406, 412, 414, 532, 563 development and, 124-128, 173, 175-197, 203 developmental modularity and, 187-191, 194-197, 364, 388, 389, 412, 452 directionalization and, 122, 128-139, 197, 325, 331,335, 348-349, 351-400, 412, 430-431,451, 517, 532, 571; see also, Anagenesis endogenous and extrinsic components of, 124-130, 178, 326, 335, 336-337, 341,348, 456, 484, 505, 506, 532 evolutionary theory and, 121-124, 591-597 gene reservoir concept and, 14 genetic basis for, 199-222, 579 impediments to realization of, 299-324, 497, 498 isotropic niche, selection profile and, 49-50, 127, 452 loci of in structure, function integrals, 139-142, 265-266 morphogenetic trajectory and, 191-197 population genetics and, 67 'versatility' and, 125, 127, 354 Adaptive radiation, 385, 435-436, 476, 546, 547, 567, 579, 585 Adaptive response, 14-16 adaptive equilibrium versus evolution in, 16-17, 74, 83, 467 logistic, 102, 377, 454, 500, 501, 503, 506 passive versus active, 14-16 reciprocal, and 'overspecialization', 81,461 structural, 102, 377, 403, 408, 409, 454, 492, 498, 501,532 structuro-logistic, 77 Adaptive shift(s), 312, 318, 387, 402-403. 407, 449, 450, 498, 593 adaptive potential and, 123 anagenetic evolution and, 321, 402-409, 483 behavior-led, 397, 408, 409, 484 ecliptic, 403-404, 413

INDEX

facultative, 347-348, 396, 397, 398, 402, 409, 532 paedomorphosis and, 376-379 partial, 403, 414 phylogeny and, 533, 538, 546, 548, 572, 573 pivotal, 403-405, 408, 410, 431, 467, 532, 574, 581 primary, 403-405, 408, 410, 414, 450, 451,457, 467, 498, 532, 533, 534, 535, 538, 557 Adaptive state, 11-12, 82, 343, 501 adaptational progress in (cf. anagenetic), 157, 546, 595 fundamental, 75, 453 locus of, 11-14 logistic component of adaptive capacity and, 77 real, 75, 453 relative adaptive states, 53-54 Adaptive substrate, 504-508, 528, 593 mass extinction and, 527-529 Adaptive system(s), 17-25 cladogenetic selection interface in, 94-96 deterministic parameters in, 500 emergent properties in, 591-597 equation set of, 17-21, 593, 596 evolutionary behavior of, 503-506, 511, 532, 589 evolutionary theory and, 591-597 extinction and, 513, 525, 527 fecundity offset strategy and, 78, 337 fitness in, 63-65 phylogeny and, 538, 562 'r' factor in, 63-64 reciprocity in, 502 'W' factor in, 63-65 Adaptive topography model, 275, 291-298, 343 adaptive capacity, equilibrium, potential and, 291-298, 294-297, 299, 308 criticisms of, 293, 294, 295-297 input to general theory of evolution, 291-298, 302, 313-314, 401, 499, 593, 596 random influences in, 294-297 Adaptive valleys, 295-296, 338 Adaptive zone, 433-435, 457, 465, 498, 527, 532 absolute size and, 132 apert and bounded, 433, 504, 529, 535, 551 clade, grade boundaries and, 534, 535, 544, 584 parallelism and, 436-438, 572 zonal separation, 535, 537, 552, 571, 574, 576, 583, 584, 589 Adjacent morphosystems, 265, 352-354, 365, 451 adaptive potential and, 124-125, 356-357, 570 developmental mechanisms and, 196, 235, 237, 388, 389 incremental change and, 262, 559 Advanced trait / grade, 545, 548, 574, 575

Affine morphogenetic transformation, 260, 271, 309, 352, 357, 399, 431, 560 Allelogenesis, 145 evolutionary mode and, 145-146, 151 evolutionary role, 231,504, 507 Allelomorphism, 58, 83, 86, 92, 124, 199, 223, 276, 281,285, 287, 291,299, 301,448, 507, 570, 593 Allometric transformation factors, 355, 361-362, 367, 368-370, 383, 390, 392, 393, 398, 522, 579, 588 adaptive significance of, 138, 165, 379, 389 Allomorphism, 68-80, 84, 277, 278, 300, 306, 411,446, 495, 502, 507, 528, 594 defined, 68-70 cladogenesis and, 105-107 gene duplication and, 243 leading-effect, 142, 218, 307-308, 318, 423, 458, 460, 484, 492, 496-497, 499, 500, 505-507, 529 recurrent, and adaptive capacity, 72, 121, 141,152, 281,283, 285, 288, 290, 296 Allopatry, 86-94, 302, 445 speciation and, 108-109, 317, 422, 448, 464, 473, 514 Allotelic evolutionary rates, 444-445, 452, 455-456, 536, 540, 553, 572, 573-574, 581, 587 Allotropism, genetic, cf also Genes, allotropic adaptive potential and, 213, 240, 321,593 alpha, 211 beta, 211 as 'false pleiotropy', 211-212 gamma, 211-212 transcriptional, 221 translational, 213-214, 222 Alpha anagenesis, 409-412, 414, 415, 423, 425-427, 430, 431,433, 444-446, 450, 452, 455, 456, 463, 465, 466, 468, 481,482, 486, 500, 534, 536, 552 Alternative morphosystems, 301,353 Ambient speciation, cf cladogenesis Amblyrhynchus, 405 Ammonoids. See Cephalopods Amphibians paedomorphosis in, 376-377, 388 Amphigenesis, 146, 148-152, 246, 469, 516, 517, 521 adaptive potential and, 147, 151 evolutionary mode, as an, 145-146 evolutionary theory and, 591-597 microevolution and, 149 paedomorphosis and, 378, 384 phylogeny and, 431-438, 436-438, 544-546, 548, 560, 565, 568-570, 580, 582, 586, 588 speciation and, 152 Amphioxus. 245, 566 Amphiphyly, 583, 555-556 Anachronism, evolutionary, 405, 450, 451,484, 498, 499, 532

INDEX Anagenesis. See also, Directionalization and adaptive potential, 146-147, 318, 341, 428, 442, 443, 466, 469, 511, 515, 521 development and, 162, 234, 386 evolutionary mode, as an, 146 evolutionary progress and, 156-160, 469, 494, 497, 539 evolutionary theory and, 591-597 incremental change in (cf.) intra- and trans-specific models of See also, Phyletic speciation, 405, 414-431 intrinsic selection gradient of (cf.) ontoanagenesis, 165, 411-412 phenoanagenesis, 165, 412 phyletic evolution and, 147, 152 phylogeny and, 431-438, 532, 544, 548-553, 568, 585 speciation, links to, 117, 152-155, 306, 414-430 Anagenetic integral curve, 425-428, 459, 517-518 Anagenetic node, 432 Anagenetic selection gradient See Intrinsic, isopatric selection gradient Anagenetic sequence, 405, 430, 442, 443, 469, 486, 497-499, 518, 522, 533, 593 defined, 404, 406, 408, 415, 418, 419 architecture of, 409-414, 431,433, 437, 455, 557 fossil record and, 422, 426 phylogeny and, 532, 535, 538, 539, 549, 552, 557-559, 561, 572-575, 581 Ancestors, 560, 578 relationship to progenitor, 557, 560, 561 Angiosperms See also, Plants, 126, 258, 385, 404, 473 Anisotopic niche interface, 48 Anisotopic niche profile, 49-50 adaptive response and, 50-51 cladogenesis and, 50 polymorphism and, 50 Anisotopic selection interface, 55, 85, 94 Anisotopic selection profile, 57 Anisotopic transformation factors, 361-364 Anisotropic niche interface, 48 Anisotropic niche profile, 49, 423 adaptive equilibrium and, 50 adaptive response and, 50 Anisotropic selection interface, 55-56, 278, 282, 283, 299, 302, 484 Anisotropic selection profile, 57 Annelids, 322, 576 Antelopes, 395 Apomorph, 545 Apomorph field, allele, 356, 362, 443 Apomorph trait, character, 580 Arachnid book lung, 402-403 Archaeopteryx, 390, 574 Arthropods, 322, 333, 366, 385, 386, 393, 394, 451, 563, 576 monophyly of, 576-577, 579

633 Artificial selection, 296, 303, 340, 442, 474, 570 Artiodactyls, 536 Assembly model of development, 189 Atavism, 152, 245-247, 394, 516, 517, 569, 578 Attractors of the adaptive systems. See major, minor and structural, logistic selectional atractors Autapomorphy. See Absolute diagnostic characters Autogenesis, 329, 331, 332, 335-342 Aves. See Birds Axolotl, 247, 393 Bats, 447, 470, 566 Behavior, 4 adaptive capacity and, 4 adaptive shifts in, 403 evolutionary progress and, 158 Behavior and the hierarchic structure of niche space, 33-40 Benign adaptive niche. See also, Evolutionary rate, 101 cladogenesis and, 101-104, 430 Beta anagenesis, 409-412, 415, 423, 425-427, 431,433, 437, 444, 445, 450, 455, 460, 461,463, 465, 466, 482 Bicyclus, 257 Bigradism, 57•, 572, 576 Binary resolution (of cladogenetic drive), 99, 317, 408, 423, 449, 514-515 Biophysical paradigm(s), cf. also, Selectional attractors, 128-130, 136 adaptive, 325, 326, 333, 334, 341, 346, 347, 349, 406, 408, 412, 419, 426, 437, 469, 481,497, 499, 501, 521, 531-534, 539, 540, 546, 549, 584 adaptive, of development (phenogenetic), 162-164, 182, 346, 349, 374, 380-381, 394, 395, 397 adaptive potential and, 129-139, 326, 347 adaptive zone and, 435 degrees of freedom ('constrainment') in, 130, 197, 326, 328, 333-334, 388, 395, 412, 418, 435, 436, 532, 539, 580, 581, 582, 586, 587 dynamics of, 132, 137-139, 348, 498 fabricational, of development (ontogenetic), 162-164, 195, 228, 336, 349, 374, 381, 397, 412 as a selectional attractor, 130-133, 326 structure and function integrals and, 139, 411, 588 Thompsonian model of evolution and, 128-138, 325-326 Birds classification and phylogeny, 482, 536, 558, 567, 583, 584, 588 evolutionary rates, 478 origins of, 470

Biston betularia, 46, 54, 69, 71, 147, 289-290 Boolean network model (epistatic array), 217-220, 227, 248, 251, 253-254, 262, 266-268, 293, 337, 353 Brachiopods, 344 Bradytelic evolutionary rate, 445-446, 456, 457, 461,462, 484, 487, 498, 501,502, 518, 547, 574-577, 581 Bryozoa, 473, 497

Caenogenesis/caenophenogeny, 165-166, 380, 382-383 Caenorhabditis elegans development, 189-190, 192, 252 epistatic gene systems in, 219, 233, 272 mutations, 270, 392 Canalization, 247 adaptive equilibrium and, 353, 356 adaptive potential and, 247-259, 299, 300, 336 Boolean network model and, 251-252, 254, 262 developmental modularity and, 294 evolutionary anachronism and, 406 evolutionary impediments and, 303, 319-320, 452, 483, 507 Canalization paradox, 451,498 Catastrophe, environmental, 525, 527 Cell adhesion/molecules, 210, 390 Centrifugal/centripetal cladogenetic forces, 87-90, 93-94 Centripetal polymorphism, 89, 107 Cepaea, 48, 57, 69, 71,239, 281, 295, 425 Cephalopods eye structure, 331,343 shell anatomy, 293, 344 Cetaceans, 447, 470, 471,536, 574, 596 Chaos, 341-342, 513 Character, 542 Character displacement, 154, 495 Chick development, 233, 247, 254, 263, 320, 331, 373-374, 390 Chondrogenesis, 263 Chordates development, 272 origins, 385, 470, 580 Chromosomes adaptive topography and, 275-298, 296 genes and, 244, 275-285 inversions, 282, 283, 317, 567 nonhomologous, 92, 289 nonpairing, 305, 306 phylogeny and, 545, 566 speciation and, 116, 306 Chromosome hybrids, 92 Chromosome number, 151, 317 Chromosome puffs, 255 Chronomorphism, 69-70, 107 Cichlids development and genetics, 256, 565 parallel evolution in, 540, 565 speciation/speciation rates in, 115, 403, 404, 476

634 cis-acting determination factors, 177-178, 276, 279, 281 CIS-acting determination factors, 177-178, 182-187, 193, 195-196, 199, 203-207, 228, 289 Clade, 533, 534-538 ambient, 533 extinction, influence in determination of, 534-537, 544, 548, 557, 559, 562, 575, 584 relationship to lineage and to taxon, 531-589 Renschian, 533 Clade selection, 118 Cladistic method, 537 evolutionary mode and, 543-545 gradism and, 550, 577 pitfalls in theory and methodology of, 481, 526, 538, 540, 542, 546, 549, 552, 557, 560, 568, 573, 574, 576, 580-586 pluralism in solutions, 583, 587, 588 relationships to evolutionary theory, 155, 553, 555, 585-589 Cladogenesis, 443 allomorphism and, 105, 117 ambient, 100, 117, 452, 544, 553, 568 anisotopic selection interface and, 85 domains of, spatial, 86 evolutionary mode, as an, 146 evolutionary theory and, 591-597 genetic (major) versus phenotypic (minor) domains, 104-107, 121, 315, 448 compared, 105-106 micro-/macroevolution and, 150 in phylogeny, 431-436 postspeciational, 117, 154, 430, 464 Renschian, 117 adaptive divergence and, 137 ambient speciation and, 155 anagenesis and, 155, 401,436, 494 as 'cladoanagenesis', 155, 432, 449 phylogeny and, 533, 544, 545, 548, 583, 584, 585 Cladogenetic capacity, 97 endogenous component, 98 extrinsic component, 97 minor cladogenesis and, 105 polymorphism and, 108-109 Cladogenetic cascade, 102 Cladogenetic drive, 88-89, 495 benign and hostile adaptive niche and, 101-104 centripetal and centrifugal elements in, 88-94, 436 extrinsic and endogenous components of, 89-91 heterozygosis and heterokaryosis in, 91-94 niche intersect factor in, 88-89, 423, 544 Cladogenetic node, 432, 539 Cladogenetic potential, 97, 416, 420, 453, 461,467 endogenous component, 98, 514

INDEX extrinsic component, 97, 423, 495 major cladogenesis and, 105 neosympatry and, 108-109, 111-112 postspeciational divergence and, 154 Cladogenetic substitution, 99, 114, 118, 306, 315-316, 423, 428, 448, 449, 467, 473-475, 481, 513, 514, 515, 517, 518, 521, 523, 526, 534, 544 Coallometric transformation factors, 368-369, 375, 379, 383, 388, 395, 396, 499, 588 Coelacanth, 411,425, 462, 537, 583, 584 Coelenterates, 157 Coevolution, 25, 501, 524, 525 Commitment, cell, 176-177 Compartments, morphogenetic, 182, 190, 194, 203, 206-207 Competence, developmental, 177 Competitive exclusion principle, 28 Complex isotropic selection interface, 56, 59 Complex isotropic selection vector, 61, 88 Concerted evolution, 244, 261-265, 312, 313, 320, 385, 406, 482 Condensate model of chromosomal organization, 280-281,286, 289, 291,297 Constraints, evolutionary, 133-136 accumulated adaptive shifts and, 134 anagenesis and, 134, 412 biokinematic systems and, 135 developmental, 135, 197, 503 directionalization and, 325, 533 fabricational influences, 135, 195-196 multiple functionality and, 134 selectional, 134-136 Convergent evolution genetic, 564, 565 structural, 134, 344, 549, 562, 589 Co-option. cf: gene duplication Corollary (of mechanism or process), 1-2 Coselectional equilibrium, 281 anagenesis and, 281-282 Cosmia trapezina, 405 Crocodilia, 502 Crossing-over, 123 Crossopterygii. See Coelacanth Crustacea, 476 Cytogenesis, 163

Darwin (unit), 442, 486 Darwinian transformation factors. See also, Darwinian model of evolution, 335, 351, 382, 394 defined, 414, 327-329, 330, 334, 347-348 Darwinism input to general theory of evolution, 128, 325-350, 487, 493, 591-597 Darwin's finches. See Geospizines Decanalization, 252-253 Boolean networks and, 253, 262

developmental systems and, 253, 287, 301, 321,341,352-353 phenocopy mechanism and, 253-255 Deme concept, 12 Demographic theory of optimum reproductive states, 60 Density dependent mortality factors 450, 453, 454 Density independent mortality factors, 461, 523 Depressor, 24 Determination, 176-179, 190, 215, 225 loci of, 180-182 signals in, 177, 233 Development adaptational and fabricational paradigms of, 162-163 architectural models of, 187-191 generalized model of (animal), 170 modularity in, 167-168, 172-173, 175-176, 187-197, 208, 215, 220, 227-228, 235, 241,243, 310, 311, 313, 406 nonviability and cladogenetic potential, 98 in plants, 172 structural paradigms of, 163-165 Developmental ratchet, 195 Developmental trajectory, 163, 170, 516 Differentiation, 176-179, 215 loci of, 180-182 Dinosaurs, 434, 566, 588 Dipnoi, 411,425, 462, 497, 563, 583 Direct ancestry, 583 Dispersive model of chromosomal organization, 280-281,286, 289, 291,297 Ditrysia. See Lepidoptera DNA, 200, 447, 565 hybridization, 558 mitochondrial, 565, 583 mutant, 250, 341 redundant, nongenetic, 200-201, 240, 243, 555, 563, 566, 579 Dog, domestic and evolutionary rate, 474 and pleiotropism, 312 Dollo's law, 151,570 Domain duplication, 243 Dominance, 286, 296, 448 evolved, 105, 284, 288, 289, 338, 493 Drosophila canalization in, 250-252 chaetae/bristle number, selection experiments, 122, 303 chromosomes, 282, 283, 306, 317 development/developmental genetics, 168, 177, 181-182, 186, 189-190, 192, 194, 196, 205-209, 212, 228, 233, 245, 251,268, 272, 280, 564, 565 epistatic systems in, 219 eversae mutant, 68 habitat preferences, polymorphism for, 72 K-/r-selection experiments, 103 mutants, fitness of, 71-72, 260, 283 mutations, frequency of, 249

INDEX phenocopies, 253-254, 256, 352 phylogeny, 340, 567 polymorphisms, 201 race crosses, 305 semispecies, 317 sibling species, 305, 494 speciation, 112-113, 340, 579 species melanogaster, 113, 122, 256, 283, 340, 494 miranda, 306 paulistorum, 283, 317 persimilis, 92, 104, 305 pseudoobscura, 48, 92-94, 104, 201,283, 305, 306 simulans, 494 willistoni, 283 superspecies, 317 Duplicational transformation factors, 322, 366, 385, 386, 393-394, 397, 434, 579 Dynamic diagnostic trait/character, 551-554, 556, 559 Dysgenesis, adaptational, 450, 513, 515, 518-527 biotic versus abiotic factors in, 521-522 geomorphological inputs to, 523 major, 513-514, 520-522, 526-527 minor, 513-514, 522-524, 526-527 partial, 522 Echinoderms, 157, 195, 438, 465, 493 Eclosion line, 171, 358 Eclosion line shift, 366, 375, 380, 382 Effect. See also, Emergent properties, 1 Effect hypothesis, 118 Elephants, anagenetic evolution in, 480 Embryogeny, 163-170, 358 evolutionary aspects of, 355 genetics of, 290 origins of, 166-167 Emergent properties in adaptive systems 1, 2, 386-387, 591-597 essentiae in adaptive systems, 594 speciation and, 118 Endocladic node, 537-538, 552, 556, 581 Endocrine system, 224-225, 388, 390 Enhancer, 24, 435 Environment, 32 Environment interface, 6 Epigenetic, 176, 231 interactivity, 203-223, 226, 250-251,275, 309, 336, 338, 341 Epigenetic noise, 248 canalization/decanalization and, 249-254, 259, 287, 595 pleiotropic threshold and, 302, 303 Episodic evolution. See also, Adaptive substrate, 442, 462-487, 492, 504 episodic substrate, 483-485 evolutionary theory and, 591-597 general model of, 483-485 versus phyletic gradualism, 466-467

635 Epistasis, 207, 214-215 'fitness epistasis', 214, 277-278, 289, 296, 338 supergenes and, 210, 214-222, 228, 231,286 Epistatic feedback, 265-266 Epistatic system(s), 215, 338, 353, 356, 394, 413, 418, 438, 545, 565, 570, 593 alloparametric, 215-216 'convex', 216-220, 267-269, 288, 303, 309 'flat', 217-220, 267-269, 288, 309, 342 propensities of, 256, 260, 288, 517 synparametric, 215-216 Equation set of the adaptive system, 17-21, 62-65, 78, 94-96, 451-452, 453-454 Equids, 263 dentition, 141,438, 443, 447 evolution, 293, 423, 539, 563 evolutionary rates, 426, 447, 480, 573 Hyracotherium, 263 Merychippus, 423 Erebia, 317 Essentiae. See Emergent properties Euryphyletic traits, 559, 560, 568, 586 Evolution, 121-122, 147, 157 dynamic equilibrium versus, 16-17 general theory of, 511,591-597 molecular, 200, 500, 502, 563 random inputs to (real and supposed), 294-297, 336-342, 348, 466, 468-469, 503, 511, 515, 591 special theories. See Darwinian/ Thompsonian models Evolutionary mode, 145-160, 442, 543, 592 Evolutionary rate, 441-489, 491, 511 anagenetic (lineage) rate, 443-447, 449-453, 500, 581 endogenous factors of, 449-452 extrinsic factors of, 452-455 anagenetic selection gradient and, 423, 444, 445-452, 458, 459~ 460, 481,486, 487, 500, 518, 552, 581, 589, 593 benign/hostile niche/corridor, 81, 449, 452-462, 463, 478, 484, 487, 502, 532, 536, 547, 571, 572, 593 cladogenesis and, 447-449 competition, predation and, 155, 430, 453, 483-484, 508 constraintive factors and, 450-452, 456-462, 503 criteria for measurement of, 442-443, 597 curves of, 426 decanalization and, 483-485 equations of the adaptive system and, 444, 451-453, 454 evolutionary impediments and, 319, 495, 503 facultative factors in, 451-452 fundamental, 486 'hard' and 'soft' selection and, 450, 452 phylogeny and [cf.]

real, 485-487 reciprocal effects of clado- and anagenesis, 463-464, 468, 481 variation in. See Allotely, bradytely, horotely, hypotely, tachytely Evolutionary substrate, 317-322, 504, 505, 527, 529 endogenous, 319-322 Evolutionary mode, 145-160 Exocladic phyletic node, 537-538 Extinction. See also, Adaptational dysgenesis, 312, 411,461,465, 511-530, 595 anagenetic integral curve and, 517-518 biotic versus abiotic factors in, 512, 521-522, 524, 526 clade, effects on [cf.] deterministic versus stochastic factors in, 512-513, 519, 526 direct and indirect causal factors of, 153, 338, 463, 512 endogenous and extrinsic factors, 433 evolutionary progress and, 156 mass, 157, 483, 526 pseudoextinction, 418, 513, 516 selectional versus nonselectional (adaptational), 513-525 species, 512

Fabricational paradigm (of development). See biophysical paradigm Fabricational parsimony in ontogeny, 168-169, 328, 374 Fecundity offset strategy, 75-76, 451, 453, 457 adaptive capacity and, 75-84, 500 intersect between selective and nonselective offsets, 79 Fi Bonacci series, 345 Fishes. See also Vertebrates, cichlidsdipnoi/coelacanths actinopterygians, 127, 568 classification, 584 evolutionary rates, 475 fin development/evolution, 320, 560 holosteans, 127 sarcopterygians, 568 tail morphology and evolution, 373 Fitness, 3, 156, 307, 504 mean, 292 Flush-crash model of speciation, 318 Founder principle and speciation on islands, 340 validity of, 318, 338-341,345 Fractal geometry in evolution, 130, 133 Free, adjacent niche space, 97-100, 128, 347, 423, 448, 449, 495 Function and adaptive capacity, 4, 539-540 Function cycles, 6 Function ensemble, 4 Function integral, 140, 405, 426, 539, 540, 547, 553, 574 and the supergene, 217 Function integral sequence, 548, 550 relationships to anagenesis, 550

636 Function integral sequence analysis, 549-561 problems with, 557-561, 562, 568, 569, 573, 587 Function shift, 406-408 anagenetic sequence and, 408-409, 426-427 phylogeny and, 538, 572 Functional analysis phylogeny reconstruction and, 538-543, 548, 549, 550, 551, 568, 575, 580-582, 586, 588

Gastrea, 167 Gastrulation, 163, 376 Gene(s), 200-201 activator/repressor, 202 additive, 58, 286, 289, 293 allotropic, 208-214, 234-237 amplification, 232, 250 eurytropic, 208-210, 234 housekeeping, 209, 234 infratranslational/ supratranslational, 201-202, 209 interactivity, 199, 293 major, 285-289, 296 maternal, 205-207 Mendelian, 200 minor, 285-288, 295, 309 mobility hierarchy (cf.) monotropic, 208-209 regulatory, 202, 207, 223, 232, 261, 290, 313, 545, 564 ribosomal, 555 structural, 202, 290 Gene duplication/divergence canalization/decanalization and, 250-251,253, 321 infra-/supratranslational domains of, 243 -245 polygenes and, 289 realization of adaptive potential and, 243-247, 268-269, 312, 321, 342, 393, 406, 412, 413, 419, 431,434, 484, 593 resolution of selectional conflict and, 240, 309 Gene loci/mutations abdominal-A (abd-A), 207 Abdominal-B (Abd-B), 207 alcohol dehydrogenase, 564 ANT-C, 205-206, 268 antennapedia, 269 Bar, 251 bicoid, 203-204, 206 bithorax. 207, 247, 269, 352 Bobbed, 565 BX-C, 205-207, 210, 222, 352, 354 creeper, 254 crossveinless, 256 Distal-less, 245, 271,394 engrailed, 212 even-skipped, 206 fushi tarazu, 206, 209 gap, 206, 233 globin, 210, 244, 279 Godzilla, 245 Hairless, 565 hedgehog, 209, 245, 564

INDEX homoeotic,183, 206, 217, 222, 245, 271,279, 313, 394 Hox, 168, 205-207, 228, 244, 245, 268-269, 271-272, 279, 290, 319, 320, 322, 393, 531 HOM-C, 205, 245 hunchback, 203 knirps (kni), 206, 245 knirps-related (knrl), 245 Kr~ppel (Kr), 206, 209, 213, 234 lin-3, 252 lin-12, 252 luxate, 560 nanos, 203-204, 206 ocelliless, 250 pair rule genes, 205-207 posterobithorax, 207 proboscipedia, 253 realizator, 271 Resurrector, 245 salm, 271 scute, 256 segment polarity, 205-207 selector, 205-207 sonic hedgehog, 204, 222 supratranslational, 201-202, 300 Ultrabithorax (Ubx), 212 wingless, 564 zygotic, 206 Gene locus assignment, 284, 289 Gene pool, 13, 83-84, 231,257, 288, 291,316, 448, 491,496, 503, 506, 511,519, 520 as 'epicenter/locus of the adaptive state', 11, 12-14, 83, 278, 497, 592 Gene pool isolating mechanisms. See Species isolating mechanisms Gene pool niche, 45 Gene products Bicoid, 212 Caudal, 212 Even-skipped, 252 Fushi tarazu, 252 Hunchback, 212 Gene reservoir, 13-14, 312, 448, 512, 523 anagenesis and, 416, 420, 423, 516, 518 cladogenesis and, 86, 464, 477, 495, 532 Gene substitution, 245-247, 462, 548, 576, 593 Generalized traits/taxa, 255, 546-547 Genetic assimilation phenocopy mechanism and, 255, 352 Genetic conservation, 564, 579 Genetic distance versus morphodistance Genetic drift, 152, 295, 338-341, 441,446 Genic occlusion, 245-246, 418 Genocentric model of evolution, 201 Genome mobility hierarchy. See also, Labile/mobile/static genes, 285-291, 570 adaptive topography model and, 296 Genomic anastomosis, 99, 315, 515

Genomic substitution, 418, 475, 482, 514-515 Geospizine finches, 28, 154, 403, 436, 494, 566 Ginkgo, 462 'Glade'/'gladistic', 585-586 Gnomonic growth, 125, 270 Grade, evolutionary, 535-537, 561 defined, 535-536 zonal separation and, 544, 551 Grade sequence, 561 Gradism. See also, Polygradism, 534-537 evolutionary rate differentials and, 571, 574, 581,582, 586 genetic analysis and, 558, 563, 565, 566, 567, 569, 579 influence in phylogeny, 557, 571-582 'structure equation' for 571 Gradistic, 425 Gradistic distance, 578 Gradistic map, 578 Gradualism. See Incremental change Group selection, 117, 480, 519, 594 Growth, 390, 178-182 Gryphaea, 60, 150, 158, 473, 496, 521 Haldane's rule, 305 Haplogenes, 305, 306, 477 Hardy-Weinberg equations, 64 Hassell equation, 20 Heat-shock proteins, 252, 255 Hemimetabolic development in insects, 172 Hemophilia mutation, 93 Hennigian method. See Cladistic Hepialidae, 75 Heritability, 17, 224, 258 Heterochrony, 259, 270, 361, 362, 365, 367, 372, 376, 379, 380, 384, 388, 389, 395, 396 defined, 355-356, 368, 390-392 acceleration/retardation of development and, 390, 392 Heterogony, 369, 389 Heterokaryosis, 91-92, 94-96, 283, 315, 317 complex, 305-306, 315 negative, 304, 316 positive, 94, 284 simple, 306, 315 Heterosis, 89, 93 Heterotopy, 269, 362, 365, 366, 367, 376 gene duplication and, 393 in evolution, 384, 385 Heterozygosity, 94-96, 282-283, 292, 304, 315, 318, 338 Hierarchic structure of niche space, 33-40 Hitch-hiking, 284, 295, 308, 402 Homeostasis, genetic/epigenetic, 222, 241,257, 279, 284, 288, 303, 306, 318, 353 Hominidae, 537, 564 Homo sapiens, 480, 583, 584 Homoplasy, 540, 541, 550, 553, 554, 569, 586 heterogenous nature of, 582 value of 'unwanted data' in, 582

INDEX Homozygosity, 284, 303 Honeycreepers, 566 'Horizontal' cladistic relationships, 552, 577, 578, 579 Hormones. See Endocrine system/ steroids Horotelic rate/range, 444-447, 450, 462, 464, 466 Horses, See Equids Hostile adaptive niche/corridor. See also, evolutionary rate, 101 cladogenesis and, 101-104, 430 paedomorphosis and, 379, 387 Hybrid depression / nonviability, 88, 90-96, 118, 299, 302, 304, 305, 316, 317, 416, 419 Hybrid viability, 416, 422, 423 Hybrid vigour, 90-94, 112, 118, 249, 282-284, 483 Hypermorphosis, 375, 388 Hypoparametric niche space, 36 adaptive potential and, 128, 523, 587 anagenesis and, 153, 407, 411,435, 456, 457, 525, 544 evolutionary rate and, 456, 457, 484 role in niche space hierarchy, 36-39 trophic level and, 37-39 Hypotelic evolutionary rate, 446, 458-460, 478, 497, 500 Ichneumonidae, 197, 480, 494 Indirect ancestors (critique of concept), 583-584 Inclusive fitness, 159 Incremental change (- gradualism) in evolution, 139, 259-265, 267, 288, 309-311, 313, 336, 354, 380, 393, 398, 463, 465, 466, 467, 472, 473, 475, 476, 480, 484, 486, 504-507, 511, 593 as phyletic gradualism, 466, 469 Induction, 183, 185, 233 Infraparameteric niche space, 36 Infra- (= lower) translational gene, 201,203, 208, 209, 232, 234-235, 239, 242, 243-244, 245, 270, 300 Insects angiosperm reproduction and, 40 adaptation to aquatic niche, 535-536 design, 366 genetic systems, 268, 565 neoteny, 255 paedomorphosis, 377 subfossils, 496, 520 Intercalation model of evolutionary rate of lineage, 455, 486-487, 492, 493, 503 Internalist model of evolution. See Thompsonian model/ structuralism Intersect, ontogeny-phenogeny, 358 Intrinsic (isopatric) selection gradient of anagenesis, 418, 419-421, 423-431,444, 445, 452, 458, 459, 460, 481,486, 487, 500, 518, 552, 581,589, 593 directionalization and, 430

637 Island biotas, 448-449, 465, 471, 483, 507, 579 Isotopic niche interface, 48, 49 Isotopic niche profile, 49-50, 455 adaptive response and, 50-51 Isotopic transformation factors, 361-362, 364, 368 Isotropic niche profile, 49 adaptive potential and, 49-50, 452 adaptive response and, 50 Isotropic selection interface, 55-57, 408, 479, 484 adaptive potential and, 123 principal components of, in adaptive ensemble, 61-62 properties of, 59 Isotropic selection profile, 57, 62, 128 anagenesis and, 153, 287, 301 Isotropic selection vector, 59-60 Isotropic transformation factors, 365 J factor in evolutionary rate, 454, 461

K factor and adaptive capacity, 19 K selection, 75, 102-104, 377, 453-454 Kangaroo rats, 261,264 Kendal concordance coefficient, 550, 553 Kin selection, 13 Kinetic behavior, 34 links to adaptive capacity and niche concept, 34-40 K-T boundary, 157, 527, 537 Kleiber's Law, 132

Labile genome sector, 286-288, 291, 295, 296, 301, 302, 309, 341, 570 Lag load, 501 Lamarckism, 257 Latimeria. See Coelacanth Leading effect impediment, 302, 307, 308 solutions to, 317-322 Leading effect phenon, 142 Lepidoptera abdominal base structure, 563 adaptive corridors and allotelic rates in, 457-458, 573 adaptive radiation, 579 anagenetic sequences in, 536, 538, 539, 553, 556, 557, 569, 578 aphagy and evolutionary rate, 457 coevolution with flowering plants, 525 diurnalist traits, 580 hypertrophic pupal mandible, 239, 372, 569 larval evolutionary trends, 165, 376, 438, 457, 540, 541,547-548, 551, 562, 563, 571, 573, 576, 581 larval prolegs, atavism, 246, 394, 569 Macro-/Microditrysia, 536, 539, 540, 551, 575-577, 578, 579

monotrysian, 457, 462, 552, 560, 567, 582, 585 parallel evolution in, 438, 536, 540, 559, 561-563, 568, 576-577, 580, 582 pupal evolutionary trends, 556, 562, 563, 569, 573, 576 thoracic sutures, 432, 562, 563, 573, 580 tympanal organs, 320, 321,538, 549, 558 vestigiational trends, 539, 570, 581 wing patterns, developmental model for, 184 wing venation, 411, 546, 556, 558, 562, 563, 581 Limulus, 462 Lineage, phyletic [cf. phyletic lineage] Linkage, 275, 276 as a corollary of two mechanisms, 276-278 'tight' versus 'loose', 280, 289 'Linkage disequilibrium', 115, 278-279, 281 'Living fossils', 461-462, 499, 502, 518 Logistic component of adaptive capacity, 6 Lotka-Volterra equations adaptive capacity and, 19-24 alpha factors in, 63-64 cladogenetic selection interface and, 94-96, 103 equations of the adaptive system and, 62-65, 78, 451-452, 454 reciprocity principle and, 22 Lungfishes. See Dipnoi Macroevolution/macroanagenesis, 321, 348, 385, 464, 484, 492, 519, 527, 533, 545, 580 defined, 148-150, 153, 242 anagenesis and, 150, 301,413, 585 cladogenesis and, 102, 430 incremental change, saltation and, 139, 260, 264, 313-314, 466, 477, 504 see also Saltation Macroniche, 47-48, 153, 452, 457, 500, 502 niche space hierarchy, relationship to, 47 Maladaptivity in evolution (arguments/ evidence for and against), 326, 331,332, 334, 337, 339-342, 344, 347-348, 365, 369, 379, 395, 396, 398, 402, 413, 415, 466, 469, 478, 483, 515, 543 Mammalia, 536, 563 development, 373 divergence of major groups, 434, 596 evolutionary rates, 444, 447, 457-458, 470, 478 extinction patterns, 523 origins, 566, 568, 583, 588 Maniola jurtina, 48, 57, 71,239, 295, 425 Marsupials, 523 May equation, 20, 130

638 Mechanism, 1, 2, 386-387, 594 Meiotic drive, 116 Mendelian (classical) genetics, 67, 85, 161,201,220, 243, 245, 275, 276, 285, 289, 327, 348, 594 Mesonychids, 412 Metabolism in adaptive capacity, 4 Metamorphosis, 166 Microevolution/microanagenesis, 148-150, 153, 242, 300, 338, 340, 348, 504, 507 anagenesis and, 150, 469, 585 Microniche, 47-48 niche space hierarchy, relationship to, 47 Mimicry, 152, 337 Minor allometric transformation factor, 451 Mobile genes/genome sector. See also genome mobility hierarchy, 285-287, 290, 291,294, 296, 302, 566-567, 570, 593 Mobility hierarchy of genes, 285 Modularity, developmental, 172, 188-197, 252, 517 Molecular clock, 447, 555 Molecular drive, 244 Mollusca ammonoids, 372 bivalves. See also Gryphaea, 344, 457, 458 cephalopods, 293, 331, 343, 344 development, 193 evolutionary rates, 444, 471 gastropods, 344, 471, 524 paedomorphosis in, 378 origin of classes, 311 shell colour patterning, developmental model for, 184 shell morphology, 125-126, 265, 326, 344 shell thickness, 56 Monophyly, 535, 539-541, 549, 551-553, 557, 559, 561-563, 565-577, 579, 580-582, 584, 586, 587 Moraba, 116 Morphocline, 549 Morphogen(s), 182, 203, 205, 225, 272 gradients, 212 Morphogenesis, 178-180, 187-191, 204, 231,233, 271,286, 293, 300, 570, 595, 596 loci of, 180-182 mechanochemical models of, 261 nongenetic determination factors and, 225, 331 Morphogenetic accommodation, 172-173, 176, 193, 196, 265-266, 379, 399, 516 Morphogenetic fields, 180-182 Morphogenetic lability, 187-191 Morphogenetic potential, 319, 335, 341, 347 Morphogenetic receptivity, 269, 287, 320, 394, 593 adaptive substrate and, 319 evolutionary impediments and, 320-322, 483

INDEX Morphogenetic topology of evolutionary change, 325, 326, 351-400 Morphogenetic trajectories, 168, 189-193, 206, 222, 252, 321, 388, 395 Morphogenetic transformations, 288, 351-400 adaptation and, 376-382 developmental models of, 266-268, 325, 349, 351-367 genetical aspects of, 269-272, 312, 386-394 observed modes of, 367-376, 382-386, 401,479 relative frequencies of, 384, 393 pleiotropism and, 239 Morphospace active, 319 redundant, 342, 344, 483 vacant, 319, 342, 537 Mosaic evolution. See Polygradism, 574-577 adaptive corridor hypothesis and, 572, 574, 576 Mosaic development, 188-191 Mosasaurs, 425-426 Mouse, development and genetics, 233, 246, 263, 393-394, 560 mRNA, 210 Muller's ratchet, 278 Multiple functionality, suboptimality in evolution and, 342, 389, 397, 398, 401,402, 403, 412-415, 498 Mustelidae, 126 Mutation(s) Arthur analysis of, 232, 234 in Boolean model of epistatic system, 219 'bottom-up' / 'top-down' models of, 220, 266-268, 312 chromosomal, 317, 477, 566 directionality of, 260, 352 epistatic systems and, 238, 240, 246 frequency of, 249, 260, 471 heterochronic, 233, 392 homeotic, 253 iterated, 303 lethal, 260 macro, 259, 353 morphogenetic, 357, 364, 389-394 Muller classification of, 232, 234 negative, 238, 289, 339 neomorph mutation, 147, 152, 232, 235-237, 240-241,244, 294, 299, 300, 301, 309, 342, 348, 356, 504, 507, 593 neotropic, 235-237, 240, 243, 245, 247, 267-269, 287, 311, 320, 321,483, 484 neutral, 68, 200-201, 300, 339, 502, 555 pleiotropy and, 237-239, 271 point, 516 protropic, 236-237, 240, 264, 309, 483 quantitative/qualitative, 268 rate change, 270 realization of adaptive potential and, 222-233

recurrent, 123, 152, 250, 283, 289, 294, 311,340, 579, 596 regulatory genes and, 240-241, 244-245, 267, 269-272 selection and, 70 spontaneous, 339 stasis and, 503 temporal shift, 270

Neo-Darwinism, 275, 325, 346, 348, 401,441,469, 497 Neomorphic transformation, 196, 261, 313, 319, 354, 361-364, 366, 367, 384, 385, 389, 398, 403, 508, 531,582, 587 complex, 364-365, 384-386 simple, 364-365 versus paramorphy in evolution, 385-386 Neosympatry, 108, 304 cladogenesis/speciation/ postspeciational divergence and, 108-109, 111-112, 155, 316, 429, 448, 464, 466, 477, 481, 495 Neoteny, 355, 368, 372, 377, 393 Neotropic transformation, 235-240 Neo-Thompsonian model of evolution, 325, 329, 441 Newtonian morphogenetic factors, 185-187, 212, 228, 390 Niche. See Adaptive niche Niche-contracting adaptive shift, 409, 410, 449 Niche-diluting function shift, 407-409 Niche-driven transformation factors. cf. Darwinian Niche-expanding adaptive shift, 408, 409-411,418, 426, 450 Niche hyperspace, 39, 41 anagenesis and, 128, 407 competition and, 40 niche space hierarchy and, 39-40 Niche intensification, 128, 407-411 Niche 'intensity', 90 Niche interface, 32 adaptive cascade and, 326 cladogenesis and, 85-93 spatial structure of, 48-49 static versus dynamic, 46-47 temporal periodicity of, 45-48 Boolean periodicity, 46 evolutionary potential and, 47 oscillatory periodicity, 46 Niche intersect, 90, 100, 378, 416, 448, 494 Niche profile, 49-51,287, 378 adaptive response and, 50 anagenesis and, 153 Niche space hierarchy, 36-40, 47, 597 limiting factors in, 37 Nonadaptivity (in evolution), 325, 394, 395, 466, 542-543, 595 arguments and evidence for and against, 125, 136, 153, 200, 331, 332, 335-342, 347-348, 369, 379, 395, 398, 415, 477-479, 483, 515 selection interface and, 58

INDEX Nonadaptive differential of Simpson, 331-333, 335, 336, 343-348, 414 niche-driven (Darwinian), 333, 344 structure-driven (Thompsonian), 333, 343, 344 Noncongruence principle, 538 Nongenetic determination factors. See also Phenoplasticity, 177, 223, 321 adaptive capacity/potential and, 223-228, 356 phenocopy mechanism and, 254, 352 Nonselective offset of fecundity, 76-80, 84, 337, 453, 512-513

'Object' gene pool/resource, 22 niche concept and, 29 Occlusion, phyletic. See also Clade, extinction, 246-247, 418-420 anagenesis and, 418-421,424, 426, 427, 432, 464, 465, 468, 473, 474, 475, 481, 544, 552, 559, 593 atavism and, 245-247 major/minor, 428-430 pseudo extinction and, 247, 512-518, 521, 526, 575, 578, 584 speciation and, 428-430 species sorting and, 515, 517 Occlusional zone (- adaptive grid), 433-436, 457, 463, 465, 504, 516, 518, 534, 535, 537, 544, 557, 571,574, 584 Ontogeny, 163-164 evolutionary aspects of, 328, 355, 373, 385, 398-399, 493, 516 genetic systems of, 206, 221-222, 228, 232, 290, 392 intersect with phenogeny, 167-168, 193, 358 origins of, 166-167, 336, 366, 381 Ophion, 39, 474, 479 Optimization, law of, 414 Orientation of adaptive ensemble, 6 'Orthogenesis', 134, 136, 150, 152, 426-427, 521,592 Ostrich, 255 Overdominance, 94, 282

Paedogenesis, 355 Paedomorphosis, 355, 367-368, 370-375, 386 adaptation and, 376-379, 396 origins of higher groups and, 384-386 phyletic senescence and, 377-379, 384 Panadaptationist model of evolution, 335, 346-349 Panda, 413 Panderichthys, 478 Panstatic system, 221 adaptive capacity/potential and, 220-228, 241, 321 chromosome morphology and, 281, 288

639 nongenetic determination factors and, 223-228 Papilio memnon, 217, 277, 281,450, 451, 535, 571 Paradigm distance, 137 anagenesis and, 301,419, 532 evolutionary anachronism and, 406 Parallel evolution anagenetic evolution and, 134, 412, 424, 436-438, 444, 452, 455, 456, 457, 469, 532 cladistic methodology and, 539, 540, 562 frequency of in Nature, 540, 559, 563, 569, 582 function integral sequence analysis and, 550, 551,554, 557, 559, 560, 561,562 genetic analysis and, 564, 565, 566, 567, 569, 578-580 phylogeny and, 136, 536, 537, 571, 574, 582, 586 Parametric niche space, 36 adaptive/cladogenetic potential and, 523, 544, 587 anagenesis and, 407, 411 evolutionary rate and, 484 niche periodicity and, 47 niche space hierarchy, role in, 36-38 reciprocity principle and, 40 trophic level and, 37-38 Paramorphic transformation, 354, 365-369, 380, 388-389, 390, 396, 399, 482, 507, 582, 587 defined, 362 frequency of, 384, 385, 396, 398, 579 Paraphyly, 571, 584 critique, 581,583 Parasegments, 203, 206-207, 212 Parasitic wasps, 151, 197, 545 Parastatic gene system, 218, 309 Parsimony, evolutionary versus topological, 539, 542, 552, 554, 557-563, 570, 582-583, 584, 587 adaptive potential, biophysical paradigm and, 563, 569 extinction and 'false parsimony', 567-569, 578 polygradism, mosaic evolution and, 573, 574, 577, 578 'vertical / horizontal' paradox and, 552, 578, 579 Peramorphosis, 367-368, 370-376, 380, 382 Phenetics, 539, 583, 586 Phenocopy mechanism, 225-226, 253-255, 269, 352 Phenogeny, 163-170 evolutionary aspects of, 328, 336, 355, 373, 493, 516 genetic systems of, 206, 221-222, 228, 271,290 phenogenetic sequence, 165, 265, 358, 366 Phenogenetic convergence, 377-379 Phenogenetic recapitulation, 373-375 Phenon, 57-59, 286, 395, 443 structure integral and, 139

Pheno-ontogenetic recapitulation, 373-375, 522 Phenoplasticity (= phenotype plasticity. See also Phenocopy mechanisrn/nongenetic determination factors), 72-73, 225-228, 353, 356, 367 evolution and, 258, 352, 378, 396, 471,474, 502 Phyla, origins of, 393 Phyletic evolution, 147, 152, 445, 464, 468, 486 Phyletic lineage, 401 architecture of the, 401-440, 532, 537-538, 592 'basal gaps' in, 428, 445, 446, 456, 465, 467, 470, 472, 478, 482, 498, 533, 534, 536, 537, 544, 549, 552, 557, 578 Phyletic (= temporal) orientation, 545-548, 554-555 Phyletic nodes cryptic, 431-432, 557-559 endo- and exocladic, 537-538 Renschian, 537-538, 544, 555, 558 Phyletic speciation, 421,466 Phylogeny, 431-433, 445, 447, 531, 533, 535, 553 defined, 431-432 gradism and, 571-580 reconstruction of, 531, 533, 538-589 evolutionary rates and, 537, 551, 578 Phylotypic stage of development, 168 Raft hourglass model and, 168, 196 Pivotal phyletic node, 450, 534, 552 Plantago lanceolata, 71 Plants. See also Angiosperms evolution of reproductive organs/ strategies, 385, 449, 457 evolution of vegetative parts, 332, 345, 405-406 extinctions, 527 parallel evolution in, 438 Pleioplaorism, 237-239, 260, 311, 312, 320, 334, 342, 344, 345, 349, 369, 395, 396, 398, 401, 402, 412, 413, 434, 469, 483, 517, 569 Pleiotrope array, 237 Pleiotropic balance, 237-239, 243-245, 248, 260, 299, 302, 309-313, 319, 342, 395, 452, 469, 484 Pleiotropic impediment, 301, 303-304, 308, 310, 498 solutions to in gene duplication, 309, 313 in incremental change, 308-310 in pleiotropic balance, 309-314 Pleiotropic threshold, 302-304, 310, 320, 321 Pleiotropy/pleiotropism, 210-213, 236-242 adaptive equilibrium and, 239-240 adaptive topography and, 293, 294, 295 analyzed, 233-239, 245, 248,259 canalization/decanalization and, 249-254, 286, 287

640 Pleiotropy/pleiotropism (continued) genome mobility hierarchy and, 291 relational versus direct, 236 Plesiomorph field, 356 Plesiomorph trait/character, 545-546, 580, 585 Plesiosympatry, 108, 304, 316, 481 Pocket gophers, 348 Poised morphosystems, 352-354, 389, 397, 406 Polygenes, 216, 256, 264, 280, 286-289, 301, 309, 310, 393, 450, 596 Polygradism, 571-577 genetic analysis and, 478-580 mosaic evolution and, 571-577 pyramid-inverse distribution and, 575 'vertical' and 'horizontal' problems, 577 Polymorphism, 107, 281,295, 301, 425, 448, 470, 494, 502 stable, conditions for, 93-94 Polyphyly, 533, 542, 547, 549, 551-554, 559, 560, 571,573, 574, 575, 577, 580, 587 Polytropism, 13, 269-271, 389-393, 565 Population genetics, 67-68, 85, 291, 337, 348, 442, 452, 483, 591 evolutionary theory and, 593 Population niche temporospatial framework of, 28, 45 Porifera, 536 Positional information, 183, 233, 390 Positional transformation factors, 358-365, 369, 376, 385 Postdisplacement, 370, 375 Postspeciational divergence, 105, 107, 117, 154, 468, 480, 494, 495, 515

Precambrian explosion, 507 Precis, 212 Predisplacement, 370 Prepattern, 183 Primitive trait/grade, 548, 574, 575, 576 Principle of similitude, 139, 545-546 Process, 1, 2, 386-387, 594 Processive behavior, 34 links to adaptive capacity and niche concept, 34-40 Progenesis, 355, 368, 372, 377, 385, 387, 392, 500, 569 Progenitor, phyletic, 554, 555, 556, 557, 560

Progress, evolutionary, 152, 156-160 Prolongation/truncation (of development), 366, 369, 372, 375, 388, 395 Prospective adaptation, 123-124, 404 Protropic transformation, 235-240 Psarolepis, 568 Pseudo-extinction, 247 Pseudorhyssa, 39

Pterosaurs, 470 Punctuated equilibrium, 318, 441, 463-483, 492, 493 defined, 465-466 evidence for/against, 469-483 'hard' versus 'soft', 477, 478

INDEX in theory, 468 Punctuated gradualism, 468

Quantum evolution, 464-483, 537, 552 evidence for, 465-466, 469-483 in theory, 467-468 Quantum punctuation, 482, 505, 506, 508, 529

r-selection, 75, 102-104, 377, 453 Races, 316 Racial merging, 98, 106, 315, 494 Rana sylvatica, 239 Reaction-diffusion models of development, 184, 336 Realization of adaptive capacity, 14-17, 278, 356, 569

adaptive potential, 123, 569 adaptive shifts and, 405, 408 behavior, role of, 123-124, 159 canalization/decanalization and, 252-258, 261,288, 301, 302, 304, 310, 319, 483, 484, 498 developmental genetics and, 199-202, 204, 266-268, 271-272, 287 gene duplication and [cf.] genome mobility hierarchy and, 290-291 morphogenetic change, pathways of, 259-265, 351-400, 401, 450 mutation and, 231-274, 294, 300, 3O4, 341 pleiotropism and, 240-242 cladogenetic capacity, 98-101 cladogenetic potential, 98-101, 105 axial and tangential components in, 99-101 Recapitulation, 354-355, 367, 373-376, 384, 386 'false', 375-376 morphogenetic accommodation and, 379-382, 516-517 ontogeny and, 169, 398-399 Reciprocity principle, 22, 138 logistic aspect of, 23-24 parametric niche space and, 40 specialization and, 22-23 Recombination, 275-276, 281,293, 317, 507 Recombination and adaptive capacity/ potential, 123, 275, 278-279, 284, 296, 299 Recombination cluster, 277-280, 281, 307 Recombination impediment, 302, 304-307, 308, 315, 481,494 solutions to, 314-317 in dominance, 314-316 in genomic substitution, speciation or species substitution, 315-317 Recombinatory positional assignment, 276-277, 280, 281,291, 593 Red Queen hypothesis, 501, 524-525

Reductional transformation factors, 367, 385, 386, 393-394, 397, 588 Redundant morphospace, 320-321, 412-414 Regulative model of development, 188-191 Regulatory positional assignment, 276-277, 279, 280, 291, 593 Renschian phyletic node, 432, 433, 452, 532 Repressor genes/gene products, 183 Reversal, evolutionary, 151, 436-438, 486, 555, 562, 568-569, 588, 589

Rhinoceros, 331, 333, 347 Rhiphidistians, 264 Rhysella, 39

RNA analysis, 579 Rotational transformation, 367 Rudwick paradigm, 128-129, 346, 469, 541

Salamanders. See also Amphibians, 255, 372, 377, 378, 396, 500 Ambystorna, 185 Saltation, 250-269, 301, 302, 303, 309, 310, 311, 313, 322, 385, 393, 466, 477, 482, 511 Scalar transformation factors, 309, 312, 357-365, 368-370, 383 Selection, natural, 15, 53, 65, 542 artificial [cf.] balancing, 89, 201 cyclic, 57 density-dependent, 63 directional, 309 disruptive, 56 diversifying, 57, 89, 497 equations of the adaptive system and, 62-65 evolutionary role, 329, 336 Fisher's fundamental theorem of, 156 genic, 76, 118, 132, 159 normalizing, 56 properties of, 57 sexual, 405 stabilizing. See also Selection interface, 249, 497 Selection interface, 54 adaptive capacity and, 55-57 anagenetic, 343 anagenetic compared to cladogenetic, 416-421, 476, 479 architecture of, 54-62 cladoanagenetic, 424, 518 cladogenetic, 59, 85-119, 304, 316, 345, 494, 517 heterozygote advantage and, 88-94 hybrid depression and, 88-94, 284, 289 configurations of in development, 163 directionality in, 55-57 dynamic behavior of, 57, 58, 86, 292

INDEX endogenous, 58-59 directionality and, 59, 327-329, 330 evolutionary rate and, 59, 484 evolutionary theory and, 591-597 exogenous/extrinsic component 58-59

extinction and, 513, 520, 523 genome mobility hierarchy and, 290-291 isopatric. See Intrinsic selection gradient of anagenesis and periodicity of the adaptive niche, 54 phenon as locus of, 57-59 postspeciational, 116-118, 448 transspecific, 141, 154 Selection plateaus, 122, 430 Selection profile, cf. also Isotropic, etc. 57, 123, 285 evolutionary mode and, 145 Selection vectors, 54, 55-56 cladogenetic, 86-88 isotropic, 59, 128 obligate, 86 Selectional attractors, cf. also Biophysical paradigm, 21-22, 130-131, 507 anagenesis and, 153 antagonistic, 61 behavior and, 159 dimensional spectrum of, 132-133, 333-334, 435 evolutionary theory and behavior of, 591-597 major (- structural), 21-22, 57, 80-82, 130-133, 327, 333, 343, 346-348, 357, 406, 414, 415, 435, 455, 500, 532, 559 minor (-- logistic), 21-22, 24, 80-82, 130, 455, 500 parallelism and, 438, 567, 571,582 Selective offset of fecundity, 76-77, 78-79, 495 Self organization, 328-329, 331,334, 335, 337, 339, 341, 342, 346, 348, 397, 591, 595 'Selfishness' in genic selection, 83-84, 328, 594 Senescence, phyletic (- lineage), 410, 552, 561 Sequestration, gene, 249-250 Sequi-adaptive correlation, 264, 587 Sequiform phenon, 142 Shared niche space/K, 88, 416-419, 453 Shifting balance model, 294-297, 314, 337, 338, 469, 593 Sibling species, 116, 305, 474, 492, 494, 585 Sigma-delta equations, 458-460 Sister group concept, critique of, 584-585 Specialized traits/taxa, 462, 546-547, 548, 576 Speciation allopatric model, 108, 110, 428-430, 468, 475 anagenesis and, 414-430, 464, 473, 479, 480 behavioral specialization and, 403 biological species concept, 110, 495

641 chromosomes, role of, 116 chronopatric, 420-423 cladogenetic capacity and, 113 cladogenetic potential and, 153, 418 competitive exclusion principle, 118 Dobzhansky-Mayr model, 110-114 evolutionary mode, as an, 145 evolutionary theory and, 591-597 general model, 114-115 geographic dynamics/isolation and, 108, 111, 114-115, 118, 445, 446, 448, 476, 480, 481,495 hybrid depression and, 110, 112 impediments to, 299 major (genotypic) cladogenesis and, 105 models of, 110-116 neosympatric model, 111-112 niche concept and, 110 nonadaptive divergence and, 339-342, 344, 345, 414, 469 parapatric model, 115 Paterson model, 110-114, 421-422, 441,447-478, 479 peripheral isolation and, 318, 469, 475, 507 phyletic, 421,422 phylogeny and, 532 postspeciational divergence and, 107, 154 postzygotic isolation mechanisms and, 112, 421,448 prezygotic isolation mechanisms and, 110, 112, 421,422, 466, 515 realization of cladogenetic potential and, 105, 315 recognition in allopatry, 112 reinforcement model, 110-116 supposed random factors in, 468-469 sexual selection and, 110-111 specific mate recognition model. See Paterson model sympatric model, 115-116, 447 Speciation (cladogenetic) rate, 146, ' 443-444, 446, 447, 461,463, 482 ambient, 148, 423, 430, 445, 475, 518 extrinsic factors affecting, 447-449 intrinsic factors affecting, 447-449 Species, 114 as a limit cycle in adaptive systems, 495-497, 503 interactions in evolution, 466, 480-481 isolating mechanisms, 110-112, 154, 416, 421,422, 448, 466, 467, 497, 515, 566 Species niche, 45 Species selection, 117, 480, 481, 515 Species sorting, 152, 515, 517, 51~ Species substitution, cf. cladogenetic substitution Specific transformation factors, 359-361, 369, 387 Sphenodon, 462

Stasis, evolutionary. See also Evolutionary rate, 443, 460, 464, 468, 471,473, 477, 485, 486, 491-509, 593 adaptive equilibrium and, 16, 492, 493, 496-497, 499-501,503 adaptive substrate for, 491-510 anastasis, 492-508 defined, 497 adaptive corridors and, 499-508 benign, 499-501 hostile, 500-501, 503 endogenous factors in, 498-508 extrinsic and integrated factors in, 495-497 structural locus of, 493 'apparent', 497, 498, 501-503, 518 cladostasis (-- species stasis), 492-504, 508 endogenous factors in, 494-495 locus of, 493 'real', 497, 498, 499, 501, 502 Static diagnostic trait/character, 551-553

Static genes/genome sector, 285-287, 291,299, 301, 302, 309 Stenophyletic traits, 559, 560, 568, 577, 581 Steroids, 224 Stochastic mortality factors, 11, 12, 74-77, 101,453, 454, 502, 504, 505, 506 Stochastic override (of selection), 454, 484, 501, 504, 506, 528, 529, 593 Structuralism, 328, 441 evolutionary theory and, 591-597 'hard' versus 'soft', 329-333, 337, 343-348, 376, 396, 397, 469 'internal evolutionary forces' and, 128, 328, 335 nonadaptivity and, 329, 337, 342, 344, 345-346, 395 shifting balance and founder principle and, 337-341 Structure in adaptive capacity, 4-5 Structure capacity/potential. See Adaptive capacity/potential Structure-driven transformation factors, cf. Thompsonian Structure integral, 139-140, 361,380, 388, 397, 443, 593 anagenesis and, 411,426, 501,549 panstatic gene systems and, 221 phylogeny and, 542, 550, 553, 558, 574 Structure integral sequence, 549 Structure potential. See Endogenous component of adaptive potential Structure unit, 139-140, 291,397, 411,443, 492 phylogeny and, 539, 542, 558 'Subject' gene pool, 22 niche concept and, 29 Suboptimal adaptive states in evolution, 344, 351, 376-379, 394-399, 412-414, 469 adaptive shifts and, 397-398 multiple functionality and [cf.] pleiotropic balance and, 397, 401-402 transient, 412-415

642 Subparametric niche space, 36, 523 anagenesis and, 153, 407, 435, 456, 457, 544 evolutionary rate and, 456, 457, 484 role in niche space hierarchy, 36-39 trophic level and, 37-39 Supergene. See also Epistatic systems, 202, 277-278 epistatic, 208, 279, 288, 290-291 'false', 217, 277, 281,283, 284 parastatic, 216, 218 Survivorship curve, 517-518 Survivorship factors adaptive niche and, 32 deterministic versus stochastic, 32, 102-103 environment and, 32 Sympatry, 86-94, 302, 317, 416, 419, 428, 445, 473 Synapomorphy, 570 critique of, 547, 580-582, 586 Tachytelic evolutionary rate, 445-446, 456, 464, 466, 470, 477, 482, 486-487, 574-577, 581 Taxic behavior, 34 links to adaptive capacity and niche concept, 34-40 Taxonomy, 532, 542, 543, 553, 585, 586, 587, 588 Teleonomy, 346, 539, 541 Temporal transformation factors, 358-365, 369, 393 Terminal addition/condensation, 178, 265-266, 379-380 Tetrapods ancestry of, 264, 560 limb, 126, 266 Therapsids, 438, 588 Theropods, 537 Thompsonian model of evolution, 122, 128-131, 161, 325-350, 401,469, 588 evolutionary theory and, 591-597

INDEX Thompsonian transformation factors. cf. also Thompsonian model of evolution, 327-329, 330, 334, 348, 351, 394, 398, 414, 532 Time arrow. See Phyletic orientation Titanotheres, 395 Totipotence, 177 Trait, function, 542, 553 Trajectory, morphogenetic, 543 Trans-acting determination factors, 177-178 TRANS-acting determination factors, 177-178, 182-185, 193, 195-196, 199, 203-207, 222-223, 228, 268, 281,289 Transcription, gene, 179, 200-201, 272 Transgressive translation, 366 Translation, gene, 175, 200-201 loci of, 180-182 Translation levels in development, 176-182, 201 Translational morphogenetic transformation, 359 Translocation, 289, 307 Transposable elements, 279 Trends, evolutionary, 152, 515 Trilobites, 151,260, 377, 422, 471, 472, 474, 482, 500, 537, 540, 563 Turing model of development, 183, 329 Typology, 386, 421,473, 533, 543, 585, 594, 595 in cladistics, 481,586 Unary resolution, 416, 419, 423, 481 Universal transformation factors, 359-361, 369, 383 Unshared niche space / K, 89, 100, 311, 344, 416-418

qualitative (= disjunct), 291 quantitative (= continuous), 258, 286, 287, 291,296, 416, 418, 474 Verhulst equation, 19, 130 Vertebrate eye, 139, 185, 331, 343 Vertebrate (pentadactyl) limb, 320-321, 336, 516 development of, 263, 266, 320-321, 564 evolution of, 126, 264, 312, 333-334, 385, 434, 560 Vertebrate jaw / teeth / skull, development and evolution, 186, 193, 247, 263, 385, 404, 463, 477 Vertebrates development, 190, 272 origins of major groups, 436 origins of terrestrial, 123-124, 385, 402, 404, 406, 434, 470, 527, 583 'Vertical' cladistic relationships, 552 Vestigiation, 153, 312, 398, 411,469, 522, 539, 543, 569-570, 581, 582 Vitamins and development, 263 Von Baer's Law, 374-375 'W' factor, 63-65, 238, 289, 292, 307, 420, 454, 458-461 Wing bats, 326, 343, 516 birds, 326, 333, 343, 390, 516 insect, 162, 326, 333, 336, 516, 522 development of, 169-170, 236, 564 Xenopus, 244

Vacant morphospace, 320-321 Variation, 336, 345, 393, 502 adaptive equilibrium and, 73-74, 497

Zonal separation. See adaptive zone