Advances in Ecological Research, Volume 3

Advances in

ECOLOGICAL RESEARCH VOLUME 3

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Advances in

ECOLOGICAL RESEARCH Edited by

J. B. CRAGG The Nature Conservancy, Merlwood Research Station, Grange-over-Sands, Lancashire, England

VQLUME 3

1966

ACADEAIIC PRESS London and New York

ACADEMIC PREYS INC. (LONDON) LTD. BERKELEY SQUARE HOUSE LONDON, W.l

U.S. Edition publishod by ACADEMIC PRESS INC. 1 1 1 F i m AVENUE,NEW YORK10003, N E W YORK

Copyright @ 1966 by Academic Press Inr. (London) Ltd.

All rights reserved NO PART OF THIS BOOK MAY BE REPRODUCED IN A N Y FORM BY PHOTOSTAT, MICROFILM OR A N Y OTHER MEANS, WITHOUT WRITTEN PERMISSION FROM T H E PUBLISHERS

Library of Congress Catalog Card Number: 62-21479

Printed in Great Britain by W. S. Cowell Ltd, at the Butter Market, Ipswich

Contri1)utors to Volume 3 MANFRED D. ENGELMANN, Department of Natural Science, Michigan State University, East Lansing, Michigan, U.S.A. €1. KLOMP, Department of Zoology, Agricultural University, Wageningen, Netherlands. J. E. G. RAYMONT, Depurtment of Oceanography, University of Southampton, England.

T. B. REYNOLDSON, Department of Zoology, University College of North Wales, Bangor, Caerns., Wales.

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Preface At the 1965 meeting of the British Association for the Advancement of Science Sir Peter Medawer said, in talking about the state of embryology: “There is no theory of development . . . there has therefore been little sense of progression or timeliness about embryological research. Of many papers delivered at embryology meetings . . . one too often feels that they might have been delivered five years before or deferred for five years without making anyone conscious of great loss.” Replace the word “embryology” by “ecology” and that statement expresses what many regard as a major problem in ecological science; how much of modern and riot so modern ecological literature helps to advance the subject. It is our hope that the special topics selected for review in this series will make a positive contribution to the development of ecology. As far as possible subjects and authors are selected to highlight important problems or fields of research, or to bring to bear on ecology the methods and outlooks of other sciences. Whilst it is important that ecologists strive to develop an adequate theoretical basis for their subject, the need for reliable quantitative information collected with a view to testing hypotheses or theories cannot be overstressed. In this number, the contributions of Dr. Reynoldson and Dr. Klomp demonstrate the type of painstaking and long-term studies which are necessary to provide the solid basis for a proper understanding of population ecology. The two other contributions are concerned with production studies which are of special significance in view of the emphasis which is being given to productivity investigations in the International Biological Programme. Dr. Engelmann has produced a stimulating review of certain aspects of ecosystem dynamics ‘in which he particularly stresses the need for constructing models which can be used as a basis for logical predictions. Professor Raymont has brought together an abundant amount of information on production studies of marine plankton. Much of what he has to say has a bearing on possible developments in other branches of ecology, because the subtle chemical factors which influence the grow-th and succession of plankton will have their counterparts in the interactions of microflora and fauna in terrestrial systems. vii

...

Vlll

PREFACE

It is important in the present state of ecological development that adequate attention is paid to methods. These should be described in a form sufficiently detailed to allow a reader to make an adequate judgement about their reliability. It is hoped that the attention to practical detail which is given in all four contributions, will be of value t o advanced students who are faced with the problem of designing certain types of research programmes. December, 1965 J. B. b ~ a a

Contents CONTRIBUTORSTO VOLUME 3 PREFACE -

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V

vii

The Distribution and Abundance of Lake-Dwelling Triclads - towards a Hypothesis

T. B. REYNOLDSON I. Introduction 11. The Taxonomy of the Triclads 111. The Pattern of Distribution and Abundance A. Introduction and Field Methods B. Results IV. Historical Aspects of Distributiqn and Abundance V. Determinants of Distribution and Abundance A. Weather B. A Place to Live C. Food D. Organisms of the Same Species E. Organisms of Different Species VI. The Explanation of Distribution and Abundance A. The Total Triclad Population B. The Individual Species VII. Conclusions and Summary Acknowledgments References -

1 4 6 6 12 20 28 29 30 34 40 43 63 63 66 62 63 64

Energetics, Terrestrial Field Studies, and Animal Productivity

MANFREDD. ENCIELMANN

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I. Introduction 11. Three Approaches to Energetics Studies 111. Historical Considerations IV. Physiological Studies which Yield Energetics Information V. Studies Concerned Primarily with Maintenance Metabolism of Populations in the Environment VI. Studies which Ernphaaize the Trophic Scheme Analysis of Communities A. Trophic Dynamic Analysis of the Salt Marsh Ecotone B. Trophic Dynamic Analysis of “Old Field” Communities C. Trophic StudiesinaSavttnnahCommunity

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ix

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73 74 78 84 87 96 96 98

103

CONTENTS

X

VII. Projection References -

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108 112

The Production of Marine Plankton

J. E. G. RAYMONT I. Introduction 11. Phytoplankton Production - . A. Methods of Estimating Primary Production B. Factors Affecting Primary Production C. Production - Temperature and Stratification 111. The Standing Crop of Phytoplankton IV. Phytoplankton Crop and Annual Production V. Grazing by Zooplankton - - VI. Zooplankton - A. Methods for Estimating the Standing Crop of Zooplankton B. Regional Crop Assessments of Zooplankton C. Rate of Zooplankton Production D. The Feeding of Zooplankton E. Alternative Food Sources for Zooplankton F. Zooplankton - Quantitative Food Requirements VII. Conclusion . References -

117 120 120 126 147 155 157 160 168 168 170 178 182 186 188 189 191

The Dynamics of a Field Population of the Pine Looper, Buplus piniarius L. (Lep., Geom.)

H. KLOMP I. Introduction A. The Area of Investigation B. The Lifecycle of the Pine Looper C. The Pine Looper as an Object for Population Studies 11. Methods of Meaauring Density A. Density of Eggs and Larvae B. Density of Nymphs C. Density of Pupae D. Density of Moths E. The Dispersion of Nymphs, Pupae, and Moths III. Annual Routine Rearings A. Rearingof Eggs B. Rearing of Larvae - C. RearingofPupae - D. RearingofMoths IV. Annual Variations of the Reproductive Rate A. The Variability of Fecundity Within One Generation B. The Variability of Fecundity Between Generations V. The Composition of Life Tables -

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207 208 209 211 211 211 220 223 229 233 233 234 237 240 240 240 242 268 267

xi

OONTENTS

VI. The Analysis of the Causes of Fluctuation A. The Pattern of Fluctuation B. Key-factor Analysis VII. The Analysis of the Causes of Regulat,ion A. The Incidence of Regulation B. Density Dependent Fecundity C. Density Dependent Mortality D. Delayed Density Dependent Mortality VIII. Final Considerations Acknowledgments References

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273 273 275 286 286 288 289 294 299 303 303

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307

SUBJECTINDEX

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The Distribution and Abundance of Lake-Dwelling Triclads - towards a Hypothesis T. B . R E Y N O L D S O N

Department of Zoology, University College of North Wales, Bangor, Ca,erns., Wales I. Introduction.. . . . . . . . . . ................. 1 11. The Taxonomy of the Triclads.. ........................................ 4 111. The Pattern of Distribution and Abundance.. ............................ 6 A. Introduction and Field Methods.. .... ............................. 6 B. Results ........................................................... 12 IV. Historical Aspects of Distribution and Abundance.. ....................... 20 V. Determinants of Distribution and Abundance.. ........................... 28 A. Weather . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 B. A Place to Live. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 C. Food ........................................... . . . . . . . . . . . . . 34 D. Organisms of the Same Species.. ..................................... 40 E. Organisms of Different Species.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 V I . The Explanation of Distribution and Abundance - a Hypothr5is. . . . . . . . . . . 63 A. The Total Triclad Population.. . . . . . . . . . . . . . . . . . . . . 63 B. The Individual Species.. ............................................ 56 VII. Conclusions and Summary.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Acknowledgments .......................................................... 63 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

I. INTRODUCTION One of the main objectives of the ecologist is the study of factors underlying the distribution and abundance of animals. These factors are numerous, often subtle in operation and interact in complex ways so that in practice research is usually restricted to include only those which experience or a priori reasoning suggests may be important. Many inconclusive studies may stem from examples in which the wrong factors have been selected for study. There is much to be said for tackling such projects with resources of manpower equivalent to those which have been successfully employed in t,he study of the spruce-budworm (Morris, 1963) but it remains important to avoid stifling the initiative and ideas of the individual worker (Lund, 1!)64). Andrewqrtha and Birch (1954) provided a great stimulus in this field of ecology and interest has been maintained in recent texts by Odum (1953) and Macfadyen (1963). But 1

2

T. B . REYNOLDSON

one of the main conclusions to be drawn from these works is the paucity of examples in which causative factors of distribution and abundance have been satisfactorily demonstrated. The majority of important studies relating to freshwater habitats such as those of Jewel1 (1935) on sponges, Edmondson (1944) on rotifere, Boycott (1936) and Macan (1950) on molluscs, Macan (1938, 1954) on corixids, Hynes (1954) on (Jammarus, Bennike (1943) and Mann (1966) on leeches and Williams (1962a, b) on Asellus are concerned mainly with descriptive aapects of distribution and although in many cases a pattern related to some basic feature of the environment has been demonstrated, how it operates remains to be determined. Although Williams’ preliminary studies (1963) on Asellus are a notable exception, there has been little testing of hypotheses by experimentation either in the laboratory or the field. The recent critical treatment of freshwater studies by Macan (1963) has made this starkly clear. It is this situation which has evoked the pleas of Varley (1967) and Cragg (1961) for more use of the field experiment, and McFadden (1963) has gone so far as to doubt the value of field work without it. The fist stage of the work on lake-dwelling triclads has been largely confined to the usual study of the distribution in the field of four main species and an attempt to fit the results into the framework o€ the physico-chemical properties of lakes as a beginning. This was based on the examination of more than two hundred separate habitats in several lakeland areas of northern Britain, Ireland and the western islands (Fig. 1); limited work has also been done in Fennoscania. S h e any pattern of distribution usually bears the stamp of historical events to some variable degree, this aspect has also been considered. I n fact, these triclads show in relation to water chemistry a well-marked pattern which is modified by their dispersal history. As the second stage in the programme, hypotheses based on correlations obtained from field data have been tested by field and laboratory experiments as part of an analysis t o determine the major factors involved. The planning of this stage has been adapted from Andrewartha and Birch’s (1964,1960) concept of environmental components as modified by Andrewartha and Browning (1961) and further amended to apply to freshwater habitats. Thus the influence of water chemistry (especially calcium) and temperature on life-cycles have been studied and tolerances determined. Food which is proving to be a key factor, has been considered in some detail and attention has also been given to predators, while competition especially between the different triclad species themselves and at the intra-specific level, has been investigated. Distribution and abundance have three main parameters, space, numbers and time. Detailed studies of the population biology of the four

LAKE DWELLING TRIULADS

SHETLAND 1s. .FAIR

*@ORKNEY

3

Is. IS.

FIQ.1. The arena in black a m thoae in which the main work haa been done: stippled ~ s ~ e p l thoee for whioh samples or reports have been provided by other workere. Ielands mentioned in the text are ale0 shown.

common species with emphasis on numerical aspects, have provided information on the mechanism of population regulation which is very . relevant t o the main objective of this work. From these various approaohes it has been possible t o f m u l a t e a hypothesis to account for the distribution and abuhdance of lakedwelling triclads in Britain, and this seems a suitable point at which to report progress. The adequacy of the hypothesis cannot finally be judged until the third stage of this programme, the testing of the hypothesis by laboratory and field experiments, has been completed.

T. B. REYNOLDSON

4

11. THE TAXONOMY OF THE TRICLADS The four species of triclad mainly involved in this work are Polycelis nigra (Miill.), P . tenuis Ijima, Dugesia lugubris (0. Schmidt) and Dendromelum lacteum (Miill.) (Fig. 2 ) . Phagocata vitta (Dug&) is also reported in the field work and although it has a characteristic distribution no further work on it has been done in Britain, but Gislh (1946) and Dahm (1949) have studied it in Sweden. Bdelloce.phala punctata (Pallas), Planaria torva (Mull.) and Dugesia tigrinu (Girard) have been recorded also but from too few lakes to provide any substantial clues to the factors concerned in their distribution. Crenobia alpina (Dana) and Polycelis felina (Dalyell)more typically stream species, have also been recorded from lakes in Scotland and while this^ was probably related to temperature in some way (Reynoldson, 1953),no further work on this aspect has as yet been attempted. There has been confusion over the taxonomic defhitions and identification of several of these species but the position has been greatly clarified during the last five years. Originally, Polycelis nigra and P . tenuis were confused but gradually from the work of Komarek (1927), Lender (1936), Lepori (1950, 1955), Reynoldson (‘1948, 1958a), Lender andMoigne (1960),Moigne(1962),Melander(1963),andBenazzi (1963a), these two species can now be recognized easily by penis structure.

Pp

.9m

Po&cefis nigra

Polycelis fenuis

Dugesia lugubris

Dendrocoelum /acfeum

Pbogocofo ViffO

FIQ.2. The five lake species of triclad; vertical linen show the relative, average size of adults.

L-4KE DWELLING TRICLADS

5

Benazzi (loc. cit.) has reported that they are able to interbreed in the laboratory but this is not our experience with British material. There can be no doubt that they are good species on morphological, cytological and ecological grounds. I n the numerous habitats where they occur together the populations remain distinct even to their epizoic fauna (Reynoldson, 1956a); M. Benazzi (private communication) has recently agreed to this view of the situation in nature. Melander et al. (1954) reported a new species Polycelis hepta closely related to P . tenuis but differing from it in the absence of adenodactyls* and in possessing a haploid chromosome number of 7 compared with 6 in P . tenuis. However, the recent work of Lender and Moigne (1960), Moigne (1962), and Benazzi (1963a), has shown conclusively that interbreeding takes place and the occurrence of adenodactyls is not related strictly to chromosome number. Therefore, P . hepta can no longer be regarded as a good species. How the ecology of the different karyotypes varies is not known. Confusion has also been rife over distinctions between Dugesia lugubris and Dug. polychroa (0. Schmidt). Funaioli (1951) on the basis of morphological examination concluded that they were the same species, with lugubris as the correct specific name. However, the extensive work of Benazzi (e.g. 1957) and his school has shown the complexity of the situation by recording several karyotypes in this species-complex and he recommended (1963b) that the distinction in Schmidt’s sense (1860) should not be retained. Dendrocoelum lacteurn has been a less controversial species and identification is straightforward. Undoubtedly there are several karyotypes in some of these species, but Dend. lacteum has been recorded only in the diploid condition (Dahm, 1961). Polycelis nigra occurs mainly in the diploid condition with 2n = 16 (Melander et al., 1954; Moigne, 1962),but Benazzi (1963a) has also recorded a triploid variety. Polycelis tenuis is more complex, possessing two haploid chromosome numbers of 6 and 7 with triploids built onto both (Lepori, 1955;Moigne, 1962;Benazzi, 1963a).Asummary of the karyotypes in Dugesia lugubris is given in Benazzi (1959) and this species seems the most complex of the Planariidae considered here. All the British material of this species which has been examined except one population from N. Ireland belongs to either Biotype B or C of Benazzi, a triplo-hexaploid (Magagnini, 1961; M.-Benazzi, private communication). The polyploid races of these three species generally reproduce by pseudogamic development of the oocytes, i.e. sperm from another individual is necessary to stimulate development of the egg but no fusion of chromosomes occurs. * Pear-shaped glandular structures opening into the genital atrium.

6

T. B . REYNOLDSON

This complex situation in the Planariidae raises problems in ecological work as was appreciated by Dahm (1958) who was dealing with stream-dwelling species which show similar conditions. Obviously, it is too laborious to examine the cytology of every individual or even a part of every sample. Nevertheless, it is likely that different karyotypes will show some contrast in their ecology as already demonstrated by Dahm (1955) for Dugesia tigrina and by Mirolli (1961) for Dug. Zugubris in Lake Maggiore. The latter concluded that the triploid races of this species were likely to replace the diploid as seems to have happened in P. tenuis (Melander, 1963). This is a problem common in ecological work and further complicated by the fact that the genetic complex of populations is changing all the time a t varying rates depending upon the species and the habitat. The only practical approach with our present meagre knowledge of triclad ecology is to ignore intra-specific differences for the time being until the main outlines of the ecology of the species themselves are known. Anomalies which have already appeared in distribution and may well stem from contrasts of this kind, can be examined more profitably a t a later date. The life-cycles of these four species are similar in outline and reproduction is only of the sexual or pseudo-sexual type. Although asexual reproduction by fission has been reported for some races of P. nigra this has not been observed in British populations to any marked degree. The young which hatch from cocoons attached to the substratum are some 2 to 4 mm long and replicas of the adult, except of course in their immaturity. The breeding seasons of these species overlap but each has a characteristic peak period, and the effect of temperature upon the life-cycles differs to a variable degree according to species (Reynoldson et aZ., 1965; Table V).

111. THEPATTERN O F DISTRIBUTION A N D ABUNDANCE A.

INTRODUCTION A N D FTELD METHODS

This facet of triclad ecology can be treated at several levels. Distribution among the various habitats to be found in most lakes is one approach which has been studied to some extent. A second is to compare triclad populations in lakes of varying type without regard to specific habitat, while a third method would be to study lakes of contrasted productivity and restrict the observations to one type of shore. Since the complexity of factors was likely to be formidable in any case, the last approach which reduced some of them, seemed most appropriate. Although lakes may be classified in different ways, one of the most fundamental is that based on the type of rock in the drainage area. Hard rocks give rise to chemically poor water and lakes of low

PL.~TE 1 . (a) Stoiiy shore typical of those used to obtain data on triclad distribution and abundaiire. (b) An upland unproductive lake (LIyn Idwal. ralciurn 1.5 iiig/litre) in t,he Siiowdonia area of Nort,h Wales whirh did not support a trirlud population. ((b) and ( r ) reproduced with permission of the Commit,tee for Aerial Pliot,ography, University of Cambridge.) [to face pl-ge 6

PLATE1. (c) Productive lakes (foreground Lake Feneinere. calcium 93 Ing/litre) in Shropshire supporting H. large and varied triclad population.

L A K E DWELLING TRICLADS

7

productivity, soft rocks to chemically rich water and lakes of high productivity (Mackereth, 1957) (Plate 1, b, c). This broad relationship is modified by other factors such as shape, depth, aspect (Gorham, 1958), and often by human activities which always complicate interpretation of field work. The preliminary work showed that all the triclad species required resting sites providing shade. They were also most numerous in shallow water, scarce or absent when the edge of the lake was undercut and leading directly into deep water. Sandy shores were unfavourable, probably due to abrasion. The basic requirements are best met either by a shore with semi-emergent vegetation such as Yellow Flag (Iris pseudacorus, Linn.), Potamogeton or Water Lily (Nymphaea sp.) etc. which would normally be found growing on a soft substratum or by a stony shore. While the presence of vegetation usually means a sheltered habitat, a stony shore may be either exposed or sheltered to a varying degree. Exposure is unsuitable for lake-dwelling triclads because of the danger of crushing by shifting of the substratum under wave action (Beauchamp, 1932); their food supply is limited in a similar way. The effect of shelter and exposure upon these triclads was shown clearly in a! large lake such as Windermere where an exposed stony shore yielded only single specimens of two species, while a sheltered stony shore harboured the four main species in large numbers. I n some small lakes the effects of exposure can be very apparent. For example, in Shaw Lough (County Armagh, N. Ireland) triclads were absent from the stony shore exposed to the prevailing wind, whilst a sheltered shore with stones yielded a population of 282 collected per hour comprising three species (Reynoldson, 1968a). Such examples could be multiplied. In deciding between a shore of emergent vegetation and a stony shore for routine sampling, the most important criterion was amenability to quantitative sampling, but availability of shores was also important. Stony shores of comparable type are characteristic of oligotrophic lakes and are to be found in about half of the eutrophic lakes, the opposite is roughly true of plant dominated shores. In amenability to sampling, stony shores are superior. The species composition and the concentration of plants vary and the vegetation cannot be so easily searched, features which complicate any standard sampling technique; also such shores are usually less accessible. For these reasons a moderately sheltered, stony shore was preferred as the standard type for routine sampling (Plate la). Before finally deciding on a stony shore the habitat had to be tested to see whether it would bias the data in favour of a particular species. During the preliminary field work both types of shore were sampled in a number of lakes. The results showed that none of the four species

8

T. B. REYNOLDSON

had any preference for either type; a single leaf, stem or stone was often found carrying the four species. These initial observations have been supported by all later sampling and the results of surveys made by other workers, e.g. Berg (1938). Mirolli’s data (1961) for the distribution of Polycelis nigra, Dugesia lugubris and Dendrocoelurn lacteum in Lake Maggiore have been analysed from this aspect. His main variations in conditions were between exposure and shelter, between muddy, sandy and stony substrata. He found triclads in general most abundant on relatively sheltered, stony shores. When the distribution of the various species was analysed by a x2 test incorporating Yates’ correction it was found that this differed very significantly from random (P < 0.001); all three species tended either to occur together or to be absent. A major contribution to the value of x was derived from one cell where the expected number of negative values was low, but those actually observed were fairly high. However, if the contribution from this cell is omitted, x2 still had a significant value (P < 0.01 >0.001). Such a result supports the observation that when these species of triclad are present in a lake they occupy the same habitat. In this sort of approach the larger the number and the greater the variety of lakes it is possible to include, the better is the chance of detecting pattern. This prohibited using a boat and meant restricting the sampling to shallow, littoral zones which could be reached from the shore. Actually, our experience suggests that shallow water up to a depth of about 1 f t (30-5 cm) is the optimal zone for all these species, especially on sheltered, stony shores. In exposed places they may be concentrated in deeper water. These triclads follow changes in water level quickly (Beauchamp, 1932; Taylor and Reynoldson, 1962), and I have observed both species of Polycelis on stones overlying grass several metres from the original level within 12 h of flooding. They do extend into deeper water as shown by Berg (1938) but not into the sub-littoral (Humphries, 1936; W. J. P. Smyly, private communication). Although the data for stony shores reveal that the four species occur at approximately the same depth and zonation is not pronounced, Chodorowski (1959, 1960) studying vertical distribution in a lake with a mud or sand substratum and a rich flora found some evidence of zonation related t o plant type. In selecting lakes for quantitative sampling, size is important for several reasons as Gorham (1958) has shown. Large water bodies such as Windermere and Loch Lomond not only provide more varied habitats than smaller lakes because of changes in soil type along the shore with accompanying changes in the flora, but there is also greater variation in severity of wave action and other factors. It is also more difficult to select the most appropriate shore without a lengthy search.

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L A K E DWELLING TRICLADS

For these several reasons data from large lakes are not included in the routine samples. In practice, the upper size limit of lakes for sampling was taken as approximately 640 acres (259 hect.) and large ponds were taken as the lower limit; Table I gives size data for most of the places included in the quaiit>itativesampling. Even in small ponds the abundance and species composition of the triclad fauna are not restricted as, for example, appears to be so for molluscs and leeches (see Macan, 1963). Thus all four were often found in abundance in ponds only a few m2 in area. But the shorter duration of small ponds may mean less opportunity for triclads to reach them and such faunas may have a greater element of chance in their composition than those of larger places. Lakes in use as reservoirs were avoided because of rapid changes in water level which can affect the whole fauna (Hynes, 1961). Recent, artificial water bodies were also disregarded although a few may not have been recognized as such and inadvertently included. T A B L EI The Range of Some Physical and Chemical Features Indicated by a Sample of 100 Lakes Included in the ~Yurve~y Acres

Size Hectares

Altitude lakes

~~~

<4

244

10-34 35-69 70-145 > 145

4-13 14-27 28-59 >59

33 -3 19.8 9 -4 13.5

Calcium concentration &: lakes mg/litre ~~

<2.5 2-6-5.0 5.1-10.0 10*1-20.0 20.1-40.0 >40-0

-

21.4 18.4 17.3 13.3 17.3 12.3

Metres

yo lakes

0-76 77-152 153-228 229-305 306457 458-610

42.4 26.8 17.1 7.1 4 -0 3.0

~~

< 10

-__

Feet 0-250 251-500 501-750 751-1000 1001-1500 1 501-2 000

Total Dissolved Matter mg/litre yo lakes

-.

&50 51-100 101-150 151-200 201-250 > 250

21.3 24.0 24.0 16.0 8 -0 6.7

In planning field work and selecting lakes for sampling, attention was paid not only to lake size and history but also to situation vis it vis soil type and altitude, to provide n range from low to high productivity (Plate 1 , b, c); accessibility wits also a practical consideration. The ideal collecting site was one in which the shore was reasonably sheltered, sloped gradually and had a substratum ofstones about 6 in (15 cm) diameter

10

T. B. REYNOLDSON

(Plate la). It is clear that no two lakes are identical in all these qualities and it was necessary to depart from this ideal to some extent otherwise too few lakes would have been available. However, if a moderately sheltered shore and shallow water less than 1 ft (30.5 cm) deep were absent or the stones were all very small ( <3 in, G7.5 cm), or very large ( 2 8 in, 2 2 0 cm), the lake was omitted from the quantitative work. Such lakes left out for these reasons were included in qualitative sampling if otherwise they provided a suitable habitat for triclads. The sampling method had to be simple, not requiring any previous visit or any complex bulky apparatus, applicable to limited variation in size of stone and able to provide an adequate number of triclads. After experimenting with various methods including trays, baiting and timed hand collections, the last was found to be most reliable. It enabled a wide area of shore to be examined which helped to even out local concentrations of triclads. The time of collecting could also be adjusted to population size so providing 50-100 specimens for analysis. A basically similar method has been used successfully in other investigations, e.g. by Macan (1950) for molluscs and by Mann (1955) for leeches. When triclads were scarce, collecting was continued up to a maximum of 1 hour and if none were found they were recorded as absent. For comparative purposes the data were converted into number collected per hour. Since much practice in this sort of collecting had been experienced prior to routine sampling, it is unlikely that the data were influenced by an improving rate of collecting-a common danger. However, the method suffered from some drawbacks. For example, as the actual population increases, relatively more time is spent transferring triclads from stone to jar. This is akin to the artificial predatorprey situation analysed by Rolling (1959) and a similar relationship was found between the real population and the number collected per hour, as Holling found between predation rate and prey number (Reynoldson, 1958a, Table 2). The divergence between an estimated triclad population and the real one became large when the collecting rate exceeded 400 per hour. However, the majority of the populations (90%) were below this value, most considerably below, so that the error from this source is not extensive. Other drawbacks arise from the fact that usually only one sample was taken from each lake thus no confidence limits can be calculated. Reproducibility was tested by taking three sets of samples from each of eight lakes in Anglesey during spring, summer and winter and examining rank correlation. It might be added that this was a stringent test since, apart from one lake of low calcium and total mineral content, the rest had fairly high values in the range where experience had indicated already that there would be no marked effect on the triclad population. The spring and summer samples showed a rank

L A K E DWELLING T R I C L A D S

11

correlation positively significant at the P = 0-02 level. The correlation between winter and eit,her spring or summer was l ~ s i t i v ebut not significant. The species composition of each triclad fauna was identical in each season. Lakes in Snowdonia have also been sampled several times and given comparable estimates of population size and the species composition has always been the same. A further potential drawback with a single sample is possible variation in the size of the population over the year. This was minimized by restricting routine sampling to the summer months and in any case seemed to be an unlikely source of large error because study of the population dynamics of the planariid species (Reynoldson, 1980, 1961a; Taylor and Reynoldson, 1962) has shown that annual changes from births and deaths were around 50%; they were larger in Dendrocoelum lacteum however, up to 500%. This argument was supported by the data from Anglesey lakes which showed only small variation in amplitude from season to season. It seems reasonable to conclude that this simple method of estimating populatioii size and species composition in triclads was adequate for the purpose of examining trends in distribution and abundance. Clearly, it is insufficiently sensitive to compare individual lakes, especially those close together on the chemical spectrum and it has not been used for this purpose. During the search for triclads, other organisms found on the stones were noted or collected for identification. Samples of water for chemical analysis were taken at the same site lts the triclad sample. Again, only single samples were taken and what has been said about the reliability of the triclad method applies here but there is no doubt that the chemical samples have a narrower range of variability as the Anglesey data showed (Reynoldson, 1958a). It has also been possible to compare our measurements of various ions with those of other workers (e.g. Gorham, 1957, on the Shropshire meres) and there was reasonable agreement. Further, the data of Tucker (1958) and Olsen (1955)indicated that the range of values over a season would not substantially alter the ranking of lakes within a season. Of the several analyses, calcium and total dissolved matter have been most illuminating. I n considering anomalies it has sometimes been useful to look a t other chemical features such as for example, magnesium, chloride, oxygen uptake from permanganate. An indication of the range in chemical qualities of the lakes is given in Table I. Under favourable conditions five or six lakes could be sampled in one day and still leave time for examination of material in the evening; triclads were generally identi6ed on the day of collection. Dugesia lugubris, Dendrocoelumlacteum and Phagocuta vitta are identifiable by eye or lens, but with Polycelis species the large specimens had to be squashed and

12

T . B . REYNOLDSON

the penis examined under the microscope to separate tenuis and nigra. Sma.11 specimens of Polycelis were allocated to species according to colour pattern. Of t'he numerous P. nigra populations which have been collected only one has been found in which the colour was sufficiently mottled to confuse with P. tenuis and this lived in brackish conditions near Cullercoats, Northumberland. Mostly P. tenuis are mottled though several uniformly black populations, indistinguishable from P. nigra externally, occur in the more northerly parts of Britain.

B.

RESULTS

The data from areas showing a restricted triclad fauna have been omitted from immediate consideration since they could be misleading in both the qualitative and quantitative contexts. Thus the proportion of lakes occupied by a particular species would be affected and any competitive element absent or reduced. In addition, size differences in the adults would influence quantitative relations. The three main areas sampled with such a restricted fauna were the islands of Anglesey off the Welsh coast, Islay off the west Scottish coast, and the extreme north of Scotland beyond the Highland Fault (Caledonian Canal) (Fig. 1). The results from the lakes in these three areas and from the two large lakes of Windermere and Lomond are used to illustrate special aspects (pp. 27, 30).

1. The Distribution of the Species Data from 107 lakes considered here are derived mainly from midand north Scotland (34),N. Ireland (19), the Snowdonia area of N. Wales (29), Shropshire (12), the Lake District (11) and two Y'orkshire lakes. They show a wide range of physico-chemical properties from high lakes in Snowdonia to lowland lakes, from those with hardly a trace of calcium to those with large amounts (Plate l , b, c). The distribution of these lakes based on calcium content of the water is shown below: Calcium mg/litre

No. of lakes ~~

G2.5 2.51- 5.0 5.1 -10.0 10.1 -20.0 >20.0

33 12 20 1.2 30

In analysing the triclad data special attention was given to calcium because of the many studies of the distribution of other organisms in relation to this ion (see Macan, 1963). Total dissolved matter could have

13

L A K E DWELLING TRICLADS

been used equally well, and from some aspects is more suitable. Figure 3 presents species distribution in relation t o the amount of calcium present in the water and a distinctive pattern emerges. There were some 12% of the lakes without triclads, and all had a calcium content less than 5.0 mg/litre and most were less than 2 - 5 mg. Of the five species, Phugocatu vitta had the most striking distribution since i t was confined to lakes with less than 2.5 mg/litre of calcium and occurred in only 26% of these. One characteristic feature of lakes supporting this species was that they were usually fringed with wet areas containing Sphagnum. Indeed, Ph. vitta is almost terrestrial, in the sense that it occurred in large numbers in wet peaty soil and did not require the presence of surface water (H. B. N. Hynes, private communication; GislBn, 1946). The factors underlying the distribution of Ph. vitta in lakes have yet to be studied, but Dahm (1949) has discussed lotic habitats of this species. The distribution of Polycelis nigru contrasts with that of Phqocata. It was the most widespread of the five species in relation to calcium concentration, occurring in lakes with as little as 0.6 mg/ to those with over 100 mg/ litre. The distribution of Polycelis tenuis was similar to that of P. nigra except that i t did not extend into such calcium-poor waters. The lowest 0.25

0.50

I

Phogocata vitta

i

I Ill

Po/uce/is nigro

rh'

I.00 I

2.50 I

5.00 I

I Ill I l l 1IlI

10.0 I

20.0 I

100.0

50.0 I

I RI I II I 1I II I 1I rlllolrlllll~lllllIIlllln1A11111 I I

II

I

I1

I i I I I i~ IIIIIIIiIIIlIi II II IIIIII IIIIII II 1111

Po/uce/is fenuis

I II Ill II I I111111llI I I 11111

Dugesia /ugubris

Dendrocoelurn lacteum 0.25

I 0.59

1

1-00

I 2.50

I

I II I1 u I I 1I11UI 11111 I 11111 I

I

5.00 10.0 20.0 Calcium mg / litre - logarithmic scale

I 50.0

J

100.0

Fro. 3. The distribution of triclads in relat,ion to calcium. hach v e r t i c a l l i n e represents one lake; broken lines indicate the occurrence of Polycelia tenuia in lakes where P . n@ra was not found.

14

T. B. REYNOLDSON

limit recorded was 1.6 mg/litre whilst only 5% of total occurrences were below 5 mgllitre compared with 22% for P. nigra. The distributions of Dugesia lugubris and Dendrocoelum lacteum were so similar that they can be considered together. Both species were absent from lakes low in calcium. Only a single occurrence was found below 5 mg/litre, at 4.8 mg/ in Newton Mere, Shropshire, and this may be exaggerated since Gorham (1957) recorded 7.4 mg/litre. Eighty per cent of the records were from lakes with more than 10 mg/litre; comparable figures for P. nigra and P. tenuis were 30% and 40% respectively. When the distribution of these triclads was examined separately in the four main areas they showed the same pattern except that each presented a less complete picture (Reynoldson, 1958b). For example, most of the Snowdonia lakes fell into the range with a calcium value less than 5 mg/litre while the Shropshire meres lay a t the upper end of the range. Table I1 presents the data in summary form from a slightly different approach, showing the proportion of lakes occupied by the various species in particular calcium ranges. Polycelis nigra is seen to occupy a gradually increasing proportion of lakes reaching a peak of 94% in the calcium range 5-1-10.0 mg/litre but above this its incidence declines and it occurs in only 72% of the lakes in which calcium exceeds 20 mg. In contrast, P. tenuis although starting off at a lower level of incidence continues to increase until in the richest lakes it is universally present. Dugesia lugubris and Dendrocoelum lacteum both tend to occur in a higher proportion of lakes as the calcium increases but their maximal incidence is about 70%, i.e. neither is quite so well dispersed as the Polycelis species, even in the most favourable lakes. TABLEI1 Percentage Distribution of Triclads in Relation to Ca,lciunz Concentration of Water Calcium mg/litre

Species Absent Phagocata vitta Polycelis nigra Polycelis tenuis Dugeaia lugubris Dendrocoelum lacteum Total lakes

<2.5 26% 26% 44% 6% 0%

0%

33

2.6-5.0 36 %

5*1-10.0

64% 27% 9% 9% 12

94% 82% 29% 24% 20

0%

0% 0Y O

10.1-20.0

0% 0%

82% 91% 36% 36% 12

>20.0 0 0% 72%

looyo 69 % 66% 30

Total lakes 13 9 68 58 30 28 107

Calcium has been selected as a convenient framework within which to describe the distribution of these triclads, but an equally convincing pattern also emerges in relation t o ttotal dissolved matter.

LAKE DWELLING TRICLADS

15

2. The Abundance of l’riclads A stricter selection of lakes was necessary to maintain comparability of collecting sites. This reduced the original number of 107 to 68 of which 22 were located in Mid-Scotland, 6 in N. Scotland extending to the Highland Fault, 18 from N. Ireland, 16 from Snowdonia and 6 from Shropshire. The samples measured the standing crop of triclads, and since the Total Dissolved Matter (abbreviated later to T.D.M.) is a more reliable indication of productivity (Larkin and Northcote, 1958; Rawson, 1960) than calcium, this parameter has also been related to triclad abundance. Data for T.D.M. were available for only 44 of the 68 lakes which were about equally divided between Mid-Scotland, N. Wales and N. Ireland. The ranges of the physico-chemical properties of the lakes used here were similar to those already outlined in considering distribution. i. The Total Population. Scatter diagrams in which total numbers of triclads collected per hour are related to calcium and T.D.M. are shown in Fig. 4 and 5. The regression coefficients measuring both relationships are highly significant (P < 0-OOl),nevertheless it is apparent that these chemical factors only account for a part of the variance (especiallywith calcium) and other factors apart from sampling errors, are important. This is not surprising in view of the complex of factors involved. These may be regarded as operating at three levels, basic physico-chemical factors, primary production and secondary production, all of which can be expected to influence organisms like triclads which are at or near the apex of a food chain. While T.D.M. will be usually closely related to productivity of the littoral zone there may be exceptions since as Margalef (1958) pointed out, it is phosphate and nitrate which normally determine primary productivity and these form only a small part of T.D.M. There is also some evidence that very dystrophic conditions are related to low triclad populations independently of calcium and T.D.M. Consideration of some of the more striking exceptions to the trends shown in Fig. 4 and 5 indicates some of the contributory factors. For example, there is a group of lakes at the lower calcium and T.D.M. levels which either do not support a triclad population at all or only R relatively small one. These are mainly lakes at the higher altitudes, nnd clearly such adverse factors as low winter and spring temperature and a short summer are reinforcing the effect of low productivity. Newton Mere (Fig. 4 ~ is) also exceptional not only in supporting a relatively high populat,ion but also in containing Dugesia lugubris and Dendrocoelum lacteum although the calcium content is only 5 mg/litre. This lake, on slightly higher ground than the others, was surrounded by good agricultural land with a thin belt of deciduous trees along one

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T. B . R E Y N O L D S O N D

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FIQ.5. The relationship between the total triclad population 4nd the Total Dissolved Matter content (TDM) of the water; the regression line is also shown. Unfilled circles refer to lakes >500 f t ( > 152 m) above sea-level. E, Loch Camilla; F, Loch Kinghorn; other letters as in Fig. 4. Location of lakes shown in Fig. 2, Reynoldson (1958a).

LAKE DWELLING TRICLADS

17

margin, but the calcium content was surprisingly low compared with surrounding nearby lakes, e.g. The Mere, Ellesmere with 32 mg/litre calcium. Gorham (1957) who recorded 7 - 4 mg/litre of calcium suggested geological and hydrological reasons for tthe low mineral content of this lake. It is probable that plant and animal material from the terrestrial zone increases the productivity of the littoral zone so that it is higher than would be judged on water chemistry alone. Lakes Lurgan, Marlacoo, and Lowry (Fig. 4, B, c, D ) all in N. Ireland also support an exceptionally high population; indeed the Irish lakes nearly all tend to have a high population relative to the other areas especially Scotland, suggesting that it is perhaps unrealistic t o group them together (Reynoldson, 1958a). However, even within the Irish area, these three lakes have higher than average numbers of triclads, especially measured against calcium. The first, of these was undoubtedly enriched by organic waste from the township of Lurgan, while the other two had farm buildings near the shore from which nutrient-rich water drained into the lakes without noticeably increasing calcium or T.D.M. ;increased productivity from such sources is well known (Hasler, 1947; Mundie, 1957; Berg, 1958). The reasons for exceptionally low populations at high calcium and T.D.M. levels are not obvicus, but the two most striking examples (Fig. 5, E, F) are both in the Scottish area surrounded by land which was noL intensively farmed. When the main areas are considered separately in the present context they all show highly significant relationships between the standing crop of triclads and calcium, T.D.M. and altitude (Table 111). There is of course an obvious reason for the relationship with altitude since high ground usually means hard and insoluble rocks (Mackereth, 1957). This is made clear in Table I I I b where the regression coefficients between T.D.M. and altitude are shown to be negative and highly significant except for the N. Wales area. The latter result is explained by the circumstance that most of the lakes a t lower altitudes occur in narrow valleys flanked by high ground and have a resultant low T.D.M. It will be difficult to separate the influence of two such intimately connected factors as altitude and water chemistry upon the distribution and abundance of triclads, but the results from the low-lying lakes of Islay showed that calcium and T.D.M. per se can be related to triclad abundance (Reynoldson, 1958a). The adverse effect of altitude in the presence of high calcium was indicated by the relatively small triclad population restricted to P . nigra, found in Malham tarn (W. Yorks) at 1 2 5 0 f t (381 m) with 48.8 mg/litre calcium. ii. The Populations of the Individual Species. 117 analysing the changes in population size of the individual species, the 68 lakes have been grouped into categories based on calcium content and the population of

TABLEI11 (a) Regression Coeficients for the Relationship between Triclads, Calciwn, Total Dissolved Mutter, und Altitude Scotland

Reg. coeff. S.E. of R.C. Probability

AltiCa T.D.M. tude 10.00 1.090 -2.240 2.25 0.189 0.256 <0*001 <0*001 <0*005 >0*001

N. Ireland

Ca

7.78 2.93 <0*01 >0*005

AltiT.D.M. tude 3.400 -9.30 0.554 1-22 <0-001 <0.001

N. Wales

Ca

17.90 4.29 <0*005 >0*001

T.D.M.

2.051 0.626 <0.01 >Om006

Total Altitude 0.709 0.244 <0-02 >0*01

Ca 5.82 1.03 <0*001

(b) The Relationship between Altitude and Total Dissolved Matter ~~

Reg. coeff. S.E. of R.C. Probability

Scotland

N. Ireland

N. Wales

- 1-140

-2.552 0.293

-0.162 0.105 >0*1

0.365

<0-01

>0*002

<0*001

T.D.M. 1.881 0-272

<0*001

L A K E D W E L L I N G TRICLADS

If)

FIG.6. The average abundance of the individual triclad species and the total population related to the calcium content of the water. Dotted lines represent samples for a single lake.

each species averaged. Figure 6 shows the arithmetic means (examination of the data on a logarithmic basis showed no important difference) and indicates that in lakes with less than 5 mg calcium/litre Polycelis nigra was the most abundant species, P. tenuis was able to maintain a foothold with small populations in a few lakes (cp. Fig. 3) whilst Dugesia and Dendrocoelum were absent with the exception of the unusual Newton Mere”in Shropshire. Above 5 mg calcium/litre, there was a dramatic change in the distribution of the Polycelis species. Instead of following the general trend of increase in population, P. nigra was overtaken and substantially passed by P. tenuis which showed a fourfold increase. Dugesia and Dendrocoelum were able to maintain small populations in this range. With calcium between 10 and 20 mg the total population increased markedly mainly because of larger numbers of P. tenuis, although the other species contributed, especially Dugesia and Dendrocoelum. F’rom 20 mg/litre upward P. nigra showed a decline in numbers which was paralleled by the occupation of a smaller proportion of lakes (Table 11),whilst the other species increased both in numbers and the

20

T. B . R E Y N O L D S O N

proportion of lakes occupied. To summarize, a t low calcium levels Poly celis nigrrr m:iint:iined the highest population, whilst ; I t intermediate levels and higher, I‘. ten& was nndoubtedly the dominant species numcrically. 1)icyesirr lirguhris and 1)endroco~lumlacteuru only formed a numerically important component when calcium exceeded 20 mg/litre. This analysis is based upon numbers, but as adult Dugesia and Dendm coelum arc several times larger than adult Polycelis, in terms of biomass the former two species would form a larger part of the total population and together would sl)proximately equal the biomass of the Polycelis species in the highest calcium lakes. Also, whilst the total number of triclads reached a maximum a t 20-40 mg/litre of calcium, in terms of biomass a continuing upwtird trend would be shown throughout the entire range (Fig. 6 ) . iii. Conclusions and Summary. It has been showu that the standing crop of triclads became larger as the calcium and T.D.M. concentrations of lakes increased. I n lakes with calcium concentrations of 20 mg/litre and upwards, all four species regularly coexisted, but as the concentration declined below 20 mg, Dugesia lugubris and Dendrocoelum lacteum occurred in fewer lakes and in smaller numbers; below 5 mg they were usually absent. Polycelis tenuis was the most abundant species from the highest range down t o 5 mg/litre of calcium and persisted in a few lakes below 2 - 5 mg/litre. At 5 mg/!itre and lower, P. nigra was numerically the dominant species. An explanation of this natural pattern is the main purpose of this account. The pattern differs from that of many other organisms in showing the co-existence of several species a t one end of the series, whilst as the other end is approached, all the species are gradually eliminated. Most other natural distributions within a restricted habitat, whether of vertebrates or invertebrates, terrestrial or aquatic, usually depict only one of these situations (Andrewartha and Birch, 1954; Hutchinson, 1961; Macan, 1963).

I V . HISTORICAL ASPECTSO F DISTRIBUTION A N D ABUNDANCE I n considering the factors which underlie any pattern of distribution, it is necessary to ask the question, how far it reflects opport’unity for dispersal and how far it is the outcome of interaction among the physico-chemical and biotic factors of the environment,. This is especially pertinent for lake faunas where habitats tend t o be more isolated and temporary than most others so that dispersal may be relatively more important. Talling (1951) with reference t o ponds, reached the general conclusion that physical barriers “do not modify Nature’s habitual abhorrence of the ecological vacuum”. His view is similar t o that

LAKE

n WE LLI N G

TR I C L A D S

21

expressed earlier by Gurney (1916), Boycott (1936), Macan and Worthmgton (1951) and latterly reiterated by Macan (1963). However, the point must also be made that the rate of dispersal of any species will be characteristic of and determined by its particular ecology. All are agreed that species may be absent from a suitable habitat simply through chance. Moon (1957) has suggested that chance has played the most important part in the distribution of Asellus in the north of England but his argument has been refuted (Reynoldson, 1961b; Williams, 1962a). Another aspect which must be considered is that a species or a group of species may be extending their range and any discernible pattern may be only a temporary phase determined largely by historical rather than ecological events. In a sense, this is true of all organisms if the time scale is of geological dimension, but here we are considering a lesser scale, which can be termed “ecological” time. Some evidence of what is happening in lnke-dwelling triclads can be obtained by comparing the faunas of the western islands and the extreme north of Scotland with those of the mainland of Britain and of Ireland. I n producing what may be regarded as a typical fauna, the data for those areas known to contain all four species have been lumped together (i.e. the faunas of lakes bhown in Fig. 3). Obviously, in any comparison of this averaged fauna with that of another area, the proportion of lakes in the various categories based on water chemistry will influence the data, as seen from Table 11. To overcome this, lakes have been d:vided into two groups, those with G7.5 mg/litre of calcium, which might be expected to support mostly Polycelis species, and those with > 7.5 mg/litre calcium which might be expected to support the four species. Table I V compares the percentage occurrence of the triclad species in a typical fauna and the combined data for the similar faunas of Anglesey off the North Wales coast and Islay off the west Scottish coast. Also shown are corresponding data for an area north of the Highland Fault. I n the island lakes with <7-5 mg/litre calcium it is apparent that Polycelis tenuis is under-represented; the apparent over-representation of P. nigra is due to the fewer low-calcium, high-altitude lakes in these islands. This trend of scarcity of P. tenuis is made abundantly clear in lakes with >7.5 mg/ litre calcium. Dugesia and Dendrocoelum are also under-represented in the higher calcium lakes of Anglesey and Islay, being altogether absent in the former and represented by a single specimen found in Loch Finlaggin on Islay. This scarcity of species other than P. nigra was amply confirmed from the examination of lakes and ponds on other, smaller western islands. For example, in a total of seventeen lentic habitats containing triclads on Skokholm, Bardsey, Isle of Man and Lismore (Fig. l),most with 2 1 0 mg/litre calcium, all records referred to P.nigra. When details of the six lakes, two on Anglesey, four on Islay, which B

22

T. I3. R E T N O L D S O N

TABLEI V d Tgp'icul Y v i c l d E'uicnu C'onipwr~dwith thosc of Auglcsey plus Isla?/,and Scotlad lVorlh of the Fwult (CaledoniarL Canal) Lakes with > 7.5 mg/litre calcium Typical Anglesey & Islay N. Scotland

Species

_ _ _ ~ - ~

Absent Polycelis rcigra Polycelis tenuis Dugesia lugubris Dendrocoelum Euctrii ?ti Total lakes -

Absent Polycelis nigra Polycelie tenuis Dugesia lugubrie Dendrocoelum lacteum Total lakes

24Yo 56% 2OYO

21% 79% 0Y O

4Yo

0% 0Y O

7%

54 _

50 Yo 10%

40YO 0% 0% 10

14

Lakes with > 7 *5mgjlitre calcium

_

0% 74% 94% 52 %

52 % 50

_

~ 0 YO

~

87 % 26% 0Y O

75 % 0 YO 25 % 0%

23

12

4%

0%

supported P.tenuis are examined, we find that they are all well-known trout-fishing lakes which have been stocked from time to time with mainland trout. The four Islay lakes have not only been stocked frequently (Reynoldson, 1958a) but also they lie close together, within a radius of 2 miles. The data for the extreme north of Scotland give an entirely different result. Here, in lakes with G7.5 mg/litre calcium the outstanding feature is the large proportion of lakes which did not contain triclads, and this was even more pronounced in the calcium-richer lakes where 75% lacked a population. It might be emphasized at this point that the same criteria for lake selection were used here as already described (p. 8). The other equally striking feature of these northern lakes is that in the small proportion (seven lakes) which did contain triclads, P . tenuis was the species recorded, a reversal of the situation on the western islands. As noted for the islands, several of the lakes containing P . tenuis are noted trout-fishing places, e.g. L. Heilin (Caithness); L. Hempriggs (Caithness); L. Ussie (Ross and Cromarty); and furthermore the other four are grouped closely around L. Garve (Ross and Cromarty). This evidence for the scarcity of triclads from the extreme north of Britain was supported by data from islands of corresponding latitude. For example, lake-dwelling species were scarce on Rhum, where one lake had a small population of P.nigra and another a population of P.tenui8. None were

LAKE DWELLING TRICLADS

23

found on N. Uist and Harris (R. C. Connolly, private communication); none in several lakes of the more northerly Shetlands (A. Milne, private communication). It seems unlikely that all these lakes were so unproductive that they were unable to support P. nigra a t least. Although details of water chemistry are available for only a few, several had calcium values exceeding 10 mg/litre. Any hypothesis advanced to explain the present-day distribution of triclads must be consistent with the following facts. First, the scarcity of triclads in the extreme north shows that these organisms have not yet occupied to anything like the full extent, the suitable habitats available, and are presumably still extending their range northwards. This is a similar situation to that found for several other common freshwater species, as shown for Gammarus pulex (Reid, 1951; Hynes, 1954); for Asellus species (Williams, 1962b); for gastropods (Hunter, 1957) and for a fresh-water mite (Efford, 1962). Second, it must explain the similarity of the British mainland fauna and that of Ireland; finally, it must account for the restriction of the more southerly western islands to virtually one lake species. Before detailed arguments are attempted, it is necessary to consider the mode of dispersal in triclads. Ullyott (1936) has denied the role of natural transport such as birds, although Thienemann (1950)reported some examples of this and also inferred from the distributions of Crenobia alpina and Pulycelis felina that birds may hare aided dispersal. Arguments for and against birds were also presented by Klie (1926)and Arndt (1924)respectively. The recent studies of Maguire (1963)on dispersal do not offer much support for transport of organisms like triclads by other animals. It appears that the balance of evidence, especially the clear-cut patterns discussed above, is against birds being an important factor in dispersal although they may have been responsible for some introductions (p. 24). It would appear that triclads mainly achieve dispersal by their own activities (Gislbn, 1946; Dahm, 1949); although the latter attributed some importance to passive transport. The most significant feature of the geographical distribution of lakedwelling triclads in the British Isles is the similarity of the Irish and mainland faunas, and also the fact that eight of the nine species comprising the entire British fauna are found also in Ireland (Southern, 1936; Reynoldson, 1958a). Bdellocephala punctata is the only absentee. The origin of the Irish fauna, especially the Lusitanian element, has been critically reviewed by Corbet recently (1962) who discussed three main theories to account for it: (a) survival in southern Ireland during the last glacial phase or from an earlier time, (b) post-glacial migration to Ireland via land connections, (c) introduction by man’s trading activities.

24

T. B. REYNOLDSON

Of these (b) is the least likely on present-day evidence of the extent, duration, condition and position of land bridges between Ireland and the mainland. Corbet favoured (c) to account for the Lusitanian fauna. Water for drinking purposes must have been transported often and in quantity by travellers, and triclads, especially the spring-dwelling species, may have been spread to some extent in this way. Fish stocking has undoubtedly contributed also in recent times and probably earlier. Bilge water of ships may be concerned in the dispersal of some aquatic animals (Williams, 1962b)but is unlikely to have been of importance for such delicate organisms as triclads. However, the widespread distribution and large number of species in Ireland argues forcibly against introduction in these accidental ways particularly in view of their slow dispersal on the mainland and the rarity of several species here, although i t is appreciated that they may not always have been ra.re. An important argument against this method of introduction is the fact that both P. nigra and P. felina have not succeeded in reaching Sweden, although both occur nearby on the mainland of Denmark and in Germany (Thienemann, 1950): the commerce across this narrow sea must have always been very heavy. This hypothesis also fails to account for the restricted fauna of Anglesey which lies on one of the trade routes between the mainland and Ireland. Anglesey also furnishes a very convincing demonstration of the ineffectiveness of birds in spreading triclads, since the island is separated from the mainland, where all four species occur, by a strip of seawater only some 300-400 m wide, a separation which has existed since early post-glacial times (Greenly, 1919). Only two lake species, P. nigra which is widespread and P. tenuis found in two lakes, have succeeded in crossing the narrow barrier; the former probably by its own movements before separation, the latter via troutstocking. Furthermore, if this type of introduction is important, Dugesia gonocephala should have been able to cross the Channel and establish itself in Brit,ain, since as Ullyott (1936) pointed out, the climatic and ecological setting i s similar on both sides. But this species has not been confirmed in Britain (Dahm, 1955; Reynoldson, 1956~).I n contrast it might be mentioned that Dugesia tigrina (Girard) has succeeded in establishing itself in some half-dozen places at least in Britain, probably as the result of trade in freshwater fish for aquaria between Britain and the Americas. However, if a narrow belt of seawater such as the Menai Straits between the Welsh mainland and Anglesey is an effective barrier, this raises the problem of how triclads have crossed the main watersheds. If not transported by the activities of birds or man, this leaves their own movement as the most likely explanation. It may be that triclads have crossed the watersheds in the plains where continuity is more likely and then dispersed up river. It is also possible that there have been

25

L A K E D W E LLIN 0 TRI C LA D S

shifts in the direction of How of rivers and correlated changes in watersheds which have permitted dispersal in directions which today appear improbable. But it must be admitted that, as for many other problems of zoogeography, we do not know the answer. Any hypothesis which suggests the survival of organisms in the icefree areas of southern Ireland and England during the last glacial phase must take cognizance of the climatic conditions which prevailed and the ecology of the organisms concerned. I t seems likely (Corbet, 1962;Efford, 1962)that on the edge of the glaciated areas, tundra conditions prevailed with summer temperatures around 9" C! (Ullyott, 1936). This climate would enable the survival of Polycelis nigra, P . tenuis and Dendrocoelum lncteum which can complete their life-cycles over a temperature range of3.5-5.0" C up to 15-20" C (Table V).A!though by comparison Dugesia is a genus more associated with warmer water, Dug. lugubris can breed at a temperature of 10" C and upward (Reynoldson et al., 1965), also it is found in Finland and in Russia near Leningrad (Luther, 1961) with their long, severe winters. It is possible that it could have survived in small numbers a t the extreme southern limit where conditions were probably less severe. In fact, survival of all these triclads may have depended more on the presence of suitable food organisms than on temperature. I n their ability t.0 tolerate low temperature triclads differ markedly from the Lusitanian fauna, and persistence during the last glacial period is much more €easible. Survival of P. felina and Crenobia alpina in Southern Ireland was also the basis of O'Rourke's argument ( 1 946) in refuting Ullyott's (1936) hypothesis concerning t,he use of

TABLEV Temperature Limits in "C of tlbe Various Stages and of the Complete Life-cycle in Dendrocoelum lacteum, Pol ycelis nigra, P. tenuis and Dugesia lugubris (Reproduced with permission from Reynoldson et al., 1965) Deiadrocoelum Polycelis lactezim dgra

Stage

Polycelis tenuis

Duge ai a lugubris

Cocoon production Lower Upper

1-5 18.5

3 -5 18.5

5 *O 20.0

10.0 23 -0

Egg development

Lower Upper

1.5 23.0

1.5 23.0

3 -5 23.0

5 .O 23.0

Maturat,ion

Lower Upper

3 -5 15.0

3-59 18.5

5.0 20.0

10.0 23 -0

Life-cycle

Lower Upper

3.5 15.0

3.59 18.5

5 *0 20.0

10.0 23.0

26

T. B . REYNOLDSON

these species to determine the climatic conditions at the time Britain was separated from the continent. The evidence from lake-dwelling species supports O’Rourke. The other fact which must be fitted into the hypothesis is the virtual restriction of the western island faunas to P. nigra. Accidental introduction may be discounted; the arguments against have already been stated, and to these can be added the uniformity itself, which suggests a natural phenomenon. This means that either P . nigra survived glaciation in these small islands, extending as far north ;t9 Islay, an unlikely event in view of the fact that its limit today is just a little farther north, or that it dispersed more quickly than the others and reached the islands before they were cut off from the mainland by the sea. There is no obvious reason from structure or life-cycle why P. ?zigra should have such an advantage, but if it is supposed that this species was mme widespread and abundant south of the glaciation than the others, just as it is in Britain today especially in harsh habitats (Fig. 3, Table 11),then it may have been able to follow the retreat of the ice more quickly. This would be enhanced by its ability to occupy streams more readily than the others (Reynoldson, 1956b); a view contradictory to that of Beauchamp (1932). Such an argument seems to be the only one which ean be advanced to account for this characteristic distribution and provides support for regarding the present-day pattern as a valid expression of the ecological ranges of these species. The argument developed here presupposes that the western islands concerned (p. 21) were a11 linked to the mainland at one stage after the retreat of the ice, and geological evidence suggests that this is likely except for the Isle of Man; here opinions are divergent (see Williams, 1962b).Such an explanation of the distribution of P. nigra is supported by that of the stream-dwelling Crenobia alpina and Polycelis felina. Both of these are more tolerant of severe climate and poor habitats (Reynoldson, 1961c),and on the same argument might be expected to follow the retreat of the ice even more closely and quickly than P . nigra, so extending farther north. They may even have been able to exist farther north than other species during glaciation and Crenobia alpina has often been regarded as a glacial relict species (Whitehead, 1922; Carpenter, 1928). Their present-day distribution supports such an argument for they occur not only on the western islands supporting P. nigra but one or both also occur on islands slightly farther north such as Mull, Rhum, Canna and Sanday (Bertram, 1939) and on the main Orkney Island and Fair Isle. They have not been recorded from the more outlying islands such as Lewis (Elton, 1936; R. C. Connolly, private communication), N. and S. Uist (R. C. Connolly, private communication) or the Shetlands (A. Milne, private communication). However, C . alpina was found on St. Kilda (J.B. Cragg-

L A K P DWELLING TRICLADS

27

private communication) while P. felina (and P. nigra) was recorded from the Outer Hebridean Island of Barra (Forrest et al., 1936)but the latter identification needs confirming based on the new taxonomy. There are also some records of Crenobia alpina in the Faroes, and Steinbock (1931) very tentatively suggested that it may have been transported to the island on icebergs, but this seems very doubtful. The presence of these populations cannot be explained satisfactorily at present. Triclads appear to be absent from Iceland (Steinbock, 1948). This general scarcity in the outlying islands is interesting since it appears that they have had no connection with the mainland since the last glacial phase (see Corbet, 1961). There are some striking resemblances between the distribution of Asellus (Williams, 1962b) and lake-dwelling triclads in the British Isles which deserve elaboration. The northern extension of both groups is similar in their scarcity north of the Highland Fault; the few occurrences of both organisms are probably due to trout stocking. The Highland Fault is mentioned only as a convenient landmark and it is not suggested that it has operated as a barrier. The most likely obstacle to northward spread is the Grampian Mountains to the south of the Fault which leave only narrow coastal plains on the east side. Another important brake on this movement is the general east-west flow of the main rivers in Britain. The distribution of A . meridianus is very similar to that of Polycelis nigra, each being the only representative on most of the western islands (e.g. Skokholm, Bardsey, Isle of Man) and the common species on Anglesey. It does not however extend so far north as P. nigra, being absent for example from Islay. Williams (ibid.) attributed this distribution to either the survival of the species in southern Ireland and England during the last glacial phase and its dispersal to the islands while land connections still existed by closely following the or to its edge of the retreating glaciers, i.e. as postulated for P. reaching Ireland from the mainland by land connections following retreat of the glaciers. As indicated (p. 24) the latter seems doubtful and unnecessary. Asellus aquaticus resembles the rest of the triclads in having a more restricted distribution which Williams attributed to its later arrival. He expressed the view that it was accidentally transported both to England and Ireland by man. Here events seem to differ from those suggested for triclads where cogent reasons have been advanced against man being primarily involved. The apparently more rapid spread of A . aquuticus compared with trricladsin recent times, probably reflects its greater resistance to desiccation and mechanical damage compared with triclads. A striking contrast to triclads in rate of dispersal is also afforded by the more suitably equipped Hydrobia ( = Potamopyrgus) jenkinsi which has been reported on by Hunter and Warwick (1957).I n general, the distributions of AseZlus, triclads and certain mites

28

T . B . REYNOLDSON

(Efford, 1962), suggest that they have been influenced by the same historical events and physiographical barriers, and they provide evidence of survival of freshwater organisms in Britain during the Ice age, in contradiction to the views of Ullyott (1936) and Thienemann (1950) who argued that Britain was re-colonized from the Continent via land connections after the last glacial period. The difficulties of accepting this have been outlined (p. 24) but the absence of Dug. gonocephala from Britain needs further consideration. It would appear that this species either never reached Britain at any time or failed to survive glaciation. Beauchamp and Ullyott (1932) have suggested that it is competitively superior to C. alpina and P . felina only when summer temperatures exceed 16" C. It is possible therefore that it was eliminated during a glacial period and never succeeded in re-colonizing, but until we know more about the basis of the supposed competition such an argument cannot be taken further. This historical approach, although unavoidably speculative, supports the view that the presenbday pattern of distribution in those areas containing all four species is the outcome of varied ecological attributes and represents a stable condition measured in ecological time. The fact that Dugesia and Dendrocoelum only occupy 70% of the most favourable habitats on the mainland (Table 11)is evidence that even here triclads are still extending their range and conceivably the pattern might alter. However, in N. Ireland where there are no important physiographic barriers, triclads seem to have dispersed more completely and Dugesia has for example occupied all the fully favourable habitats without in other ways altering the pattern. Admittedly this is based on few data, and more extensive sampling especially in Southern Ireland would be instructive. Further support for the reality of the pattern can be derived from triclad distribution in a large lake such as Windermere. Here there is a range of habitats from relatively sheltered, productive bays lined by deciduous trees with a correspondingly richer fauna supporting all four triclad species, to less productive, more exposed places supporting mainly Polycelis species. Thus we see the same pattern in a, single lake, produced by ecological and not historical events.

V. DETERMINANTS OF DISTRIBUTION A N D ABUNDANCE All environmental factors which influence the survival and reproduction of the individual are involved in any explanation of distribution and abundance, they differ only in degree. Andrewartha and Birch (1954) produced a classification of such factors which although criticized provides an orderly approach to the problem and their initial ideas have been further discussed and amended by Browning (1962). This author has classified the environment into five components: wen ther,

L A K E DWELLING T R I C L A D S

-..)

()

resources, numbers of the same species, numbers of other species and hazards. The component “resources” now includes the “food” component, and part of the component, “a place in which to live” of Andrewartha and Birch’s original scheme. While Browning’s arguments for doing this have much to commend them, in the particular treatment of the triclad environment adopted here, it seems more appropriate to use the original classification. The main reason for doing so is that in the quantitative work sampling was restricted to sheltered, stony shores. This was an attempt to eliminate any differential effect of the resource “substratum))and to reduce certain “hazards” in the sense considered by Browning. Under these circumstances five components are dealt with; weather, a place to live, food, other organisms of the same species and of different species.

A. WEATHER This factor is from some aspects less complex in aquatic than in terrestrial environments mainly because humidity is not involved, but also because the extremes of temperature are less and change is not so rapid. Indsed, temperature is the main variant for aquatic organisms although rainfall may have indirect effects mainly by altering the water level of lakes and the ionic composition of the lake water. Wind can also be important but, as already indicated, variations in this factor were reduced to a considerable extent. A detailed comparative study of the tolerance of the four triclad species to temperature and its effect upon the life-cycle has shown contrasts among them. The temperature ranges for the complete life-cycle are shown in Table V and while this factor has a differential influence, all the species would be able to breed in British lakes if temperature were considered in isolation. The species most affected by low temperature is Dugesia lugubris which is unable to breed at 7.5” C and below. Water temperatures in our highest lakes would seem to permit breeding of even this species (Reynoldson et al., 1965). For example, it is able to breed in southern Finland and Leningrad (Luther, 1961) where winter temperatures are severe, although summer temperatures may be higher than in Britain. While breeding experiments suggest there is some parallel between altitude and the distribution of the Polycelis species afid Dug. lugubris which involves temperature, this factor cannot alone account for the pattern, as shown clearly by the distribution of Dendrocoelum lacteum. This latter species is the most active breeder at the lowest temperatures, yet in Britain it is almost restricted to the warmer, more productive, lowland lakes. Temperature may prove to be a factor in distribution and abundance, but only in conjunction with other more important factors. Although rainfall may cause some rapid changes in the chemistry of lake water, B*

30

T . B . REYNOLDSON

especially the proportions of t’he ions (Macan, 1950) the magnitude of thesc in relation to the range found between lakes is small. Such a factor would appear unlikely to be directly concerned in the pattern, and experiments described on p. 31 confirm this. The other effect of rainfall, change in water level, does not differentiate between the species from what we know of their reaction. Extension of the level is certainly exploited by them in feeding on drowned terrestrial organisms; lowering of the level by evaporation is normally such a slow process that few will be stranded. Bearing in mind the restriction of sampling to favourable stony shores it is reasonable to conclude that weather does not have a direct bearing on the characteristic pattern of distribution and abundance of these four triclad species.

B.

A PLACE TO LIVE

A primary requirement of triclads is a firm substratum of leaves or stones, preferably in shallow water, which provides shaded resting sites. The sampling restrictions reduced variations from this source and also such hazards as abrasion from moving sand; effects of wave action have already been mentioned. Therefore, such physical attributes of the habitat as these are unlikely to be involved. The chemical properties of the lake water may be regarded as an aspect of (‘a place in which to live” and as we have seen, they show a relationship to distribution and abundance. The first problem to be examined here is the nature of the correlation, whether it is direct or indirect. Macan (1963) reviewing the relationships between calcium and freshwater organisms concluded that a direct effect was unlikely except in special cases like Procerodes ( = Gunda, Pantin, 1931) but each case requires testing; a similar conclusion would apply for the T.D.M. relationship. It is obviously preferable to test the ability of the various triclad species to survive and reproduce in lakes with low calcium and T.D.M. by retaining the natural conditions as far as possible during the experiment. This is best achieved by keeping the organisms in a suitable lake in cages which allow exchange of water between cage and lake. This avoids or reduces greatly the possibility of unnatural conditioning of the water, shown to be important for survival in some circumstances (Alee, 1951); it also permits the natural temperature regime to operate. For these several reasons triclads were kept in polythene cylinders 10 cm long and 5 cm internal diameter, closed a t each end with bolting silk of mesh fine enough to exclude organisms such as planktonic Crustacea. The cylinders>were clamped on to a metal frame by Terry clips and the apparatus kept in a sheltered part of the shore at a depth of about 30 cm. Lake Ogwen was selected for the experiments since it has a low calcium content ( 0 - 5 mg/

LAKE DWELLING TRICLADS

31

litre) and supports only Phagocata vitta, although it had the disadvantages of being popular with summer visitors and of suffering rapid changes of water level from time to time by withdrawal of water for local industry. Ten adults of each species collected from habitats with a moderately high calcium content were kept in separate cages and fed on earthworm slices a t approximately fortnightly intervals; the water temperature was read at each visit. Three experiments of this type were made, the first lasted 54 days from 30 October to 9 December 1957, when a sudden fall in water level killed all species except P. tenuis. A second using the original P. tenuis, ran for 113 days from 23 December to 22 April 1958, when visitors wrecked the cages; a third with new specimens lasted 112 days from 22 October 1958, to 10 February 1959. The experiments ran through two winters and temperatures were below 5" C and the lake ice-covered for long periods. Survival of the species is shown below: P. P. D. D. nigra tenuis lugubris lacteum 10 9 8 Expt. 1 54 days 0ct.-Dec. 1957 9 Expt. 2 113 days Dec.-Apr. 1958 5 8 10 10 Expt. 3 112 days 0ct.-Feb. 1959 10 10 6 8 Totals 24 28 25 26 All species survived in good condition and in large enough numbers to show that the chemical features of the water did not affect them adversely. Thus Dugesia and Dendrocoelum which are not usually found in unproductive, low-mineral lakes survived as well as P. tenuis and P. nigra which are characteristic of such lakes. The low number of P. nigra in Expt. 2 was partly due to the accidental squashing of two specimens during feeding. It was noticeable that the Polycelis species fed better than Dugesia when the lowest temperatures (1-3" C) prevailed. During such periods several of the Dugesia secreted a mucilaginous envelope around themselves. This is a general reaction to unfavourable conditions and has been recorded in the laboratory in water of high calcium content. I n the Ogwen experiment it was probably a reaction to low temperature. I n a further experiment the survival of these triclads in water of low calcium and T.D.M. without food was also tested using these cages in Lake Ogwen. Five specimens of each species except Dendrocoelum, not available at the time, were kept in the lake for 3 w ~ k during a May 1959. They all remained normal in appearance and behaviour and also produced cocoons during the period. The untimely end of the longer experiments meant that the main breeding season had been missed so that an additional experiment was made during April-May 1959 in which ten specimens of each species

32

T. B. R E Y N O L D S O N

were kept in the cages in Lake Ogwen and observed for cocoon production; these triclads were fed regularly. During a period of 30 days P. nigra produced two, P . tenuis twenty, Dugesia five and Dendrocoelum eleven cocoons. The majority of these proved fertile in the Ogwen water showing that these species are not only able to tolerate such conditions but are also able to breed under them. The growth and development of t'he young of each species except P . nigra was followed in the laboratory under a standard feeding and temperature regime in Lake Ogwen water, for comparison with similar experiments in water of higher calcium content (20 nig/litre, see Young, 1963 for details). Progress was similar in both types of water, culminating in the production of fertile cocoons in all species. Dendrocoelum lucteum took a little longer in the calcium-poor Ogwen water where the average maturation period was 217 days with limits of 188-232; in calcium-rich water it averaged 180 days (S.D. 19) at 10" C. The conclusion to be drawn from these various experiments is that the chemical nature of lake water plays no direct part in determining the pattern of distribution; Dugesia and Dendrocoelum are as capable of living in calcium and T.D.M. poor water as are the Polycetis species, nor were either of the Polycelis species specially fitted for life under such conditions. The occurrence of several freshwater organisms in large lakes normally outside their usual range as measured by edaphic factors has always been puzzling, and various interpretations have been offered (e.g. Macan, 1950; Tucker, 1958; Williams, 1962a). I n the case of triclads it is clear that the presence of Dugesiu and Dendrocoelum in Lake Windermere with 5.0 mg/litre calcium and in Loch Lomond with 3-0mg need not be explained in terms of physiological races as the Ogwen experiments showed. Nor is lake size necessarily involved, since both are found in the small Newton Mere with 5.0 mg calcium, while Dendrocoelum also occurs in the small Llyn Mair with only 2.4 mg/litre. This ability of the four species to tolerate equally well such a wide range of calcium and other ions, while of much interest to physiologists, lies outside the context of the present ecological problem. There are of course many other variables such as pH and dissolved oxygen which have not been considered, but there was no indication in the field work that they are relevant to distribution. Apart from some dystrophic lakes on Islay, low pH values have not been encountered and it is unlikely that dissolved oxygen becomes limiting in the littoral zone of stony shores. There was some indication (Reynoldson, 1958a)that in lakes with comparable water chemistry, those dystrophic in character supported a smaller population, but more work is needed to substantiate this view.

33

L A K E DWELLING T R I C L A D S

One further aspect of the habitat suggested itself as a possible determinant of distribution, namely the biological quality of water, which may also differ as shown by Wilson (1051) for sea water. Were Dugesia and Dendrocoelum in the course of dispersal selecting water characteristic of productive lakes and avoiding that of unproductive lakes? This possibility was tested by choice experiments in an apparatus which allowed waters of different origin to be tested (for details; Young, 1963). Usually fifty triclads of each species collected from a calcium-rich habitat were used in each test. Observation showed that the triclads explored the experimental habitat before settling down. Eight such tests were made with P. tenuis and in seven there was no significant difference between the numbers settling in each water. I n one a significantly higher number was found in the calcium-poor water, but overall there was no selection. A similar result was obtained with Dugesia (Table VI). Dendrocoelum however behaved differently and in fifteen tests this species selected the calcium-rich water each time in significant numbers (P < 0.001). The specimens were then kept in Ogwen water for 5 weeks and tested again in five experiments with a similar result. They were kept for a further 7 months in Ogwen water, being fed a t regular intervals on Asellus. A further seven tests were made and this time the Dendrocoelunz showed a preference for Ogwen water, not so marked as the original preference for calcium-rich water, but nevertheless significant (P .= 0.05 > 0.02) (Table VI). It appears that this species can become conditioned to some property of the water of its habitat. However, if triclads disperse by their own locomotory activity (p. 24) it seems unlikely that such conditioning can play an important part in producing a pattern of distribution because normally changes in the TABLEVI The Distribution of Triclads between Calcium Rich and Calcium Poor Water in the Laboratory; ( a ) after no conditioning, (b) after 5 weeks, (c) after 7 m o n t h conditioning in calcium poor water Species (a)Polycelis tenuis ( a ) Dugesia lugubris ( a ) Dendrocoelum lacteum ( b )Dendrocoelum lacteum ( c ) Dendrocoelum lacteum

Ca poor water CE rich water No. expts. (0.5 mng/litre) (24.0 mg/litre)

Significance

8 8

146 114

133 117

none none

15

87

302

P < 0.001

5

47

110

P < 0.001

7

103

'73

P < 0.05

> 0.02

34

T. B. REYNOLDSON

chemical properties of water are gradual. Support for this interpretation is given by the wide distribution of Dendrocoelum lacteum in Feniioscania (Reynoldson, 1958c) where it had a pattern corresponding to that of P. nigra in Britain. It seems reasonable to conclude that a biological property of water per se does not determine the distribution of these triclads.

c. FOOD I n the present context we are not concerned so much with scarcity and abundance of food but rather with the kinds taken by the four triclad species as indicating the degree of overlap in their requirements. Food has been found to be a key resource in deciding the ability of ecologically similar species to co-exist, and has often been implicated in determining pattern. This aspect has been studied most thoroughly in birds (Lack, 1954; MacArthur, 1958); it has been less well studied for invertebrates, but work on gastropods (Kohn, 1959), and on tsetse flies (Weitz, 1964) using a serological technique, is an example of what can be achieved. No detailed study of the food of triclads occurs in the literature, and certainly none that would provide the kind of information which is required to determine the extent of overlap among the four species in nature. Hyman (1951) has stated that triclads do not feed on plants or decaying organisms (cp. Popham, 1955) and this has been confirmed by our studies. She also expressed the view that one species may feed upon another and that cannibalism may be extensive, as it seems to be for some strains of Dugesia tigrina (Root, 1960; Armstrong, 1964). Both aspects have been tested in our laboratory in various ways and the results showed (Reynoldson and Young, 1963)that neither phenomenon is common in these British species. Only two defbitive observations of predation have been noted, both by Dugesin lugubris, one upon Polycelis nigra and the other upon P. tenuis; in the latter instance the pharynx of the P . tenuis “ate” its way through the body wall of Dugesia within a few minutes of being ingested. No successful attack of one specimen upon another of the same species has been observed, but a few isolated examples of this have been reported (e.g. D. Clegg-private communication) again for Dugesia lugubris. It can be concluded that interactions of this sort are not important in nature and play no part in determining distribution and abundance. The behaviour-patterns which cause predation and cannibalism among triclads would appear to be subtle and have not been studied yet. The literature suggests that triclads as a group feed on small aquatic annelids, crustaceans and insect larvae, and they also take terrestrial organisms trapped in water, but the observations are too incidental to

35

L A K E D W E L L I N G TRICLADS

construct any sort of picture. This problem has been tackled in three main ways : (a) by examination of squashes of triclads recently collected from the field for the remains of prey. This method has the disadvantage that results may be biased in certain directions, especially towards oligochaetes, which are more likely to be detected on account of their setae. (b) laboratory experiments in which selected prey were exposed to triclads starved for a uniform period (Holling, 1963). This approach has two obvious disadvantages, the range of prey is restricted compared with natural conditions, and the normal behaviour of either prey or predator may be interfered with. The latter was probably reduced in the experiments by the provision of cover for both organisms. (c) the use of a serological technique for detecting prey in squashes of field specimens. This is the most reliable approach but it has only been used to a limited extent so far. The results from the examination of field specimens, both young and adult, are shown in Table VII. The main conclusions are that various TABLEVII Food Organisms Found in the Guts of Triclads Collected from the Field. (Reproduced with permission f r o m Reynoldson and Young, 1963.) Expressed as percentage of total identifications Polycelis . Dugesia Deiadrocoelum ri igrc, I’ dermis lugubris lacteuin, Adult Total . . ....-- -

Oligochaot,a Lumbriculus variegatus Naididae TubXicidac * Lumbricidae

28 -6 31.4 5.7

2.8

Arthropoda Insecta Asellus Others

14.3 Nil 11.4

Mollusoa t Lym.naeu sp. Hydrobia j enki mi Ancylus lacustris

X il Nil Nil

Others

5 *7

35.0 11.6 46.5 Nil

14.3 21.4 10.0 5.7

404 20.0 Nil Nil

Nil 78-6 3.6 Nil

70-6 29.4 Nil Nil

1.4 Nil 1.4

Nil Nil

5.7

Nil 18.6 2.3

5.0

3.6 Nil 10.7

Nil Nil Nil

Nil Nil Nil

Nil Nil Nil

15-7 11-4 1.4

Nil 35.0 Nil

Nil Nil Nil

Nil Nil Nil

Nil

1.4

Nil

3.6

Nil

40.0

2 -8

31.4 8 -6 2a 8 2 -8

5 *7

* May include Enhy!meidae. t Based on radulae only.

36

T . B . REYNOLDSON

oligochaetes appeared to be the main diet of all species except Dugesia which also fed extensively on gastropod molluscs; arthropods seemed to be of lesser importance in all four species. The food range of young was similar to that of adults and because communal feeding occurred on large prey, the size-ranges of the food of young and adults also overlapped (Young, 1963). When these results are compared with those from laboratory experiments (Table VIII) based on summation of data where single species were exposed, and data where several were exposed together (Reynoldson and Young, 1963)) the main conclusions based on squashes are confirmed for P. tenuis and Dug. lugubris, but in the case of P . nigra it was surprising how few oligochaetes were eaten. Dendrocoelum showed a very different result; in the laboratory it fed extensively on both arthropods and oligochaetes, in the field specimens only the latter were detected. When both Asellus and the oligochaete Lumbriculus were exposed to this species the former were all eaten in 3 days, the latter not until eight days had elapsed. The greater emphasis on arthropods in the laboratory shown by all species, although only slight for P. tenuis and D u g . lugubris, was undoubtedly due in part to the difficulty of detecting triclads which had fed on this sort of prey in the TABLEVIII

The Kinds a d Number of Organisms Eaten by Triclud.s in Laboratory Experiments. (Reproduced with permission f r o m Reynoldson and Young, 1963.)

Prey

I’olycelia iaigra.

No. oaten by Diigesin Deridrocoelum 1’. teri rcis lucpbris lncteum

Oligochaeta Lumbriculus variegatus

2/90

17/90

22/90

54/60

Arthropods, Asellus meridianus Gammarus p u k x Cloeon dipterum Diura bicaudata Chironomus sp. larvae Total Arthropoda

81150 0150 0160 9/50 6/50 13

11/150 0150 0150 4/50 6/50 21

20jl.50 0150 0150 3/50 3/50 26

100/100

Mollusca H?jdrobia jer ik ir 1 s i Lymiucea pereger Tot a1 Molliiwa

0/50

01150 0

1 /a0 1/150 2

15/60

1 Fi/15O

Bo

35/50 47/50 50150 45/50 277

0150 o/ 100

0

37

L A K E DWELLING TRICLADS

TABLEI X Positive Reaction to Rabbit anti-Asellus Serum by Squashes of Field Specimens of Triclads. (Reproduced with permission frowi Young et al., 1964.)

Species

The Mere Cole Mere No. NO. tested %+ve tested %+ve

Newton Mere No. tested %+vr

Beaumaris Reservoir No. tested %+ve

Dendrocoelurn lacteum

50

100

50

68.0

50

8.0

-

-

Dugesia Eugubria

56

5-4

48

0

12

0

-

-

Polycelis tenuis

52

9.6

48

48

8.3

-

-

Polycelia nigra

-

-

-

__

__

36

2.0

8.3 .-

field by the squash method. These experiments confirmed that gastropods are not important in the diet of any species except Dugesia. The results from the serological approach (Young et al., 1964) showed conclusively that Dend. lacteum fed much more on Asellus (Table IX) and probably arthropods in general, than the planariid species. They support the laboratory data and indicate that bias occurred in the results from the squashes. These various approaches to a study of the food of trirlads show that there is considerable overlap in the type of prey eaten by the four species. However, the Polycelis species take a larger proportion of oligochaetes than of other prey, Dugesia alone feeds on gastropods, and Dendrocoelum eats a greater proportion of arthropods, especially Asellus. An outstanding feature of the laboratory approach is the contrast between the planariid species and Dendrocoelum in the number of prey eaten. The behaviour patterns of the former seem to be such that they do not react very markedly to the presence of intact prey behaving normally. Although these triclads had been starved prior to the experiment and fed readily afterwards on punctured animals, they largely failed to recognize intact organisms a s potential food; a total of 1531840 only were eaten. I n contrast Dendrocoelum devoured 331/510 prey; if gastropods are excluded this becomes 331/360. Further experiments were made to study the behaviour of the triclads when damaged animals from which the body fluids had leaked were exposed to them, and in the case of the planariid species, to organisms trapped in vaseline. In

38

T. B . REYNOLDSON

the former (Table Xa), the planariid species showed a preference for oligochaetes with arthropods second choice, while gastropods were relatively unattractive ; Dendrocoelum showed a preference for arthropods (Asellus).When the rate of attraction was measured, again the planariid species reacted more quickly especially to oligochaete material (Table Xb). The reaction of the planariids to various prey trapped in vaseline TABLEX Triclads Feeding on Damaged Prey. (Reproduced with permission f r o m Reynoldson and Young, 1963.) Attractiveness of various prey exposed simultaneously Prey organism Asellus L y innaea Triclad species Earthworm meridianus pereger a.

Polycelis nigra P. tenuis Dugesia lugubris Dendrocoelum lacteum Total

14 25 19 6 64

0 0

11 9 9 10 39

Total 25 34 30 16 105

2

0

2

b. Rates of attraction t o t w o types of prey Earthworm Gammrus -

T i m e Polycelis ( m i n ) nigra 5 10 15 20

8

11 12 15

P. tenuia 3 7 10 11

DendroDugesia coelum lugubris lacteum 5 12 16 20

0 3 4 4

P. Polycelis n@ra tsnuis 5 10 12

-

7 13 17

-

DendroDugesia coelum lugubris laoteurn 8 13 18

-

2 9 13

but undamaged, was also illuminating (Table XI) and showed conclusively that organisms behaving abnormally are attacked with high frequency . These results not only confirm the differences in tho feeding behaviour of the several species, but also illustrate the considerable degree of overlap. While Polycelis species and Dugesia feed rather more on oligochaetes than arthropods, the reverse is true of Dendrocoelum; Dugesia alone attacks gastropods. A difficult problem, so far unresolved is whether or not P. nigra and P. tenuis take different foods. Scrut,iny of the data certainly shows some differences but the evidence is so far insufficient for reliable conclusions to be drawn, The planariid species do not seem to be primarily hunters attacking undamaged organisms, but feed more

TABLEXI AVumberof Prey Eaten when Fastened in Petroleum Jelly, Fastened and Allowed to Free Themselres, and under Nornial Conditions. (Reproduced with permission from Reynoldson and Young, 1963.) Twenty-five prey and twenty triclads used in each regime.

No. eaten by P . tenuis

Polycelis nigra Prey Asellus meridianus Cloeon dipterum LymnaecL pereger Hxdrobja jEnkinsi _ _

Fixed 18 4

~ -

Freed

I

1

-

Control 1

0

-

-

Fixed 19 11 -

Dugeaia lugubris

Freed

Control

-

-

9 5

3 0 -

Fixed 19 14 13 7

Freed 11 2 -

Control 0 0 2 8

40

T. B . R E Y N O L D S O N

on damaged individuals or those behaving abnormally, e.g. struggliug in mucus, trapped in the water film, or perhaps damaged by other predators. Dendrocoelum is an active hunter of small organisms and uses ail envelopment technique aided by its anterior sucker t o attack prey. While the role of mucus produced by triclads in ensnaring prey has been described by Jennings (1957) for P. felina, we have seen no evidence that it is important in the lake species of Planariidae; but mucus probably helps Dendrocoelum to catch prey, a t least under laboratory conditions.

D.

O R G A N I S M S O F THE S A M E S P E C I E S

The isolation of the intra-specific events which are considered here is entirely artificial and their influence upon the distribution and abundance of the several triclad species is indirect. However, this approach affords background information on the conditions under which the triclads are living and may indicate the important types of interaction occurring among the species in nature. During the ten years of observation there has been no hint in the field or in the various experiments that co-operation between individuals, of the type described by Allee (1938), determines the pattern of distribution of these triclads. It has already been shown that cannibalism is a rare phenomenon (p. 34). This leaves intraspecific competition as the main focus (sensu Milne, 1961). The population dynamics of the four species have been studied in some detail (Reynoldson, 1960; 1961a; Taylor and Reynoldson, 1962; Young and Reynoldson, in press), and while they all show basic similarities, there are interesting differences (for example in life-span) between the Planariidae and the Dendrocoelidae which influence events. Apart from differences in the time of year a t which breeding commences, which although slight probably influence distribution, the population biology of the three planariid species is similar. They all have a low birth rate and recruitment to the population is only about 50% of its pre-breeding size under natural conditions; in the laboratory with ample food the birth rates are several times greater. The low recruitment is due to the gradual development of a condition of food shortage after the initial hatching of young; this puts a brake upon and finally stops breeding. A t the same time the individuals decline in size because of food scarcity, and this is accompanied by some mortality which readjusts the population to its food supply. This cycle is repeated each year and represents a self-regulatory system operated by intra-specific competition for food. The more obvious operation of this homeostatic system compared with most natural populations arises from two properties of these triclad species. First, their capacity to remain alive under conditions of food shortage for long periods by resorbing their tissues and shrinking in size. Laboratory observations have shown that an adult

41

LAKE DWELLING TRICLADS

Polycelis tenuis of 8-9 mm length can live up to 8 months without food, in the meantime shrinking to 0.5 mm length; similarly Dugesia lugubris can shrink from 14 mm to 2 mm; the accompanying change in biomass is of course much greater. Such tenacity has not been observed in the field but shrinkage to 2-3 mm in both species has been noted. Furthermore, such field specimens are able to grow and breed again when fed, showing high resistance to senescence. Thus, triclads react initially to food shortage by a considerable change in biomass; they are more resistant to change in numbers. Secondly, these triclads appear to have no important predators or parasites in the stony, littoral zone of lakes (p. 44) and therefore intra-specific competition is able to exert a maximal effect. This hypothesis has been tested by field experiments in which the amount of food per individual has been increased artificially both by adding food and by reducing the triclad population. Also, newly created habitats have been studied in which the prey was initially numerous relative to the triclads (Reynoldson, 1964). Such populations showed an increased birth rate and recruitment, while shrinking was delayed and its extent reduced (Table XII). It seems evident that natural populations are under some restraint both in growth of the individual and in fecundity for a considerable period of each year, and that t,hey show great numerical stability which provides optimal conditions for survival (Martin, 1959) to which their longevity will also contribute (Hutchinson, 1957). They show to a high degree the population homeostasis which forms a key part of Wynne-Edwards’ hypothesis (1962), even to the extent that those individuals which fail to breed in a particular year may form a strategic breeding reserve. But in these simple organisms there is no evidence of social organization which could result in selfregulation, and in competing for food they show what Nicholson, (1054) TABLEXI1 Effect of Increasing the Food Supply upon Total Recruitment and Proportion of Adults during the Climax Month. (Reproduced with permission from Reynoldson, 1964.) Triclad species Polycelis tenuia (College pond) P . tenuis (New pond) Dugesia lugubria Polycelia nigra

Total recruitment,

Normal Increased food

Percentage adults Normal Increased food

(%I

(%)

50

350

4-3

55.2

50

175

4 -3

13.5

38 90

137 500

2.2 -

36.9

-

42

T. B . REYNOLDSON

describes as the scramble type. It is perhaps significant that as a group they appear to be inefficient predators and suffer from a shortage of food, absolute rather than relative (Andrewartha and Browning, 1961; Birch, 1962). Recently, MacArthur (1961) and Pimentel (1961, 1963) have emphasized the fact that predators can only feed on the “interest” and not the “capital” of their prey populations if they are to survive. The planariid triclads seem to be a good example of this, indeed their special properties make it imperative that some safety valve should be built into their biology. They have avoided over-exploitation of their prey by the evolution of a behaviour pattern which restricts their feeding largely to damaged organisms or to those behaving abnormally (p. 38). This may have evolved by the genetic-feedback mechanism now being explored by Pimentel, provided some degree of population isolation occurs; aquatic,populations are probably isolated to a much greater extent than terrestrial populations. On the other hand, one would expect considerable selective pressure in favour of increased predatory efficiency. I n my view, this mechanism which Pimentel assumes to have evolved by natural selection and which is supported by experimental evidence (Pimentel et al., 1963), sets the limits within which a population normally oscillates, i.e. it functions as a coarse adjustment, while the fine adjustment is achieved by a proximate (Baker, 1938; Lack, 1954) density governing factor (sensu Nicholson, 1954). Orians (1962) and Bakker (1964) have discussed the inter-relations of ultimate (evolutionary) and proximate (ecological) factors. I n the case of triclads the proximate factor is intra-specific competition for food. This can be clearly seen in tricleds by comparing rates of reproduction under natural conditions and under adjusted field conditions (Table XII).A genetic mechanism has too great a lag period, especially in those species with a long generation time, to operate speedily enough. Lack (1954) believed clutch size, an indication of birth rate, to be adjusted directly to food supply by natural selection, but as MacArthur (1961) pointed out, even in birds the problem is often more complex than this. If a population is to survive, the birth rate must also be adjusted to take into account the hazards the species has to meet, and the apportionment of nutriment between the needs of the parent for survival and the production of young (Fisher, 1930; Birch, 1960) will vary among the different species for this reason. For example, triclads have few natural hazards and when food becomes scarce after limited breeding they soon divert it from reproduction to maintenance of the individual; blowflies have to face more hazards among which is dispersal of their food and when this resource is short they convert as much food as possible to reproduction and sacrifice size of the individual to some extent; internal parasites with extreme hazards to meet are virtually egg-laying machines.

LAKE DWELLING TRICLADS

43

In Dendrocoelum lacteum the position is altered to some degree by the fact that a considerable proportion of the population are annuals and die after breeding (Yoiing and Iteynoldson, in press). As a result, when the young are hatching a food crisis is postponed because adults are dying a t the same time. This is shown by characteristic differences in the population size-structure of Dendrocoelum and the planariid species. Also stemming from the contrast in longevity is both a higher birth rate in Dendrocoelum (6-7 per adult compared with 1 in the planariid triclads), and a higher recruitment, 350% compared with 50-1000/. This means that the amplitude of population fluctuations is several times greater in Dendrocoelum during an annual cycle. It is also significant that Dendrocoelum is a more efficient predator than the planariid species and seems to cause a detectable reduction in the population of its main prey Asellus (p. 40)but other factors such as variation in severity of inter-specific competition are also involved. Although the mechanism of population regulation seems particularly evident in these triclads, Maguire (1962) has suggested in the case of Cura ( = Curtesia)formanni that some control on reproduction is exerted by ectocrine substances. Thers are some puzzling features of his data which suggest that the phenomenon he describes is more likely to be a physiological effect of laboratory crowding in a lotic species and is not applicable to field conditions. From the viewpoint of distribution and abundance, the important feature of intra-specific relationships is that serious food shortage occurs periodically in all species and it is against such a background that interspecific relationships must be considered.

E.ORGANISNS

OF DIFFERENT SPECIES

Here we are concerned with the effects of predators and parasites of triclads and the competitors for resources, all of which theoretically are capable of influencing the pattern of distribution and abundance. These are treated under two heads.

1. Predators and Parasites Predators may influence not only the abundance but also the distribution of their prey, but little is known of this factor among aquatic invertebrates (Macan, 1963). The literature suggests that some animals such as newts, sticklebacks and certain carnivorous insect larvae eat triclads (Whitehead, 1922; Bolen, 1938), while Hyman (1951) maintains that they are rarely eaten. The relative immunity of such soft-bodied organisms is attributed to their unpleasant taste, Fnd Jennings (1957) has produced experimental evidence of this. However, no substantial observations have been reported on which to assess the extent of

44

T. B. REYNOLDSON

predation. In the present programme Taylor (1960) confirmed that dragonfly and damselfly larvae fed extensively on Polycelis nigra and there was some indication that Erpobdella sp. ate a few. These experimeiits were taken further by Young and Reynoldson (1965) who tested a series of potential predators against young and adult P. nigra, P. tenuis, Dugesia lugubris and Dendrocoelum lacteum. The results (Table XIII) show that of nineteen invertebrates selected over a range of phyla, only adults of Dytiscus marginalis and the Odonata larvae took triclads in any numbers, and in these cases young rather than adult triclads were eaten. Fish, especially rudd (Scardinius erythrophthalmus) ate them to some extent. All these predators took approximately equal numbers of the four triclad species but the experimental regime did not offer a choice. There are several reasons for suggesting that such restricted predation is likely to be even less in the stony, littoral zone of lakes. First, those invertebrates which attacked the triclads occur most commonly in heavily weeded habitats with a muddy substratum. Second, it was evident that apart from rudd, only one or two individual fish fed upon the triclads, despite their evident unpleasant taste. This would account for Taylor’s ( 1 960) conclusion that minnows did not eat P. nigra. In nature, with alternative food it is unlikely that many triclads are eaten. Third, rudd are so sparsely distributed in Britain that they cannot influence triclad distribution; furthermore, fish with similar feeding habits are found precisely in those lakes where triclads are so numerous and diversified. Finally, triclads are so slow-moving or immobile that they will not attrart fish to the same degree as when both are confined in a dish with limited cover. Indirect evidence from the study of the population dynamics of the individual triclad species (p. 40) also suggested that predation was insignificant. However, before this factor can be dismissed altogether it will be necessary to examine feeding on triclads by some method applicable to field conditions such as the serological technique used successfully by Dempster (1960). Parasites of triolads can be dismissed quickly, since of the several thousands exanlined by squash techniques (Reynoldson and Young,

1963)jess than ten were found to harbour a trypanosome and less than

twenty populations were infected by a species of Sporozoa. I n the latter case, such populations were usually found in polluted regions of lakes. There is no evidence of the extent to which the triclads (all species) were harmed, if at all, by the sporozoan but the populations were not obviously reduced.

2. Competitors The two main resources for which inter-specific competition usually occurs are adequate living space and food (Nicholson, 1954; Milne,

TABLEXI11

The Number of Adult ( A )and Young ( Y ) Triclads Eaten by Predators in Laboratory Experiments. ( p ) = Portions Eaten. (Reprdueed with permission from Young and Reynoldson, 1965.)

Predator COELENTERATX Hydra oligactis Pallas HIRUDIKEA Helobdella stagnalis (Linn.) Erpobdella octocuulata (Linn.) COLEOPTERA adults of ~4gabzl8dirlyn~us(oliv.) A . paludosw, (Fab.) Colymbetea fuscw, (Linn.) Ilybiua fuliginosw, (Fab.) Rhantw, bistriatw, (Bergst.) Deronectes sp. (adults) Dermectea sp. (larvae) DytiscuB marginalis (Linn.) (adults) Dytiscw, marginalis (larvae) Haliplus ~ p (adults) . Haliplus sp. (larvae)

No. of predators used

No. of each size of triclad sp. used

20

50

@

20 20

50 50

0 1

10 10 10 10 10 10 10

50

0

5 5 10 10

25 25 50 50

50 50 50 50 50 50

No. of triclads eaten P . tenuis D. lugubrk A Y A Y

P . nigra A Y

1400

2

0

5

0

6

16

0

0 0

0 5

0 0

0 3

0

0

0 30

4

2 0 0 0 0 0 0

0 0 0 0 0 0 0

1 0 0 0 0 0 0

0 0 0 0 0 0

0 0 0 0 0 0

13 3 0 0

11

16 0 0 0

7

0 0 0 0

0 0 0 0

10 0 0 0

12 2 0 0

11 0 0 0

0

Total eaten

0

3

0 0 0 0 0 0 0

0

D . lucteum A Y

0 0

* 9Sj200 t 10,'200

0

UP)

0 0

4

95* 10t 0 0

TABLEXI11 - continued No. of Predator HEMIPTERA Notonecta gluuca (Linn.) N e p cinerea (Linn.) TRICHOPTERA Polycen tropw jlavomaculatus (Pictet) ODONATA Coenagrion puella (Linn.) Aeuhna cyunea (Mueller) PISCES CTaaterosteus aculeatus (Linn.) Phoxinus phoxinw (Linn.) Salmo trutta fonna fa& (Linn.) Scardiniw erythrophthdmw (Lh:) AMPHIBIA Triturua helveticus (Razoumowski)

predators used

No. of each size of triclad sp. used

10 10

50 50

0 0

0 0

10

50

_

_

10

50

10

50

P. nigra A Y

8+ 26 19(P) 45 42

No. of triclads eaten P. tenuis D . lugubris A Y A Y ___

0

0

0

0

_

_

14+ 31 WP) 44 40

0 0

3+

21(P)

49

0 0

_

D. lacteum A Y 0 0

0

32 43

0 0

lo+ 3(P)

@+ 35+

W P ) 6(P)

41+

46

5(P) 10 10 10

50 50 50

11 7 13

15 12 12

10 14 9

17 13

10

50

25

32

10

50

1

5

Total eaten 1400 0 0

lo+ (P) 149 +(P) 350 (P)

+

18 9 15

9 8 11

16 14 18

109

16

13 9 14

26

38

24

26

19

35

225

0

4

0

7

0

8

25

86

108

L A K E DWELLING TRICLADS

47

1961). Within the range of population size observed in this work, living space does not appear to be critical. Although it is shared by a large number of other organisms such as Cammarus, leeches of several species, oligochaetes, molluscs and various insect larvae, the requirements are usually not specific and living space as represented by the undersurface of non-bedded stones does not usually restrict the size of the littoral fauna of lakes. I n this connection Macan and Mackereth (1957) have discussed the possibility of jostling in overcrowded conditions causing Cammarus to be exposed to current and predation in streams but this does not occur in triclads. It has been shown (p. 40) that the food of triclads is in short supply especially during the 2-3 months after breeding, and it is reasonable to assume that triclads are sensitive to any inroads which may be made upon this resource. Depletion may result from the feeding activities of a wide range of animals, from those closely related to those only related in the sense that both are aquatic animals. For example, Asellus may be eaten by several species of fish, molluscs by leeches, oligochaetes by insect larvae and so on. The effects of such predation will be several and complex. For example, reductions in food supply will lower the overall triclad population or a specific part of it, depending on the type of food. It will also increase the intensity of any inter- and intra-specific competition in triclads and its timing. But the evidence, admittedly meagre, suggested that timing ;vas largely the result of intra-specific activities (Reynoldson, 1964). Generally it can be assumed that the more distantly related the predators using a food resource, the less intense and prolonged the ensuing competition. This follows because the more contrasted the ecology, usually but not always a function of taxonomic relationship, the less likely are peak demands to coincide and the more likely the availability of alternative food. Therefore the main pressure from inter-specific competition is likely to come from other triclad species. However, occasionally unrelated species may exert an influence sufficiently powerful to restrict distribution (Harper, 1964) but we know insufficient about this aspect of triclad ecology to indicate its prevalence. Leeches, because of their abundance in the littoral zone (Mann, 1955) and because they show appreciable overlap in food with triclada (Mann, 1962), are likely to be the most important component of the fauna in this respect and should be the tirst to be studied. Reliable evidence of inter-specific competition among triclads, almost certainly for food, in view of the demonstrated shortage (p. 40) and overlap (p. 38), has been obtained from several sources. It is most clearly demonstrated between Polycelis nigra and P . tenuis by comparing the size of the P. nigra populations in Anglesey where the species occurs mostly alone, with that of the mainland where it occurs with

48

T A B L EX l V a. The Size of Polycelis nigra Populatioiis i/i the Absence (Anglesey Lakes) and Presence (Mainland Lakes) of P . tenuis

t5.0 _

_

~

5*1-10*0

~-

Ca mg/litre 10.1-20.0 20.1-40.0

- -

>40*0 __

..-

P . nigra alone

17

-

P. nigra in presence of P. tenuio

42

49

76

40

38

P. n e r a

53

136

226

209

322

+ P. tenitis

173

140

179

b . Size of Polycelis nigra Populutiori in Two Anglesey Lakes C'ontaining also P . tenuis ~

P. nigra P. n e r a

+ P . tenuis 2 j P. nigra IP. nigra + P. tenuis

__

.

~

-

-

-

-

-_

-

-

--

__

35 213

-

_..

86 234 -.

-

-~

-

-

__

Triclad populations recorded as number collected per hour averaged for lakos in each calcium category; a dash means no lakes in that rategory.

P . tenuis and other species. It, is clear froin 'Fable XIV that P . tenuis has a markedly depressive effect upon the size of the P . nigra population. It seems unlikely that the environments of Anglesey and the niainland are sufficiently different to account for this. Indeed, this argument is destroyed by comparing the P . nigra populations o f two lakes on Anglesey (Llygerian and Coron, Table XIV, b l , b2) which a!so contain P . tenuis, with the rest: they show a P. nigrn population reduced to mainland proportions. It is interesting to note that while the total Polycelis populations of Anglesey and the mainland are of the same order, the latter tend to be slightly larger. This aspect will be discussed when considering the effect of inter-specific competition (p. 61).A further striking illustration of the effect of inter-specific competition on population size is afforded by the Ialay lochs (Fig. 7 ) . Here the species involved are mainly P. nigra and P . felina but in a few cases P. teriuis is also concerned. The same sort of result is apparent, a reduction of t
49

L A K E DWELLING T R I C L A D S

300

1

50 I

100

Size of

triclad

150

200

population

250 I

I

I

I

0-0

Polycelis tenuis

.. ..

C--l-.-l

I00

rn

..: ..... .,.... .. :.:. ....

IlClII 1121131141

Loke

300

350 .

400

I

450 1

I...D-. 1

,_..I.-.!...I

m

m

FIG.7. The species populations of lochs on Islay in ascending order of total population to illustrate the influence of Polycelis nigm, P . lenuia, and P . f e l i n a upon one another. (Reproduced with permission from Reynoldsoii, 1958a).

species. The low-calcium lakes in which P. tenuis is found occur in areas (Northern Scotland, artificial tarns of the Lake District) where P. nigra is absent. Evidence of another sort was obtained when the P. tenuis population in the College Pond was depleted by removing large numbers for experiments on the peritrich Urceolaria which is epizoic on this species (Reynoldson, 1957); lesser numbers of P. nigra were removed. These removals are referred to subsequently as "predation". Changes in the proportions of the three species in the pond are shown in Table XVI. During 1950-52 large numbers of P. tenuis were removed and by 1952 the proportions had altered considerably. From 1952 to 1956 no TABLEX V Distribu,tion of Polycelis nigra a i d P. tenuis in Lakes of Low Calcium Content <2*5

P . nigra alone P . nigra & P . tenuis P . tenuia alone Total lakes

13 0 6 19

Calcium mg/litre 2.6-5.0 14 2 6

22

6-1-7.5

6

5 2 13

T. B . R E Y N O L D S O N

50

TABLEX V I Changes in the Proportions of Triclad Species du,e to Artijcial Predation on Polycelis tenuis Percentage of total population Sample size

_ _ _ ~ _ _ ~

Before predation After predation (1948-1952)

Polycelia tenuia

.- -.

-

_. .

P. nigra

Dugeaia lugubris

__

-

>500

63

10

13 33

25 67

630 440 400 420 720 400

17 30 41 57 70 55

35 38 28 15 14 15

47 32 31 28 16 30

400

Recovery period (1952-

1954 1955 1956 early 1956 middle 1956 late 1957

“predation” occurred and the species gradually re-adjusted to the initial proportions. Unfortunately it was not possible to measure changes in absolute numbers, so that interpretation must be cautious. It could be argued that the data show nothing more than the recovery of the P. tenuis population without reference to the other species. However, this cannot be so because from 1952 to 1955 both species of Polycelis increased: if it was simply a matter of proportional change due to recovery of P. tenuis, P. nigra would decline persistently. The apparent more rapid response to “predation” on P. tenuis by Dugesia may be explained partly as an artefact due to the use of proportions and partly due to the potentially higher fecundity of Dugesia (Reynoldson, 1961a). Such changes are most satisfactorily explained by the hypothesis that P. nigra initially increased its numbers when competition was less severe as a result of the removal of P. tenuis. When P. tenuis was allowed respite from “predation” after 1952, both species increased at first, but ultimately P. tenuis was able to do so more effectively. The original proportions were reached 4 years after “predation” on P. tenuis ceased. Dugesia reacted in a similar manner. Apart from providing evidence of competition these data are of particular interest since they indicate, for a particular habitat, the period of time necessary for equilibrium to be reestablished among the three species. Further circumstantial evidence of competition was obtained by introducing species into natural habitats. Llyn Teryn is a high altitude

L A K E DWELLING TRICLADS

51

lake oiily 6 acres (2.5 hect.) in area with a relatively large population of P. nigra (72/h). In January 1956, 2 500 Y.tenu,is were introduced into this lake and collections of triclads have been made from it at intervals since. Up to 1063 no P. tenuis had been recovered and it appears as if this species has been unable to establish itself. It may be that the numbers of P . tenuis introduced were too few in relation to Y.nigra to enable it to succeed in this harsh habitat, or, less likely, it has not had sufficient time to build its numbers high enough to be detected. The second experiment of this sort was made in a small springfed pond with a restricted fauna (p. 61) 4 m2 in area in the College grounds. Baiting over 8 days showed that this small pond initially supported about 5 000 P. tenuis. Of these, 1 500 were returned together with 400 P . nigra. Subsequent sampling showed that P . nigra failed to establish itself under these initially favourable conditions; only a few were found 2 years after introduction and these have disappeared since. A similar but smaller introduction of Dugesia lugubris was successful and the implications of this are considered later (p. 61). The final evidence of competition between these two species relates to reproduction. Taylor and Reynoldson (1962) showed that in a habitat containing only P . nigra this species was able to achieve two peaks of breeding, in early spring and late summer. I n a habitat also containing P. tenuis and Dug. lugubris the second peak did not occur. Evidence of competition for food between triclad species belonging to different genera is not so striking, and this may have several causes. Competition is probably not so intense as between congeneric species because the overlap in food is less (p. 38) and it is therefore not so clearly demonstrable. There are no productive lakes which lack Polycelis and yet contain either Dugesia or Dendrocoelum so that any numerical restriction due to the presence of Polycelis cannot be measured. There are lakes containing Polycelis with and without the other two species, but these do not provide such a useful comparison since Polycelis is so dominant numerically whenever it occurs. Also, the fewer lakes containing Dugesia and Dendrocoelum make the comparisons less valid. However, the considerable degree of overlap in food between the species of different genera (p. 38) and the shortage of this resource (p. 40) would be expected to lead to competition at the inter-generic and inter-family levels, and there js some evidence of this. I n presenting such evidence it has been necessary to lump together the data for Dendrocoelum and Duqesia since they are so few taken separately. Table XVIIa compares the increase in total number of Polycelis species with that of Dugesia plus Dendrocoelum over the full range of lakes; and it is clear that the increase in size of the Polycelis population is halted at the point where the numbers of Dugesia plus Dendrocoelum become

TABLEXVII a. A Comparison of the Increase in Pdycelis Numbers with those of Dugesia lugubris plus Dendrocoelum lacteuni b. The Numbers of Polycelis in the Pnesence and Absence of Dug. lugubris plus Dend. lacteum.

.

a

Calcium mg/litre Species Total Polycelis Dug& Dendrowelum

+

Total Po1ydi.a when alone Total Polyw1i.a when others present

<2*5 30.7 0

-

-

2+5-0 104.7 5 *6

b

-

5.1-10.0

10.1-20.0

20.1-40.0

136.3 36.5

250.0 46.4

209.0 141.6

198 68

289 213

224 190

Triclad populations recorded aa number collected per hour averaged for lakes in each calcium category; a dash means no lakes in that category.

__

>40*0 222.3 144.2 222.3

LAKE DWELLING TRICLADS

53

substantial, i.e. within the calcium range of 20-40 mg/l. This suggeststhat the latter two species are curtailing further increase in Polycelis numbers. Table XVIIb compares the sizes of Polycelis populations in the presence and absence of Dugesia plus Dendrocoelum and it is apparent that in all cases Polycelis occurs in smaller numbers when the other species are present. Unfortunately, the few lakes providing data of this kind do not permit statistical analysis to measure significance but the results are in the right direction in each case. The only other evidence of competition relates to a comparison of fecundity in the laboratory and in the field for the planariid species. Both P . nigra and P . tenuis show fecundity in the field amounting to about 5 % of the laboratory value, but in Dugesia the corresponding value is about 2%. Such a contrast is probably explained by the fact that Dugesia is the last to breed and does so under more severe conditions of food shortage following breeding in the Polycelis species. It seems reasonable to conclude that these triclad populations live under a condition of severe food shortage and that competition for this resource occurs not only at the intra-specific level but also at the interspecific and inter-generic levels. This could play a decisive role in determining their distribution and abundance. OF DISTRIBUTION AND VI. THEEXPLANATION ABUNDANCE - A HYPOTHESIS

The four triclad species considered here show many similarities in their ecology such as habitat, feeding mechanism and life-cycle, so that it is convenient to consider the total tricled population as a unit initially and then to treat the individual species and their inter-actions.

A. THE TOTAL TRICLAD POPULATION A relation has been demonstrated between the size of the triclad standing crop in lakes and both the calcium and total dissolved matter of the water. Similar relations based on more qualitative data have been suggested for other littoral organisms such as gastropods (Boycott, 1936; Macan, 1950), leeches (Bennike, 1943; Mann, 1955), Asellus (Reynoldson, 1961b; Williams, 1962a) and tubificids (Kennedy, 1964). However, the phenomenon is even more widespread, extending to other lake communities. Thus bacteria and productivity have been correlated (Hayes, 1961), while Rawson (1960) has demonstrated the importance of the dissolved mineral content of lake water in relation to productivity. Larkin and Northcote (1958) have shown that significant correlations exist between this chemical feature and the amount,of plankton, biomass of benthic animals and fish. While these trends are unmistakable, nevertheless the individual features of a lake may be over-riding and 0

54

T. B. REYNOLDSON

give rise to exceptions based on any single edaphic measurement as emphasized by Larkin and Northcote (Zoc. c i t . ) and several examples of this in regard to triclads have been discussed (p. 15). The evidence already presented shows that the relation between water chemistry and the distribution of triclad species is indirect, which is not surprising for organisms at or near the apex of the food chain. These would be more immediately dependent on the kinds and numbers of their prey, and a closer, more direct relation between biomass and variety of littoral organisms and triclads would be anticipated. It is surprising that such comparative measurements of the littoral fauna are scarce, although Tucker (1958) has shown that the variety and numbers of littoral organisms are greater in calcium-rich, eutrophic ponds. Two sets of such data have been obtained for strongly contrasted lakes, one in North Wales, the other in the Loch Lomond area of Scotland. Both represent crude measurements of the standing crop in the spring and summer seasons respectively. Although Macfadyen ( 1963) has rightly pointed out the limitations of standing crop as an indication of productivity, in this case it is not likely to be grossly misleading since only macroscopic organisms were measured with life-cycles of comparable length. Standing crop is also influenced by the amount of predation on it. However, since predation is likely to be greater in minerally rich lakes, any correction for this would further emphasize the contrast in productivity between chemically poor and rich lakes. The North Wales data refer to five lakes and represent the pooling of independent estimates by nine students. They were obtained in two ways; by removing all the animals from five stones of fist size and by five-minute collections in the shallow littoral. Table XVIIIa shows clearly the relation between calcium, triclad numbers, biomass and numbers of the total littoral fauna. The variety of the fauna in the chemically richer lakes is less striking, but key secondary production such as Gammarus,Asellus and Lyrnnaeapereger was much greater in the minerally richer lakes. The Scottish data were obtained by Dr. J. 0. Young and the author by making a fifteen-minute collection in the stony, shallow littoral zone. The results (Table XVIIIb) show a clear relation between the standing crop of the littoral organisms (excluding triclads) expressed as biomass and the size of the triclad population. The regression coefficient is highly significant (b = 17.5, P < 0.02 >0.005) but this cannot be pressed since only twelve lakes were sampled. It is interesting that this relation is stronger than that between calcium and the triclad population. Rusky is an interesting lake in showing a much larger triclad population than the low calcium value would suggest. But this is matched by a comparably high littoral biomass, although Gummarus, a species not regarded as potential food of planariid triclads unless damaged

TABLEXVIII Comparison of hmbers and Biomass of the Littoral Fauna with Calcium and Triclud Numbers. For method see text

Lake Open Mymbyr Teryn Hendref Coron

Lake Arklett Con Ross *Lochan X Ard ArdGan Mentieth Dougalston +Pond Y Caldarvan

Rmky

Bardowie

Cangllitre

Triclads/hour

0 -4 1.1 0 -4 18.7 !6*5

0 30 72 160 299

a. Five lakes in N. Wales Biomass (gm.) Timed 5 stones 0.02 0.76 0-47 8-69 34-16

0.02 0.40 1-23 3.38 15-73

Number Timed 5 stones 2 46 41 208 650

2 34 29 97 317

Species Timed 5 stones 2 12 13 16 15

2 11 13 12 15

b. Lakes in Mid-Scotland (1963) arranged in ascending order of triclad numbers Caw Triclads Bioaass (gm) Dominant groups lire per h. Species per h. No. Species Biomass Number (8 16 12 20

58 :2 €0 2(8 E4 2 16

40 1f4

0 0 10 56 64 160 164 210 220 300 340 350

0 0 1 1 2 4 2 4 3 4

1 4

0.38 1.52 0 -54 3 -82 4-90 4.60 6 -05 6.45 3.04 6.60 7 -96 6.12

8 41 18 96 85 121 116 83 60 68 95 54

2 5 6 9 13 10 10 10 14 11 9 9

* h h a n X 3 miles (4.8 lon) N. of Drymen. Pond Y

1 mile (1.8km) 9. of Strathbhne.

Ephemeroptera Ephemeroptera Ephemeroptera Eph. Plecoptera Hirudinea Asellus Gastropoda Hirudinea Hirudinea Hirudinea Qammrua Hirudinea

+

Ephemeroptera Ephemeroptera Ephemeroptera Eph. Plecoptera Plecoptera AseUus Chironomus sp. AseUwr Asellus Hirudinea

+

Clammarus

Hirudinea

56

T. B. REYNOLDSON

(Reynoldson and Young, 1963), is numerically dominant. This briclad population is also exceptional in showing an increase since it was sampled 12years ago (Reynoldson, 1958a)when a population of 88/h was recorded compared with 340 in 1962. This was due to an increase in P. tenuis. Apart from the poorest calcium lakes the increase in number of littoral organisms is not marked, the increase in biomass being due to the prevalence of larger species. A similar conclusion applies to the variety of species but the key organisms alter; Plecoptera and Ephemeroptera of poor lakes give way to gastropods and Asellus in richer lakes. Leeches which probably compete with triclads for food, also dominate the richest lakes especially in biomass, along with triclads. Apart from Loch Rushy mentioned above, the variety of triclad species increases with standing crop. The conclusion which seems permissible from these results is that triclad numbers are related to the potential food supply in the littoral zone, and from what has been said earlier, are limited by this resource.

B. PZi? ZRazTzaZkz SPXCZZ# Before considering complex causes of distribution one obvious explanation of the co-existence of the four species in productive lakes must be dealt with, namely the possibility of vertical stratification of micro-habitats. If each species had an optimum micro-habitat a t a slightly different depth which still allowed mixing in the shallow littoral zone, it might not be detected by the sampling method used. However, apart from Chodorowski’s (1959,1960) work in rather different habitats there is no indication of this from the literature (Humphries, 1936; Berg, 1938). Proof that these four species are able to co-exist in the shallow littoral zone of productive habitats is given by their occurrence for upwards of 20 years in several small ponds around Bangor (N. Wales) with depths no greater than 1-2 f t (25-50 cm). Zonation would also fail to account for the reduction in species as lakes become less productive. I n Section V the major components of the triclad environment have been examined and the only factor which seems to be eligible as a determinant of the observed field distribution is inter-specific competition. The evidence of intra-specific competition for food, the overlap in range of food among the four species, the larger population size of species in isolation compared with mixed populations, the scarcity of predators and the resistance to senescence all indicate with reasonable certainty that food is the resource in short supply. This conclusion seems permissible despite the justified view of Mundie (1957) that the influence of single factors tends to be overstressed when they are considered separately and despite the ample demonstration (e.g. Elton and Miller, 1954) of the complex inter-action of organism and environment.

LAKE DWELLING TRICLADS

57

Competition in the narrower sense (Birch, 1957) is often regarded as including two facets, “exploitation” and “interference” (Brian, 1956; Park, 1962). There was no evidence from field or laboratory observations that “interference” is important in these triclads. Since the “exploitation” type of competition enters largely into this discussion some comment on definitions is necessary. Klomp (1961) has recently discussed competition from both the historical and definitive viewpoints, and my reading of his paper is that Birch’s (loc. cit.) and Milne’s (1961) definitions emphasizing a resource in short supply and Klomp’s clear enunciation of the role of a common regulatory factor are all acceptable since they reduce to the same essential. Pontin’s (1963) reluctance to accept Milne’s definition is misleading since he was dealing with the result of a process, Milne with the cause. DeBach and Sundby (1963) have suggested that competition occurs whenever a resource is used by two or more organisms, even when it is abundant. This is a matter of definition, but their view that competitive exclusion (or displacement, as they prefer) can take place when all resources are abundant, is misleading (cp. Solomon, 1957). Their supporting experiments suggest that “local” food shortages (Andrewartha and Browning, 1961) developed; in addition, their technique appeared to incorporate an artificial densitydependent factor. Deternination of distribution (and abundance) by inter-specific competition leads on to this concept of competitive displacement about which a great deal has been written since Darwin. At one extreme we have the improbable (Gilbert et al., 1952; Klomp, 1961) or absurd (Pontin, 1963) situation of different species with identical ecology; such species, if they existed, could not be differentially influenced by any ecological process. At the other, species which as a result of their evolutionary history are so different ecologically that they never compete. Between these extremes are all grades of severity of competition and outcome which may for convenience be reduced to three main categories. There are those situations in which one species will always eliminate another in a particular environment, those in which co-existence is usual, and those where intermittent co-existence is common. Although a mathematical approach to this problem with special reference to Tribolium populations has produced the same three cabgories (Park et al., 1964), the underlying causes may be dissimilar since co-existence in the field is usually associated with special circumstances as indicated below (cp. Pontin, 1961). It is interesting that Park et al. (loc. cit.) were unable to establish conditions for co-existence of T . castaneum and T . confusum in their experiments although a few populations came near to this. Examples from nature of elimination are usually inferred from patterns of distribution in space or time, but as Park (1948) and more recently Klomp (1961) and Hairston (1964) have pointed out,

’

58

T. B. REYNOLDSON

this is not conclusive and needs to be supported by experiment. Displacement by competition has been reasonably established for the special case of sessile animals (e.g. Connell, 1961) and plants (e.g. de Wit, 1960), and recently in the parasitic insect genus Aphytis (DeBach and Sundby, 1963). But the frequent reference in ecological texts to competitive displacement in stream-dwelling triclads (Beauchamp and Ullyott, 1932) a study unsupported by experiments, is symptomatic of the paucity of sound evidence on this matter, especially for invertebrates. In theory, co-existencedepends on one of several possible circumstances. There may be seasonal reversal of competitive superiority for the resource in short supply (Hutchinson, 1948, 1957) which Klomp (1961) has shown to demand density-dependent reaction; overlap in resource may be temporary as suggested by Lack (1946) for birds of prey, or it may be incomplete e.g. Kohn (1959) on gastropods. I n the latter case Andrewartha and Birch (1960) have pointed out the frequent need in laboratory experiments to provide a special niche (space resource) for one of the species if co-existence is to occur, although Utida (1957) was able to achieve this without such manipulation. Intermittent co-existence may occur when the average population level of one species at equilibrium is so low that periodically elimination occurs, for example during a “low” in the course of natural fluctuation; an aspect often overlooked in this context. Here, dispersal will re-establish the less successful species from time to time (cp. Skellam, 1951). Comparable examples illustrating these several categories were discussed for plants by Harper et al. (1961). With this short summary of competition and co-existence as a background we can now consider the special case of lake-dwelling triclads, bearing in mind that any hypothesis must explain exclusion a t one end of the habitat series and co-existence at the other. Study of the food of the four triclad species has shown that while there is considerable overlap in prey organisms nevertheless species representative of the three genera show some distinct contrasts. Thus Dendrocoelum lacteum is a more active hunter than the others and is able to capture Asellus so that in any competition which may develop for this prey it will be at an advantage. Dugesia lugubris alone feeds on gastropods to a considerable extent and this type of prey therefore provides a “food refuge” for it. Polycelis sp. tend to feed more on oligochaetes than the other species but they do not appear to have any special “food refuge” and indeed may not have been under any selective pressure to develop one since they are the most successful triclads. Thus each of these triclads would be expected to co-exist in habitats which provided sufficiently large populations of the more specific prey organisms. Correspondingly,if one or more of these “food refuges” are absent or too small then competition might be expected to proceed to elimination.

59

L A K E DWELIdINO TEICLADS

TABLEX I X The Distribution of Two Main Pwy Or
a. Lymnaea and Hydrsbia together (:a (mgllitre) t5.0 5.1-10.0 -~~

N. Ireland Mid-Scotland N. Wales Shropshire Total

014 3/11 2/14

N. Ireland

014 011 1 2/14 111 3/30

111 6/30

> 10.0

114 515 111 111 8111

8/11 13/15 9/12 11/11 41/49

114 415 111 111 7/11

711 1 11/15 12/12 11/11 41/49

b. Asdlus

Mid-Scotland N. Wales Shropshire Total

It would appear therefore that the key to understanding the distribution of these triclad species is LO be sought in the faunas of the lakes, and these have been examined from data collected a t the same time as the triclad observations. Table X [Xrecords the distribution of the two main types of prey providing “food refuges” in relation t o calcium. Although presence and absence cannot be pushed too far on such brief searches, the pattern shown for A s e h s (Reynoldson, 196lb) has been confirmed by Williams (196%~). These data show that as lakes become less productive the main “food refuges” of D.lncfeum and Dug. lugubris become fewer; fiirthermore the populations probably become smaller before disappearance. Thus Hunter ( 1957) has stated that although Lymnaea pereger occurs in the less productive north basin of Loch Lomond it is several times more iL5undant in the more productive lower basin; similar examples of this could be quoted from our own observations. It is clear from Table X LX that there is a broad parallel between the distribution of a particular ti-iclad species and its “food refuge”. The case of Dendrocoelum and Asellus has been analysed more fully (Young, 1963). The results (Tablo X S ) show conclusively (P < 0.001) that Dendrocoelum is usual y f m n d only in lakes containing Asellus. The few occurrences of Asellues without Dendrocoelum may be attributed to either the shortcomings of the data, the incomplete distribution of the triclad even in the most f s v o ~ r a b l habitats t or the small size of the Asellus population. Records of Dcndrocoelum in lakes without Asellus, all from N. Ireland habitats, may mean that under certain conditions it can co-exist with other triclad species in the absence of Asellus

60

T. B. REYNOLDSON

TABLEXX The Comparative Distribution of Asellus sp. and Dendrocoelum lacteum Asellus Present Absent Total

Dendrowelum Present Absent 31 7

38

7

41 48

but is more likely to be an artefact due to limitations of the data. The hypothesis that the occurrence of Dendrocoelum in the presence of the other triclad species is dependent on Asellus as a “food refuge” is also supported by consideration of the anomalous lakes in the relationship between triclad distribution and calcium. These are the artificial LIyn Mair (N. Wales) with 2.4 mg/litre calcium and Newton Mere with 5 mg/ litre. Among the large lakes the occurrence of Dendrocoelum in Loch Lomond with 3 mg/litre and Lake Windermere with 5 mg/litre come also into this category. Since Asellus occurs in these lakes also outside its normal calcium range in Britain it would provide the necessary “food refuge” for Dendrocoelum. The more frequent penetration of Dendrocoelum into low-calcium lakes in Fennoscania (Reynoldson, 195%) is again paralleled by a similar penetration by Asellus (Reynoldson, 1961b in Discussion). Some recent work by Mr. I. R. Ball on the triclads of streams and ponds in Cambridgeshire and nearby counties supports this view. He has found (private communication) that of thirteen localities with a triclad fauna, the eight which contained Asellus in numbers also supported Dendrocoelum usually with other triclad species. Of the remaining five, one contained a few Asellus, the rest none. This close link between the triclad and main prey raises the question whether we are dealing with a specific dependence on Asellus or a non-specific one. Consideration of the food of Dendrocoelum which includes a wide range of organisms (Reynoldson and Young, 1963) supports the latter view, and here it is assumed on the basis of both similarity in food and feeding mechanism that if one species of triclad can maintain a sizeable population in a particular lake, then any of the others can do likewise in isolation, but field experiments have not been completed to test this. Differential temperature effects may demand some qualification of this generalization but not in the case of ~ e ~ r o coelum (Repoldson et al., 1965) which is the most tolerant Of low ternperatures. Dugesia lugubris also occurs in Newton Mere, Loch Lomond and Windermere outside its normal calcium range and this is also

L A K E DWELLING TRICLADS

61

paralleled by the presence of snails. The importance of this type of prey was nicely illustrated by a simple field experiment. Previously (p. 51) reference was made to the failure of Polycelis nigra to establish itself in a small P . tenuis habitat ‘which contained largely Asellus meridianus, Hydrobia ( = Potamopyrgus)jenkinsi and Luwi,briculus variegatus. When the comparable experiment was done with Dugesia, although the initial numbers introduced were smaller than in the #caseof P . nigra, 250 compared with 400, it had no difficulty in establishing itself and this is attributed to the presence of Hydrobia in lslrge numbers. The broad relationship suggested between the distribution of gastropods and Dugesia is also supported by the work of Boycott (1936), Macan (1950), and Hunter (1957) on snail distribution, but it is worth mentioning at this point that the rapid spread of Hydrolrict in Britain (Hunter and Warwick, 1957) may well influence the futurls distribution of Dugesia, because this snail is more tolerant of unproductive habitats than the common species Lymnaea pereger. This may make less productive habitats available to Dugesia. The overall picture presented here suggests that as lakes become less productive the total hriclad population declines and ultimately disappears because of food shortage. The parallel restriction of species, ultimately to Polycelis wigra, is due to the lesser numbers and variety of prey so that “food refuges” become smaller and eventually disappear, forcing the triclads to compete for the same food resource to an increasing degree. An explanation of the co-existence of Polycelis nigra and P. tenuis is more difficult although evidence of competition between them is more obvious, both features resulting from the c1oc:e taxonomic relationship. The elimination of P . tenuis a t low calcium levels and the reduction or elimination of P. nigra at high levels is almost certainly due to competition for food; their co-existence in lakes of intermediate type suggests incomplete overlap of food. This was not demfonstratedconvincingly by the study of feeding, but it is to be expected because of close taxonomic relationship that any difference might be slight and difficult to detect. In this connection it is interesting to note that P. nigra fed more extensively than P. tenuis on Plecoptern (Reynoldson and Young, 1963), a group characteristic of unproductive lakes, but this needs further testing. A second point is that lakes containing only P. nigra seem to have a rather smaller population than those containing P. tenuis in addition (Table XIVa), suggesting that the two species together are able to tap a wider food source. A third point is that co-existence seems to be more difficult in the most, productive lakes, for example in Shropshire P.nigra was not recorded in 5/12 meres. Here the faunas are likely to depart farthest from those of unproductive lakes and therefore would suit P. tenuis more. Although some aspect of their ecology other than C*

62

T. B . REYNOLDSON

food might be involved, this seems unlikely in view of their similar biology; but Harper (1964) has made the point that biology is not always an adequate basis on which to forecast ecological interactions. This work started from a correlation established between the chemical condition of lakes and their triclad faunas. We now know that this is a very indirect relation which nevertheless was detectable through a food chain of at least three trophic levels, a fact which illustrates the over-riding influence of the physico-chemical background of the environment. It follows that for a complete understanding of the distribution of triclads it will be necessary to follow the food chains back to the primary producers. Again, looking beyond the hypothesis suggested here which is now being tested experimentally in the laboratory and the field, it will be ultimately necessary to consider the reasons why a particular species is successful or unsuccessful in the struggle for existence. It is at this level of inter-action that other modifying factors of the environment such as temperature and water chemistry may operate differentially. AND SUMMARY VII. CONCLUSIONS

The four main lake species of triclad, Polycelis nigru (Mull.), P . tenuis Ijima, Dugesiu lugubris (0.Schmidt) and Dendrocoelum lacteum (Mull.) all occupy the shallow littoral zone and feed on other organisms found there. The feeding mechanisms of all are similar and there is wide overlap in the type and size of prey eaten by them and also by the young and adults of the same species. At the species level, triclad populations show restricted fluctuations in numbers and live under conditions of food shortage for long periods of the year. Numbers are regulated by intra-specific competition for food, which stems mainly from two biological properties: high resistance to death by starvation because of their ability to resorb and then regenerate tissues, and a high degree of immunity from predators. The triclad populations of lakes vary in size from complete absence to very high numbers and there is a general, positive correlation with both the calcium content and the total dissolved matter of the water. The pattern of species distribution is also related to these factors. The relation is indirect and triclad abundance is determined primarily by the amount of food available in the littoral zone, itself ultimately dependent on the water-chemistry. The distribution and abundance of the individual species of triclad are determined primarily by inter-specific competition for food. The outcome depends upon the pattern of distribution and abundance of certain numerically important types of prey because, despite the high degree of overlap, each triclad species feeds on a particular kind of prey

LAKE DWELLING TRICLADS

63

to a greater extent than the others, i.e. each lhas a “food refuge”. Thus Dug. lugubris alone feeds upon gastropod molluscs, Dend. lacteum captures Asellus most efficiently and Polyeelis species take more oligochaetes . It is suggested that because these import$iit food organisms become both less numerous and less varied in the littoral zone as lake productivity declines, the triclad species are forced to compete with increasing seventy. As a result, lakes of low productivit:r (minerally poor) support smaller numbers of triclads and fewer species than lakes of high productivity (minerally rich). Thus only P.nigru exists in the poorest lakes while all four species co-exist in the richest lakes. The basis of coexistence of P. nigru and P. tenuis in all but the poorest lakes has not been established, but it is probably due to a “food refuge” difficult to detect because of the very similar nature of %heirfood. It is important to emphasize that competitive displacement depends not only on the ecological properties of the organism but also on the properties of the habitat. For example, in unproductive lakes all the triclad species are effectively ecologically similar in their food, in productive lakes this is not so.

ACKNOWLEDGMENTS I wish to acknowledge the help of Dr. J. 0. Young who was my assistant for three productive years and also his permission to use the data on littoral organisms collected jointly. The following people kindly helped either by collecting and sending me triclads or making observations on their occurrence in the remoter places; Dr. M. Angel, Dr. R. Carrick, Mr. R. C. Connolly, Dr. Llyr Gruffydd, Mr. H. G. Lloyd, Miss S. MacLachlainn, Dr. A. Milne, Mr. P. Langton, Mr. R. J. Spittle, Mr. T. Warwick and Mr. D. R. Williams. I have also to thank Mr. F. J. Mackereth for providing some of the chemical data. I am grateful to Dr. A. G. Dahm and Dr. (3.B. Corbet who gave me the benefit of their advice on the historical aspects of distribution and to Dr. P. O’Donald who advised on the statistical analysis of Dr. Mirolli’s data. The manuscript was read for me by Mr. L. H. Jackson to whom I am grateful for several improvements. The Department of Scientific and Industrial Research have generously provided money for an assistant during the last three years and are continuing to do so. I am grateful to the Nature Conservancy and the Royal Society who financed a major pan; of the travelling incurred by the field work. I also wish to thank the Leverhulme Trust for the grant which enabled me to study triclads in Sweden and N. Ireland. Finally, I wish to thank Professor F. W. FCogers Brambell, F.R.s., for his encouragement and support at all times, *

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Young, J. O., Morris, I. G. and Reynoldson, T. B. (1964). Arch. Hydrobiol. 60, 366-373. A serological study of Asellus in the diet of lake-dwelling triclads. Young, J. 0. and Reynoldson, T. B. (in press). 0i.kos. A quantitative study of the population biology of Dendrocoelum lacteccm (Miill.) (Turbellaria, Tricladida). Young, J. 0. and Reynoldson, T. B. (1965). Hydrobiologia 26, 307-313. A laboratory study of predation on lake-dwelling triclads.

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Energetics, Terrestrial Field Studies,

and Animal Productivity M A N F R E D D. E N G E L M A N N

Department of Natural Science, Michigan State University, East Lansing, Michigan, 1J.S.A.

..........................................................

I. Introduction 73 11. Three Approaches to Energetics Studies.. ................................ 74 111. Historical Considerations.. ............................................. 78 IV. Physiological Studies Which Yield Energetics Infcmrmation. ................. 84 V. Studies Concerned Primarily with Maintenance Metabolism of Population8 in the Environment 87 VI. Studies Which Emphasize the Trophic Scheme Analysis of Communities. 96 A. Trophic Dynamic Analysis of the Salt Marsh Ekotone 96 B. Trophic Dynamic Analysis of “Old Field” Communities.. 98 C. Trophic Studies in a Savannah Community.. ......................... .lo3 VII. Projection ............................................................ 108 References ................................................................ 112

.................................................... .... .................. ...............

I. INTRODUCTION There is currently a feeling among ecologists that their science has reached maturity, and that the concepts and knowledge of this science are destined to shape the future of our burgeoning human population (Sears, 1964; Odum, 1964; Blair, 1964; Cole, 1964; and others). These scientists consider ecology to be a “respectable” science for reasons ranging from the fact that problems of ecology are concerned with practical considerations (such as atomic fallout, overpopulation, pollution, and pesticides) to the fact that the ecologisI;s are using models, both mathematical and verbal, to guide future experiments. I n this age of an accelerated pace of human events and immense social prmsures, a p p mium has been placed upon the directed approach and rightly or wrongly scientists are called upon to justify their studies and indicate their importance either to the body of knowledge called science or to human problems, or both. If ecology, then, is to be a part of the new trend and to be in the mainstream of science and human destiny, ecologists must 6 the human effort. justify their science and elucidate its importrince t The goal of this paper is to evaluate the growth and development of 73

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terrestrial energetics at this point in its history. The task is by no means a small one. Even though the accumulated literature a t present is rather limited, the studies that have been reported are recorded in many different journals covering diverse approaches to ecological research. In this article, the subject of field estimation of productivity will be approached in three ways: first, the historical and theoretical bases which undergird terrestrial productivity studies will be considered; second, the various works in the field will be reviewed, with particular emphasis upon the relationships of the papers to one another and the type of data each yields; finally, the progress of terrestrial energetic studies as a whole will be evaluated and areas wherein critical research is needed will be indicated. I must admit that I face some difficulty performing the task set before me with necessary thoroughness, especially with respect to the final point. However, I hope that my efforts will give others further insight into the problems in the field and thus enhance its progress.

11. THREEAPPROACHES TO ENERGETICS STUDIES There are probably three main approaches to the problem of field estimates of animal production. The preceding statement is qualified because the word productivity has various interpretakions. Not one of the definitions given in Webster’s Unabridged Dictionary would suitably characterize the highly specialized nature of “production” as used in the field of energetics. The cattlemen and farmers use the word to mean such measurements as number of head or bushels per acre, the biologist refers to number of individuals born per unit time as “production”. Most of the time, the ecologist also employs the latter meaning when constructing life tables or dealing with other aspects of population. However, when the term calorie is considered, the terms production and productivity take on more restricted meanings. The restricted meaning, moreover, was not immediately recognized, but evolved slowly through the 1930’s and 1940’s. Variations in the use of these terms by different authors are eloquently summarized by Macfadyen, 1963a, pages 160 and 161. His table, clearly demonstrates why the term productivity provokes a confused response from “production scientists”. To avoid many of the difficulties raised, I wish to sidestep the issue by stating the two definitions of productivity used in this paper. They are: (1) net productivity, the number of calories represented by the new individuals and the increase in weight of the population per unit of time; and, (2) gross productivity, the total number of calories expended by the population in maintenance, i.e. respiration, plus the calories represented by numbers produced and increase in population weight or biomass. In referring to the three main sources of productivity information, then, I

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am specifically referring to that portion of the literature which is concerned with caloric values and transfers. The first major source of information on energetics of natural communities has its origins in physiological studies dating from the investigations of Lavoisier in the late 18th century. They emphasize the homeostatic mechanisms of the organism, the iinvestigator exploring the individual’s response to an environmental stress. Some aspect of the animal’s metabolic rate is measured during the various stress situations. When respiration rate or heat production is used as the measure of response of the animal to stress, the data aro potentially useful in an energetics analysis. The stress studies themselves, however, are usually not sufficient for energetics analysis because field data on numbers or biomass are lacking. The studies of the physiological ecologist (or the ecological physiologist) are concerned primarily with the individual and form a tremendous and diverse reservoir of information, useful in making field estimates. The second major source of information on energetics of natural communities comes from analysis of maintenance energy by what I refer’ to as the “Bornebusch” approach, which is b,ased on the assessment of three key parameters -numbers of individuals, biomass, and oxygen consumption. When these parameters are known for different populations in the field or for different communities, the resulting data can then be used to compare the impact of the dijfferent populations on the community or the relative amounts of energy flow through the different communities. The key factor in a Bornebusch type study is comparison of the total metabolism of different populations as reflected by respiration rates. Respiration rates can be a sound means of comparing populations, because in most animals about 70% of the assimilated calories are used for maintenance and thus show up as respiration. From the community point of view, all of the calories captured aa radiant energy will eventually be dissipated as heat via respiration (exceptions are peat bogs and rapidly buried organic deposits). On the other hand, population or community analysis using species diversity or numbers presents great problems. Here we are comparing unlike elements and more or less objectively making them equivalent, i.e a species as a unit. The Bornebusch approach utilizes units which are common to all animals and plants, i.e. mass and respiratory metabolism. Thus, the comparisons are less subjective. The third approach to this subject of energetics of natural communities comes from the trophic-dynamic or Undeman school of community metabolism. The guiding principle in this type of study is the Lindeman (1942) model. It consists of a flow diagram of energy made up of the following components: A,, the energy coming into a trophic or feeding

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level of the system in the form of food or sunlight; A,, the energy found in the bodies of individuals which make up the trophic level, i.e. the standing crop energy; R,,the energy lost to the trophic level in respiration; D,, the energy lost to the trophic level by way of the decomposers; and Adl, the energy lost to the trophic level from consumption by the next trophic level (see diagram). The flow diagram is in turn based upon several laws and assumptions. They are as follows: (1) the laws of thermodynamics hold for plants and animals; (2) plants and animals can be grouped together into trophic levels according to their feeding habits; (3) there are at least three trophic levels (there may be more) which are: (a) producers (green plants) ; (b) herbivores (animals feeding upon the green plants); and (c) ca.rnivores (animals feeding upon the herbivores); and (4) the system is in equilibrium; and ( 5 ) calories are the basic units of the trophic scheme. From these assumptions, it can be deduced that: (1) each succeeding trophic level will have fewer calories than the preceding one, and (2) that there is a finite number of trophic levels. I n a steady state condition, A,, will equal the sum of R, D, Adl. For increasing or decreasing populations, A, will equal R, D , hdl AA,, where AA, is the increase or decrease in energy of the standing crop. However, the Lindeman model is not designed to

+ +

+ +

+

TO NEXT TROPHIC LEVEL

Fra. 1. Schematic representation of the Lindeman Model. The drawing depicts a single trophic level with the energy flow indicated by the arrows. For a complete representation of the trophic levels of an “old-field’’community see Engelmann, 1961, p. 236.

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handle situations of imbalance because of the equilibrium assumption. A very important point should be emphasized here, one that is most apt to cause confusion when discussing the Lindeman model. A body is made up of both matter and energy. The energetics approach is concerned only with energy, not the matter. The matter is recycled through the biosphere, being used again and again through successive ages. Energy is not recycled by the biosphere. Each time organisms transfer potential energy from one trophic ievel to the next, a portion of the energy is lost in the transfer, never to be regained by the system. Thus, when we speak of standing crop, we are concerned not with the matter this represents but with the amount of energy necessary to hold that matter together. The trophic dynamic approach to the problem, then, is concerned primarily with food relationships (i.e. the food of the community), the assignment of populations to food levels, and the total energy flow through an area or community. A complete analysis of this kind results in an energy balance sheet for the community and therefore should give a number of internal checks on the consistency of the various estimates of energies. If a model is to be a useful guide t o further research, it must have particular characteristics which result in logical deductions and predictions. Three important criteria for judging whether a model will result in useful information are as follows: ( I ) the internal consistency of the model; (2) the number of important testable hypotheses resulting from the model; and (3) the relevance of the inodel to existing concepts and hypotheses. How does the Lindeman model hold up under these criteria? Slobodkin (1962) has indicated that Lindeman’s model is more or less internally consistent and leads to testable hypotheses. This model immediately raises three testable questions, which are: (1) What is the maximum number of food links in an a,rea? (2) Is there a characteristic ratio between the calories contained in one trophic level and the calories contained in the succeeding level? and (3) Are there any consistencies between the ratios of the productivity of a species and that of its predators? Criterion three mentioned above (the clarification and integration of existing concepts and hypotheses) seems also to be met at this stage of our knowledge by Lindeman’s model. It fits logically with the concept of community. If the community is-real, then energy flow within community boundaries will be much greater than across community boundaries. Therefore, the tool for more certainly delimiting and defining communities may be within the ecologist’s grasp. It is very likely that the Lindeman model or some modification of it will give us a better understanding of the community concept. Other ecological concepts can be re-evaluated by use of the energetics a,pproach.For example, the

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subjectively determined, dominant, characteristic, influential, conspicuous, and rare species categories can be given a more objective basis using energetics criteria. A species with a large number of slow metabolizing individuals may be less important to the community than another species with fewer metabolically or reproductively active individuals. Finally, the Lindeman model depends heavily upon natural history observations, life tables, metabolic data, phenology, physiology, and, in short, the majority of the factual information accumulated from natural communities over the years. This model, though imperfect, can give a new dimension to the old concepts in ecology. There are, of course, other models in the ecological literature which are designed to define and characterize elements of certain ecological concepts (e.g.MacArthur, 1960; Hairston, 1959; Hairston et al., 1960; Patten, 1959; et cetera). All of these are of value in our present stage of knowledge. Some models may eventually have greater significance than do those based on energetics. Others may contribute much to the Lindeman model. Of course all of them are subject to a great deal of debate, and the resolution of the debate will come from a conclusive experiment or observation. As has been pointed out by Slobodkin (1962) and will be underlined again in this paper - the paucity of the data in the field of energetics at this time emphasizes the need for research rather than discourse.

111. HISTORICAL CONSIDERATIONS At first glance there is a parallel between the spread of the study of energetics in ecology and the evolution of the vertebrates. Both had their origins in fresh water and then spread to the sea, but only with reluctance did they clamber to the land. It required 20 years from the beginning of the productivity studies t o the enunciation of the guiding principles of those studies and it required another 20 years for those studies to spread to terrestrial situations. Although the work of Birge and Juday laid down the beginnings of productivity studies in 1922 and the trophic dynamic approach was proposed by Lindeman in 1942, the first major work on terrestrial systems did not appear in the literature until 1960 when Golley published a Microtus food chain analysis in the Lindeman tradition. The limnologists and oceanographers during the forties and fifties produced numerous works on freshwater and marine habitats. The terrestrial biologists were not completely inactive during this period, for Bornebusch (1930) did his classical study on beech forests in Denmark. He paid attention not only to the number of individuals in each species but also to their weights and respiratory rates. It was apparent to Bornebusch that the different rates of metabolism of the

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different species populations could alter their importance to the community. His methods, however, were not utiltced by others working on natural communities and his work remains a solitary landmark in the literature. To be sure, the engine-like nature of the living organism was elucidated by Lavoisier in 1777 and many workers through the years turned their attention to the bioenergetics of animals. All these works, however, were concerned with single individuals of either man or domestic species (Atwater and Benedict, 1903; Armsby, 1903; Brody, 1945).

Ecologists of the 1940’s and 1950’s presumably had the techniques and information available to carry out energetic studies on terrestrial communities. Why were not these studies carried out earlier? There is no certain answer to this question, but part of the explanation lies in the different characteristics of the two major envJronments (terrestrial versus aquatic), as well as in the elements of human whim and communication. The aquatic environment is easily definable with rather clear-cut boundaries. The majority of the physical components of the liquid environment can be measured by simple chemical tests. The portions of an aquatic environment stay relatively congtant during the die1 cycle and have a limited range of variation during the annual cycle. Last and by no means least, most aquatic environments have a biota which is taxonomically well defined and not tremendously complex. On the other hand, the terrestrial situation is very complex. For example, moisture variation from day to day and place to place has a tremendous influence on the biota of an area and poses a formidable measurement problem for the investigator. Moisture can precipitate in an area in the form of rain, snow, sleet, or dew, and can be lost in the area as run-off or evaporation. A single aspect of the moisture content of the air can be recorded as relative humidity, vapor pressure, saturation deficit, absolute humidity, specific humidity, and mixing ratio (Platt and Griffiths, 1964). The obvious variability of the physical terrestrial environment is one of the deterrents to a complete energetics study. The biological elements of this environment further complicate the matter. Many of the taxa important to terrestrial communities are poorly known. It has been stated in the literature that there are about 650 000 species of described insects in the world (Metcalf and Flint, 1939), and it is estimated that 2 500 000 species exist at this time. The insects are an important component of every terrestrial community, both from the standpoint of numbers and of ,activity. Thus, almost half the species present in the natural community are not as yet recognized by science. Taxonomically, the insects are well knQwn when compared to some other taxa such as mites or nematodes. Furthermore, the number of species present in any single area may be great. Evans (1964), for

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example, reported 1 700 species captured from the herb strata of an “old field” in Michigan. Two hundred and sixty of these species occur commonly and were believed to represent the resident fauna of that field. Hairston (1959) and Hairston and Byers (1954) recorded 271 species of arthropods found in the soil of the same “old field”. For this 15-acre field in southern Michigan then, nearly 2 000 species of arthropods have been recorded, of which about 320 are part of the normal resident fauna. The task of keeping the species categories separated during energetics analysis is formidable. The problems which made terrestrial communities less suitable for energetics studies in the 1940’s are still present. The need for making such studies is becoming more evident and more urgent, and thus these pioneer studies set forth the first crude guides to the methods necessary for such an endeavor and yield data which begin to define the limits of the problem. To make a complete energetics analysis we must have estimates on ingestion rates, assimilation rates, egestion rates, respiration rates, growth rates, death rates, numbers and biomass, and the calories represented by these figures. None of these parameters is directly measurable in the laboratory or field but must be calculated from several kinds of data. Paradoxically, a good portion of the data necessary for field estimates must come from laboratory studies. If energetics studies are to be properly evaluated, it is essential to understand the general procedures of obtaining the relevant data. Measurement of ingestion rates requires knowledge of the amount of food the animal consumes during a certain time period and the caloric value of the food consumed. If the amount ingested cannot be measured directly in the field, estimates must be made from ingestion data on animals in enclosures or in culture cages. Direct measurements of assimilation rate must be done in the laboratory, but this parameter can be estimated from an equation when ingestion and egestion rates are known. It should be noted that every rate estimated from an equation eliminates one of the internal checks inherent in the Lindeman system. The calories egested are not important to the particular population or trophic level which “produce” them, but the feces are important for the decomposer system since they make up part of the energy source of the decomposers. Energetically, feces contribute no calories to the population for performing work and require only that the organism expend energy to move them through the digestive tract. The animals which can move great quantities of non-utilizable material through the digestive tract with small amounts of energy would of course have some adaptive advantage, but present methods used in energetics studies are not sufficiently refined to answer such questions.

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The respiration rate represents the maintenamce portion of the energy budget, that portion of the assimilated food necessary to keep the organism together and functioning. Respiration can be estimated by measuring either oxygen consumption or carbon dioxide production. There are numerous devices which measure oxygen uptake, but they generally fall into three major types: the constant pressure, constant volume, and differential (Dixon, 1952). The most widely used apparatus in tissue culture study is the constant volume type represented by the Warburg respirometer. Yet in most of the energetic studies at present, some form of a constant pressure apparatus is employed. The major exception to this statement is found where very small organisms (mites, collembola, etc.) are concerned, and then the Cartesian diver apparatus (a constant volume type) is used. Several studies employ some method of estimating respiration rate by CO, production. This usually involves capturing the CO, in a standard basic solution, thus converting the base to a salt and then titrating the remaining base with an aoid standard. It must be kept in mind that in energetics studies the number of units of 0, respired is not so important to know as the number of calories represented by this respiration, because it is an estimate of the amount of heat the population loses in the process of maintenance. Conceivably, it should be possible to measure the heat production directly via calorimetry in the field. However, at present the technique required for direct field calorimetry has not yet been attempted. Growth rates are measured either in the 5eld or in the laboratory where the animals are kept in cages or culture,g.Each approach presents problems. I n the laboratory, growth rates ca2 be measured very accurately, but the conditions under which the animals are kept are not those of the field. Field studies, on the other hand, have the advantage of natural surroundings, normal activities, and usual diets, but present the problem of measuring and keeping track of the growth rates of particular individuals. Still another approach to the measurement of growth rates is that of deducing them from the numbers of individuals found in various size categories during successive field samplings. This approach is particularly useful for the meiofauna and the microfauna where marking, release, and recapture techniques have not yet been worked out. Data on death rates are obtained in the r3ame way as are data on growth rates. Cage or culture studies, however, yield only data on deaths resulting from physiological limitations, and the survival rate is higher than that found in field populations due to the absence of predation. The most reasonable approach at this time seems to be the construction of a life table (Allee ct al.,1949, page 265) from laboratory or enclosure data, and the adjustment of this table to field conditions. One of the most complete life tables we have for ,an animal other than man

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is that of the human louse, Pediculus humanus (Evans and Smith, 1952), yet no one has yet seen fit to work out the energetics of this animal. Complete life table data are very hard to obtain, but yield estimates of standing crop and turnover rates, these being far superior to the estimates derived from simple field counts. The entire field estimate depends ultimately upon the estimate of the numbers of individuals present in the area. A large amount of literature has accumulated concerning the many and varied techniques for sampling populations. The techniques vary with the type of terrain and the kind of animal being sampled. Dice (1952)and Macfadyen (1963a)among others have written good general chapters on sampling techniques. Each investigator, however, has his own modification of some existing technique made necessary by the kinds of animals and the terrain encountered as well as by the time, materials, and money available to him! Several other estimates (e.g. total numbers of individuals present during a period of time, biomass, standing crop, age and/or size classifications, and total respiration per annum) are derived directly from the number of organisms counted in the field sampling program. Thus, it is important that these counts be as accurate as possible. When field data on numbers are not accurate, as in the case of Bornebusch (Birch and Clark, 1953), the study loses a good deal of its usefulness. As previously stated, numbers of individuals, per se, are not useful’to the energetics analysis and, thus, conversion must be made to energy units. The information necessary for the conversion is: (1) the weight of each individual and (2) the calories represented by the weight. Weight or biomass, then, is the intermediate step between numbers and calories. Under certain circumstances, weights are assigned from graphs or equations relating some aspect of size to weight. Dry weight or live weight may be used, but dry weight is preferable because it eliminates the possible variation in water content of the individual. The weighed material must then be burned in a calorimeter to obt9in the equivalent calories. Lists of energy values for various animals and plants have been compiled by Golley (1961) and Slobodkin and Richman (1961). Average values derived from such lists are often used where direct calorimetry cannot be undertaken by the investigator. Aside from the techniques neceasary for making energy estimates, there are also several ratios or relationships which are useful in comparing different species, populations, or communities. Three such ratios appear to be important to the studies of energetics of terrestrial animals. The first,relationship is more or less characteristic of the individual, the efficiency of digestion. The efficiency of digestion can be calculated also for a population and, thus, can be used in a broader sense; however, it is ultimately based upon each individual’s ability to consume and assimilate food. The ratio is

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defined as follows: the efficiency of digestion ia equal to the number of calories assimilated divided by the number of calories ingested. This ratio is important because food consumption in the field is difficult to measure directly. If the investigator has information on either the amount of ingested material or the growth plus the maintenance amounts, then the formula for digestive efficiency can give him some estimate of the food ingested during the period of time in question. The second ratio of importance to energetics studies is the relationship between metabolic rate and weight of the animal. This is used also as a predictive tool in an effort to estimate respiratory rate or metabolic rate when only the weight of the animal is known. The general formula for this relationship is: M = aWb, where it1 represents metabolic rate, W is the weight of the individual, and a and b are constants. The value obtained for the constant b in a set of experiments can be used to compare the metabolism of two animals. Theoretically, a and b should be constant, and b should be equal to 0.67. However, this is not actually the case, and the formula for the weight mei;abolism relationship becomes a comparative as well as a predictive tool. The third ratio is one characteristic of the .Lindeman or trophic efficiency model. When this ratio was first proposed by Lindeman (1942) he called it “progressive efficiency” and defined it as A, divided by An-l times 100, where A, was the number of calories ingested by the organisms feeding on An-l, and An-l is the number of calories ingested by An-l. Hutchinson (Lindeman 1942) called this the “true productivity’’ of the energy level. Slobodkin (1960) recognizing the confusion surrounding this important ratio renamed it “eco!’ogicalefficiency”. Patten (1959) in his paper on cybernetics and energetics renamed this same ratio the “efficiency of transfer of ingested energy”; Davis and Golley (1963) called it “utilization efficiency”; while Wiegert (1964) pleading for uniformity in nomenclature and for names which outline the important features of the efficiency ratios, introduced the title of “gross efficiency of yield divided by ingestion”. The term “ecological efficiency” seems to me to be the most convenient and the least ambiguous and I shall use it when discussing the ratio of the number of calories removed by the predators (A,) divided by the number of calories ingested by the prey (An-l) times 100. Note that the ecological efficiency does not compare gross productivity of two successive levels, but rather compares the ingestion rates of the two successive levels. Ecological efficiency, then, is an important ratio when one community is compared with another, as well as when two trophic levels are compared. The ratio is primarily important to the Lindeman model rather than to any practical applications by man. There are other comparisons in the form of efficiency ratios, made by the trophic analysis, Patten (1959). It may

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be that through increasing knowledge one or more of these ratios will become more important to the ecologist studying the energetics of ecosystems as well as to the production manager. However, at this stage, the three relationships listed above seem to be the most important; discusion will be confined to them. Using the approaches and ratios listed above as a framework, we can now look at the research in the field in an effort to: (1) understand what has been done or attempted to date; (2) view data thus far accumulated on net and gross productivity in terrestrial communities and (3) evaluate the information in terms of theoretical and practical objectives.

IV. PHYSIOLOGICAL STUDIES WHICH YIELD ENERGETICS INFORMATION I have set a rather arbitrary limitation on my discussion of the physiological literature. I will consider chiefly papers which either have used another author’s field data, made estimates of field energies, or have provided physiological data used by other researchers in making field estimates. Several studies have reported oxygen consumption a t various temperatures: for a spider, Lycosa pseudoannulata (It6, 1964), the collared lizard, Crotaphytus collaris (Dawson and Templeton, 1963), crossbills, Loxia curvirostra sitkensis and L. 1. leucoptera (Dawson and Tordoff, 1964), the eastern cardinal, Richmondena cardinaZis (Dawson, 1958), the English sparrow, Passer d . domesticus (Kendeigh, 1944 and 1949) and Emberiza (Wallgren, 1954) and several rodents including Zapus, Eutainias, Microtus, and Glaucomys (Morrison and Ryser, 1951), Dipodomys and Citellus (Dawson, 1955). Other studies deal with food consumption in relationship to temperature (e.g. Sealander, 1952) or with food utilization and digestion (e.g. Waldbauer, 1964; Gere, 1956a, b; Van der Drift, 1958). Still others have done notable works compiling great areas of knowledge, such as the books or chapters by Brody (1945), King and Farner (1961). Several of the papers are worth particular note. It6 (1964) is one of the few whose writing concerned some aspects of the energetics of a predator. Using a microchemical technique for carbon dioxide production, It6 was able to estimate energy utilization of the spider which averaged about 35-81 g cal/g (live weight)/day, or about 150-94 g cal/g (dry weight)/day. Using these data and making assumptions on assimilation, he estimated that the spider required 73 g cal/g (live weight)/ day in food to maintain itself. This stud has most of the elements necessary for a field estimate and lacks only data on numbers present in a natural habitat. The book by Brody, “Bioenergetics and Growth”, deserves special

Y

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mention because of its importance as a standard reference on energetics. This work is concerned with domesticated farm animals and thus is useful in calculating farm productivities. However, many of the chapters are of a general nature and contain a wealth of information concerning such vital subjects as energetics and energy units ; energetic efficiencies of growth and work processes; nutrition, the principle of diminishing increments in efficiency; homeostasis and organismic theories; methods in animal calorimetry; and the energetic efficiencies of muscular work. For the most part, the book discusses such aepects as the processes of growth and metabolism. Marshall “Biology and Comparative Physiology of the Birds”, Vol. 11, contains much information on energetics. The chapter on energy metabolism, thermo-regulation, and body temperature contains information on calorimetry, met.a,bolicrates, energy metabolism and the variation in energy metabolism. The chapters on flight, long distance orientation, behavior, and bird populations also contain information which is potentially useful in making field energy estimates. The study undertaken by West (1960) on the tree sparrow, Spizella arborea, met all but one of the requirements of a complete field productivity study; field data are lacking on numbers of individuals. West’s primary concerns were: (1) the number of calories necessary to support the birds in their environment; (2) the caloric burden of migration and incubation. Food consumed and excrement produced (West used this term to mean egestion plus excretion) by the ;birds was measured both in the laboratory and in outdoor cages at Churchill, Manitoba, Canada (the birds’ breeding range) and a t Urbana, Illinois, U.S.A. (the wintering range). Values averaged around 4.4 kg cal fm the food and 3.7 kg cal for the feces. The energy consumption of the birds varied with the ambient temperature from 34-23 kcal/bird/day (1-64 kcal/g/day) at -30” C to 10.77 kcal/bird/day (0.49 kcal/g/day) at 30” C. Day length also caused variation in calorie requirements rmd caloric consumption. From these and other data West constructed a series of equations and a graph for the annual energy budget of an adult bird. The equation which related grow energy intake of the bird to temperature was GE = 25.89 kcal/bird/day-0.254 T o C. The equation which represented metabolizableenergy with relationship to temperature was M E = $9.05 kcal/bird/day-0-167 T o C. Each bird required roughly 7 460 kg cal each year to live, migrate and reproduce in the wild. West had no figures on the area necessary to provide these calories and, thus, no productivity figures per unit area for the population were given. The last paper of a primarily physiological nature I wish to discuss is that of Pearson (1960) which has many elements of the Bornebusch approach although emphasizing the homeostatic mechanisms of the harvest mice. Pearson considered oxygen consumption and its relationD

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ship to ambient temperature. The effects of nest, insulation of hair, huddling and exercise upon metabolism are investigated. Finally, Pearson turned to the bioenergetics of the mice and using data from several sources, calculated the oxygen consumption for an average mouse during an average June day and an average December day in California. He calculated energy estimates for the mice, assuming both diurnal and nocturnal activity patterns. These values equalled 1 370 cc and 1 782 cc of oxygen respectively, averaging 1 576 cc of oxygen per day and were equal t o 7.6 kcal/mouse/day for the nocturnal pattern. Using population data from another investigator, Pearson estimated that the mouse population dissipated on an average 91 kcal/day/acre which is about one-half to one yoof the daily energy stored by the plants on that acre. If Pearson's average daily estimate were used to calculate an annual respiration sum, it would equal 8.741 kcal/m2/ann. The final question in Pearson's paper concerned the cost of nocturnal activity of the mouse Reithrodontmys megalotis. Pearson estimated that nocturnal activity costs 420 g callday or the energy contained in three and one-half grains of wheat. This, then, is the price a mouse must pay to keep away from hawks and other diurnal predators. Comparison of these papers as a group with respect to their productivity significance is a difficult task, for the papers do not approach the problem of metabolism in the same manner. The data were inconclusive, in most cases, due to the lack of information about popuiation size and structure, lack of data on the temperature of the environment, and lack of information on the natural diet. We can compare respiration ratios (Table I),but this information will lead only to statements about the metabolic intensity of each species. Even the estimates of the annual population respiration totals by Pearson were unsatisfactory, for although we have estimates of the maintenance requirements of the mouse, we have no estimates of the calories produced in the form of new tissue. The value of the papers just discussed lies rather in the potential value of the data for field ecologists rather than in their direct contribution to the energetics field. TABLEI Comparison of Respiration Rates of Several Wild Animals Oxygen Consumed g cal/g animal/day

Temperature of Exp.

Common Name of Animal

Author

160.94 960 to 731 1 6 4 0 t o 490

Dec. t o June

29" C

Spider Mome sp8mOw

Itti 1964 Pearson 1960 West 1960

-30" to $30" C

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V. STUDIESCONCERNED PRIMARILY WITH MAINTENANCE IN T H E ENVIRONMENT METABOLISMOF POPULATIONS

I describe the studies discussed under this heading as the “Bornebusch school”, although most have gone one step further than Bornebusch in that they calculated the calories burned by the population rather than just the oxygen consumed by it. This approach can be employed at one of three different levels of organization: ( I ) the species population, (2) the higher taxon (e.g. order and class), and (3) the community. The work of Pearson (1960) could be considered under the Bornebusch approach as well as under the physiological approach, for the final portion of his paper deals with maintenance meta,bolismof the field population. Others dealing with maintenance metabolism of species populations in the field are McNab (1963), Nielsen (1!#61),O’Connor (1963), and Phillipson (1962). Berthet (1963) attacked the problem at the taxon level while Bornebusch (1930) and Macfadyeri (1963a, b) dealt with the community. McNab’s (1963) paper dealt witth three species of the field mouse Peromyscus. Star\ing with the physical and physiological elements which influence the metabolism of a mouse, McNab d.erived a series of formulae which eventually described the metabolic requirements of the mouse for a 24-h period. Using these formulae and information about environmental temperatures, size of animals, and numbers of individuals present in a tract of chaparral near Berkeley, California, and assuming 60% assimilation, McNab came to the following conclusions about the mouse populations. (1) Homiotherms have little energy available for work other than homeostasis. (2) The amount, of energy for activity has an Averse relationship with body weight. (3) Mouse populations consume only 2-5% of the primary productivity of the chaparral. P . manicuhtas was estimated to consume 14 kcal/day in June. Of the 14 kcals, it assimilated 8.37 kcallday. The total mous,e population of the three species of Peromyscus on the 26 acres of chaparral (32 P . maniculatus, 22 P . truei, and 13 P . californicus)during a typical June day consumed 24 kcal/acre. During a typical February day they dissipated 59 kcal/ acre in respiration and consumed 100 kcal/acre/day in food. Using another set of data on grassland, McNab estimated the “mice” (Reithrodontomys, Peromyscus, and Microtus) required 203 kcal/acre/day in summer and, thus, consumed 338 kcal/acre/day. McNab commented upon the estimates of Odum et al. (1962), noting that their 2.5 activity factor was arbitrary and too high, and recalculated the energy flow of the “old field” mice to 19.8 kcal/acre/day - a value which represented only 1.8 to 3.6% of the seeds produced on the old field. Nielsen (2961) also deals with the respiratory metabolism of field

88

MANFRED D . ENOELMANN

populations and adheres to the Bornebusch pattern in that oxygen consumption was estimated, but, the values were not converted to caloric equivalents. Nielsen obtained data on respiration rate of enchytraeid worms via Cartesian diver in the laboratory. Using field information, he calculated respiratory+values for field populations of both enchytraeids and nematodes. He took into consideration (1) environmental temperature, (2)activity, (3)oxygen tension, (4)drought or moisture content of the soil, and (5) mean body weight, in making the field estimate (see Table 11). If we make the assumption that the RQ of the animals is 0.85 (an average RQ for a mixed diet), then each litre of oxygen will yield 4.8 kcal of heat. TABLEI1 The Numbers of Individuals and Calories Respired by the Enchytraeid and Nematode Worms in a Permanent Pasture in Denmark. Data from Nielsen, 1961 Respiration Total Litres of Oa/ma/yr

Calories Released Yearly via Respiration kcal/ma/yrt

Taxon

Station

No. of Individuals x 10a/ma

Enchytraeidae

1 4 18

44 30 74

7 10 32

33.6 48-0 153.6

Nematoda

1 4 18

i x 104 5 x 103 1 x 104

43-63 3 1-46 71

2064-302-4 148+3-220.8 340-8

t Calculated by the present author using

4.8 kca1:L conversion factor.

Using the respiration figures and making some assumptions about the nature of assimilated food of the nematodes, Nielsen estimated that these animals required 800 kg of bacteria (live weight) and 320 kg of plant root cells (live weight) to satisfy the respiratory requirements indicated by his calculations. The diet of enchytraeids was assumed to be bacteria and the amount requireg to maintain the enchytraeids was estimated at 300-400 kg (live weight). Nielsen pointed out succinctly that knowledge of numbers of individuals alone is not sufficient to allow judgement of population. Data on the enchytraeids indicated that the site with the smallest numbers of individuals per meter square did not have the lowest respiratory metabolism. Presumably, then, the animals at “station 4” had a greater impact upon the environment than did those at “station 1”. However, the consumption of energy for body

89

ENERGETICS A N D ANIMAL PRODUCTIVITY

maintenance .is not the sole influence an animal can have upon its environment. O’Connor (1963) studied three species of enchytraeid worms from Epglish coniferous soils, obtaining information on (1) mean monthly population density in the field, (2) the numbers of individuals in each size category, (3) monthly age structure of the population as well as weights of the size categories, and (4) mean monthly field temperatures. From these data, he estimated that 14.33 x lo4 worms/m2 will weigh 10.794 g (dry weight), and respire 149.5 kcal. O’Connor also pointed out that the number of individuals alone can be unreliable as an indication of the importance of a species. I n Table III[ we see the relative rank each species holds with respect to a particulsx characteristic; first rank representing the largest value and the third rank representing the smallest value. Cognettia is the third in numbers present in the field when compared to the others, but first in the annual dissipation of calories. O’Connor compared his data obtained from the Douglas fir forest with the data Neilsen obtained from pasture soil. The figures from “Station 18” of Neilsen’s study yielded about the same values as O’Connor’s, both populations releasing about 150 kcal/m2/year. The physical factors of the two sites (Wales versus Denmark), were similar. TABLEIrI The Relative Rank held by Three Species of Ehchytraeidae when c m pared with one another. Original Data fiom O’Connor, 1963

Species ~~~

~

Numbers/m*

Biomass

Individual Total Calories Respira- Population Dissition pates Annually

~~

Hemihenleu cambrensis Achaeta ebeni Cognettia cognettii

~

First Second Third

First Third Second

Second Third First

~~

~~~

Second Third First

Phillipson (1962) dealt with the populations of Mitopus morio and Oligolophus tridens (Phalangiidae). Using a continuously recording, constant pressure respirometer which automa ticnlly replaced the oxygen used, Phillipson obtained respiration values for all stages of the two species of harvestmen which showed that the day-night respiration rates of the animals differed as well as did daily respiration totals. Using a series of independent observations on food consumption and respiration requirements, he concluded that the animals were not utilizing the components of their diet (i.e. fat, proteins, and carbohydrates) in the same proportions as they occur in the food. Uniform absorption is

90

MANFRED D . ENQELMANN

widely assumed in energetic studies, but .Phillipsoncontended that there is differential absorption especially by the immaturc stages of the animals. Employing field data and biomass estimates from other studies, Phillipson estimated that the phalangids free from 1-34to 1-47 kcal/ma of ground layer in an English deciduous woods in a year. The daily respiration rates of the phalangids agreed closely with those of the lycosid spider (Table IV). However, though the harvestmen showed a decreasing respiration per unit size with increasing weight (a common relationship in animals), data on lycosids did not follow that pattern. The respiration rate of the lycosid was measured a t 29” C, while those of the harvestmen were measured at 16” C. If we assume a &Io of two, then the lycosids respired about 56 cal/g/day (dry weight). This is the expected value for an animal of that size (note Table 4 gives live weights for size comparison rather than dry weights). Phillipson’s paper is important because of the conclusions drawn about differential assimilation of food and the information gained on energy utilization by arthropod predators. TABLEIV Comparison of Respiration Rates of Xeveral Predatory Arthropods. (Data from Phillipson, 1962 and ItB, 1964.) Specie8

Cal Respired/ g dry wt/day

Live Wt Individuals (mg)

Mitopus morio Oligolophue tridena Lycosa pseudoannulata

85-95 120-130 150.9

3.7-56.1 3-1-17‘3 1-150

The study by Berthet (1963) also concerned with soil arthropods, was centered on herbivores or generalized feeders. He dealt with all the species of a particular taxon (the Oribatei) found in the soil layers of the Meerdael Forest, Belgium. The animals were removed from the forest soil to the laboratory, where their respiratory rate was measured in a Cartesian diver respirometer. The respiratory rates were measured at 1 5 O , lo”, 5”, and 0” C, respectively, during successive two-hour intervals. The respiration rate of the 16 oribatid species was related to temb X , where Y is the log to perature according to the equation Y = a the base 10 of the oxygen consumed x ml; X is the temperature; and “a” and “b” are constants, “b” being one-tenth the antilog of the &Io value. Values of the &Io ranged from 2.6 to 5.6 and averaged 3-9 for the 16 species tested at these temperatures. The relationship between daily oxygen consumption, weight of the individuals, and temperature was described by the formula Y = 18.059 0.7W - 0.4872, where Y

+

+

ENERGETICS A N D ANIMAL PRODUCTIVITY

91

equals the log 10 of the oxygen consumed x ml/individual/day, W equals log 10 rate of the individuals in pg, 2 equals 1 x lo4 divided by the temperature in degrees A. Using these formulae, data on numbers and biomass of the oribatid mites, and data on the annual temperature fluctuation of the forest soil, Berthet estim,%tedthat the oribatids respired a total of 4.488 L (oxygen)/m2/annum.(See Table v.) TABLEV The Numbers, Biomass, Respiration and Calorie Requirements of Oribatid Mites Found in Belgium Forest Soil. (Original Data from Berthet, 1963.)

Taxon Oribatei (46 SPP)

No. of Individuals x 103/me

Biomass

&m/me

Oxygen Consumption L/ma/yr

Calories Released kcal/m*/yrf

133.6

5.377

4.488

21.54

t Assuming 4.8 kcal/L Oxygen coilsumed.

Berthet, like Nielsen, did not calculate the caloric equivalents for the respiration figures. If we convert by the factor of 4.8 kcal/L oxygen, we find that 21.54 kcal were released by the population in one m2 during a year. The two authors who studied the problem of maintenance metabolism on the community level of organization were Bornebusch (1930) and Macfadyen (1963a, b). Bornebusch confined his calculations to the areas he sampled, while Macfadyen, in an effort to point out some norm or pattern of energy utilization, analyzed the data of other workers as well as his own. The analysis of the five Danish forest soils is summarized in Table VI. It has been claimed by various authors (Birch and Clark, 1953; Macfadyen, 1963b) that the density figures given by Bornebusch were low and, thus, that all of his calculations were deficient. This contention was supported by a comparison with the figures of Van der Drift (1951) on beech forest soils in the Netherlands. Even though comparison of Bornebusch’s figures with those of other authors was thus difficult, the significance of his conclusions is not altered. The efficiency of his extraction technique was probably the same for each of his sites and, therefore, the same magnitude of error was present in all of his calculations, thus, the data had comparative values. Bomebusch’s observations include the following: (1) The slower the decompositior, of the humus, the greater were the numbers of arthropods present and the rower was their total weight. (2) The weight of the forest soil fauna waa a more reliable index

M A N F R E D D . ENOELMANN

92

to their activity than was the number of individuals. (See Table VI.) The best index, however, was the oxygen consumption rate of the fauna. (3) Large earthworms were most important in rich mull soils, mixing and aerating the top layers. (4) In raw humus where earthworms are sparse, arthropods initiated the breakdown of the material to be decomposed. Bornebusch concluded with a statement which underlines the importance of the soil fauna to the soil building process, and he called the attention of the forester to this fauna and directed him to take heed of soil organisms, a directive which has, on the whole been disregarded or has passed unnoticed. TABLEVI Density, Biomass, and Respiration of the Fauna Found in Five Forest Soils. (Datafrom.Bornebusch, 1930.) Mean Density Soil Type

Oak Mull Beech Mull f 5 Beech #4, raw humus Spruce Mull Spruce, raw humus

#/m2 Rank 2978 4424 14163 10790 11 938

5

4 1 3 2

Mean Biomass g/m2 Rank 76-81 37-76 24-02 10.72 9.84

1 2 3 4 5

Respiration 13” C

-

mi3

Ol/hr/maRank 17-74 11-51 12.08 6.74 7.09

1 3 2

6

4

Macfadyen employed the maintenance metabolism of populations as a comparative tool, but his scope was much broader and his figures admittedly more approximate than those of other authors. The purpose of a study such as Macfadyen’s is creation of a framework, admittedly imperfect, in an effort either to reveal some pattern or principle which will be useful as a predictive tool, or to give a basis of organization which, as new data accumulate, may be modified into another more precise framework. I n his book, “Animal Ecology’’ (1963a, page 234), Macfadyen set forth the framework of a hypothetical grassland soil community, indicating the approximate relationship each taxonomic component should have to this community. I n the grassland soil, bacteria were more numerous and harvestmen were the least numerous. Plants (bacteria and fungi) accounted for 1 400 g/m2 of the soil biota, while animals accounted for only 225.9 g. In terms of metabolic activity, nematodes were the most important animal group, followed by earthworms, enchytraeids, and collembola. In Doeksen and Van der Drift (1963), Macfadyen sets forth a more

ENERGETICS A N D ANIMAL PllODUCTIVITY

93

comprehensive framework, comparing different communities (pages 8,

9) as well as components within the communities. He used data from

several authors in the compilation of this table. The table contained data from both forest (coniferous and deciduous) and grassland communities. In Table VII are listed the percentage of animals comprising each major trophic group as given by Macfadyen and the rank each group held with equivalent trophic groups of the other communities. I have used these data to compute a rough carnivore-herbivore ratio and several generalizations emerge: (1) There is a rather constant percentage (20 to 33%) of herbivores -this category includes anima@which reside in the soil and feed upon algae and roots of’green plants but not upon bacteria and fungi. (2) There is an inverse relationship between the percentages of predators and large decomposerig (sig. at the 5% level using Spearman rank correlation (Siegel, 1956,page 202) ). (3)It would appear that there is an inverse relationship between the percentages of large decomposers and small decomposers; however, the rs equals 0.5, which is not significant. Most of the deviation comw from a single observation (Spruce, R. H. (6) ). If this item were removed, the relationship between large and small decomposers would attain statistical significance at the 5% level (r, = 0.69), but since we have no justification for eliminating the data on the Spruce, R. H. (6) communil;y, the relationship remains doubtful. It is also important to note that in Madadyen’s data the predatorherbivore ratio was not constant and did not seem to correlate either directly or inversely with any other element of the community. Macfadyen (1963b) points out that, although the various taxonomic components vary considerably from community to community, the total picture of metabolism remains remark ably constant. Although in view of the adjustments and assumptions made, the figures thus derived must be considered as tentative. From information on bacterial respiration and field experiments with soil reupirshion, Macfadyen estimated that animal respiration represented from 10 to 20% of the total soil metabolism. He concluded that the soil fauna is important in its %atalytic” activity and control of the energy passing through the decomposition cycle. When the studies on maintenance met,abolism are reviewed as a group, at least three salient points emerge. First, annual maintenance metabolism is a better indication of the impmt of a population or group on an area than are numbers or biomass. However, it was pointed out by Phillipson, Macfadyen, and O’Connor that respiratory metabolism rates alone do not represent the full impact of the population. The eating habits, efficiency of digestion, and rate of reproduction can have D*

TABLEVII The C m p r k o n of % or Rank of Annual Calorie Dksiption and Predator-Herbivore Ratio of Different Trophic Groups Found in Nine Natural Communities on the British Isla and the i3uropeun Continent. (Datafrom Macfadyen, 1963b.) 1

community

2 Limestone Grassland Grass

Herbivore Rank Herbivore yo Large Decomposer Rank L. Decomposer yo Small Decomposer Rank S. Decomposer yo Predator Rank Predator yo €tank Total kcal/yr Ratio carnivoreFerbivore

7

3

Juncus Moor

4

Oak MUll

5

Beech RH

6

7

8

9

Beech MUll

Beech Mull

Spruce MUll

Spruce RH

(15)

(4)

(1)

(6)

5 28.36

1 32.91

8 22-29

25-65

3 31.77

4 30.85

9 20.36

6 27.25

2 32.08

4 27-36

1 55.54

8 1.21

2 33.49

5 8.42

3 31.24

6 3 a46

7 3.3

9 0.54

4 39.32 6 10.95

9 17.38 9 1.38

1 64.18 8 2-85

6 29-87 5.79

2 46.06 3 25.15

8 23.92 5 17-58

3 45.41 4 19.05

5 36-48 2 31-86

29.12 1 37.43

1

2

4

7

9

5

3

8

6

0.1232

0.0140

0.0293

7

0.0614

0-3360

0.2133

0.2353

0.4675

7

0.5981

ENERGETICS A N D A N I M A L PItODUCTIVITY

95

marked effect upon the community - effects which are not indicated in the Bornebusch type of analysis. Finally, it is of interest to note that the majority of the investigations were on soil animals or soil communities. This could be due either to tradition or to the fact that the soil provides many species and complex relationships readily accessible in small areas. The added fact that this system plays an important role in the economy of man probably also lends impetus to the pursuit of soil study.

VI. STUDIES WHICH EMPHASIZE THE TROPHIC SCHEME ANALYSISOF COMMU:YITIES This last group of studies gives us our best figures on animal productivity in natural communities. These studies are concerned not only with estimates of maintenance energies, but also with the incorporation of calories into new protoplasm. These growth calories can either fall prey to another trophic level, or increase the biomass of the population. The capacity of the population to produce these surplus calories determines the ultimate structure of the community as well as the usefulness of that community to man. With regard to this last point, we must bear in mind that the net productivit,y of a natural population is not equivalent to its yield useful to man. If man were to utilize the complete net production of a population, he would have to aasume the role of predator and decomposer for the entire population. Man begins to approach this relationship with his domestic animals, but the natural community presents a different situation. Investigators utilizing the trophic dynamic approach at the population level were: Golley and Gentry (1964), Odum and Smalley (1959), Odum et al. (1962), Petrides and Swank (1965), Smalley (1960), and Wiegert (1964). Only one author (Golley, 1960) has approached the subject of field energetics from the standpoint of energy flow through a food chain, while two investigators (Engelmann, 1961; Teal, 1962) have attempted some kind of analysis at the conimunity level. Three of the papers reported data on homiotherms (Golley, 1960; Odum et al., 1962; Petrides and Swank, 1965), while the remainder dealt with poikilotherms, particularly insects. Most of the investigators used field data to create complete energy budgets.

A. TROPHIC D Y N A M I C A N A L Y S I S O F THE SALT MARSH E C O T O N E Smalley (1960) working on the insects of a salt marsh has provided basic information utilized by other authow. His data for the grasshopper, OrchelimumJidicinium, were used in his own 1960 paper, the paper by Odum and Smalley (1959) and the paper by Teal (1962). His basic sampling tool was a sweep net, standardized against captures in a square meter cage placed randomly on the sampling area. With these

96

MANFRED D . ENOELMANN

tools, Smalley could collect data on numbers of individuals, and size categories of individuals. Weights were assigned to the size categories by weighing representative individuals from each size category. A simple constant pressure respirometer was used to measure respiration rates. Observations on caged individuals were used in making estimates of egestion rates. Calorific values for various biological materials were determined in a Parr bomb calorimeter. Ingestion was figured as the sum of respiration, “production” and defecation. “Production” in this case then refered to net production which included estimates of new nymphs produced and numbers of individuals lost to the population through death. Estimates were lacking on numbers of eggs produced by the population. Smalley calculated that a biomass equivalent to 10.8 kcal/m2respired 18.6 kcal of oxygen annually. Gross production by the population equaled 29.4 kcal/m2/year. Assimilation efficiency averaged 2’7.4% and ranged from 20.8 to 35.4%. Smalley estimated that the grasshoppers ingested 107 kcal of the 5 200 kcal produced annually on each square meter of the marsh. The grasshoppers consumed only 2% of the net amount produced by the flora available to them. It is of interest that the net productivity of this population was estimated entirely from the data on calories lost to the population via death. This population, as in the case of many insects, overwintered in the egg stage and, thus, the adults died off at the end of the season, their bodies going directly to the decomposer system. The net production estimate of the grasshopper, however, was still short, for Smalley did not have data on the number of deaths for every stage in the life cycle. The paper by Odum and Smalley (1959) summarized energetics data for grasshopper and snail populations living in the salt marsh on Sapelo Island off the coast of Georgia. The data for this study were collected by Smalley. The authors calculated that the grasshopper, Orchlimum, ingested 48 kcal/m2/year of Spartinu grass. Thirty-six per cent of the food ingested was assimilated. The gross production of the grasshopper was 28 kcal/m2/year. The snail (Littorina) feeding upon the decaying grass stems and algae, etc., was 45% efficient in assimilating its food and yielded a gross productivity of 290 kcal/m2/year.No ingestion figure was given for the snail. Since the organism was 45% efficient in assimilating food, it must have egested 55% of the material, or 354 kcal/m2/year. Thus, the Littorina population ingested annually a total of 644 kcal/m2. Littorim used only 14% of its assimilated energy for production of new individuals, while the grasshopper utilized 37% of its energy in reproduction. These figures can give us a minimal estimate of net productivity in the two species, but losses due to death were not stated in this paper. Net production in the grasshopper was 10.4 kcal/m2/year, and in the snail, 40.6 kcal/m2/year. The major point Odum and Smalley

ENERGETICS A N D ANIMAL PRODUCTIVITY

97

made was that even though numbers of individuals and biomass varied in the salt marsh “community” the energy jlow through the population remained relatively constant. It is also worth noting the difference between the figures used by Odum and Smalley (1959) and those used by Smalley (1960). First, there was a 1.4 kcal/m2/year difference in the figures on gross productivity in the two papers. Secondly, Odum arid Smalley used an assimilation figure of 36%, resulting in an estimate of 7 7 - 7 7 kcal/m2 ingested annually, while Smalley set the assimilation rate at 27.4 and the ingestion rate at 107 kcal/m2/year. I n the first CiiSe, the maximum assimilation rate was used. I n the second assimilation was an average rate. Thus, the first paper compared the average efficiency of the animal, while the second compared the maximum efficiency. The salt marsh is not typically a terrestrial community but is rather an ecotone. The fact that typically marine populations as well as terrestrial populations can be found at times in the same square meter plot tends to complicate analysis of this type of habitat. Allowances must also be made in the analysis for immigration and emigration of materials and populations, particularly if the inflow and outflow of energy is not equal. Teal (1962) attempted an analysis of the energetics of the salt marsh community. He employed data from several sources in making his estimates. A number of assumptions were used to give estimates where data were lacking. He stated production equalled 0.25 to 0.3 respiration; energy degradation was equal under anaerobic and aerobic conditions; the racoons had an assimilation equal to that of the Clapper rails; spiders and carnivorous birds took the same proportion of the prey as did the mud crabs, rails, and racoons which preyed upon detritus algae feeders. Some of these assumptions were supported by logic or circumstantial evidence; others, such as the last two listed, were not. The energy flow through the salt marsh system was summarized by Teal as follows: Input as light 6 x 106 E:cal/m2/year, loss in photosynthesis 563 620 kcal/m2/year, gross production of the producers 36 380 kcal/m2/year,respiration by the producers 28 175 kcal/m2/year, net production of the producers 8 205 kcal/m2/year, bacterial respiration 3 890 kcal/m2/year, primary consumer respiration 596 kcal/m2/ year, secondary consumer respiration 48 koal/m2/year. The total energy released by the consumers equaled 4 534 kcal/m2/ year or 55% of the net production of the pi-oducers, leaving 3 671 kcal/ m2/year to be exported by tides and other losses. This “community” contained a great number of marine and fresh wqter species. If we confined attention to terrestrial animals then his data on the grasshopper, Orchelimum, the plant bug, Prokelisia, and the nematodes should

98

MANFRED D . ENGELMANN

be considered. The data on the grasshopper were those of Smalley (1960). The gross productivity of 29.4 kcal/m2 was used by Teal. A gross productivity figure of 275 kcal/m2/yearwas reported for an average standing crop of 70 kcal/m2for Prokelisia, the plant bug. Teal calculated that the nematodes respired 64 kcal/m2/year, and he assumed production in the marsh to be 21 kcal/m2/year or 25% of the respiration rate. Teal did not calculate ecological efficiencies for the various trophic levels, although he did report efficiencies for the utilization of the Spartina standing crop by the insects 4.6%). If we use the formula by Engelmann (1961) which is correctlyreported by Slobodkin (1962, p. 98), an ecological efficiency of 6.8 can be obtained for the herbivore-carnivore trophic levels. Teal’s paper is important because it deals with an ecotone. The work suffers because it relied too heavily upon assumptions and was not sufficiently comprehensive.

B. TROPHIC DYNAMIC

ANALYSIS OF (‘OLD FIELD” COMMUNITIES

The second group of papers to be discussed center on the “old field” habitat. Studies have been made under the very different climatic conditions of southern Michigan and Georgia. Golley and Gentry (1964) studied the bioenergetics of the southern harvester ant, Pogonomyrmex badius in South Carolina. They located ant hills in the “old field” study area, labeled individuals radioactively with P32 to estimate the numbers of animals in each hill by mark -release - and recapture methods. Ant hills were excavated to ascertain the numbers of all stages present, and respiration measurements were made on the various stages. Counts indicated that there were 0.0027 hillslm2 and that each hill contained from 4 000 to 6 000 individuals. From data on numbers present and respiration studies, it was calculated that 14.2-47.7 kcal/m2/yearwere lost by the population in respiration. Using the numbers of young found in the hills, plus supplementary data, Golley and Gentry estimated that the ants produced 0.09 kcal/ma in new individuals each year. The authors did not make an estimate of calories lost to the population through death. The total estimates for P . badius were: net productivity 0.09 kcal/m2/year;gross productivity 14.29 to 47.79 kcal/mZ/year. Golley and Gentry reported that the ant was primarily a gramnivore and that the field produced 22 kcal/m2/ year in seeds. The ant, then, consumed the equivalent of 64 to 213% of the seed crop each year. Since the field also supported other gramnivores (mice and sparrows), the authors concluded that other foods must have been used by the ants in addition to seed. The authors noted that the ant consumed more energy than either the sparrow (4kcal/ma/150 days) or the mouse (7-17 kcal/mQ/year)populations associated with it in the “old fields”.

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Because of the division of labor within the colony, the marking technique was not successful for estimating the total number of individuals in the hill. Data for net production were also difficult to evaluate, because the authors took the top birth production figures rather than averages; yet they had no estimate for deaths of adults or young during their life span. Net production, in this case, requires estimates for both parameters because most of the individuals lived more than one year. The important point is, however, that maintenance metabolism required 99.6% of the total assimilated energy. No estimate of ingestion was attempted and, therefore, we have no information on the total number of calories consumed annually by the population. The data presented by Golley and Gentry indicated that, in the “old field”, the harvester ant was an important herbivore converting most of its assimilated energy into maintenance and very littlo energy into net production. Odum et al. (1962) worked in the abandoned fields (“old fields”) associated with the Savannah River Plant of the U.S.A. Atomic Energy Commission, Georgia. The authors concentrated on two grasshopper species (Melanoplus femur-rubrum, and M . biliteratus), the tree cricket (Oeconthusnigricornis), a mouse (Peromyscw polionotus), and a sparrow (Passerculus sandwichensis). The mice were live-trapped, the sparrows captured with mist nets, and the Orthoptera were captured with sweep nets and in cages after the procedures originated by Smalley. Caloric equivalents were obtained by Parr bomb cdorimetery . Metabolism was measured both in terms of caged animals sad by respirometry. The field energy was assumed to be twice maintenance energy (an assumption questioned by McNab, 1963). The authors estimated that gross production of the sparrow was 3.6 kcal/m2/year. However, since Southern Georgia is the wintering range for these birds, there was virtually no net production (0.04 kcal/m2/year).Gross production for the mouse was 6.7 kcal/m2/year, with average net production at only 0.12 kcal/m2/year. Gross production for the Orthoptera was 25-6 kcal/ mZ/year and net production was 4 - 0 kcal/m’a/year.Once the authors had determined the total amount of each food consumed, they could find out how much of the standing crop of peen plants the herbivores utilized. The gramnivorous birds and mice used from 10% to 50% of the seeds consumed, whereas the herbivorous Orthoptera utilized only 2% to 7% of the plant foliage. Golley and Gentry estimated that the ant, P. badius, consumed the equivalent of 64% to 213% of the seed crop on these same fields. Thus it would appear that from 74% to 263% of the seed crop produced on each m2 was used by these three species during the year. This can only imply that ei1;her the seed crop was underestimated or the animal utilization overestimated, or both. Analysis of droppings of vesper and field oparrows in Michigan showed

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MANFRED D . ENGELMANN

that during the spring and early summer before a seed crop was produced, these animals were carnivores. Even during the fall, the birds continued to include insects in their diet along with seeds (personal communication, F. C. Evans). McNab (1963) believed that the food utilization data on the mouse (Odum et al., 1962) were too high. Golley and Gentry (1964) recognized the fact that P. badius must have been using foods other than seeds. Thus, these calculations on seed utilization demonstrate that studies on energetics require careful observations on feeding habits, as well as careful measurements of metabolic and reproductive processes. It is of interest to coppare data from Wiegert’s very careful study (1964) on the spittle bug Philaenus spumarius of “old fields” with the data previously discussed from the salt marsh and the southern “old field”. Wiegert also used the aforementioned sweep net and cage method to measure the spittle bug population. He reported the confidence limits for his samples. Respiration rates were measured on all stages of the animals; the caloric values of these rates were determined; also feeding habits and migratory patterns were studied. A great deal of Wiegert’s study was devoted to the feeding efficiency of the various stages of the spittle bug. He found that the immature individuals were 30% to 58% efficient (average 36%) in assimilating nutriment from the plant sap, while the adults were 71%-80y0 efficient (average 76%) on the same material. However, when it came to listing the productivity for the “old field”, Wiegert ran into difficulty. A population must be able t o produce a minimum number of new individuals, if it is to maintain itself from year to year. The Philaenus population could not do this on the “old field”. Wiegert calculated the intrinsic rate of natural increase of this population on the “old field” to be -5.8 to -6.0. The continued presence of the spittle bug population on the “old field” was supported by immigration of new individuals from surrounding alfalfa fields. Thus, the net production of P. spumarius ranged from 0.048 to 0.096 kcal/m2/ year and the gross productivity ranged from 0.582 to 1.167 kcal/m2/ year. Immigration contributed from 0.516 to 1.138 additional kcal annually to each square meter of the “old field” in the form of immigrants which later failed to survive. I n contrast, a sma€l alfalfa field produced (net) 15.125 kcal/m2of animals. Gross productivity amounted to 38.565 kcal/m2/year. When the alfalfa in this field was cut, and the quantity of primary producers drastically reduced, thereafter the spittle bug adults moved out of these fields into other areas which could support them. Thus, although the “old field” was able to provide sustenance for a certain number of adults, there was not energy sufficient to maintain the population on a permanent basis. Ninety to ninety-five per cent of the adult animals dying on the “old field” were immigrants. Wiegert

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was able to calculate the ecological efficiency (gross efficiency of yield/ ingestion) by assuming “instantaneous predahion”. The figures he obtained ranged from 0.8~0-17-4%. Wiegert’s paper is significant, not only because it is an example of careful analysis, but because it dealt with a species in the two extremes of its total habitat range. The gross and net productivities in the alfalfa field exceeded most other productivities for arthropods reported in the literature (save that of P.badius,Golley and Gentry, 1964). Yet, in the “old field” the spittle bugs could not survive. Wiegert’s study pointed again to the inadequacy of the Lindeman model in a situation of imbalance. Another study made on this “old field” of the E. S. George Reserve was concerned with the soil arthropods (Engelmann, 1961). The study used the author’s results and data collected previously by Hairston and Byers (1954). The mite population was estimated from monthly soil samples processed in Tullgren funnels. Indivilduals of each species were weighed on a quartz helix balance, and the numbers and weight data were used to estimate biomass. Data on respiration rates measured with a, simple constant pressure respirometer were used in conjunction with biomass information to calculate total maintenance metabolism. Radiotracer experiments gave figures on ingestion. Soil organisms were cultured in the laboratory and studied to gain information on life span, ingestion and egestion, and birth rate. Infor mation from cultures and field data provided a basis for making assumptions on survival. From these data a complete energy balance sheet was constructed for the Oribatei. The study approached the problem of energetics at two levels: fist at a lower level, or taxon, concentrating upon the Oribatei; on a second level all of the soil arthropods were included. The analysis of data on oribatids resulted in estimates as follows: a standing crop of 0.27 kcal on an average square meter of “old field”; ingested 10.248 kcal; assimilated 2.058 kcal; respired 1.965 kcal, and lost through mortality 0.43 kcal each year. These data and preserved materials of Hairston and Byers (1954) were used to estimate the ecological efficiency of the carnivores with respect to the herbivores. Knowledge of respiration estimates and assimilation efficiency for both herbivores and carnivores made possible calculations of efficiency values. The most reasonable ecological efficiencies ranged from 8% to 30% with 16.90/,, the most probable value. The production on this field was very low when compared with the area sampled by Berthet, for example. Nematodes andnrotiferswere scarce in the poor, well-drained field soil. The combined respiration of these organisms yielded about 0.36 kcal/m2/year.

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MANFRED D . ENGELMANN

This study had two positive aspects from the standpoint of energetics. First, the work represented an attempt to analyze total flow of energy through the soil. Second, all of the data in the oribatid balance sheet were a product of separate observations; none of the figures were derived from equations. The study had several inadequacies which could affect the significance of the results. Taxonomic identification was the greatest deficiency. Secondly, there was a problem of questionable efficiency of the Tullgren extractor, particularly when used on dry summer samples. Finally, temperatures of microhabitats were not known. I am now acquiring additional new information which may increase the figures for net and gross productivity of the Oribatei. Let us move to another study of an “old field” habitat. The subject of a paper by Golley (1960) was the food chain involving the bluegrassvole-least weasel. Golley obtained data on abundance, age structure, respiration, assimilation, and egestion rates of the vole Microtus. The least weasel (Muste&) data were largely based upon assumptions, the majority of them reasonable! Good information was obtained on the food of the mouse which was Kentucky bluegrass ( P o a pratensis). Golley calculated that a standing crop of 0.021-0.553 kcal of mouse on 1 m2 would release 17 kcal in respiration and produce 0.517 kcal in young each year. As was the case in Wiegert’s study, it was difficult to balance the ledger because of caloric transport. The mice were able to maintain themselves in the area, although Golley found evidence of both immigration and emigration. An estimated 1-35 kcal/m2/year of mice moved into the area, a quantity almost twice that accounted for by net production. Thus, on the portion of the “old field” studied, the number of deaths was higher than the number of individuals produced on that area. The gross productivity of the Microtus population was 17.517 kcal/m2/year. Mustejh, the least weasel, had a net productivity of 0.013 kcal/m2/year and a gross. productivity of 5.564 kcal/m2/year. Nicrotus used 1.6% of the total net production of the Kentucky bluegrass, while Muste& consumed 31% of the net production of the Microtus population. Though not calculated by Golley, ecological efficiencies for the weasel and mouse would be 2.3%. This percentage represented only a portion of predation, as the weasel was not the only predator on the mouse population. Most of Golley’s figures seemed to be reasonable. An analysis of the food chain is a very fruitful approach to the energetics problem. He did, however, get an unexpectedly high estimate for the assimilation rate of Microtus (90%). Most other herbivores assimilate from 65% to 76% of their food (Brody [1945, p. 801,McNab [1963], Pearson [1960]). If the rate cited by Golley truly reflects the ability of the animal to absorb food, rather than an experimental error, then, unlike most other animals

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Microtus had a great advantage in being able t o utilize most of the food it consumed.

c. TROPHIC STUDIES IN A SAVANNAH COMMUNITY Last to be reviewed in this paper is an energetics study done on the African Savannah and concerned with the largest land animal, the African Elephant. Petrides and Swank (1965) studied a population of Loxdonta africana in 28-5 square miles (7381.5 hectares) of Queen Elizabeth National Park, Uganda. They count,ed the individuals in the total population and classified them according to sex and age. Their age distribution was as follows: 14.6% calves, 24.3% immatures, 14.4% sub-adults, and 46.7% adults. Growth rate data came from other sources and were chiefly based on measurements of captive elephants in zoos. From these data a growth curvg was plotted which fitted the size of the wild individuals. The authors then created a life table, using growth rates and population structure. They estimated that 70% of the calves survived the 1st year. Their survival rate then jumped to 80% in the 2nd year and was 95% by puberty in the 14th year. After the beginning adult years when the survival rate was 98%, it began to drop again. An average elephant fixed as new protoplasm 165.6 x los kcal/year, but since there were only 5-31 elephants per square mile, net production amounted to only 0.34 kcal/m2/yem. The physiological data of Benedict (1936) on elephants were used to calculate maintenance metabolism and rate of ingestion. Petrides and Swank established that for the elephant an tbverage standing crop of 7 . 1 kcal on 1 m2 respired 23 kcal and consumed 71.6 kcal of food annually. Gross productivity was 23.34 kcal/m2/yesr, while net productivity was only 0.34 kcal/m2/year.The elephant used 9.6% of the total browse available. Petrides and Swank compared the productivity of the African elephant to that of the mouse, white-tailed deer, and cattle. They found that the elephant maintained a tremendous biomass 0x1 a relatively coarse diet. Assimilation was poor (44%) when compared with that of other mammals, and growth rate was slow; however, net production of the African elephant was 40% that of good beef cat,tle. The authors also pointed out that the elephant changed conditions in the Savannah by such activities as digging water holes and pushing down trees, making areas habitable for other game. The authors went on to suggest how herds could be managed so as to give maximum benefit to man and other animals. The paper by Petrides and Swank is significant in that it demonstrates how physiological data can be applied to field data and good energetics estimates thereby obtained. The paper also demonstrated

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MANFRED D . ENGELMANN

how energetics data could be useful in practical application. Some of the figures given by Petrides and Swank may be questioned because only a few observations were represented, but allowing for the paucity of observations, this remains a stimulating and valuable study. There are not enough trophic efficiency studies as yet to give a clear picture of either the structure of communities or the validity of the Lindeman model. Yet, the data thus far gathered suggest several interesting trends or hypotheses at the population level which could guide future research. The values determined for several population parameters in various energetics studies have been listed in Table VIII. If net production and maintenance metabolism are analyzed by using Spearman rank correlation, there is indicated a relationship, significant at the 5% level. Yet, when all the data are plotted on a graph (Fig. 2), only a slight indication of a regression is shown. If, however, the points are separated with respect to the degree of temperature regulation, data for poikilotherms reflect a rather clear-cut trend. One point on the graph, representing information on the harvest ant, P . badius, is far removed from those of other poikilotherms, the rest falling along a line described 0.86 Log p . (“R”represents by the following formula: Log R = 62 the number of k calories respired by the population found per m2/year and “p” represents the net productivity in kcal/m2/year.) Slobodkin (1960) pointed out that in Duphniu after the maintenance requirement was met, the remaining calories went into reproduction, a fact borne out by this graph. If the data on P. badius are included in the regression, 0.62 becomes one and the slope changes to 0.55. There is, however, at least one good biological reason for considering the ant to be an exception to the usual pattern of energetics found in most animals; namely, the workers, and soldiers are sterile. Although there were 4 000 to 6 000 individuals in a colony, only two were capable of reproducing. One would expect that, when compared with respiratory metabolism, productivity in ants would be low. From the point of view of energetics, the ant colony is inefficient, burning a disproportionate amount of energy to produce so little; yet, ants seem to be very successful in the world today. It is of interest to note that the point on Fig. 2 representing data for the ant falls among the group of points representing the data for homiotherms. The homiotherms, too, apparently burn a disproportionate amount of energy for what is produced in the way of new protoplasm, a t least by standards of poikilotherm production. Yet, the homiotherms are also very successful today. The five points representing the birds and mammals fall along a regression line described by the following formula: Log R = 2-59 1-75 Log p ; “R” and “p” having been previously defined. The regressions for homiotherms and poikilotherms converge, but

+

+

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105

I -2

I

0

I

2

LOG NET PRODUCTIVITY

FIU.2. The relationship between maintenance metabolism and net productivity. The points represented by “x’s” are poikilotherms and the “o’s” are homiotherms. The solid line represents the poikilotherm regression while the do tted line represents homiotherm regreosion. The numbers associated with each point correspond to the identification numbers in the left-hand column in Table VIII.

it is difficult to say that the closely grouped points for the homiotherms represent the true slope of the line. Points Nos. 10 and 14 have a greater effect on the regression than do the other three. It is conceivable that the slope of the line is actually nearer that of the poikilotherm data. More information is needed on the energetics of homiotherms. If we generalize from these data, we come to a rather startling conclusion. First, the biological world is divided into two separate realms with reference to energetics :the thermoregulators and the nonregulators. Second, the nonregulators are more efficient producers than are the thermoregulators. If this were the whole story, mammals and birds could not compete with the rest of the animal kingdom, and beef farmers would be raising grasshoppers for meat. The key to this apparently paradoxical situation is the assimilation efficiency of the organisms concerned. Poikilotherms are at most 30% efficient in digesting food whereas most hoaiiothekus are around 70% efficient. Thus, the poikilotherm has to consume more calories if it is to

TABLEVIII Productivity, Maintenance Metabolism, % Utilization, and Ecological Eficiency of Different Animals Found in Various Communities. (Data Compiled from Several Authors.)

Taxon

Prod in kcal/m*/yr Gross Net

Invertebrates 1. Littorina sp. 40.6 290 2. Nematodes 21.0 85 3. Orchelimurn Jidicinurn 10.8 29.4 4. Prokelisia sp. 275-0 -5. Orthoptera 4.0 . 25.6 (3 SPP.) 6 . Philaenus spumarius 0.048-0.096 0.582-1.167 7 . P . spumarius 15.125 38.565 8 . Pogonomyrmex badius 0.09 14.29-47.79 0.43 2.008 9. Oribatei Vertebrates 10. Passerculus 11. Microtus 12. Peromyscus 13. Loxodontu africana 14. Muatella id-e.

Maintenance yoUtilizaMetabolism tion of Net in Production Ecological kcal/m*/yr Food Efficiency 249.4 64.0

-

2 4.6

21.6

2-7

18.6

31.03 t 1.578

64-213 -

10-50 1a6 10-50

3.6 17.517 6.7

3.56 17.00 6-58

0.34 0.013

23-34 5-564

23.00 5.551

:Single species.

0 -8-1 7 '4

0-778t 23.44

0 *04 0.517 0.12

6 -8

9 -6 31.0

8-30

Habitat

Authority

Salt marsh Salt marsh

Odum and Smalley, 1959 Teal, 1962

Salt marsh Salt marsh

Smalley, 1960 Teal, 1962

Old Field

Odum et al.. 1962

Old Field Alfalfa field

Wiegert, 1964 Wiegert, 1964

Old Field Old Field

Golley and Gentry, 1964 Engelmann, 1961

Old Field Old Field Old Field

Odum et al., 1962 Golley, 1960 Odum et al., 1962

Savannah Old Field

Petrides and Swank, 1965 Golley, 1960

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gain sufficient nutrition fsr the maintenance and reproductive tasks. Does the efficiency of digestioii and assimilation compensate the organism for the cost of homiothermy? This question has no answer at the present time. However, when the five situations (two homiotherms, and three poikilotherms) are considered wherein total calories ingested are known and if they were plotted on a graph similar to Fig.& the new plot would suggest that the curves for poikilobherms and homiotherms approach one another, and may even merge broadly. Thus, it would appear that poikilothermy and homiothermy are two answers to the same problems of existence in the environment. It would be interesting to know where data for populations of heliotherms (such as lizards and snakes) and the “variable homiotherms” (such as the sloths, opossums, and the true hibernators) will fall on the graphs of maintenance metabolism -net production. The studies seem to suggest a second point concerning the productivity of various populations. Populations in the southern latitudes appear to be more productive than do those !n the northern latitudes. Such a difference seems reasonable, because warmer temperatures and longer growing seasons make possible greater productivity. Still a third additional hypothesis suggested by these data is that populations have greater productivity in simpler situations (such as pioneer communities). Thus, the salt marsh populations are more productive than are those of the southern “old field” which in turn are more productive than are those of the northern “old field”. I n a like manner, the populations studied in the northern alfalfa field far exceed the production of the same populations found on the northern “old field”. We must remember that here productivity of single populations within different communities is under discurision rather than productivity of a community. The trends suggested in these studies seem to support our present ideas about population size within communities (i.e. that pioneer communities are made up of a few large populations while climax communities are made up of numerous relatively small populations). Finally, the data on ecological efficiency and on efficiency of use indicate that each population utilizes only a small portion of the available calories (the one exception being the use of seeds on the southern “old field”). The most frequently reported figures, on food utilization were: 2% for herbivores and 30% for carnivores. When considering ecological efficiency of a trophic level (i.e. the soil arthropods) the maximum efficiency is only 30% and the remaining 70% then goes into other energy pathways. Thus, it is obvious that the energy fixed by the plants “cascades” into a number of energy “sumps” before i t is completely dissipated through respiration.

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VII. PROJECTION

I stated in the introduction that many ecologists feel their science has come of age. Odum (1964) in particular points to energetics as the new ecology. If energetics is indeed the new ecology, what guiding principles and predictive models have been developed to guide future inquiry and to aid the energetics ecologist to answer the crucial practical questions of the day! We must admit that, thus far, the Lindeman model has been the major guiding principle in energetics. We must also state that this model has been very little tested and practically unchanged since its inception over 20 years ago. If it is to be useful, a model for a community must apply to all situations. Since this paper is primarily concerned with terrestrial communities, let us consider the information contributed by the terrestrial ecologists in the light of the Lindeman model. First, only three terrestrial communities have been studied thus far and none has been analyzed completely. Second, none of these studies was able either to support or refute the Lindeman model, since populations, not trophic levels, were studied. ‘Third,the data in the studies were all tentative, since the magnitude of the errors involved in the computations cannot be analyzed. The proponents of the Lindeman model are further hindered by other problems, inherent in the nature of the model: (1) many animals do not fit into a single trophic level, but by their food habits, fall into two or more levels; (2) situations of imbalance are common in all communities although they are usually reduced in the climax community. The model must be modified to take these problems into account. Ours may be the age of ecology, but it appears that energetics has not yet come of age. If the study of energetics is to mature in “its era”, energetics ecologists must make a concerted effort to sample more communities with the Lindeman model in mind. Research should be aimed at analysis of food chains and food webs. Such studies would serve not only to document the metabolism of the populations concerned, but also to test hypotheses concerning energy transfers and biomass ratios between trophic levels. Only in this way can the true relationship between reality and the model be found. It seems to me that the second area ripe for study is delimitation of communities. To date, no natural area has been investigated to sea whether energy units can define or locate the boundaries of a community, and to find out whether the energy boundaries, if detectable, correspond with other observable signs, interpreted as community boundaries. Finally, at this point, some relationship is indicated between net

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productivity and maintenance metabolism (see Fig. 2). It is important to remember that the relationship (Log Rp == 0-62 + 0-86 Log p ) waa obtained from data provided by 5 different authors, working on several species of animals and using markedly different techniques to make energetics estimates. The majority of the points on Fig. 2 represent single species populations. Point 7, however, represents all of the oribatid mites in the “old field” soil (Engelmann, 1961). While working with the plot, I questioned the position of point 7, for it represents data from about eighteen species. Yet this point lies near a regression line derived mostly from points representing single species data. I used the new formula to check further the position of the oribatid data on Fig. 2 as well as to make a preliminary check on the plausibility of this formula. In my original analysis (Engelmann, 1961) the productivity estimates came from two independent sources, one based on egg production in three species of mites (particularly Oppia nova and Scherloribates leuigatus) in cultures, and the other from the deduced death rate of the adult population. This net production figure, then, was not compiled from individual production rates for each population. By using the net productivity formula for poikilotherms listed ,tbove, I was able to calculate from the annual respiratory metabolism the net production for each species of oribatid found on the “old field’’ (Table IX). The immature individuals were not reproducing and thus were not included in the calculation. Certain other populations (marked with asterisks) were not originally separated into groups of adults and young, because all stages were readily identified as belonging to the mme species. Thus, I arbitrarily assumed that one-third of the population were adults, capable of reproduction, and two-thirds were immatures. The total net productivity as calculated by the net productivity e quation for poikilotherms (using the above-mentioned omissions and assumptions) was 428 cal/ m2/yr while the net productivity calculated by oviposition data and turnover rate was 430 cal. If no assumption were made about the mixed populations (*), the total would have been 568.3 cal/m2/yr. I n the first case the agreement would be phenomenal and in the second instance there would still be reasonable agreement. Thus, I feel that the new equation has great potential, but should be more fully tested. If we are concerned with predicting net productivity of a community, we cannot use the simple equation for respiration and net productivity. As more data on species respiration are added, the calculations deviate further from the true figure, e.g. if we take the total respiration data from Macfadyen’s (1963b) Grassland No. 1 and use it in the equation, net productivity is estimated at 650 kcal/m2/yr.If the productivity is then calculated for each trophic level and taxon listed, an estimate of only 470.7 kcal/m2/yrresults (some 27% lower than the estimate based

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MANFRED D . ENGELMANN

TABLEIX Net Reproduction of Oribatid Mites Calculated f r m the Maintenance -Net Reproduction Formula. (Respiration Data from Engelmann, 1961.) Species Number t

Species Name

Net Productivity in g cal/ma/yr

Tectocepheua velatua (Mich.) Scherloribatea pallidulua Camiaia sp. Immature Oppia nova Cultroribula sp. (divergena) Suctobelba sp. Oppia minutisaim Rhyaotritia ardua Peloribatea curtipilua Allogalumna alatum Immature Immature Adult Oppidae Trhypochthonius sp. (tectorum) Belba sp. Immature ThyriSom ovata Immature Immature Liochthoniua perptmillua and Braohychthoniua jugatua Zygoribatula roatrata Tamonomid Tamonomid

101 102 103 105 108a 108c 108d 1080 109 110 111 112& 112b 113 114 115 116 117 118 119 120 121 126 128

TOTAL

86.0 39-3 25.0f

-

'32.4 9 -5 4 a4 0.6 28.1 27.4 17.5

-

1.1 69.5 0 -5 14.6

-

17.2: 27 *6 13.5: 14.3: 428.4

t Identiflcatfon system wed by Engelmann, 1981.

:Assumed 1/3 population productive.

upon total annual respiration). But, the taxa listed by Macfadyen were not species. Rather they were orders and phyla and thus we could predict that net productivity of the entire community is still less than the, estimate made using taxon analysis. If the poikilotherm net productivity curve is valid, then the net productivity of this portion of an animal community could be calculated, where the annual respiration is known. The formula would be 1

Logp

2Log Rp =

- 0.62

0.86

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where N is the total number of poikilothermic species in the community, P,net productivity in calories and Rp, annual respiration in calories. It follows that estimation of net productivity should be possible, if the average respiration ( R p )and the total number of species present in the community are known, by using the formula: Logp

N Log R1,

=-

-

0.83

0.62 ~-

When testing this formula on Macfadyen’s (1963b) community data and my own oribatid data (Engelmann, 1961 Table 4, p. 226), I found that the average respiration consistently gax-e an estimate which was 8 to 12% lower than net productivity calculated from the respiration of each individual species. The formula for crdculating community net productivity, using average respiration rate would then become : Logp

=

N Log Rp - 0.62 0.83

+ 0.1 (!Log

T8;

)

0.62

which is not very satisfying. Finally, if we are to calculate the total net productivity of an entire animal community, we must include a term for the homiotherms. The homiotherm regression in Fig. 2 does not show a significant correlation with the points on the Figure. If we assume, however, that the regression line fits, then the equation for total net productivity of the community would be : 1

ZLog Rp - 0.62

Log p

=N ~~

~

+ N’ ZLOg Rh - 2.59

~

1

2-61

_

_

_

where N equals the total number of poikilothermic species, N 1 equals total number of homiothermic species, Rp = annual respiration (in kcal) of poikilotherms, and Rh = annual respiration (in kcal) of homiotherms. If, however, the homiotherm slope is actually that of the poikilotherms, then the constant in the homio1;herm portion of the equation would be 1.7 and the divisor would be changed to 1.72. These equations, if valid, will be useful tools for the further analysis of communities, inasmuch as the respiration of a species is relatively easy to measure. Finally, it is reasonable to hypothesize that a relationship exists between total caloric ingestion and net productivity. It is also probable that the relationship of calories ingested ancrnet productivity at the community level, though simpler, is not so aclxrate as the relationships of respiration and net productivity.

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I n summary, then, we have taken a brief look a t the growth of the principles of energetics as applied to field populations. At the start, studies were concerned mainly with the physics of combustion by animals. Subsequently the science grew and fragmented into three lines of attack. The physiological studies provide a potential reservoir of information. The maintenance metabolism studies provide comparisons a t the population and community levels which emphasize the intensity of the energy flow. The trophic-dynamic studies yield a model and date on net productivity. From a close examination of the field as a whole, one can say that the study of energetics (particularly terrestrial) is still in its developing stage -not yet in any sense so mature as is sometimes proposed. Yet, the Lindeman model, and maintenance metabolism studies, are providing guidelines for field investigations. Such studies are, in turn, yielding data necessary for further speculation, prediction, and model refinement. Even though methods are still crude, new principles are beginning to emerge, and this discipline shows great promise. I wish to express my gratitude to Dr. John A. Wallwork (Westfield College, London, England) and Dr. Tyler Woolley (Colorado State University) for the identifications of the Oribatei, to Dr. George Petrides. (Michigan State University) for making the manuscript of his paper available, to Dr. D. Strawbridge and Mr. W. Weist (Michigan State University) for their discussions on mathematical aspects of the work, to the National Science Foundation for funds supporting a portion of the mite research reported in this paper. I am particularly grateful to my wife, Patricia, for her patient help with the manuscript. REFERENCES Allee, W. C., Emerson, A. E., Park, O., Park, T. and Schmidt, K. P. (1949). “Principles of Animal Ecology”. Philadelphia: Saunders. Armsby, H. P. (1903).“Principles of Animal Nutrition”. New York. Atwater, W. 0. and Benedict, F. G. (1903). “The Metabolism of Matter and Energy in the Human Body”. U.S.Department of Agriculture Bulletin 138. Benedict, F. G. (1936). “Physiology of the Elephant”, Washington: Carnegie Institute, Publ. 474. Berthet, P. (1963).MBsure de la consommationd’oxygAne des Oribatides (AcarieG) de la litiAre des for&. I n “Soil Organisms”, 18-31. Birch, L. C. and Clark, P. D. (1953).Quart. Rev. Biol. 28, 13-36. Forest soil as an ecological community with special reference to the fauna. Birge, E. A. and Juday, C. (1922).Bull. WkconSin Beol. Nat. Hiet. Sum. 64,l-222. The inland lakes of Wisconsin. The plankton. Part I. Its quantity and chemical composition. Blair, W. F. (1964).Bio.Sci. 14, 17-19. The case for ecology. Bornebusch, C. H. (1930).“The Fauna of The Forest Soil”. Copenhagen. Brody, Samuel. (1945).“Bioenergetics and Growth, with Special Reference to the Efficiency Complex in Domestic Animals”. New York: Reinhold. Reprinted (1964).New York: Hafner.

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Cole, L. C. (1964). Bio. Sci. 14, 30-32. The impending emergence of ecological thought. Davis, D. E. and Golley, F. B. (1963). “Principles in Mammalogy”. New York: Reinhold. Dawson, W. R. (1955).J. Mammal. 36,543-553. Thl3 relation of oxygen consumption to temperature in desert rodents. Dawson, W. R. (1958). Physiol. Zool. 31, 37-48. Relation of oxygen consumption and evaporative water loss to temperature in ];he cardinal. Dawson, W. R. and Templeton, J. R. (1963). Physlol. Zool. 36, 219-236. Physiological responses to temperature in the lizard Crotaphytus colhrb. Dawson, W. R. and Tordoff, H. B. (1964). Auk, 81, 26-35. Relation of oxygen consumption to temperature in red and white-winged crossbills. Dice, L. R. (1952). “Natural Communities”. Ann Arbor: University of Michigan Press. Dixon, M. (1962). “Manometric Methods”. London Cambridge University Press. Doeksen, J. and Van der Drift, J. (eds.) (1963). “Soil Organisms”, Amsterdam, Netherlands: North Holland Pub. Co. Engelmann, M. D. (1961). Ecol. Monogr. 31,221-238. Reprinted in Hazen (1964). 332-349. The role of soil arthropods in the einergetics of an old-field community. Evans, F. C. (1964). Bull. Ecol. Soc. Amer. 45,96. Seasonal changes in composition of a insect community. Evans, F. C. and Smith, F. E. (1952). Anter. Nat. 86, 299-310. The intrinsic rate of natural increase for the human louse, Pedkulua humanus L. Gem, G. (1956a). A d a Biol. Hung. 6, 258-271. The examination of the feeding biology and the humificative function of Diplopoda and Isopoda. Gem, G. (1956b). Opus. Zool.l,29-32. Investigations concerning energy turnover of Hyphuntria cunea Drury caterpillars. Golley, F. B. (1960). Ecol. Monogr. 30,187-206. En3rgy Dynamics of a food chain of an old-field community. Golley, F. B. (1961). Ecology, 42, 581-584. Energy values of ecological materials. Golley, F. B. and Gentry, J. D. (1964). Ecology, 45, 217-225. Bioenergetics of the southern harvest ant, Pogonomymx bodiua. Hairston, N. G. (1969). Ecology, 40(3), 404-416. RElprinted in Hazen (1964), 319331. Species abundance and community orgarthation. Hairston, N. G. and Byers, G. W. (1964). Contr. Lab. Ve‘ert.Biol. Univ. Mich. 64, 1-37. A study in community ecology: The soil arthropods in a field in southern Michigan. Hairston, N. G., Smith, F. E. and Slobodkin,L. B. (1960).Amer. Nat. 94,421-425. Reprinted in Hazen (1964), 288-292. Community structure, population control, and competition. Hazen, W. E. (ed.). (1964). “Readings in Population and Community Ecology”, Philadelphia: Saunders. Itd, Y. (1964). Ree. Population Ecol. 6, 13-21. Preliminary studies on the respiratory energy loss of a spider, Lywsa pseudoaniizdah. Kendeigh, S . C. (1944). J. exp. Zool. 96, 1-16. Effect of air temperature on rate of energy metabolism in the English sparrow. Kendeigh, S. C. (1949). Auk, 66, 113-127. Effect of temperature and season on energy resourees of the English sparrow. King, J. R. and Farmer, D. S. (1961). In Marahall 1(1961),216-288. Energy meteboliam, thennoregulation, and body temperature.

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Lavoisier, A. L. (1777). Mem. Acad. Sci., p. 185. Experiences sur la respiration des animaux et sur la changements qui arrivent a’l’air en passant par leur poumons. Lindeman, R. L. (1942). Ecology, 23, 399-418. Reprinted in Hazen (1964). 206225. The trophic-dynamic aspect of ecology. MacArthur, R. H. (1960). Amer. Nut. 94,25-36. Reprinted in Hazen (1964). 307318. On the relative abundance of species. Macfadyen, A. (1963a). “Animal Ecology, Aims and Methods”. London: Pitman. Macfadyen, A. (1963b). I n “Soil Organisms”, 3-17. The contribution of the microfauna to total soil metabolism. Marshall, A. J. (ed.). (1961). “Biology and Comparative Physiology of Birds, Vol. 11”.New York: Academic Press. McNab, B. K. (1963). Ecology, 44, 521-532. A model of the energy budget of a wild mouse. Metcalf, C. L. and Flint, W. P. (1939). “Destructive and Useful Insects”, New York: McGraw-Hill. Morrison, P. R. and Ryer, G. A. (1951). Fed. Proc. 10(1), Part I. Temperature and metabolism in some Wisconsin mammals. Nielsen, C. 0. (1961). Oikos, 12, 17-35. Respiratory metabolism of some populations of enchytraeid worms and free living nematotods. O’Connor, F. B. (1963). I n “Soil Organisms”, 32-48. Oxygen consumption and population metabolism of some populations of Enchytraeidae from North Wales. Odum, E. P. (1964). Bio.Sci. 14, 14-16. The new ecology. Odum, E. P. and Smalley, A. E. (1959). Proc. Nut. Acad. Sci., Wash. 45, 617-622. Comparison of population energy flow of a herbiverous and a deposit-feeding invertebrate in a salt marsh ecosystem. Odum, E. P., Connell, C. E. and Davenport, L. B. (1962). Ecology, 43, 88-96. Population energy flow of three primary consumer components of old-field ecosystems. Patten, B. C. (1959). Ecology, 40, 221-231. A n introduction to the cybernetics of the ecosystem: the trophic-dynamic aspect. Pearson, 0. P. (1960). Phyaiol. Zool. 33, 152-160. The oxygen consumption and bioenergetics of harvest mice. Petrides, G. A. and Swank, W. G. (1965). Estimating the productivity and energy relations of an African elephant population. Proceed. 9th Interimtwnal armslunda Congress, SBo Paulo, Brazil. Phillipson, J. (1962). Oiko8, 13, 311-322. Respirometry and study of energy turnover in natural systems with particular reference to the harvest spider. Platt, R. B. and GriEiths, J. (1964). “Environmental Measurement and Interpretation”. New York: Reinhold. Sealander, J. A. Jr. (1952). J . Mamm. 33, 20&218. Food consumption in Peromyscua in relation to a& temperature and previous thermal experience. Sears, P. B. (1964). Bio.Sci. 14, 11-13. Ecology - a subversive subject. Siegel, S. (1956). “Nonparametric Statistics for Behavioral Science”. New York: McGraw-Hill. Slobodkin, B. L. (1960). Amer. Nut. 94, 213-23G. Ecological energy relationship at the population level. Slobodkin, B. L. (1962). In “Advances in Ecological Research, Vol. 1” (J. B. Cragg, ed.), pp. 69-101. London: Academic Press. Energy in animel ecology.

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Slobodkin, B. L. and Kichman, S. (1961). Nature, Lond. 191, 299. Calories/gm. in species of animals. Smalley, A. E. (1960). Ecology, 41, 672-677. Energy flow of a salt marsh grasshopper population. Teal, J. M. (1962). Ecology, 43, 614-624. Energy flow in the salt marsh ecosystem of Georgia. Van der Drift, J. (1951). “Analysis of the Animal Community in a Beech Forest Floor”, Wageningen. Van der Drift, J. (1958). The role of the soil fauna in the decomposition of forest litter. 15th Intern. Congress Zool., London, Sect. 4, paper 3, 357-360. Waldbauer, G. P. (1964). Ent. Exper. Appli. 7 , 253-269. Consumption, digestion and utilization of solanaceous and non-solanaceous plants by larvae of the tobacco hornworm, Protoparce sexta (Johan.) (Lepidoptera: Sphingidae). Wallgren, H. (1954). Acta Zool. Fenn. 84, 1-110. Energy metabolism of two species of the genus Ernberiza as correlated with distribution and migration. West, G. (1960). Auk, 77, 306-329. Seasonal variation in the energy balance of the tree sparrow in relation to migration. Wiegert, R. G. (1964). Ecol. Monogr. 34,217-241. Population energetics of meadow spittle bugs (Philaenus apurmarius L.) as affected by migration and habitat.

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The Production of Marine Plankton J. E

. G. R A Y M O N ' I

Department of Oceanography. University of Southampton. England

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I Introduction ...................................................... I1 Phytoplankton Production .......................................... A Methods of Estimating Primary Production ........................ B Factors affecting Primary Production ............................. 1 Light ...................................................... 2 Temperature ................................................ 3 salinity.................................................... 4 Nutrients -Phosphate and Nitrate ............................ 6 Minor Nutrients ............................................. 6 Organic Requirements ....................................... C. Production -Temperature and Stratification ...................... I11 The Standing Crop of Phytoplankton ................................. IV Phytoplankton Crop and Annual Production .......................... V Grazing by Zooplankton............................................ VI Zooplankton...................................................... A. Methods for Estimating the Standing Crop of .Zooplankton........... B Regional Crop Assessments of Zooplankton......................... C Rate of Zooplankton Production ......................... .-. ...... D The FeedingofZooplankton ..................................... E . Alternative Food Sources for Zoopla.nkton. ........................ F. Zooplankton - Quantitative Food Requirements . . . . . . . . . . . . . . . . . . . VII Conclusion ........................................................ References .............................................................

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117 120 120 126 126 133 134 136 138 140 147 165 167 160 168 168 170 178 182 186 188 189 191

I . INTRODUCTION Production in the marine environment must depend as in any other eco-system on the synthesis of organic matter of high potential chemical energy from inorganic materials of low potential energy. There are only two such primary autotrophic forms of production occurring in the marine environment. Firstly there are the autotrophic bacteria which by relatively simple chemica.1reactions such as oxidations obtain energy to synthesize complex organic matter . Although our knowledge of the distribution of bacteria in the sea is limited, it appears that the contribution made by these autotrophic bacteria by chembsynthesis must be very small (cf. Steemann Nielsen. 1960). Kriris (1963) considered that in a special region such as the Black Sea. such production might be very E

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significant. However, Sorokin (1964a) points out that the main autotrophic bacteria are probably those oxidizing H,S to sulphate. These are only abundant at the boundary in the Black Sea between the oxygenated and de-oxygenated layers. Even in such an atypical sea as the Black Sea, autotrophic chemosynthesis makes only a small contribution to overall production. The second source of autotrophic production, the photosynthetic activity of green plants, is overwhelmingly the more important. With solar radiation the plant can build up from carbon dioxide, water and simple inorganic compounds the complex organic materials of high potential energy. Some of this organic material, when synthesized, might be liberated in dissolved form into the sea water. In addition, by death and decomposition of plankton much larger amounts of dissolved organic substances are released to sea water. These dissolved organic materials can be utilized by bacteria, fungi and Protista so synthesizing particulate living matter, which can be used as food, and thus contribute to the biomass of marine plankton. But the production of such dissolved organic substances must depend in the first case on autotrophic synthesis which is due essentially to the photosynthetic activity of plants. Any consideration of production in the sea therefore, as on land, immediately focuses attention on the plant life, in this case of the oceans. The marine plankton may be regarded as drifting and floating organisms whose existence is independent of the sea bottom. The community may be thought of as consisting of the green plants, the phytoplankton, and the animals, the zooplankton, together with bacteria, yeasts, fungi and other similar organisms. There is a continuous flow of energy through the marine eco-system and it is relatively easy to envisage the transfer of energy through the primary production of the phytoplankton to the herbivorous zooplankton and thence to the carnivorous zooplankton and nekton. Even in the plankton itself the food web is complex, and there is also the interchange of energy between the plankton and the nekton, and with the various divisions of the benthos. Although it is artificial, therefore, to separate the plankton from the remainder of the marine community, for the purposes of this review production of plankton will be examined as a separate entity. It is misleading to consider primary production in the marine environment by the phytoplankton without paying some attention also to those plants which occur in shallow waters fixed or lying on the bottom, and which may be referred to as the benthic plant population. These benthic plants, either as living or dead material, are swept into the waters above the bottom and thus may contribute significantly to the food of planktonic animals. The benthic plants may be roughly

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divided into the macrobenthic plants which are the typical large seaweeds which occur fixed to rocks around the coast, particularly in temperate regions of the world, and the microbenthic algae. The fixed seaweeds appear to form dense forests in regions where they are abundant, and it might be felt that they make a very appreciable contribution to the production of organic matter in the 8 8 8 3 . Equally conspicuous in certain shallow marine regions are a few species of flowering plants, such as Zostera, Ruppia, and Thalausia, which grow successfully in fairly soft bottoms of sandy mud. Less obrious but of considerable importance are the microbenthic algae which occur as single celled diatoms and flagellates on rocks, muds and sands, and also on the fronds of the larger seaweeds. All plants require light as an energy source for the synthetic process. Benthic forms are thus limited to a fairly shallow layer on the coasts. The macrophytes are especially typical fringi ng the continental shelves in temperate latitudes, but they are relatively uncommon in tropical regions, and do not persist very far into really high latitudes. Around island fringes, especially oceanic islands, the benthic algae have very little foothold, but in shallow areas, constant turbulence and increased turbidity sharply cut down light penetration, thus reducing the level a t which these fixed benthic plants can live. Off north-western Europe macrophytes may persist to a depth of some 30 metres; in clear waters as off California or in the Mediterranean, somewhat deeper. In shallow, muddy areas such as the sheltered Danish fjords, the fixed algae and Zostera zones may not exceed 10 or 15 metres. Since the average depth of the world’s oceans is approximately 3 800 metres, the very small contribution of benthic plants to the production of the oceans as a whole is only too obvious. Wood (1963a) quoting Braarud suggests that the macrophytes may contribute some 2 94. Ryther (1963) however has recently suggested that we may be under-estimating the role of the benthic algae in productivity and that they may contribute to the particulate organic matter even some distance offshore. Apart from macrophytes, the algal microbenthos on the bottom deposit may add significantly to inshore production. Grrantved (1960) has investigated the productivity of microbenthos and phytoplankton in very shallow Danish fjords. For the more productive season March to October phytoplankton production amounted to only approximately a quarter that of the bottom microflora which consisted mainly of benthic diatoms. I n a further study Grrantved (1962) has investigated the production of microbenthos on exposed tidal flats. The plant population was again mostly benthic diatoms attached to sand grains, though some plankton cells descended to the bottom and were able to live for a time. There was a marked seasonal variation in production but again the

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bottom microflora was far more important than the phytoplankton. In offshore waters, and especially in the open oceans, however, the phytoplankton must be all-important in production.

11. PHYTOPLANKTON PRODUCTION The term production in the oceans is usually restricted to primary production, the synthesis of organic matter by the phytoplankton. So few parameters of production on the higher trophic levels (e.g. zooplankton, benthos, nekton) are as yet established, that estimates of production are normally restricted to primary production alone. Even here it is only comparatively recently that we have been able to gain a reasonable appreciation of the rates of production of plant material. Rate of production must be clearly distinguished from standing crop of phytoplankton which is the amount of the living plant substance existing under a unit area of sea (e.g. beneath mz) or per unit volume (e.g. m3) a t a particular place at a point in time. Standing crop is itself of great significance, but we shall first discuss rates of production.

A. METHODS O F ESTIMATING PRIMARY PRODUCTION One of the first methods used for estimating primary production was the so-called oxygen bottle method, which is still widely used. In this kind of experiment a series of bottles filled with sea water and containing a phytoplankton population is suspended at various depths in the sea starting at the surface. The rate of photosynthesis as a measure of plant production is estimated by the rate of change of oxygen. concentration (measured by the Winkler method). Various precautions must be taken such as avoiding shading by a bottle at a higher level in the water, and ensuring that no loss of gas occurs during the course of the experiment. The change in concentration of oxygen in any bottle (AO,) may be due to several factors which may be expressed as follows:

+ AO,=P

-RI -RR, -Rb

where R, = Respiration of plant tissue originally present; R, = Respiration of newly formed plant tissue during the course of the experiment; Rb = Respiration of bacteria and any zooplankton. The change in oxygen, apart from that due to bacterial and zooplankton respiration, would thus be an estimate of net photosynthesis. But the amount of oxygen consumed due to the respiration of the plant tissue originally present (R,) and the amount of oxygen consumed by bacteria and zooplankton (Rb) can be estimated by suspending a series of so-called “dark” bottles at the same time and at the same depths as the normal “light” bottles. If the amount of oxygen consumed in a “dark” bottle

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is added to the amount of oxygen produced in a “light” bottle, the total amount of oxygen is equivalent to (P - R,). As R, is normally very small in short-term experiments, this total amount of oxygen change is practically a measure of gross photosynthesis. If longer term experiments are employed R, may become considerably larger and the estimate of photosynthesis then approaches a net value again. One disadvantage of the oxygen bottle method is that the temperatures in the “dark” bottle series may be somewhat different, respiration proceeding at different rates in the “light” and “dark” bottles. Furthermore, fat may be synthesized to some extent rather than carbohydrates, particularly by diatom cultures, which will af Fect the amount of oxygen produced. Growth, especially of marine bactwia, tends to be increased by surface, and therefore there may be an almormally high density of bacteria in the enclosed phytoplankton cultures. I n any event, probably no population of phytoplankton can live perfectly normally enclosed in a relatively small volume of virtually stationary sea water. But, above all, the most serious disadvantage of the oxygen bottle experiment lies in its comparative insensitivity, especially with low concentrations of phytoplankton as in oligotrophic areas of the ;sea;under such conditions the amount of oxygen produced over a moderately short-term experiment may be quite small (cf. Currie, 1959, 1962). The technique is also unsuitable for productivity experiments in very rich, highly polluted, inshore waters, especially with high bacterial populations. Other methods have been tried for estimating the rate of primary production in the marine environment. Changes in the quantities of nutrients such as nitrate and phosphate, which are essential for the upbuilding of cell tissue, have been used as a measure of plant growth. One of the main difficulties is that unless a steady state in water movements can be assumed, any large scale lateral exchange of water through the area may introduce major errora in calculations. Vertical exchange of water may also be important. In a deep oceanic area the extent of vertical mixing may be assessed so that any nutrient brought into the photosynthetic zone from deeper water may be included in the calculations. In shallow water it may be possible to integrate the whole changes in nutrient from surface to bottom, but the leaching of nutrients from the bottom deposits can be significant. Perhaps the greatest difficulty with using nutrient changes as a measure of production, however, turns on the problem of regeneration. The regeneration of inorganic nutrient materials from organic matter (or mineralization) can be rapid under certain conditions. Investmigations such as those of Harris (1959) suggest that at least a portion of the phosphorus and some of the nitrogen, particularly as ammonia, may be fairly rapidly recycled. Ketchum (1962) suggests that phosphorus may be cycled some 6 or 7 times a year

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in the waters of the continental shelf off Woods Hole, and similar determinations for the North Sea over the 7 months of main phytoplankton growth suggest that phosphorus may go through perhaps half a dozen regeneration cycles. Vaccaro (1963) has also pointed to the importance of ammonia in the upper layers being rapidly regenerated and maintaining the cycle of phytoplankton growth. With the possibility of considerable regeneration of nutrients, any estimate of primary production dependent on changes in nutrient level may give only minimal values. These errors were recognized in the early work of Atkins, Harvey and Cooper for the English Channel; nevertheless Cooper (1933) was able to estimate minimal production of phytoplankton for the English Channel over a period of about 5 months from changes in CO,, 0,, phosphate, nitrate, and silicate. The agreement (Table I) is fair except for the case TABLEI The Theoretical Minimal Production of Phytoplankton in, the English Channel Calculated on the Basis of Chemical Changes in. the Water (the period of production i s from JanuarylFebruary to July) . (from Cooper, 1933) Basis

Minimum production of phytoplankton wet weight metric tons per square km. 1600

COZ

1000 1 400

0 2

Phosphate Nitrate Silicate

1600 110

of silicate which probably arises from the rapid recycling of this element. Steele (1956, 1958) has also used the changes in phosphate concentration to calculate the production of phytoplankton on the Fladen (North Sea) ground, where apparently little lateral transport of water occurs. The estimates of production based on phosphate changes and on 14C (vide infra) methods gave fair agreement. Several workers have used the dependence of photosynthesis on light intensity to establish equations for the rate of primary production. For example, Ryther and Yentsch (1957) suggest that, on average, marine phytoplankton has an assimilation rate of 3.7 g.C/h/g. chlorophyll at light saturation values. They have established the relationship

P=

R

-x

k

cx

3.7

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for calculating production in a column with a homogeneous distribution of phytoplankton. P = photosynthesis of the population in g/C/m3/day; R = relative photosynthetic rate, dependent on the light surface intensity; C = chlorophyll/m3 in the column. Such a calculation gives only an approximation since the assimilation rate assumed is a mean value for various species. Phytoplankton is very often also markedly stratified rather than homogeneously distributed and there is the difficulty that the existing stock of algal cells must be estimated from the amount of chlorophyll present. One of the most successful and widely used methods for estimating primary production was developed by Steemann Nielsen (1954) (cf. Steemann Nielsen and Aabye Jensen, 1957). 1-nhis technique the radioactive isotope, I4C, is added, as bicarbonate, to a bottle of sea water, the productivity of which is to be measured. The Lotal content of CO, in the water must be known and, assuming that the labelled carbon has been assimilated by the algae, the total amount oS carbon photosynthesized during the period of time may be calculated by determining the amount of 14Cpresent in the plankton when the experiment ends. The plankton is removed by filtration and the amount of 14C measured by the /3 radiation from the plankton retained on the filter. The carbon technique is undoubtedly far more sensitive and iiherefore is of great use in measuring the primary productivity of oligotrophic waters; it avoids the long term experiments necessary with the 0x3gen bottle technique. At the same time there are certain difficulties in using this method. For example, it is necessary to assume that “C and the normal isotope are absorbed at the same rate; Steemann Nielsen has suggested that the error due to isotopic discrimination is not more than 5%. Again, the precise method of filtering, the type of microfilter, and the pressure used for filtration may also be critical in that more delicate phytoplankton cells may be destroyed and EL loss of material encountered. The 14C method may be particularly sensitive to errors of this sort where delicate flagellates form a relatively large part of the phytoplankton population. A difficulty found with the oxygen bottle experiment also applies to the I4C technique, namely that the enclosure of a photosynthetic population in a static volume of sea water does not reflect precisely the conditions operating in the natural environment. Other errors may arise; the time of day in which the estimate is made can be important, since diurnal variations in photosynthetic activity of algae are now recognized, particularly the “afternoon depression” (Doty and Oguri, 1957) which may be especially marked in plankton from warm waters. Difficulties may also be encountered when the algal cells have shells or inclusions of calcium carbonate (e.g. if the phytoplankton is dominated by coccolithophores). Steemann Nielsen ( 1964a)

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advocates the use of fuming hydrochloric acid to reduce errors arising from this source. Since “C02 fixation” can occur in darkness and can occur with non-photosynthetic organisms, without any real gain in carbon (Steemann Nielsen, 1960), Steemann Nielsen (1964a) suggests the use of a “dark” bottle; the changes in I4C occurring in the “dark” bottle can then be used as a correction factor for the normal “light” bottle. Perhaps the chief criticism which may be levelled against the 14Ctechnique is that some of the carbon assimilated during the course of the experiment may be used for respiration purposes. The quantity is not known and therefore it is not entirely clear whether the I4C technique measures gross photosynthesis, net photosynthesis, or some measure of photosynthetic activity between these two extreme values. Some workers such as Ryther believe that the value approxiniates t o the net photosynthetic rate; Steemann Nielsen believes that with moderate production rates, respiration amounts to about 10% of photosynthesis, so that 14C experiment estimates about 90% of gross production. There is little doubt, however, that the difference between net and gross production varies with the time of year at high latitudes, and also geographically. Thus in oligotrophic tropical waters, net production may be less than 60% of gross production, whereas in high latitudes, during the height of summer, it may be a much higher proportion. If rates of primary production are to be compared, they must be related to a standard unit of concentration of phytoplankton present in the sea. The measurement of the standing crop of plankton in the sea is a very difficult problem (vide infra).Usually the amount of chlorophyll, as the active photosynthetic pigment, has been used as an approximation of the standing crop of phytoplankton, but this is not constant, varying from species to species and being dependent on the state of nutrition of the individual cell. The chlorophyll content may also change with time of day, light intensity, and with other factors. Chlorophyll and degradation products of this pigment may also occur free in the water and the length of life of such material is still uncertain; the amount of chlorophyll found by the normal filtration and extraction processes may thus be misleading. The precise method of extraction may also affect the amount of chlorophyll; for instance, grinding of the cells during extraction may lead to an increase in the amount of pigment extracted. Clear1y”theconcentration of phytoplankton expressed as the amount of organic carbon or of dry organic matter would be 8 much more accurate measurement, but no rapid and accurate method is known for determining either of these quantities. Chlorophyll, therefore, is widely used as an index of the standing crop of phytoplankton. Any technique which estimates photosynthetic activity may not necessarily be measuring accurately the increase of phytoplankton

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substance which is the essence of primary production. For example, respiration has already been noted as reducing growth. But there may be excretion of some material in soluble forin which would not appear in 14C measurements. The amount of such “lost” material is usually believed to be small, but Fogg (1963) suggests that the quantity may at times be considerable (vide infra). Other discrepancies between photosynthetic and growth rate may arise. For instance, many nutrients are required for the further synthesis of algal cell substance; the concentration of these nutrients may influence the amount of phytoplankton substance produced, though this is clearly closely related to photosynthetic activity. Ideally, we should measure the actual amount of phytoplankton material synthesized in a given volume of sea water over a period of time, but this again requires rapid and accurate methods for the determination of organic carbon or dry organic matter, and these are at present not available. Apart from the difficulty of estimating standing crop, the 14C method may be used to measure primary productio I throughout the euphotic zone in the sea, but the precise technique i3 important (cf. Steemann Nielsen, 1964a). Undoubtedly the best determinations are made employing the i n situ method by which a seiies of bottles is placed at different depths in the ocean and the light intensity throughout the euphotic zone is also measured. A reasonable method where the timeconsuming and difficult in situ method cannot be employed is to place sealed bottles of sea water from each depth on board the research ship, the whole being surrounded by a jacket of ;sea water, and illuminated by fluorescent light sources of known intensity. It is essential, however, to employ glass filters of known spectral transmission; these must be placed above the plankton samples according to the light which they would encounter at their normal depth distribution. Recently investigations comparing the production of phytoplankton by different techniques have been made. McAllister et al. (1961) enclosed a natural population of coastal phytoplankton in a large plastic sphere sunk just beneath the sea surface. Primary production rates were estimated by oxygen bottle and 14C methods, and showed rather wide differences. Some of the discrepanciea were reduced, if the 14C method was assumed to measure net photosynthesis, and if in the oxygen experiments the photosynthetic quotient was high (1-3). Net production of organic particulate carbon was also estimated over three weeks by five methods; 0,-production, 14C, #changesin CO, as revealed by pH, cell counts, oxidizable particulate carbon produced. There was a reasonable measure of agreement, especially witb three of the techniques (cf. Fig. 1). In a later study by Antia et al. (1963)using the same plastic sphere, the 14C method gave good agreement with an estimate of t?

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production based on the production of particulate phosphorus. A discrepancy between the 14Cand oxygen bottle estimations was believed to be due largely to the 14C method measuring net production whereas the oxygen method measured gross production. Other comparisons have been made using tank mass-culture techniques by Ansell et al. (1963, 1964). Estimates of production based on

I 1400 - --Values

from cell counts

1200

from

- 1 values

'Oo0-

E

PH

1 Oxidizable carbon increase 0

Radiocarbon uptake

600400

-

I2345678910i11213141516171819202122

Time (days)

FIG.1. The net production of carbon in plastic sphere experiments as measured by five independent methods; (from MoAllister, Paraons, Stephens, and Strickland, 1961).

0,bottle experiments, changes in pH and in phosphate concentration, and packed cell volume obtained after harvesting the algae, were found to show fair agreement. 1.

Light

B. FACTORS AFFECTING PRIMARY PRODUCTION

Whatever method is used for estimating primary production, it is clear that photosynthesis is dependent on light intensity. I n a typical oxygen bottle experiment such as that of Gaarder and Gran (1927) whereas at a depth of 10m there was no change in oxygen content, at higher levels in the water there was an increase in oxygen content, and a t lower levels a decrease. The depth of 10m therefore in Gaarder and Gran's experiments corresponds to a level where the amount produced by photosynthesis during the course of the experiment (in this caw 24 hours) was exactly balanced by the amount of oxygen consumed by respiration. This depth where no effective production occurs, but where respiratory and photosynthetic activity just balance, has been termed the compensation depth. Its extent will depend on the transparency of

THE PRODUCTION O F MARINE PLANKTON

127

the water. Light is relatively very rapidly reduced in the sea, being partly absorbed and partly scattered. Particlies in the water, whether inorganic or organic detritus, as well as living plankton, all reduce transparency; there is also some dissolved “yellow substance” which absorbs light. Greater light penetration is t,ypical of less productive waters, since algal cells are sparser, but the relatively rapid reduction of light in richer seas is partly due to greater quantities of detritus (cf. Ryther, 1963). The compensation depth is greatly affected by latitude and season, but it is not an absolute value - it will depend aIso on the time of day. At night it does not exist. Light is absorbed logarithmically in sea water, and even for the clearest oceanic waters about SOYo of the total solar radiation is absorbed in the upper 10m. Although infrared rays are especially rapidly absorbed, even of the visible wavelengths only some 50% remains for the clearest water at 10m depth. Whereas about 1%of incident visible light reaches some 120m in clear tropical oceans, the same reduction to 1% is reached at ca. 50m depth in boreal waters, and in turbid inshore areas the 1 Yolevel is reached at depths approaching only 10 or 20m.

TABLEI1

Culture Experiment 22-25 N w c h , 1916 Average Increase in 24 hours (from Bmvder and Bran, 1927)

yo Increase in Cell Numbers Depth, m 0

2 5

10

20 30

40

Oxygen, cm8/1

+ 0.20 + 0.19 + 0.13 0

- 0.03 - 0.05 - 0.07

Lauderia glacialis

Tlialassiosira gravida

77

59 58 55

79 70 28

0 0 0

34 0 0 0

Thalaseiosira nordenekioldii 10

73 67 23

0 0 0

In the oxygen bottle experiments such as those of Gaarder and Gran (Table 11),the decrease in the amount of oxygm produced with increase in depth of the water reflects the rapid reduction in light intensity. These experiments were conducted over a 24-hour period; had shorter term experiments been made during daylight hours only, there would have been greater oxygen production at each depth and the estimated compensation depth would have been greater. Frog the view point of overall primary production, the 24-hour experiment is the most satisfactory. The compensation depth will vary with season in a temperate

128

J . E. G . RAYMONT

latitude. Thus the experiment in Table I1 was carried out during the spring; other experiments carried out later in the year, with increasing length of day and greater light intensities, showed the compensation depth much deeper in the water. Other similar experiments such as those of Marshall and Orr (1 928, 1930) who worked on a single species of diatom, Coscinosira polychorda, suggested that whereas in winter, the compensation depth was only a metre or two beneath the surface, during summer it might lie at about 20-30 metres. One of the most complete studies on the effect of light on photosynthetic activity is that of Jenkin (1937), working with the diatom, Coscinodiscus escentricus. For the English Channel, Jenkin found a compensation depth a t about 45 metres, corresponding to a light intensity of approximately 0.13 g cal/cm2/h. Using the oxygen bottle technique she showed that between this light value and some 1 * 8g cal/ cm2/h ( 3 5 000 lux), oxygen production, as a measure of photosynthetic activity, increased practically linearly with light energy. At light intensities above this value it continued to rise but at a somewhat lower rate, indicating that some inhibition was occurring; maximal photosynthesis occurred a t a light energy approximating to 7.2 g cal/. cm2/h (of the order of 20 000 lux). Above this intensity, which may be termed the light saturation value, inhibition began to be more obvious and at high light intensities photosynthesis was markedly reduced. These experiments have been confirmed by others. Thus Talling (1960) using Chaetoceros afinis, showed photosynthetic activity to increase linearly from a compensation intensity approaching that of Jenkin to a value of some 5 000 lux; light saturation occurred at a mean value of 25 000 lux. Jenkin’s clear demonstration of inhibition at high intensities shows that even in temperate latitudes about midday during the summer some degree of inhibition of photosynthesis can occur, but this will be confined to algae close to the surface (cf. Fig. 2). The results of early experiments on primary production such as those of Gaarder and Gran (1927), suggest that some species of diatoms in a mixed phytoplankton population differ in their light requirements. Thus the diatoms Lauderia and Thalassiosira gravida grew best in the upper 2 metres, the latter species probably growing fastest right at the surface. On the other hand, the related species, T . nordenskioldii, appeared to grow best at a depth of 2-5 metres, and presumably had a lower light optimum. Later work, particularly that of Steemann Nielsen and his colleagues, has indicated clearly that different species of phytoplankton have different light optima. Although an average compensation intensity for phytoplankton species of some 0-13g cal/cma/h, as suggested by Jenkin, appears to be reasonable, the various species exhibit considerable differences in their light optima and saturation

120

THE PRODUCTION O F MARINE PLANKTON

values. But for all of them a similar curve may be constructed for the relationship between photosynthetic activity and light energy. A t low light intensities the photosynthetic rate rises almost linearly with light intensity; a less rapid rise then follows to an optimal value a t light

, Time

(h)

FIO.2. Variation of photosynthetic activity estimated hy oxygen production with depth by the diatom Coscinodkcus ezcentricus in the English Channel; (from Jenkin, 1937 reprinted from “Plankton and Productivity in the Oceans”, Pergamon Press).

saturation, followed by inhibition at high light intensities (Fig. 3). Ryther (1 956) summarizes his results for various phytoplankton species by stating that species of the Chlorophyta including Dunaliella, Chlamydomonas, Nannochloris, Platymonas and Carttiria were light saturated a t

Radiant energy (cal crn-2rnin-’1. 400 to 700 rn)L

FIO.3. The relationship between photosynthesis and 1 ght intensity in phytoplankton, based on the mean curve of Ryther (1956); (from Currh, 1962).

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J. E. a. RAYMONT

intensities of about 5 000-7 500 lux; diatoms such as Nitzschia, Coecinodiscus, and Skeletonema became light saturated at rather higher intensities from about 10 000 to more than 20 000 lux; while species of dinoflagellates (e.g. Exuviella, Gyrodinium, Gymnodinium) were light saturated at much higher intensities of about 25 000-30 000 lux. For all the species investigated, however, inhibition occurred at intensities about 10 000 lux above the light saturation values. Steemann Nielsen and Hansen (1959) have called attention to the different light requirements of phytoplankton from various regions and different depths. Thus they distinguish surface arctic, surface temperate, and surface tropical populations from other phytoplankton assemblages which occur deeper in the euphotic zone at each of these geographical latitudes. The light saturation values differ very considerably for these various groups of species, and the rate of photosynthesis per unit of chlorophyll at light saturation shows very wide discrepancies (compare Fig. 4). It is thus possible to distinguish what may be termed a “sun” plankton, which occurs near the surface and is adapted to relatively high light intensities, from a “shade” plankton which lives towards the bottom of the euphotic zone and is adapted to low light intensities. On the whole, the amount of chlorophyll per cell, or more accurately, the ratio between chloro-

Lux

FIQ.4. Light intensity and the rate of gross photosynthesis for marine phytoplanltton from different habitats. a = surface plankton; b = plankton from depth corresponding to 1% of green surface light; 1 = tropical; 2 and 3 = temperate summer; 4 = northern plankton with slight vertical stabilizetion; 6 and 6 = arctic summer; 7 = temperate winter; (from Steemtmu Nielsen and Hansen, 1969).

,

I I

THE PRODUCTION O F MARINE PLANKTON

131

phyll and carbon, tends to be higher in the E:hade forms. The existence of these shade and sun types of phytoplankton, particularly in the deeper euphotic zones of highly stratified tropical waters, has been noticed recently by many authors, for exam:ple, by Ryther and Menzel (1959). These investigators show that in an area of the Sargasso Sea during winter, when the euphotic zone may approach some 150 metres in depth, the water is mixed and is virtually isothermal to a depth of 400 metres. During this time the phytoplankton at three depths, corresponding to loo%, 10% and 1% respectively of the surface light, was of a similar sun type, being light saturated at about 50 000 lux. I n summer, however, marked stratification occiirs so that a clear thermocline exists at a depth of about 25-50 metres. The surface plankton during summer is still of the sun type, but below the thermocline, at a depth of about 100-150 metres, which corretiponds to about 1% of the surface radiation, the phytoplankton is now of the shade type and is light saturated at less than 10 000 lux light intensity. At intermediate depths, between the surface and 100 metres, the plankton is rather intermediate in character. Again, Saijo and Ichimura (1962) have shown for the Japanese waters of the Kuroshio Current that photosynthesis varies more or less directly with light energy at relatively low light intensities. However, for plankton from the surface, 20 metres, and 50 metres depths respectively, there are clear differences in the light saturation values which reflect the sun (surface) type and shade (deeper) type of phytoplankton. Although many species of phytoplankton may be classed as sun or shade types, the position is by no means simple in that one and the same species can undoubtedly become adapted to different light intensities. Harvey (1955), for example, demonstrated that growth rate in Biddulphia mobiliensis varied according to whether the cells had previously been grown in dim or bright light. Thus Biddulphia grown previously a t intensities of about 4 000 lux grew best in dim light, while cells grown at relatively high light intensities showed their maximum growth rate at about 18 000 lux. But light ie not the only factor which affects the relationship between photosynthesis and light intensity: there appear to be interactions between light, temperature and nutrient level (cf. also Maddux and Jones, 1964). Nutrient level can affect the ratio between chlorophyll and carbon in a pliytoplankton cell, lowered nutrient level tending to reduce the relative amount of chlorophyll (cf. Steele, 1962; Steele and Baird, 1963). Steele indeed considers that there are peaks in the relative amount of chlorophyll in the phytoplankton of temperate regions during spring and early autumn, when nutrient levels tend to be high, and that nutrient limitation during summer may affect the chlorophyll/carbon ratio more than having the usually recognized

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J . E . G . RAYIIZONT

effect on photosynthetic rate. Steemann Nielsen and Park (1964) have demonstrated that the adaptation of phytoplankton to changed light conditions can be quite rapid. They took plankton from an area in Friday Harbour (Washington State) where there is strong vertical turbulence and where with the lack of stratification the whole phytoplankton is adapted to relatively high light intensities. This plankton was isolated in bottles and transferred to a depth where the light was only 5% of the surface value. The phytoplankton cells showed a change to the dark adapted type within three days, the main change being a marked increase in chlorophyll content. But although surface (“sun”) plankton generally has rather lower chlorophyll content, inactivation of plankton exposed to high light intensities does not necessarily involve an immediate destruction of the chlorophyll. Steemann Nielsen (19624 demonstrated that Chlorella grown in low light intensities and then transferred to high intensities showed a depression in the rate of photochemical and of enzymatic processes; after a short period of being returned to darkness, however, these processes were completely reactivated. The complex relationship existing between light optima, temperature and nutrient levels, and possibly other factors, is illustrated by the experiments of Curl and McLeod (1961) with the diatom Skeletonema costatum. A t temperatures between 5 and 18°C the photosynthetic rate increased with temperature, and the light saturation value was fairly stable a t intensities of 12 000 to 16 000 lux. At temperatures from 20-30°C photosynthesis was diminished but the saturation intensity was also reduced to a value of only about 5 000 lux. Provided nutrients (nitrate and phosphate) were present in maximal amounts, the temperature optimum approached 20°C, but when nutrients were in limited supply, not only did the photosynthetic rate fall off but the temperature optimum was lowered (cf. also Smayda, 1963). Lanskaya (1963) has shown that even when optimum conditions for such factors as light and nutrients exist, phytoplankton species (diatoms, dinoflagellates, and flagellates) show marked variations in rates of division. Although phytoplankton species adapted to higher as well as to lower light intensities exist in the oceans, in general the very rapid light absorption means that much phytoplankton must carry out photosynthesis a t relatively low light intensities. Some diatoms for instance have been found in the Arctic which will actively photosynthesize under ice (cf. Smayda, 1963). Moreover, when phytoplankton blooms occur, the cells will cause shading to those deeper in the water layers. Thus in experiments using artificial addition of fertilizers (Raymont and Miller, 1962; Ansell et al., 1964) the compensation depth can be very close to the surface because of self-shading by the very heavy crop of

THE PRODUCTION OF MARINE PLANKTON

133

phytoplankton. Similarly in the experiments of Antis et al. (1963), selfshading occurred with the very heavy crop of phytoplankton, although with stirring, the algal cells could photosynthesize at remarkably low light intensities. With the marked differential absorption of wavelengths of light in the sea, marine algae must not only be adapted to photosynthesis at low light intensities but itlso at wavelengths which may not be maximal for chlorophyll itself. It ;seemsextremely likely that the many carotenoids which are present in different forms and in different concentrations in the various algal groups in the phytoplankton, are of significance in absorbing all light wavelengths. Although not every carotenoid may be of equal importance in absorbing energy, it appears to be the total quantity of solar radiation reaching the depths which is of real importance. The marine algae therefore appear to have become adapted to the generally low light intensities in the sea by increasing the chlorophyll content and by possessing active accessory carotenoids. 2. Temperature

While light intensity must be of major significance in relation to primary production in the sea, other factors may also play a part. Temperature is probably of little direct importance since lowered temperature will reduce the respiratory needs of the plant cells and higher temperatures, by increasing respiratcry requirements, can have a beneficial effect on photosynthesis only if very high light intensities are available. It is obvious that photosynthe3is occurs a t high efficiency in the Antarctic where the temperatures may be permanently below O"C, and equally well in tropical regions where temperatures approach 30°C. On mudflats in tropical regions, much higher temperatures may be experienced for at least part of the day. Experimentally it can be shown that increased temperature may have a direct effect on photosynthetic rate provided light saturation is achieved. Thus in the experiments of Curl and McLeod (1961) already quoted, it was shown that the temperature optimum for Skeletonema approached 20°C provided that sufficient light was available. Similarly Wimpenny (1958) investigated the carbon uptake of Rhizosolenia using a, standard illumination of 16 000 lux. Provided this high light intensitj. was available, Wimpenny showed that if the photosynthetic rate at lO'C was regarded as loo%, a reduction in temperature to 5°C lowered the photosynthetic activity to about 45% and a rise to 15°C increased it; to approximately 140%. Although temperature may not appear to have a direct effect on photosynthetic activity in the marine environment, it has extremely important indirect effects on production, particularly in relation to the establishment of stratification and the setting up of a thermocline during the

134

J . E . Q. RAYMONT

warmer period of the year in temperate and high latitudes. Temperature also plays a part in the species succession of phytoplankton, especially in temperate latitudes. Thus, Thulassiosira nordenskioldii is an important diatom a t the very beginning of the spring increase in the temperate northern Atlantic of America and Europe. Later in the spring, species of Chuetoceros and particularly Skeletonema take over. It has long been considered that Thulussiosira is favoured by the lower temperatures at the start of the spring increase, and that the slight rise in temperature later on is largely responsible for the subsequent flowering of Skeletonema. Even this succession, however, may not be entirely a result of temperature, since Braarud (1962) has suggested that Thalassiosira has very high nutrient demands which would be satisfied only at the beginning of the spring increase. But temperature has a part to play in species succession. The abundance of peridinians, mainly in the summer period, in temperate latitudes, is thought to be associated with the generally higher temperature requirements of these algae. To some extent this agrees with Braarud's (1961) observation that for several dinoflagellates temperature optima are relatively high. Species succession in phytoplankton, however, is by no means limited to temperate latitudes; it is found clearly in Arctic waters (e.g. Digby, 1953; Bursa, 1963; Holmes, 1956); it is true of Antarctic waters (Hart, 1934), and is found also in warmer, subtropical waters (e.g. Riley, 1957; Hulburt, Ryther and Guillard, 1960). Thus although temperature may play a part, it is undoubtedly not the only factor in the succession of phytoplankton forms; the rapid take over from one species to another and the fact that one species may flower at two different periods in the year when temperature conditions are considerably different, points to the collective action of several factors (cf. Smayda, 1963). 3. Salinity Other factors beside light and temperature may influence primary production. Salinity variations can be shown experimentally to have an effect on photosynthetic rate. Curl and McLeod found Skeletonema had an optimum rate of photosynthesis at salinities ranging between 15 and 20%,, though the process could go on over as wide a range as 11 to 40%,. Braarud (1961) demonstrated that some species of dinoflagellates, Ceratium, Peridinium, Prorocentrum, reproduce more actively at lowered salinities. Provasoli and McLaughlin (1963) have shown t8hat Peridinium balticum and Peridinium chattoni are even stenohaline brackish water forms with an optimum range of only 8 to 12%"for photosynthesis. By contrast, Exuviellu is a common brackish water form, but has very wide salinity limits, occurring a t salinities of 8 t o 35%"; the optimal salinity for photosynthesis is about 20 bo 25%,.

THE PRODUCTION O F MARINE PLANKTON

135

Similar work by Pintner and Provasoli (1963) has shown that marine chrysomonads may also be either stenohaliiie or euryhaline forms. For example, Coccolithus huxleyi has a remarkaldy widespread distribution in the seas and can tolerate salinities certainly down to IS%,. Although salinity therefore may have some effect on productivity rates of individual species, generally in the sea even near the surface, the variations in salinity are so very slight that this factor cannot be important in oceanic productivity. Even in inshore waters the variation in salinity is much more likely to operate in the successicm of phytoplankton species than as a factor in overall production. Since salinity and temperature, however, influence the density of sea water, salinity can affect the flotation of phytoplanktonic species. Thue Braarud (1962) suggests that oceanic phytoplankton usually consisto of either species with large cells with good flotation, or of minute forms with a higher reproductive rate. A number of coastal species are unable to avoid sinking when temperature and salinity changes reduce the specific gravity of the water. They therefore may disappear for some time, and only spore formation will carry the species over to a later flowering when changes in the density of sea water permit active reproduction again. Significant indirect effects of lowered salinity on production in relation to stratification are mentioned later. 4. Nutrients - Phsphate and Nitrate

For many years the concentration of two major plant nutrients, nitrate and phosphate, has been recognized as one of the major factors limiting primary production in the oceans. The cycle of phytoplankton growth in temperate latitudes with the marked spring and autumn peaks and the depression of production during the summer has been linked with the changes in nutrient levels. Investigations such as those of Atkins, Harvey, and Cooper at Plymouth, and of Marshall and Orr in the Clyde sea area, as well as those of Bigelcw, Lillick, and Sears (1940) for the Gulf of Maine area, suggest that the lack of nitrate or phosphate, whichever is in shortest supply, during summer when a thermocline is strongly established, acts as a marked brake on phytoplankton production. The work of Riley and his colleagues in Long Island Sound (e.g. Riley and Conover, 1956), where greater quantities of nitrate and phosphate are present over winter, indicateri that a limitation is placed on phytoplankton production during the summer by the depletion of nitrogen. I n certain areas of the Gulf of Maine, over the Faroe-Shetland Ridge and in Friday Harbour, where marked turbulence occurs and there is a lack of stratification so that nutrients are not normally depleted over the summer, production may be increased. The clearest demonstration of the relationship between EL constant supply of nitrate

136

J. E.

(f. RAYMONT

and phosphate and primary production is provided by the major upwelling areas such as those off West Africa, off Chile and Peru, and off the coast of California. I n each region the relatively high concentrations of nitrate and phosphate are accompanied by rich growths of phytoplankton (cf. Hart, 1953; Hart and Currie, 1960; Clowes, 1950, 1954; Gunther, 1936; Sverdrup and Allen, 1939). Just recently the investigations of the Indian Ocean Expedition have pointed to a fairly rich production off southern Arabia associated with upwelling water. Above all, in the Antarctic (Hart, 1934, 1942), constant upwelling on a relatively gigantic scale permits a high rate of production as long as the light conditions are sufficient for photosynthesis. Areas of divergence may also be marked by nutrient-rich water reaching the surface. The well-known divergence close to the Equator in the Pacific Ocean is marked by a high rate of productivity (Austin and Brock, 1959; Hela and Laevastu, 1962) in the rich surface water. Holmes (1958) and Bogorov (1958) similarly relate high rates of production and of standing crop in Pacific waters to areas marked by nutrient-richer surface water. Indeed, turbulence, convection currents, current boundaries, as well as more major upwelling, are of significance in renewing phosphate and nitrate to the surface and raising primary production. In the absence of such vertical water movements, generally in tropical and subtropical regions a strong thermocline is permanently established, and the lack of nitrate and phosphate occurring in the euphotic zone puts a sharp brake on primary production. Admittedly much of the earlier work dealt with the standing crop of phytoplankton in tropical and subtropical areas rather than with primary production, but the work especially of Steemann Nielsen (1954) and Steemann Nielsen and Aabye Jensen (1957) permits some summary to be made for production. Thus for tropical areas the rate of primary production is low amounting to some 0.1 to 0 . 2 g C/m2/day, and in areas such as the Sargasso Sea, where the upper water layers are especially depleted in nutrients, the production may be even lower. As against this, inshore temperate areas which are fairly rich in nutrients and also rich upwelling areas anywhere in the world may show a production varying from 0.5 to 3.0 gC/m2/day. If we assume a direct dependence of production on nutrient level, it must be admitted that in temperate regions the fall in phytoplankton after the spring increase does not always precisely accompany the reduction in nutrient concentration. The picture is confused here by our inability often to distinguish between the standing crop of plankton and rates of production. During the summer also the standing crop may be maintained at a relatively low level by grazing although production may be proceeding at a somewhat higher rate than was originally

T H E PRODUCTION O F MARINE PLANKTON

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supposed. Equally Cushing ( 1959a and b) has demonstrated for tropical waters that rates of production may be higher than were earlier envisaged, and that our ideas on tropical production have been unduly influenced by the usually low value of the phytoplankton standing crop. Nevertheless, rates of production are limitled by nutrient levels, although there have been relatively few laboratory experiments which have demonstrated conclusively this precise dependence for any particular phytoplankton species. The work of Ketchum (1939) demonstrated that the growth of Nitzschia was unaffected as long as about 16 mg of phosphate-phosphorus/m3 were present. Growth could continue at concentrations below that figure although on a somewhat reduced level, but at concentrations below 5 mg/m3 the rske of division fell off very sharply. More recent investigations such as those of Curl and McLeod (1961) also demonstrate the importance of nutrient level on photosynthetic rate. It is almost certain that just as different species of phytoplankton may have different light cha,racteristics so the precise nutrient levels demanded by different species also varies. Barker (1935) showed that some flagellates could grow effectively at greater dilutions of both nitrogen and phosphorus than typical diatoms. On the other hand, the investigations of Ryther (1954) suggest that the green algae Nannochloris and Stichococcus flourish only at relatively high nitrogen concentrations. Again Kain and Fogg (1958) ;suggestthat Isochrysis has higher phosphate needs than most diatoms. Precise phosphorus requirements are particularly difficult to establish since many phytoplankton cells apparently absorb phosphate extremely rapidly, though they may later release a considerable proportion of the nutrient either as phosphate or in labile organic forms which :me rapidly converted into orthophosphate. Unfortunately even less is known of the precise nitrate requirements for single species of phytoplankton. Field observations suggest that the diatom Thalassiosira node wkioldii possibly has very high nutrient requirements as also does the neritic coccolithophore, Cricosphaera carterae. Although therefore we may know but little concerning the precise concentrations of nitrate and phosphate required, the history of the culture of phytoplankton diatoms and flagellates focuses attention on the absolute need for i;hese nutrients. From the classical work of Allen and Nelson (1910) to the highly specialized techniques of Provasoli and his school, the successful culture of phytoplankton organisms depends inter alia upon a relatively high concentration of nitrate and phosphate. Moreover the mass culture experiments carried out by Ketchum and Redfield (1938) and by Ketchum (1939), as well as the field fertilization e~periinents~of Gross et al. (1947, 1950), Raymont and Adams (1958) and Anriell et al. (1963, 1964), all point to the importance of nitrate and phosphate in primary production.

138

J . E. 0.R A Y M O N T

Under culture conditions it is possible by varying the amounts of nitrate and phosphate in the medium to affect to some extent the composition of the phytoplankton crop. However, Redfield (1934) showed early on that the N:P ratio in the sea approximates by atoms t o 16: 1, and though there are considerable variations in parts of the ocean, the average phytoplankton in the oceans maintains the same ratio. In a recent review Redfield, Ketchum, and Richards (1963) have shown that despite low N: P ratios which may occur in Long Island Sound and south of New York, the ratio in the phytoplankton still keeps fairly constant until extremely low nitrogen values are reached. Jeffries (1962) has also called attention to remarkable variations in the N : P ratio in polluted estuary waters, but phytoplankton composition remained probably near normal. I n nature therefore it seems that the algae assimilate only as fast as the limiting nutrient is regenerated, and marked variations in the N:P ratio of the phytoplankton are unlikely. The remarkable growth of marine phytoplankton at such great dilutions of all nutrient requirements as normally occur in the sea is partly explained by the microscopic size of the phytoplankton cells, which allows better diffusion of nutrients and also confers a vastly greater surface to volume ratio, thus promoting absorption. It is likely, however, that to some extent the variations in the size of phytoplankton species, and even within a species, are related to nutrient requirements. Braarud (1962) suggests that Rhizosolenia styliformis and Thalassiothrix longissim are mostly oceanic species of relative large cell size which require favourable nutrient conditions. With the more coastal diatom Skeletonem costatum, under satisfactory nutrient conditions there is rapid cell division, followed by auxospore formation, which maintains a relatively large cell size. As nutrients are used up, however, the cells diminish in size and tend to sink; spore formation then commonly follows. Margalef (1958) has also studied the succession of phytoplankton forms with particular reference to average cell size. He believes that in a spring burst, growth commences mainly with small cell diatoms which are capable of rapid division, but these are succeeded by medium-sized species and finally by an increasing proportion of the motile phytoplankton forms with a lower rate of division. One factor in this “size succession” is believed to be changing nutrient concentration.

Miw Nutrients So far only what are frequently called the major phytoplankton nutrients, nitrate and phosphate, have been considered. Largely as the result of laboratory experiment, it has become increasingly obvious that a number of other elements normally present in trace concentrations in sea water are also easential to healthy plant growth. Iron, manganese, 5.

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copper, zinc, cobalt, and molybdenum are usually considered as such limiting trace elements. With the more crude culture media such as are used for mass cultures of marine algae, there are usually sufficient concentrations of these elements in the chemicals added, or in such materials as sterilized soil extract added to the cultures, to provide sufficient trace substances. However, where precise artiflcial media for the culture of marine algae are listed (e.g. Provasoli et al., 1957; Provasoli, 1963) small quantities of these elements must be added to the medium. Although culture experiments demonstrate that these elements are essential to the growth of phytoplankton, our knowledge of the concentrations of these elements in the sea, and even more of the spatial and temporal variations, is so limited that we cannot say whether they are ever limiting in nature. The position is corn plicated by the fact that some of these elements such as manganese and iron occur to a remarkable extent as particulate matter varying in size from colloidal aggregates to particles that may be retained by normal filtration. Indeed the amount of true ionic iron which can exist in sea water is extremely small, Algal cells can make use of some particidate forms, for example, of iron, and therefore the question of whether such elements ever become limiting is even more difficult. Silicon might be considered as a possible limiting nutrient in so far as it is essential to the growth of diatoms and to silicoflagellates.Normally silica is present in relatively considerable quantities, though even in the Antarctic where very large amounts exist, Ha& has reported the presence of exceptionally thin-shelled diatoms which may reflect a lack of silica over a short period of time. Silica, however, appears to be rapidly regenerated in sea water, and it is extremely doubtful whether it can ever be regarded as seriously limiting production. The possibility still exists that with iron, and possibly with manganese, aggregation of particles may occur in the upper layers of an ocean so that the element might sink and be lost to the euphotic zone. If' this depletion occurs at all, it will take place in nutrient-poor waters, especially in open oceans far from land. The experiments of Menzel, Hulburt, and Ryther (1962) in which Sargasso Sea water was enriched with nitrate, phosphate, and iron may be of interest here. I n short-term experiments iron as well as nitrate and phosphate appeared to be essential for growth of phytoplankton, but to some extent the result varied with the species of algae present. This raises the very interesting possibility that not only may phytoplankton algae differ in their minimum nitrate and phosphate requirements, but they may show differences with regard to their requirements for trace elements. For example, it has been suggested that Skeletonem has fairly high iron requirements, and indeed this mainly

140

J . E . G . RATMONT

coastal species may be limited to neritic regions partly on nitrogen and phosphate requirements, but equally on the relatively greater demands for trace elements. I n this connection Hulburt and Rodman (1963) have suggested that the sporadic blooms of neritic species in the open sea may be occasioned by the temporary presence of larger quantities of iron or some similar nutrient which normally limit their distribution. However, the experiments of McAllister et al. (1961) in which coastal plankton species bloomed successfully indicated that trace metals (Fe, Cu, Mn) were not limiting. It is probable that species have different trace element requirements. Jones and Haq (1963) believe that blooms of P h e o c y s t i s may depend on some minor nutrient. Tranter and Newel1 (1963) suggest that iron may be important in oceanic waters off Australia. Pintner and Provasoli (1963) state that trace metal requirements are excessively low for the chrysomonads. Johnston (1964) also believes that different species may have varied requirements. He has emphasized the great importance of trace metals such as iron, manganese, copper, and molybdenum; under special conditions in a few areas some of these elements may be temporarily limiting. Although in northern seas sufficient quantities of these trace metals are normally present, with the high pH of sea water they may be virtually unavailable to the phytoplankton cells. A chelating agent may therefore be of the greatest significance in making the metals available. I n the sea, organic acids present in great dilution may act as such chelating agents. This in turn focuses attention on dissolved organic factors in sea water. 6. O r g a n i c Requirements

Early experiments on the laboratory culture of marine algal species proved fairly conclusively that even when nitrate, phosphate and trace elements were supplied to the algae, growth was often impeded unless some organic constituents were also present in the water. Work over the last few years has shown an increasing number of organic substances which are mostly present at very low dilutions in the sea (cf. Hood, 1963) (Duursma, 1961). Although most of these are extremely difficult to identify, a recent review by Provasoli (1963) lists such materials as carbohydrates, amino-acids, fatty acids, organic acids, vitamins, and inhibitory substances as occurring in sea water. The variety of organic substances present in sea water is remarkable. Analyses by Tatsumoto et al. (1961) and by Park et al. (1962) have revealed some 17 or 18 amino-acids existing in surface and deeper ocean waters. The studies of Koyama (1962) showed not only a variety of amino-acids, but of carbohydrates, fatty acids, metallo-organic substances as well as vitamin compounds. Much dissolved organic material arises from the decomposition of planktonic and nektonic organisms.

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141

But some may arise from the excretion of planktonic organisms; Pomeroy et al. (1963) have called attention t o the importance of excreted phosphorus in production. Organic nitrogen (urea, amino-acids, etc.) typically forms a fraction of the excr1:ted nitrogen of marine animals. But organic material is also liberated during the metabolism of phytoplankton algae, though Duursma (1!361) contends that practically all the dissolved organic matter in sea water is derived from decomposition and no clear evidence exists for appreciable quantities being liberated. Apart from highly toxic materials liberated in the growth of species like Gymnodinium, Goniaulax, Prymnesium (cf. Gunter et al., 1948; Abbott and Ballantine, 19b7; Brongersma - Sanders 1957) which can affect adversely a wide range of animals, there are a number of algae which can favour or discourage the growth of other species by excreting growth-promoting or growth-inhibiting substances (cf. Jerrgensen and Steemann Nielsen, 1961). There are a number of investigations reporting the production of ext ra-cellular substances by marine algae. Collier (1953) described carbohydrate-like substances, apparently produced by algae, and later (1958) showed the production of carbohydrate-like substances by Prorocentrum and by Gymnodinium breve. Guillard and Wangersky (1 958) demonstrated the production of soluble extra-cellular ca,rbohydrates by a variety of flagellates, the amount released being highest in stationary c r declining cultures. Curl and McLeod (1961), studying the culture of Skeletonema, suggested that extra-cellular substances are produced a t certain stages of growth. Parallel work with fresh water algae such as that of Fogg and of Proctor (1957) indicates that nitrogenous cirganic materials, carbohydrate-like substances and lipids produced by algae may be liberated into the water. Many workers have suggested chat the secretion of these substances tends to occur when algae are becoming somewhat unhealthy, especially during intensive blooms. While there is considerable evidence that this is true for many specie,3, Fogg (1963) advances strong arguments for the view that some excretion of material occurs during normal healthy growth of both fresh .water and marine algae. Indeed, Fogg criticizes the 14Cmethod for estimating primary production by suggesting that an appreciable propclrtion of the fixed carbon may appear in soluble form in the filtrate, quite apart from losses from the breakage of cells during filtration. The recent experiments of Antia et al. (1963), using the plastic sphere technique, have confirmed a considerable excretion of organic matter by healthy algae. Fogg draws particular attention to the importance of glycollic acid in algal metabolism; his experiments suggest that quite an appreciable amount may be released during active photosynthesis of phytoplankton. Though this may introduce errors in calculating the primary production, it should

€42

J. E.

a. RAYMONT

be noted that some of the glycollate released may be used by bacteria to synthesize particulate matter, thus contributing to production as a whole. The possibility also exists that algae may themselves absorb such extra-cellular substances and use them in synthesis. A moat interesting related observation by Smith et al. (1960) is that carbaminocarboxylic acids may be used as a carbon source by phytoplankton, apparently even preferentially by Nitzschia. Similarly, Parsons and Strickland (1962) have commented on the limited heterotrophy of algae. Although in their work uptake of such dissolved organic carbon as glucose and acetate was due to microorganisms, such as bacteria, we know that limited uptake of carbon compounds can occur in algal groups. Thus Lewin and Lewin (1960) and Lewin (1963) showed that different diatom species show marked differences in their heterotrophic abilities; some can utilize such organic carbon as glucose and lactate, though generally their heterotrophic powers appear to be rather limited. Among the flagellate chrysomonads, however, Pintner and Provasoli (1963) showed that an array of organic acids as well as carbohydrates may be used as carbon sources, though specific differences again are evident; Coccolithus huxleyi, for example, shows very little ability to utilize organic carbon. These same authors noted that glycero-phosphate may be used in place of orthophosphate. As regards nitrogen, such substances as adenylic acid and a range of amino-acids may be employed by these flagellates, though these substances appear to be inferior to inorganic nitrate. Guillard (1963) had shown that some diatoms and unicellular flagellates could make use of organic nitrogen (amino-acids, urea, uric acid) in bacterial-free culture, and Provasoli and McLaughlin ( 1963) demonstrated limited utilization of dissolved organic nitrogen by dinoflagellates. At first sight it might seem that this limited heterotrophic ability of phytoplankton is unimportant in the oceans, but it must be remembered that the amount of dissolved organic matter, relatively, is very large in sea water. Provasoli (1963) suggests that it may be some 7 to 8 times the amount of particulate matter in the euphotic zone, where the plankton is, of course, relatively rich; in deep waters the dissolved organic matter may approach 1 000 times the particulate matter (cf. Duursma,, 1961). Parsons and Strickland (1962) suggest that the average amount of dissolved carbon in .sea water is about 1 g/m3,but in surface waters and near land the concentration may be 5 to 10 times greater. Despite the earlier work of Krogh (1934) which suggested a mean value of > 2.OgC/ m3 and that the amount of dissolved organic matter was relatively stable in the oceans, there appear to be considerable variations both horizontally and vertically. Duursma (1961) finds lower values in the northern Atlantic; few areas exceeded 1.0 gC/mS,but the upper layers

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143

showed considerable seasonal variations. Values quoted by Provasoli (1963)include 2.8-3.4 g C/m3for the Black Sea with a marked seasonal variation, and up to 4.(igC/m7in the Ihltic. Inshore regions may have very high values; even 8.0g C/mJ in the Wadd:n Sea (Duursma, 1961). If photosynthetic organisms can make use, a t least temporarily, of some of this vast reserve of dissolved organic substance, it can play a significant part in particulate production. Eut the possible heterotrophic powers of phytoplankton must be also considered in relation to the important observations of Bernard (19!i3; 1963), Bernard and Lecal (1960) and of Kimball et al. (1963) that considerable populations of photosynthetic organisms may apparently exist in some seas, such as the Mediterranean and parts of the Indian Ocean, a t depths well below the euphotic zone. Many of these algae are not dying populations which have descended into the deep layers, but are in healthy condition and are actively living at these depths. Wood (1963a and c), Bernard, as well as Kimball et al., have all suggested that such organisms must be living heterotrophically at such great depths. Though coccolithophores often tend to dominate these deeper-sea populakions, other algal groups, diatoms, flagellates, and dinoflagellates, are also represented. Especially in such seas where primary production in the euphotic zone may not be very high, and therefore the amount of particulate matter reaching deep water may be much reduced, productioi due t o this deep-living phytoplankton may be extraordinarily significant to the whole economy of the deeper layers. Apart from the possibility that some pl1,ytoplankton may utilize dissolved carbon and nitrogen, certain species are known to have definite demands for specific organic constituents. Organic substances may be important as chelating substarices m d a number of marine phytoplankton forms are now known to have specific vitamin requirements. Among the many growth-promoting and growth-inhibiting substances in sea water, Belser (1959) demonstrated 10 growth-promoting substances on a marine bacterium of which three, biotin, uracil, and isoleucine appeared frequently in sea water s#tmples.Other substances have been recently assayed (Belser, 1963). Collier (1953) and Wangersky (1952)both reported the presence of ascorbic acid in sea water, and later studies by Collier et al. (1956) suggested that nicotinamide as well as ascorbic acid could affect the growth of marine species. Harvey (1955) suggested that cystine was necessary for the growth of some diatoms, and Provasoli et al. (1957) indicated that divalent sulphur is probably necessary, a point which has also been recently taken up by Curl (1962a) for the growth of Skeletonenza. Wood (l”963b) lists several organic substances which influence photosynthesis and growth of flagellates and diatoms. At this stage we crinnot list all the organic

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J . E. G . RAYMONT

compounds which may be present in sea water and which may promote the growth of phytoplankton, but three vitamins (cobalamine or vitamin B,,; thiamin or vitamin B,; and biotin) appear to be of more general significance to a number of species (cf. Belser, 1963). The main producers of these vitamins are marine bacteria, but some algae apparently synthesize vitamins; the red algae are often especially rich, though there is some question as to whether these are not really accumulated by these macrophytes (Provasoli, 1963). Kanazawa (1961) records a considerable list of vitamin B complex from algae. The very fact that some algae can synthesize vitamins underlines the point that phytoplankton species differ greatly in their precise requirements even for these three vitamins. Since also it is only by most careful culture techniques that we can test for vitamin requirements, it is not surprising that specific needs are known only for comparatively few phytoplankton forms; the oceanic phytoplankton is particularly unknown in this regard. As regards vitamin B,,, the work of Provasoli and his colleagues (e.g. Provasoli, 1958), of Droop (1957) and others, as summarized by Provasoli (1963), suggest that a number of dinoflagellates and some diatoms (e.g. Xlceletonema) all require vitamin B12. On the other hand, some algae such as Rhodomonas, Dunaliella, Nannochloris, and Phaeodactylum do not require the vitamin. Presumably they synthesize it from simpler substances. Species which require B,, show considerable differences in their ability to grow successfully with various analogues of this vitamin; how far such analogues occur in the oceans is unknown. Differences in the spatial concentration of B,, or temporal variations might, however, limit production. Investigations by Droop suggested that a considerable amount, probably sufficient for the needs of the algae, were present in inshore waters (5-10 mpg/l), but work by Cowey (1956) in the North Sea and the Norwegian Deeps indicated that while this order of concentration might be present in winter, in summer the concentration fell to 1/10 of the value. Daisley and Fisher (1958) also showed for the Bay of Biscay that the euphotic zone had only about 0.6 mpg/l as against about 4 times that value at intermediate depths (from 200-2 000m). For the Sargasso Sea, Menzel and Spaeth (1962) found only up to 0.1 mpg/l of vitamin B,, in the upper layers with some seasonal variation; below 200m the concentration of about 0.2 mpg/l. was relatively constant. Several authors therefore (e.g. Provasoli, 1963) doubt whether sufficient B,, is always present for phyDoplankton, especially in the open sea. Skeletonema as a main spring diatom has been observed to reduce the vitamin B,, content of waters in Long Island Sound appreciably, though the amount there is relatively large (cf. Vishniac and Riley, 1961). Antia et al. (1963) obtained evidence

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for considerable utilization of vitamin B,, in their culture experiments, but biotin did not appear to be used. The work of Guillard and Cassie (1963) suggests that phytoplankton B,, requirements may be slightly greater than was first considered. Thus they find minimum needs for both neritic and oceanic forms of about 5-18 molecules of B,, per cell, as compared with 3 per cell suggested by Droop. These authors make the interesting suggestion that B,, may be required by some phytoplankton species only a t a particular stage in their life history; for example, by Skeletonema at auxospore formation. The absolute requirement for thiamin varies also from species to species of marine phytoplankton. For example, Phaeodactylum and Nannochloris, which do not require B,,, do riot need thiamin. On the other hand, Skeletonema, which requires B1,, citn grow without the addition of thiamin. Pintner and Provasoli (1963) found that chrysomonads generally required B, rather than BIZ.A sum :nary of the requirements of various algae for B12,thiamin and biotin as given by Provasoli (1963) is seen in Table 111. Vishniac and Riley (1961) found only barely detectable amounts of thiamin, in contrast LO B,,, in the more open water of Long Island Sound; such small concentrations could limit the growth of species unable to synthesize the vitamin. We lack knowledge, however, of the variations in concentration of growth promoting substances in the oceans and of the precise nutrient requirements of individual species so that it is not possible to imsess their exact role in primary production. It seems likely that at times insufficient amounts may be present, at least in the open sea far from land. The requirements of neritic species also probably exceed that cbf most oceanic forms (cf. Hulburt, 1962; Hulburt and Rodman, 1963) and, more generally, the vitamin requirements of planktonic species probably play an important part in spatial and temporal succession. The whole array of dissolved organic substances may be of significance in this connection. The production of extracellular substances imposes a biological history on the water, and Lucas (1947, 1955, 1961) in particular has called attention to the great importance of this biological conditioning to both phytoplankton and zooplankton. Several studies of species succession have included conditioning of the water as one factor. Lillick (1940), for the Gulf of Maine, thought that subtler differences due to conditioning of the water were responsible in part. Conover (1956), describing a rather simila,rstudy of seasonal succession in Long Island Sound, stated that conditioning of the water was an important aspect of the species succession, and suggested that Schroederella was particularly favoured by the products of blooming of earlier species. Margalef (1958) has also called attention to t’he importance of external metabolites. He describes three main phases i n a species succession, the

Sunant any algal group

TABLEI11 of Vitainin Requirements of Fresh- Water and iWari?ze Algae (from Procasoli, 1963)

Number of species

KO vitamins

Require vitamins

B,,

Thiamine

68 9

24 0 0 1

10 2 2 11 2 11 1 4

8 1

Chlorophyceae Euglenineae Cryptophyceae Dinophyceae Chrysophyceae* Bacillariophyceae Cyanophyceae Rhodophyceae Totals

22 39 10 4

21 9 0

44 9 11 16 21 18 1 4

180

56

124

11

17

Totals for single vitamins *Two chrysomonads require Blr

+ biotin

1

Biotin

+

B,, thiamine

3

26 6 7 0 9 4

43

18

52

103

78

1

5

10

+

+

Biotin B,, biotin thiamine thiamine

+

1 1

4 2

2

6

THE PRODUCTION OF MARINE PLANKTON

147

third consisting mainly of more slowly dividing motile algae characterized by species with metabolites of high toxicity. He suggests that these phytoplankton species havc n relatively high immunity to these toxic substances. It has long been recognized that in a given region, inshore areas usually show greater production and standing crop than more oceanic areas. The difference is normally attributed to the more turbulent mixing of coastal regions assisting in the replenishment of essential nutrients in the euphotic zone (vide infra). But examples were known when even though nitrate and phosphate were relatively plentiful, inshore areas displayed increased production. Bran (1931) suggested that coastal regions might benefit from other micronutrients brought down by land drainage. I n the Antarctic where phosphate and nitrate is abundant, Hart (1942) noticed that neritic areas, which could stretch out to a considerable distance from land, showed greater production. He suggested that the important factor might be micronutrients, such as trace metals, which were carried out from che land. It may well be that an organic growth-promoting substance, rather than a trace element, is in part responsible for this beneficial neritic influence. To some extent a similar condition is found at the boundaries of ocean currents. For many years it has been widely recognized that standing crop and productivity tends to be higher at current boundaries. Undoubtedly part of this increased production is due to extra nutrients which are made available in the euphotic zone in such areas. But even in situations where there is no nutrient lack or appreciable difference in concentration, a marked improvement in production is often found in areas of water mixture. The so-called “island effect” is possibly explained on the same hypothesis. This effect (e.1;. Doty and Oguri, 1956; Jones, 1962) is a tendency to an increase in primary production and also to a genera1,rise in standing crop of plankton in the regions round oceanic islands. Jones found, for example, an increase in plankton crop to a distance of nearly 200 miles from the Marquesas Islands. Although increased nutrients such as nitrate and phosphate can certainly occur around oceanic islands, it seems impossible from Jones’ results to explain the increased plankton as due to nutrient level at such a distance from the island. The presence of an increased concentration of a trace element such as iron, or equally likely, of a mi cronutrient organic substance draining from the regions of the islands, seems a more probable explanation.

c. PRODUCTION - TEMPERATURE A N D STRATIFICATION In tropical regions the small variation in light intensity over the year means that the euphotic zone is more or less constant in depth. On the

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J . E . G . RAYhZONT

other hand, in temperate and high latitudes the change in the compensation depth from winter to summer is very appreciable. An indication of the steadily rising amount of light energy reaching increasing depths of the sea in a temperate latitude from January to June is given in Table IV. The rate of primary production must be markedly reduced at such latitudes during the winter owing to the shorter day and the very much reduced light beneath the surface ; the compensation depth is so near the surface that only the uppermost stratum can be actively photosynthesizing. But owing to turbulence, the algal cells may easily be carried out of this surface layer, and in the subsurface layers light penetration is no longer effective. Thus primary production is nonexistent except for the surface itself. In the absence of turbulence, algal

TABLEIV Average Energy in gcallcm2/day in Lat. 52" N , January to June, reaching the Surface and Reduced by the Energy Extinction Coeficient of Coastal Water (Type 1 of Jerlov, 1951) (after Cushing, 1959)

Surface l m 5m 10 m 20 m 30 m

Jan.

Feb.

18-98 7 -00 2-70 1.12

44.91 16.57 6-38 2.65

March 92-09 33.98 13.08 5 *43 1-20

April

May

164.25 60.61 23-32 9-69 2.14

219.20 80.88

31-13 12-93 2-85 0.66

June 242.06 89.32 34-37 14.28 3.15 0~~73

cells might be confined to the surface and thus there might be even during winter at least a surface blooming of phytoplankton. Even with the increase in light during the spring, the vernal blooming of phytoplankton, which is such a conspicuous feature of temperate and high latitudes, is dependent to a large extent on how far turbulence is active in the region. Normally some degree of stratification of the water is essential to reduce the passage of algal cells from the relatively shallow photosynthetic zone. Riley (1946) in particular has stressed the importance of stratification in initiating the spring increase in temperate latitudes. For the Gulf of Maine, Riley has demonstrated a direct correlation between the phytoplankton rate of increase and the stability of the water column (Fig. 5 ) . This stability of the water depends to a large extent on temperature conditions insofar as warming of the surface layers will cause them to become less dense, so restricting mixing with underlying layers. Stability therefore tends to increase in the spring with rising temperature, and thus it is possible to establish a correlation

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149

in higher latitudes early in the spring between the rate of primary production and temperature increase. Although! therefore, temperature may have little or no direct effect on phytoplankton production, it plays a most important part in stabilizing water layers. Slight reduction in surface salinity may also play a part in stabilization, and some of the more marked production (of coastal shallow water can be attributed to this increased stability (cf. Braarud and Klem, 1931; Gross et al., 1947; Marshall and Orr, 1948:. Under such conditions phytoplankton production may be possible during the winter but it is

-

I Depth

FIG.5. Estimated mean daily rate of phytoplankton increase during March-April in relation to the reciprocal of depth of the zone of vertical turbulence; (redrawn from Riley, 1942).

restricted to an extremely shallow surface layer. I n parts of the Baltic reduced salinity of the upper layers produces this stability throughout the year so that production of phytoplankton may also continue over winter months (cf. Steemann Nielsen, 1935; 190-0).Recently Steemann Nielsen (1964b)has studied in some detail two areas in the Baltic which show different rates of primary production. I n the Kattegat the rate at the surface was remarkably stable over much of the year, at least for the period, March-November; light appeared to be a limiting factor for the surface algae only during the very darkest months of December and January. At greater depths, light was a limiting factor throughout many months of the year. The relatively efficient praduction and the maintenance of a fairly even rate at the surface was m.ainly due to the marked stratification which prevented algal cells from being carried away from the lighted surface. By contrast in the Great Belt region, stratification waa less strong, and with the greater degree of mixing, production over the year was much less constant; even at the suIface illumination could become a limiting factor over a considerable period of the year. The importance of light penetration in relation to the depth of the P

150

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a. RAYMO NT

mixed ( i t . unstratified) water layer has been emphasized by Riley (1942-46) and also by Sverdrup (1963). Sverdrup has used the term “critical depth”, which may be defined as the depth above which the total photosynthesis is equivalent to the total respiration per unit of surface. In a thoroughly mixed upper water layer it might be assumed that the plankton cells were practically evenly distributed; production would therefore decrease logarithmically with depth since light decreases logarithmically, but respiration will be approximately constant with depth (cf. Fig. 6). For effective production, there must be a critical

d 2 4 1 2 1 4

0

6

8

10

Relative photosynthesis

PIG.6. The relation between total photosynthesis and respiration in a column of water. Total photosynthesis is shown for three dates: A in summer with bright sunshine; B in summer with cloud; C in winter; (modified and redrawn from Ryther. 1966).

depth which must exceed the thickness of the mixed layer. I n the Norwegian Sea, Sverdrup demonstrated that the spring increase in phytoplankton occurred in early April, and that the period coincided with time of increasing stabifity, so that the mixed layer was only about 50-100m depth, whereas the critical depth exceeded 100m. Kalldal (1953), investigating the phytoplankton seasonal changes in the Norwegian Sea, states that a fairly early spring growth commences with increased light penetration, but that the considerable mixing of the water layers prevents a real increase of phytoplankton until May/June when stability is established. The main growth (June/September)

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151

appears to coincide with the period of stability. Holmes (1956) finds for the Labrador Sea that from November to April there is very little phytoplankton with the marked instability of the water column. Over the May/June period, increasing stability rtnd increased radiation apparently are mainly responsible for the phjtoplankton peak. In the Arctic waters off Bear Island, Marshall (19,58) showed that during March/April the mixed layer shallowed to less than the critical depth and effective production of phytoplankton commenced, whereas in the warmer Atlantic water nearby, the mixed layer only became shallower than the critical depth by about May and June, and phytoplankton production was correspondingly delayed. At these high latitudes the stability of the water in late spring may be due in part to the melting of ice; the phytoplankton outburst in polar regions frequently seems to follow the melting ice edge (cf. Braarud, 1935; Hart, 1934). Zenkevitch (1963) also mentions that in Arctic seas the algal bloom follows the ice melt and believes that this is due t o the importance of critical depth exceeding the mixed turbulent layer. The vernal blooming of phytoplankton, while mainly due to increasing light intensity and length of daylight, is tlius dependent to a considerable extent on stabilization. Some of the cliscrepancies in the time of commencement of the spring increase, observed by many workers (e.g. Kreps and Verjbinskaya, 1932; Corlett, 1953; Conover, 1956; Fish, 1925; Bigelow et al., 1940) may be explained as due to differences in stabilization of the water column. Strong winds will reduce stability; thus shelteredareasmay bloom earlier than exposedregionsat similarlatitudes. The continued rise in temperature during late spring and early summer in temperate regions causes increased stratification of the water, so that typically a marked seasonal thermocline exists over the summer. I n normal seas this thermocline restricts the continued supply of essential nutrients to the euphotic zone where they are being extensively utilized. Reduced surface salinity with a stable water column may also be detrimental to nutrient replenishment later in the season when nitrogen and phosphorus have been extensively utilized, and thus may lower productivity. Steemann Nielsen (1 958) has shown that in coastal areas off Greenland, zones of very low piioduction are associated with lowered salinity surface water which prevents the vertical transport of nutrient rich water from below. Where there is considerable mixing of the water layers, a high production follows. Anderson (1964) refers to the outflow of the Columbia River off the M’ashington and Oregon coasts, producing a permanent halocline. This may effectively reduce the thickness of the mixed layer in winter, but in summer, with the addition of a seasonal thermocline, may act ;LS a barrier to vertical movement of nutrients.

152

J . E.

a. RAYMO NT

When such density differences restrict vertical transport of nitrate and phosphate to the euphotic zone, regeneration processes in the photosynthetic stratum itself may be of the greatest significance, in that excretory material and some organic detritus can be converted relatively rapidly to inorganic phosphorus and nitrogen, mainly as ammonia, so keeping some phytoplankton growth continuing. Rates are the major factors and there appears to be variation between nitrogen and phosphorus regeneration (cf. Harris, 1959; Vaccaro, 1963; Pomeroy et al., 1963; Hoffman, 1956; Menzel and Ryther, 1964; McAllister et al., 1961; Antia et al., 1963). Nitrate regeneration appears to be especially slow. In any event, regeneration usually is insufficient, and with the restriction in vertical transport of nutrients, a reduction in primary production typically occurs during the summer months. With the autumn breakdown of the seasonal thermocline and the consequent increased supply of essential nutrients to the euphotic zone, an increased production again leads to the so-called “autumn peak”, but this is usually short-lived owing to the rapidly decreasing light. Too often this picture of a spring and autumn peak in phytoplankton with a smaller and variable production over summer (cf. Fig. 7) has

lee. I Jon.

-

I Feb. I Mar. 1 Apr. I May 1 June 1 July I Auq. 1 Sep. I Oct. 1 Nov. I Dc

FIG.7. Diagrammatic representation of the seasonal cycles in light, nitrate and phosphate, and phytoplankton in a typical northern temperate sea. (Reprintedfrom Plankton and Productivity in the Oceans, Raymont 1963, Pergamon Press).

been based on estimates of standing crop of phytoplankton rather than on rates of primary production, though the few seasonal estimates of productivity such as those of Ryther and Yentsch (1958), Anderson (1964), Steele (1958) and Steele and Baird (1961) confirm the high rate in spring and the lowering of rate in summer. The large densities of zooplankton over summer may reduce the phytoplankton standmg

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crop very greatly, although primary production is continuing at a very high level, so that crop estimates may give misleading impressions of production (vide infra). There is a marked tendency at higher latitudes for the spring increase to occur much later, for example, in May or June as recorded by Gran (1931), Steemann Nielsen (1935), Kreps and 'Jerjbinskaya (1930), and Gillbricht (1959), in the Arctic. Digby (1953) did not obtain any appreciable phytoplankton production until May o f eastern Greenland; the peak density occurred in July, with a smaller scxondary peak in August, but the whole production was finished by September. Corlett (1953) also shows differences in timing of the spring diatom outburst with latitude in various oceanic areas of the northern Atlantic. I n the Labrador Sea, Holmes (1956) finds the double peak in phytoplankton production; until March there is virtually no algal growth owing to the marked instability of the water column and the poor light conditions. The spring peak occurs about May and June, a,nd there is a smaller rise in September. Zenkevitch (1963) has summarized the position for the Arctic: the nearer to the Pole, the later becomes the vernal outburst and the more rapidly is it over. In the Circumpolar Ocean, for example, the phytoplankton burst lasts hardly more than one month (August);in the Laptev Sea the outburst lasts from the end of June to about the end of September. On the other hand, in the most southern of the sub-Arctic seas, the south-western Barents Sea, the period of phytoplankton growth may approach 8 months (April to October/November), and there is a typical spring and smaller autumn bloom. In. the Antarctic, Hart (1934, 1942) has also shown that the timing of the spring increase becomes later as one proceeds farther south. Not only does the outburst become later, but the amount of time during which diatom growth proceeds becomes shorter until at the highest latitudes there may be only one short continuous burst of phytoplankton production. Although typically in north-western Europe and the north-eastern American coast the spring increase is about March, the phytoplankton flowering may occur earlier; for example, Ccmover (1956) and Riley (1952) found an increase in early February in Long Island Sound and Block Island Sound, and Fish (1925) believes that at Woods Hole the increase is as early as December. This earlj flowering may depend partly on the sheltering of waters in these areas. Certainly the timing of the increase is not entirely associated with latitude. Thus Riley (1957) recorded for the North Sargasso Sea (latitude :35"N)a small diatom increase as late as April and this was confirmed by Hulburt et al. (1960) off Bermuda. However, Menzel and Ryther (1960; 1961) find slightly farther south that a winter flowering may occur in any month between November and April. I n contrast to temperahe latitudes, in tropical

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areas the small variation in light and temperature throughout the year tends to maintain phytoplankton production at a relatively constant level. Normally in tropical regions, the thermocline is permanent, and therefore there can be little effective nutrient replenishment and little variation in nutrient level in the euphotic zone throughout the year. At all times, nutrient level is low and regeneration inside the euphotic zone is a most important factor in the maintenance of primary production. Regions of upwelling or of current divergences are, of course, exceptional in that nutrients are brought near the surface and production tends to be high. Apart from these regions, however, there may be areas in warmer seas where the relatively small differences between “summer” and “winter” temperatures are sufficient to cause further stratification of the upper layers and the establishment of a seasonal thermocline. If the cooling of the uppermost strata is sufficient and there are also strong wind effects, some mixing may occur in the cooler months leading to a small winter flowering of plankton. Menzel and Ryther (1960; 1961) found areas of the Sargasso Sea near Bermuda where such a winter blooming might occur depending on the degree of vertical mixing. Maximum production occurred when the upper water . was practically isothermal to ca. 400m, approximately the depth of the permanent thermocline. When over the summer months a seasonal thermocline was evident at about 100m. depth, production was reduced (cf. Steele and Menzel, 1962). Hulburt et al. (1960) suggest that the April flowering near Bermuda may be three or four times that of the autumnlwinter level of production; summer production is even lower. Farther south, in tropical waters, the stratification of the uppermost layers is permanent; mixing cannot occur appreciably even throughout the euphotic zone and so a winter blooming does not normally occur. There is a tendency therefore in tropical areas for there to be relatively little change in phytoplankton density over the year. Corcoran and Alexander (1963) have suggested that there is little seasonal cycle in Florida current waters, though they have recorded occasional high levels of production and crops reaching even 0.5 mg chlorophyll alms. Cushing (1959a and b) has pointed out from the results of earlier workers such as Riley et al. (1949) and Bernard (1939) that for the Sargasso and Mediterranean a slight seasonal fluctuation in phytoplankton crop with a more productive season in winter may be evident. But close to the Equator the productive season is perhaps even earlier and the seasonal fluctuations are less. Cushing suggests a seasonal amplitude of 5 times for the Sargasso Sea, whereas a fluctuatior, of some 50 times might be true for higher latitudes. Zenkevitch (1963) has pointed out that although very high crops of phytoplankton can occasionally be found in the coldest Arctic waters,

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this is not necessarily a true estimate of productivity. He suggests using an index which averages the crop to a depth of 30m, and takes into account the duration of the phytoplankton increase in months, relative to the whole year. The index is: mean crop (0-30m) x duration of flowering (months) _ _ ~ ~ _ _ _ _ _ _ _ _ ~

12

Using this index he shows that for the Arctic basin the biomass may be only one-twentieth that of the northern I3arents Sea. The factors responsible for this low production are fairly obvious. Although in seas north of Siberia the low surface salinity may impede circulation and reduce productivity, in the Arctic Ocean proper it is essentially the thick ice cover, which does not permit phytoplankton growth for some 10 months of the year, which is mainly responsible. Even the northern Barents Sea is far less productive on this annual basis than a warm temperate area. Zenkevitch includes an index based on this same formula for the Sea of Azov, a warm temperate area which being largely enclosed, has a high productivity. But the rich ;$owth of phytoplankton also ccntinues for between 9 and 10 months of the year, so that the index of production for the Sea of Azov is some 15 times that of the northern Barents area.

111. THESTANDINQ CROP OF PHYTOPLANKTON These estimates of Zenkevitch really represent an average biomass of plankton over the year; they are therefore estimates of standing crop rather than production. Reference has already been made to the difficulty of estimating standing crop; one widely used method is chlorophyll concentration although we have already noted some of the errors in this technique. Earlier methods for estimating standing crop were almost all based on counts of phytoplankton cells. These were collected mainly with the finest silk nets, which though rihowing some variability in porosity, have an average pore size of 40p x 5Op. But apart from variations in mesh size due to manufacture, to the degree of wetting, to age and strain, such nets will clog to varying degrees depending on the concentration of phytoplankton and detritus They will therefore in effect vary greatly in catching power. but in any event a large number of the finest photosynthetic organisms (below 50p) will normally pass through them. The term nanoplarikton has been given to these very small photosynthetic organisms which normally escape the finest nets, and it has become obvious, especially in the last 20 or 30 years, that the nanoplankton may make a significant contribu1;ion to the standing crop and indeed to production. The nnnoplanktoii plants belong to a variety of algal groups; some

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are small diatoms or dinoflagellates, but others belong to the Chrysophyceae, Chlorophyceae, and Cryptophyceae. Various methods have been used to try to estimate nanoplankton densities; for example, the fixation of samples of sea water, followed by sedimentatiQn and counting with reversed microscope; centrifugation; filtration through hardened filter papers or through membrane or sintered glass filters. All such methods have disadvantages. Many of the delicate cells are destroyed by fixation and by centrifuging, and cells cannot be adequately counted if they are first filtered. Counting of unconcentrated samples is equally unsatisfactory. Although, therefore, we have no single method which estimates nanoplankton adequately, it is abundantly clear that the use of fine silk nets to estimate the phytoplankton as a whole is entirely misleading as a quantitative method. Contributors to a recent symposium on primary production have indeed stated that net samples alone should no longer be employed for quantitative estimation (Braarud, 1958). The chlorophyll extraction method probably gives a fair indication of the standing crop of phytoplankton under most conditions, since provided a suitably fine filter is employed, both nanoplankton and larger phytoplankton will be captured. But the imperfections of the chlorophyll method (see page 124) must still be taken into account. A comparison of the density of the nanoplankton and of the remainder of the phytoplankton, often termed the “net” phytoplankton, shows that nanoplankton may be sometimes important in certain regions. In more inshore waters at temperate latitudes the net phytoplankton, especially diatoms, is frequently dominant over much of the year, but Lohmann (1908; 1911) showed that the nanoplankton could be very important at certain months. Harvey (1950) for the English Channel found a very much larger crop by filtration estimates, which included nanoplankton flagellates, as against fine net samples which would normally retain only the larger phytoplankton. Gross et al. (1947, 1950) found that the nanoplankton could form a very appreciable part of the crop in shallow temperate waters. Yentsch and Ryther (1959) have also called attention to the importance of the nanoplankton fraction in the waters off Woods Hole. Small flagellates have been recorded in considerable numbers in the North Sea (Gramtved, 1952) and in the Baltic area (Steemann Nielsen, 2951). The same author (1935) has recorded nanoplankton flagellates in cold seas, as did Braarud (1935) around Iceland, and Halldal (1953) found appreciable numbers of coccolithophores and flagellates in the Norwegian Sea (cf. also Bursa, 1963). More generally at high latitudes it is the larger diatoms which tend to dominate the phytoplankton. Although much of the earlier work at high latitudes did not specifically estimate nanoplankton but relied on

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net hauls, more recent work such as t,hat of Burkholder and Sieburth (1961) indicates that in the waters of Antarctica diatoms are probably all-important; the only other organism which bulked large in the phytoplankton was Phaeocystis. It is perhaps in the warmer seas that the nanoplankton algae, including the coccolithophores, become of particular significance. The investigations of Lohmann and of Bernard (1953) in the Mediterranean, of Riley (1957) for the Sargasso Sea and of Bsharah (1957) for the Florida Current call attention to the importance of nanoplankton in warmer waters. Hulburt, Ryther, and Guillaxd (1960) report on the prevalence of coccolithophores in waters off Bermuda; though the nanoplankton was not quantitatively measured, small coccolithophores, flagellates and other nanoplankton forms made a considerable contribution to the total crop. Hulburt (1962), dealing with the tropical north Atlantic finds that small flagellates and coccolithophores are fairly regularly distributed in these warmer waters together with diatoms and dinoflagellates. Wood (1963a) considers that the nanoplankton generally becomes increasingly important in tropical seas, although there are exceptions, such as a considerable abundance of diatoms occurring off the Australian coast, end also off the western coast of India. On the other hand, north and south oS the subtropical convergences, and above all, at really high latitudes, especially south of the Antarctic Convergence, diatoms become all-important. A comparison between the nanoplankton and larger net phytoplankton has recently been made by Teixeira (1963) and Teixeira and Kutner (1963) for Brazilian waters. In the shitllow lagoon waters, the net plankton, consisting mainly of large diatoms, comprised only about 3% of the total which was dominated by the nmoplankton; but even in offshore waters up to 400 miles from the coast the dominance of the nanoplankton was still very clear, with the net plankton contributing less than a fifth to the total standing crop. A f13wnanoplankton species seem characteristic of polluted waters with high organic content (e.g. Ryther, 1954), but in general these very small algae are particularly adapted to oligotrophic waters where they may contribute considerably to the overall production. Thus in Teixeira's investigations, it appeared that the net plankton contributed only 10% to total photosynthetic activity in offshore waters when the 14Cmethod. was used.

IV. PHYTOPLANKTON CROPAND ANNUAL PRODUCTION The size of standing crop is a most significant factor in total production since rate is reckoned as the amount of cai-bon (or organic matter) synthesized per unit of carbon (or organic mcitter) present as phytoplankton. I n general, as Steemann Nielsen has pointed out (1958b; 'F

158

J. E . ct. RAYMO NT

1963), arms of high standing crop tend to have fairly high productivity rates (cf. Holmes, 1958, 1962; Bogorov, 1958). High latitudes tend to have very high plankton productivity for a short period of the year. Boreal regions also usually have a higher standing crop and productivity; Bogorov (1958) states that in the Pacific, the boreal area is some 10 times richer than tropical waters (cf. Holmes, 1958). The earlier work of Hentschel and Wattenberg (1930) also associates the distribution of phosphate in the southern Atlantic Ocean with the richness in density of plankton organisms. In relation to total production the standing crop under a square metre of sea surface is of importance. Riley et al. (1949) suggest that in the offshore waters of the north-western Atlantic the total crop of phytoplankton beneath a square metre of surface at lower latitudes may not be very much smaller than that at a higher latitude, such as the Gulf of Maine, provided that the very short spring burst of phytoplankton in boreal waters, which may not be effectively utilized, is omitted from the calculation. One of the chief factors in calculating the crop beneath a unit of surface at different latitudes is the greater depth of the photosynthetic zone in more tropical areas. Riley’s comparison of the total annual crop in the Gulf of Maine area and in the continental slope water to the south-east suggests that the difference in biomass is not very great, largely owing to the greater depth of the euphotic zone in the more southern waters. With Sargasso Sea waters, however, the total population is probably lower even though the photosynthetic zone is greater. Ryther and Yentsch (1958) have shown that although offshore waters can occasionally show high rates of production which are comparable to inshore areas, these are due to temporary enrichment and are not sustained; production over a whole year is greater st inshore stations. Their suggestions for the annual production from the nutrient rich Long Island Sound waters to the impoverished Sargasso Sea are: gC/m2/year

Long Island Sound = 380 Shelf waters = 160-100 (depending largely on distance from coast) North Sargasso’Sea = 78. Ryther (1963) has summarized regional differences in annual productivity: (1) for tropical open oceans, production is 18-50 g C/m2,(e.g. Sargasso) though where some mixing occurs as off Bermuda the annual value may reach 70 g C/m2.

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(2) in temperate and subpolar waters rates arc! about 70-120 g C/m2.A t high latitudes very high rates may hold for E,hort periods (even up to 5 g C/m2/day)but the flowering period is short. (3) Antarctic production - approximately 100 g C/m2/year except for especially rich zones (e.g. South Georgia). (4) Arctic - very low production in true Arctic - perhaps < 1 g C/ m2/yearin Polar Sea.

Apart from very shallow, highly productive inshore areas, continental shelf waters do not exceed offshore regions at the same latitude very greatly. The timing of the phytoplankton cycle may be strongly affected, and the crop per unit volume is far higher. Both Anderson (1964) and Teixeira (1963) suggest that productivity and standing crop are both much higher in inshore waters than offshore in temperate and tropical regions respectively. Ketchum et al. (1958) point out that tropical oceanic waters may sometimes show high rates of production, but in general the net photosynthetic production in tropical oceanic waters is low; nutrient impotrerishment of the surface layers and the lack of effective vertical mixing probably causes the phytoplankton to be in less “healthy” cordition, so reducing the effective production over the year. Yentsch and Vaccaro (1958) point out that nitrogen deficiency causes a reduction in chlorophyll, and may also lead to temporaiy disbalance in the chlorophyl1:carotenoid ratio. Steele (1962) and Steele and Baird (1962) have demonstrated that the chlorophyl1:carbon ratio is influenced by nutrient level, thus in turn affecting productivity. A factor in the total production of a column of sea water is not only the depth of the euphotic zone but also the precise distribution of the algal cells. I n earlier considerations of critical depth it was assumed that the algae were regularly distributed throughout the photosynthetic zone so that production rate decreased logaritl-.micallyfrom the surface (cf. Fig. 6). We know little of the precise distribution of phytoplankton throughout the euphotic zone at high latitudes; the photosynthetic zone is relatively thin and continual wave action may give a reasonably equal distribution, though the recent study by ‘Burkholderand Sieburth (1961) for Antarctic waters suggested that the maximum chlorophyll concentration occurred at the surface. Halldal (1953) observed a fairly even distribution of phytoplankton in Norwegian Sea waters with a deep mixed layer, but in July, August and September when stratification was obvious, the majority of the aigae were massed in the upper 25m. I n tropical waters, surface inhibition of photoeynthesis has been clearly demonstrated, and a maximum of phytoplankton is frequently found at some depth in the photosynthetic zone (e.g.Menzel and Ryther,

160

J . E. G . R A Y MO N T

1960; 1961). Hulburt, Ryther, and Guillard (1960) found in the seas off Bermuda that the phytoplankton at 50m depth was always richer than at the surface; usually different species were represented also at the two levels. Several recent investigations indicate, indeed, that the phytoplankton maximum in warmer waters may be near the bottom of the euphotic zone. In temperate latitudes during winter the photosynthetic zone is extremely shallow; there may be surface algal maxima temporarily, but mixing is usually active. In spring and summer the phytoplankton may by no means be equally distributed, and with surface inhibition, there may be a maximum somewhat below the surface (cf. Anderson, 1964). Sometimes, where a marked thermocline occurs, maximum density of algae may be associated with this layer. For example, in the Black Sea a thermocline occurs at a depth of about 20m and at this level there is a maximum of phytoplankton although the total depth of the euphotic zone approaches 60m (Sorokin, 1964a). Steemann Nielsen (1964a)has drawn attention to the importance of the vertical distribution of phytoplankton throughout the euphotic zone in relation to production under a unit of surface. I n tropical latitudes, or in temperate latitudes during bright summer days, overall production may be markedly increased by a greater density of phytoplankton at somewhat deeper levels. By contrast, at temperate latitudes with average or poor light conditions, production may be increased by a more or less regular distribution of phytoplankton or even by having algae massed nearer the surface. In the tropics, if plankton were equally distributed from the surface throughout the euphotic zone, the rate of production would be maximal at some intermediate depth (ca. 20m). Only with a reduction of incident light to 50% throughout the day would maximal production approach the surface.

V. GRAZING BY ZOOPLANKTON Although the standing crop of phytoplankton is closely related to overall production beneath a square metre of surface, the size of standing crop may be at times misleading since the quantity of algae removed by grazing, essentially by the zooplankton, is not taken into consideration. Harvey et al. (1935) drew attention to the remarkable reduction in phytoplankton crop immediately following the spring outburst in English Channel waters and noted that this was accompanied by marked grazing activity of the increasing zooplankton population. Over the summer, Harvey et al. concluded that although replenishment of nutrients from below the thermocline limited production, the generally rather low, but fluctuating, phytoplankton crop waa largely determined by the rate of grazing of the zooplankton. Regeneration of nutrients within the euphotic zone was also important. Clarke

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(1939) also believed that over the productive periods of phytoplankton growth in temperate latitudes, the zooplankton was largely responsible for regulating the size of plant population. The importance of grazing activity had been noted in Arctic waters by Braarud (1935), by Bigelow et al. (1940) for the Gulf of Maine, by Wimpeiiny (1936, 1938) for the North Sea, by Holmes (1956) in the Labrador Sea, by Hart (1942) for the Antarctic, and in other areas. Grazing intensity of course may vary, especially at high latitudes. Thus Halldal (1953) considers that in the Norwegian Sea it was much more intensive in spring than later in the year. I n very productive areas, such as Long Island Sound (Riley, 1956; 1959), Block Island Sound (Riley, 1952) and Tisbury Great Pond (Deevey, 1948), the phytoplankton crop may be rich, and grazing appears to exert little influence on the density of the algae (cf. also Gross et al., 1947). Despite these exceptions, the effect of the herbivorous zooplankton - appendicularians and salps, a majority of copepod species, many euphausids, the shelled pteropods, cladocerans and many meroplanktonic larvae - on the phytoplankton crop can be remarkable. The rapid reduction in phytoplankton crop seen in temperate and high latitudes may therefore not be a result of nutrient lack but of grazing activity. Cushing et al. (1963) deal with the relations between a Calanus population feeding on a phytoplankton burst in the North Sea over a period from March to June. From a comparison of the crop of phytoplankton present and the estimated rate of algal production, he believes that grazing is the dominant cause of algal mortality; there was no evidence of a lack of nutrients during the erdy decline in the algal population. Grazing is believed to be the niajor controlling factor, according to Cushing, in the temperate spring outburst of phytoplankton. With intensive grazing there is considerable regeneration of nutrients in the euphotic zone, and only when the rate of regeneration decreases does the reduction in concentration of nutrients due to the thermocline becoming a limiting factor. Harvey et al. (1935) obtained a minimal estimate of overall production of phytoplankton from the reduction in nutrier.t level over the period of the spring increase. For 1933, density was estimated at 85 000 plant pigment units/m3,* whereas the actual value of the standing crop was only 2 500 units/m3. For the following year, Harvey found that the standing crop was only 2-3% of the estimated total production. Hart (1942), following Harvey’s calculations, suggested that the standing crop of phytoplankton in the highly productive South Georgia region of the Antarctic was only 2% of the calculated production; for oceanic * Arbitrary pigment units were used as a measuremimt of chlorophyll before pure

chlorophyll was used aa the standard method of estimation.

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Antarctic areas the grazing activity was so intense that the standing crop was only 0.5% of the calculated productions. A number of workers (Riley, 1946; Gauld, 1950; Cushing, 1950a and b; Mare, 1940) have noticed the relatively small standing crop of plant plankton when zooplankton density is high. But the time relations between phytoplankton and zooplankton growth must be remembered; a zooplankton population can graze down plant cells in a matter of a few days, although the animals grow and reproduce more slowly. On the other hand, a relatively small algal population can reproduce exceedingly quickly, and thus with good growth conditions and in absence of grazers, can become a very dense population in a few days. The importance of this time factor in phytoplankton/zooplankton relationships has been well emphasized by both Steemann Nielsen (1937, 1963) and Clarke (1939). The importance of grazing as a factor in phytoplankton production has led to a number of mathematical treatments. Fleming (1939) expressed the difference between an initial population of phytoplankton and the population at some time interval as the “increment”. Clearly total production can be equivalent to increment only if no death of cells or removal by grazing occurs. Most workers agree that relatively little natural mortality of algal phytoplankton normally occurs, but an animal population may remove a considerable proportion of the phytoplankton by grazing. Fleming proposed the term “yield” for the difference between the total production and the increment, assuming that the difference was due to the removal of algae by zooplankton alone. Fleming proposed an equation : d- P _ - P(a - (b dt

+ ct))

This expresses the rate of change of a phytoplankton population (P), where a = rate of division of the phytoplankton cells assumed constant over a period; b = initial grazing rate; c = the increase of grazing rate which is assumed to be linear. If the grazing rate is assumed t o be constant and if (a - b) is positive (i.e. if the rate of division of the phytoplankton exceeds the constant grazing rate) then the phytoplankton population must continue to increase. However, the rate of increase in density of the algae is slower than the true rate of division owing to the constant grazing. The actual population increase may be so slow that the phytoplankton appears hardly to change a t all although the actual fraction per day removed by grazers may be very considerable. If the rate of grazing exceeds the algal reproduction rate the population will decline, and if grazing is very intense may lead to a typical rapid reduction following the spring bloom. Fleming integrated his equation using values for phytoplankton and

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zooplankton coefficients suggested by Harvey, and obtained a symmetrical curve for the algal population change which agreed fairly well with field observations. He also computed the total production of algae, assuming a cell division rate of one division in 36 hours and that this rate remained constant over the period iinder investigation. The peak in standing crop was achieved in 37 days, and the total production was calculated over double this period, by which time the crop had declined to a very low value. Fleming obtained a calculated total production for the whole period of > 80 000 pigment units - a value which agreed remarkably well with Harvey’E estimate from nutrient depletion. Thus the yield increased enormously in the second month of the spring increase and the standing crop was a mere fraction of the total population (cf. Fig. 8).

Feb.

Mar.

Apr.

FIG.8. Calculated total production, total yield, and population baaed on observations of

Harvey et al. Total yield represents total amount removod by grazing (assumed rate of division once in 36 hours); (from Fleming, 1939; reprintel from “Plankton and Productivity in the Oceans”, Pergamon Press).

Riley and Bumpus (1946) have also emph:tsized the importance of grazing on Georges Bank. After the expected phytoplankton winter minimum, there is a spring burst, followed by a decline. The zooplankton which is also low in winter over tht: Bank rises rather more slowly than the phytoplankton, but! with increasing speed from about May onward. There is therefore 8 positive correlation between the phytoplankton and zooplankton in winter and early spring, but this changes to a marked negative correlation during May. A number of zooplankton species showed this same change, though the exact time of

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the onset of the negative correlation depended on the month when the zooplankton species reached its seasonal peak. Riley and Bumpus conclude that while the early correlation is due to some beneficial factor such as increasing temperature, common to both phytoplankton and zooplankton, the sharp change to an inverse relationship in May is due to the grazing activity of the zooplankton. The authors have also calculated that while the percentage of the phytoplankton production consumed by the zooplankton is relatively small (less than 10%) until April, it rises sharply in May to over 40%. Riley (1946, 1963) has developed a mathematical model somewhat similar to that proposed by Fleming for the rate of increase in a phytoplankton population. He believed that SO-SO% of the phytoplankton variations on Georges Bank (Gulf of Maine) could be accounted for in terms of depth and illumination, temperature, nutrients (phosphate and nitrate) and zooplankton density. The relationship may be expressed : dP - = P(Ph - R - G ) dt where P is the total phytoplankton population, expressed per unit area’ of sea surface; P h = photosynthetic coefficient; R = coefficient of phytoplankton respiration ; G = zooplankton grazing coefficient. Riley states that these must be regarded as ecological variables rather than constants. Photosynthesis was found to vary more or less linearly with incident illumination during winter and early spring. It may thus be assumed to vary similarly with depth. By experiment, a photosynthetic constant (p) was established: its value, if light intensity is measured as g cal/cm2/minwas 2.5. Thus: P h = PI (where p

is ca. 2.5)

Illumination decreases logarithmically in the sea so that at depth z the illumination I, is: I, = I,e-kz (where I, is the incident illumination, and k is the extinction coefficient). Riley assumed a limiting depth for photosynthesis where the light intensity was 0.0015 g cal/cm2/min (i.e. this is the compensation intensity). If the depth a t this intensity is z (i.e. the depth of the euphotic zone), then an average photosynthetic rate may be computed for the whole euphotic zone by integrating the illumination from the compensation depth to the surface and dividing by the depth. Thus:

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165

The rate will also be affected by nutrient depletion, designated as N. For phosphate, this is believed to vary with the concentration below a maximum of 0.55 pg atoms P/1 (i.e. 16 mgP/ni3).

If the thickness of the mixed layer is greater than the euphotic zone, turbulence (V) will also reduce the photosynthetic rate. Riley suggests that the depth of the mixed layer may be somewhat arbitrarily defined as the maximum depth a t which the density does not exceed the surface density by more than 0-02 at units. Thus:

V =

depth of ______ euphotic zone depth of mixed layer

(provided mixed layer is the greater). Thus:

As regards R =respiration rate of the algae, temperature must be taken into account. Thus:

RT = RoerT (where RT = respiration a t temperature T ; R, a t temperature 0 " ; and r is a constant for the rate of change in respiration with temperature). This value has been experimentally determined as 0.069 for a 10°C increase. Lastly the grazing rate G may be stated as:

G

= gZ

where g is the rate of reduction of phytoplankton per unit of animals; Z is the quantity of herbivorous zooplankton. It'is likely that g will vary

with temperature, though perhaps not lineaiily ; different broods of herbivores and of course specific differences may affect the grazing rate also. An approximation can be arrived a t from the minimum daily food requirements of Calanus as deduced from the respiratory rate. Riley supposes a daily food intake of from 1'2% (winter) to 7.1% (summer), and calculates an average value for g from these data. Thus:

becomes :

dP dt

= P(Ph

- R, - G )

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J . E . Q. RAYMONT

The rate of change of phytoplankton population may be expressed therefore in terms of five ecological parameters : solar radiation, transparency of water, depth of mixed layer, temperature, and zooplankton quantity. Riley obtained average numerical values from seasonal field data from Georges Bank. Over short periods of time approximate integration was possible, assuming a constant mean value for the variable over that period. A relative curve of seasonal change was obtained. By statistically determining the best fit of the curve for all the phytoplankton cruise data, the actual seasonal changes and the theoretical curve may be compared. Figure 9 shows the good measure of agreement.

FIQ.9. The seaaonal cycle of phytoplankton calculated by approximate integration of the equation for the rate of change of the population. For comparison, observed quatitias of phytoplankton are shown as dots; (from Riley, 1946; reprinted from ‘‘Plankton and Productivity in the Oceans”, Pergamon Press).

Riley has applied the same methods to other areas showing seasonal phytoplankton cycles. I n the coastal waters of New England off Woods Hole, the cycle is considerably different from that of Georges Bank owing to different values of some of the various parameters. Riley has been able to obtain again a fairly good agreement between the mathematical model and the field data. I n a more recent study (Riley, 1963) he has been able to make a similar calculation for data obtained by Kokubo from Husan (Korea). The changes in the phytoplankton in these waters differed quire appreciably over the two years, but the theoretical and field data agreed very well. The autumn of 1932 waa more favourable to phytoplankton owing to light, nutrients and sparse zooplankton (see Fig. 10). The development of other models introducing certain refinements has been reviewed by Riley (1963). A correction may be introduced, for example, for the loss of algal crop due to sinking and death, apart from

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the grazing activity of zooplankton. The phosphate distribution, as one of the major limiting nutrients in the upper lityers, may be computed by an assessment of the eddy diffusion in the water layers and the concentration of phosphate in deeper water. An equation for phytoplankton p at depth z, introducing these terms is as follows:

where v = sinking rate, p = density of water, A = coefficient of vertical eddy diffusion. Such a type of equation may be applied to two depth intervals to deduce grazing and sinking rates. A succession of depth

.., 0 0 1

-.

300

h

I \

I

Husan

IAI

100

1932

1933

FIQ.10. Comparison of observed seasonal cycles of phyboplankton (solid lines)]with theoretical cycles (dotted lines) at Husan; (from Riley, 1963; reprinted from “The Sea”, Interscience Publishers).

intervals from the surface to below the euphotic zone ks then studied in turn. Steele (1956) used this type of equation for calculating production on the Fladen ground and compared the production by 1% measurements with these theoretical calculations. The good measure of agreement in his results underlines the usefulness of such models. Cushing (1953) developed rather similar models, but includes the preying of zooplankton carnivores on the herbivorous members of the community, thus introducing another term in the mathematical equation. I n a later study Cushing (1959a) developed a ldathematjcal model for studying an area in the North Sea over a period covering the spring outburst of phytoplankton. He believed that no significant depletion of nitrate and phosphate occurred during this increase and that regeneration of nutrients maintained the nutrient level. Thus the rats of change of the phytoplankton population was dependent on algal rates of division with changing light intensities and the depth of light penetration; on the

168

J. E . G. R A Y M O N T

thickness of the mixed layer; and on the rate of change of the zooplankton population. Cushing believes that grazing in this area of the North Sea was so intense that practically the whole of the production was grazed down over the spring outburst so that the final standing crop was extremely small. Other models have been developed recently by Steele and Baird (1962), but it is agreed generally that until we have greater knowledge of the precise physiology of algae, and especially of the factors affecting grazing and the rates of change of the zooplankton population, we cannot obtain much more accurate pictures of the seasonal changes in phytoplankton.

VI. ZOOPLANKTON Although the zooplankton grazes upon the phytoplankton and therefore temporally and spatially the two populations may show some alternation, over the broad oceans, areas of rich zooplankton correspond to productive phytoplankton regions (Steemann Nielsen, 1958b, 1962b). At any latitude there is also a marked tendency for shallow coastal regions and for submarine banks to have a richer phytoplankton and a correspondingly higher zooplankton crop than deep oceanic regions. Such observations on zooplankton abundance are founded upon biomass and not on a rate of production of zooplankt,on. Even biomass of zooplankton, however, is open to varied interpretation since the methods for sampling zooplankton are by no means accurate or uniform (cf. Zooplankton Symposium, 1962). A. METHODS FOR ESTIMATING THE STANDING CROP O F ZOOPLANKTON Essentially almost all methods for estimating zooplankton crop rely upon the catching power of fine mesh nets, usually of nylon or silk. Mesh size is, therefore, of the utmost significance and poses problems of selection. Whilst a few species of zooplankton may measure several centimetres in length, few plankton animals exceed a few millimetres in size. A whole range exists however from those of several miilimetres, the macroplankton, to the very small-sized protozoans, especially small ciliates and flagellates, measuring a few p in diameter. The finest silk nets (200 mesh per inch) will capture the very young, small, stages and eggs of planktonic animals, as well as rneroplanktonic larvae, the smallest copepods, appendicularians, an'd similar small animals, providing quantitative estimates. Such fine nets filter too slowly and too small a volume of water t o sample quantitatively the larger, more active, zooplankton -euphausids, the larger copepods, chaetognaths, mysids and especially large pelagic decapods. Relatively coarse nets can be used for the macroplankton, but between these two extremes every mesh size selects a particular range of zooplankton. Even the finest silk nets do

T H E PRODUCTION O F MARINE PLANKTON

169

not catch the very smallest protozoans quantitatively, and these must be sampled by other methods. Recently, high-speed samplers such as the Isaacs Kidd mid-water trawl have been developed to sample large volumes of water and to obtain samples over considerable areas. While such techniques are of great advantage in estimating the distribution of the larger forms, alone they cannot give an accurate quantitative sampling of the whole zooplankton. Another problem is the clogging of the meshes. I n a rich phytoplankton bloom the filtration power of a net may be so reduced that it prevents quantitative sampling. Equally, certain of the more gelatinous zooplankton such as salps, medusae, ctenophores and siphonophores, when abundant, may clog the meshes of the net and reduce filtration. Some salps, jelly-fish and ctenophores show a marked tendency at times to intensive swarming. Not only will the net tend to be clogged in passing through such populations, but any quantitative sampling is always made more difficult if the zooplankton has marked patchy distribution. Even apart from salps and ctenophores, patchiness is an extremely common feature of zooplankton distribution. Various types of meter have been developed to measure the actual volume of water passing through nets. Usually they are placed in the mouth of the net. While such devices increase the accuracy of volume measurements, their presence may reduce catching power, and some animals may actively avoid the mouth of the net. The whole problem of the proper sampling of the zooplankton is dependent on precise knowledge of vertical distribution. Unfortunately zooplankton varies enormously in its vert'ical distribution; often there is a rich layer close to the surface and another maximum at a depth approaching a thousand metres. The work of Leavitt (1935, 1938), Jespersen (1935), Sewell (1948), Zenkevitc h and Birstein (1956), Vinogradov (1962a) and Hardy and Gunther (1936), all deal with the problem of the vertical distribution of animal plankton. Though there is fairly general agreement that very deep wa,ter has reduced populations, there appears to be no clear pattern of general distribution. I n Arctic as well as Antarctic seas (cf. Hardy and Gunther, 1936; Zenkevitch, 1963; Johnson, 1963) there is a marked tendency for the greater biomass of zooplankton to be beneath the surface layers but the distribution varies. Moreover, the zooplankton is characteristically marked by vertical migration. This may occur diurnally, and more especially in colder waters, there may be marked seasonal migration. The problem of correct quantitative assessment of the richness of various strata thus becomes more difficult. Apart from the problem of catching plankton quantitatively there is the question of estimating the catch. The direct numerical count is

170

J . E . 0.RAYMONT

laborious and time consuming, and the taxonomic identification of the great variety of zooplankton species is difficult. Even if this is done, numbers of various zooplankton animals may not be a satisfactory index to the crop, the size and biomass of species varying enormously. Wiborg (1954) and others have estimated the relative volumes of the major zooplankton representatives, and thus computed the volume of the crop. Another widely used method is to measure the total volume of the zooplankton haul, usually by a displacement technique or estimate of settled volume. This is open to error if the catch contains a considerable proportion of the more gelatinous zooplankton. Many investigators attempt to avoid this error by first removing such animals as salps, medusae and siphonophores. A pump-and-hose method is used by some research workers to avoid the errors associated with nets. While useful for quantitative work in shallow water, it is inapplicable to oceanic depths. For the measurement of zooplankton biomass, volume is obviously imperfect; a better estimate would be wet weight of crop or dry organic weight. One of the few observations employing these methods is that of Curl (1962b) who studied the biomass of plankton south of New York. Curl includes data for converting wet and dry weights, and carbon, nitrogen and phosphorus content for various species of zooplankton. He emphasizes that organic weight is the best unit for biomass, but for general assessments of zooplankton crop it would be difficult to use organic weight methods. I n any event, the problem of selection of net mesh size is still a major difficulty. The symposium held on zooplankton estimation (Rapports et Proces Verbaux, 1962) emphasized the di%% culties of agreeing on standardization. Wickstead (1963) has recently suggested that two nets of different mesh size should be vertically hauled together. The recent discovery of an abundant population of zooplankton animals living right at the surface in oceanic regions poses again problems for the correct sampling for this particular layer.

B.REGIONAL CROP ASSESSMENTS O F ZOOPLANKTON Despite the difficulty of estimating zooplankton, the crop tends to be richest where primary production and the size of standing crop of phytoplankton tend to be high (Steemann Nielsen, 1958b; 196213). The work of Hentschel (1933-36) in the southern Atlantic Ocean demonstrated the remarkable agreement between the quantities of phytoplankton and the crop of zooplankton, despite seasonal and other fluctuations. A recent survey by Reid (1962) for the Pacific Ocean also indicates good correspondence between the phosphate concentration of the upper waters, suggesting high primary production and the volumes of zooplankton. There are several broad oceanic surveys which demon-

T H E P R O D U C T I O N O F M A R I N E !?LANKTON

171

strate the relative abundance of zooplankton i n colder, boreal waters as compared with the low crop in warm seas. Jespersen (1924) found that although there may be considerable variations in zooplankton abundance in warmer waters, for instance, in the Atlantic considerably greater quantities of zooplankton were found north of the Azores than off the American coast and near Bermuda, the boreal regions were much richer. Thus in subtropical and tropical regions, plankton volumes varied from less than a litre to two litres an hour; in the northern Atlantic west of Ireland, Jespersen found volumes approaching 7-8 litres per hour; and in the colder seas north of Scotland much greater amounts approaching 18 or 19 litres per hour. I n general, Jespersen suggests that for the open oceans the average crop of zooplankton in cold northern waters is at least some eight times that of tropical seas. Such waters are characterized by low nutrient level and poor production. Wherever in tropical regions upwelling brings nutrients to the surface, increased primary production is accompanied by richer zooplankton. King and Hida (1957) have recentby recorded a new area of abundance in the region of upwelling and divergence in the equatorial central Pacific. A summary of the varying standing crops of zooplankton in different oceanic regions is given by Hela and Laevastu (1962). One of the problems in comparing zooplankton production at low and high latitudes is that the seasonal abundance of zooplankton shows very wide changes at higher latitudes. By contrast, though there is usually some seasonal change and though different species may breed at different times of the year, in general in warm seas .bhe fluctuations are comparatively small. I n Indian waters the zooplankton as a whole shows some fluctuations in abundance over the year and this is probably associated with the monsoon affecting phytoplankton production. Wickstead (1958) demonstrated changes similar to the spring and autumn peak of zooplankton production in the Singapore Straits, probably associated with monsoon weather conditions. Moore ( 1949) suggested for waters round Bermuda that the zooplankton under these more oceanic conditions showed relatively little seasonal fluctuation, and Menzel and Ryther (196lb) found a small spring maximum of zooplankton in the Sargasso Sea, but as a whole the fluctuation was small with a low standing crop of zooplankton. Bsharah (1957) found in the Florida current region a small seasonal fluctuation in plankton, but the maximum averaged no more than two or three times that for the remainder of the year. By contrast in temperate and high latitudes the abundance of plankton in spring and summer shows a remarkable increase over winter, and frequently there may be a peak production in late summer

172

J. E. G . RAYMONT

or early autumn. The amplitude from winter minimum to annual maximum may be a t least 40 times, with inshore waters (cf. Russell and Colman, 1934) showing fluctuations far greater than 40 times. High latitudes may show an enormous increase in zooplankton volumes over the productive season (cf. Fish, 1954 for the Labrador Sea). A typical cycle of zooplankton seasonal changes in northern temperate waters comes from the work of Harvey et al. (1935); from a minimum in January -February there was a rise in zooplankton to a maximum in spring and a second maximum occurs in late summer. The zooplankton was dominated by copepods. Deevey (1956) dealing with the zooplankton in Long Island Sound and Block Island Sound also found marked seasonal fluctuation in zooplankton with the maximum in summer. Wiborg (1954) recorded a spring or early summer peak in zooplankton and a second rise between August and October, the chief contributor to this reproductive cycle being the copepods. Digby (1954) observed a later summer maximum for Greenland waters when the volume was some 20 times that of the winter minimum. Fish ( 1 9 5 4 and Kielhorn (1952) found very great changes in zooplankton abundance between summer and winter with a maximum about July and August in waters of the Labrador Sea. Comparative work in the Antarctic (e.g. Mackintosh, 1934; 1937) suggests that a rapid increase in the zooplankton occurs during the spring and summer and that a peak value is achieved during the Antarctic summer, about February. By the late summer the population is declining again and reaches low values over winter. To some extent, however, this pattern can be changed by vertical migration. Foxton (1956) has stated that seasonal variations in plankton volume in the Antarctic are much reduced if sampling is continued down to at least a thousand metres depth. Hansen (1960) also refers to this problem of vertical migration and the biomass of zooplankton with reference to the Norwegian Sea. Hansen was investigating mainly the upper 50 metres, and in the open Norwegian Sea the average biomass in June was some 30 times that for the minimum period in November/ December. This, however, was partly explained by a marked migration especially of copepods. I n coastal waters, where some of the neritic copepods remained nearer the surface, the fluctuation between summer and winter was not nearly so great. Despite seasonal fluctuations, however, zooplankton at high latitudes tends to be more abundant than in warm waters, and at any latitude neritic plankton tends to be richer. Clarke (1940) investigated the waters south-east of New York and found them to be very much richer than in the area of mixing between the continental slope and the Gulf Stream to the south-east. The fluctuations between winter and summer in the

THE PRODUCTION O F MARINE PLANKTON

173

coastal waters were far greater ( x 20 to x 40) than in the “slope” water (some x lo), but the average volume of zooplankton in the coastal zone was about 4 times greater than in the “slope” area. In the Sargasso Sea, Clarke found that the average volume of plankton hauls was much less - only approximately one-quarter that of the “slope” stations. The seasonal fluctuation in the Sargasso was negligible. Foxton (1956) also found that the mean volume of zooplankton increased fairly steadily from the subtropics through the sub-antarctic to Antarctic areas. He believes that the standing crop in the Antarctic was at least 4 times that of tropical southern areas; even then the Antarctic plankton may not have been adequately sampled. There was some indication of a reduction at the highest latitudes. Certainly in the northern hemisphere at the very highest lakitudes it appears that the biomass of zooplankton is very much reduced. Zenkevitch (1963) has summarized the general quantitative distribution of zooplankton in northern seas. Allowing for the fact that the zooplankton in very cold seas may be richer in the lower layers, it appears from the work of Russian investigators that the total biomass of zooplankton is very low in the Polar basin. In the area north of Siberia the markedly lower salinity may affect the biomass, but the gene]-a1low productivity of Polar waters is reflected in the low zooplankton crop. Figure 11 illustrates the remarkable rise in zooplankton density from low numbers in the warmer Pacific seas, through high numbers in boreal waters, and the very sharp reduction in really Arctic areas. As regards the Arctic and sub-Arctic seas of the U.S.S.R., Zenkevitch points out that the south-western Barents Sea is by far the most productive. A zooplankton biomass up to 2 000 mg/m3 was recorded in the summer in some areas, but even for the whole Barents Sea, the mean annual biomass is quoted as 140 mg/m3. As compared with this, the biomass in the colder seas is much lower; thus in the Laptev Sea and the eastern Siberian Sea Zenkevitch quotes Jashnov that even in the summer, the biomass does not exceed 72 mg/m3 on average. But Zenkevitch points out that in the more central Arctic basin there seems to be a very significant decrease in zooplankton. He quotes only 12 mg/m3 in the upper 100 metres; a rise to nearly 30 mg/m3in an intermediate layer; but only some 7 mg/m3 in the deep layer below 800 metrlss. Johnson (1963) also refers to the low standing crop of zooplankton in the Arctic basin. This agrees with the very low primary production. A summary of the biomass of zooplankton, as measured by displacement volume, is given by Bigelow and Sears (1939) for areas of the northern Atlantic. Seas around Iceland, the Faroes and the north of Scotland appear to be especially rich. Bigelow and Sears suggest that the continental shelf waters off the north-east coast of U.S.A. rank next in

174

J. E. G . R A Y M O N T

quantity for the northern Atlantic. There is a considerable seasonal fluctuation but the summer maximum (0.7-0.8 cc/m3) compares favourably with that of the North Sea and is considerably higher than the volume of zooplankton in the English Channel (cf. Table V). Tranter (1962) has studied the biomass of zooplankton in Australian seas. Oceanic regions, except where upwelling occurs, have a low crop normally < 25 mg/m3 (wet biomass weight). Continental shelf areas had a higher crop, and inshore shallow stations, for example a t Port 3000

n E

-

._ c 2000 c VI

E ._ 0

3 L

0

1000

n 8

5 z

Inn 1

2

4

-ILL 6

7

8

FIG.11. Change in number of specimens per ma from tropical part of Pacific Ocean (l), through northern part of the Pacific (2, 3), Bering Sea (4, 5), Chukotsk Sea (6, 7), and Arctic Basin (8) - after Brodsky, 1956; (redrawn and modified from Zenkevitch, 1963).

Hacking, even larger amounts. At times the Port Hacking plankton included large numbers of salps, but if these are excluded, the biomass (> 200 mg/m3) is still higher than offshore. Tranter uses a conversion factor to compare his data with plankton volumes recorded by Bigelow and Sears. He also includes zooplankton quantities obtained by Russian workers from the Pacific and converts these data to plankton volumes (Table V). Tranter’s values for oceanic Australian waters (0.02-0.05 cc/m3) are similar to those of the Russian investigators for the subtropical Pacific. The richer equatorial Pacific area (0.1 cc/m3)is approximately equivalent to Australian shelf waters. But in large area of the boreal northern Pacific zooplankton volumes are very much greater, reaching even 1.0 cc/m3 in summer, and being maintained throughout the year at amounts exceeding 0 - 5 cc/m3. Zenkevitch (1963) quotes very high quantities for the summer zooplankton of far northern Pacific seas. If the same conversion factor be applied to his data to

THE P R O D U C T I O N O F M A R I N E P L A N K T O N

175

obtain approximate plankton volumes, the plankton during the summer in the Bering Sea and Sea of Okhotsk exceeds 1.0 cc/mJ (Table V). Similar values are found in summer in the sou:h-western Barents Sea. By contrast the biomass in the Laptev and eastern Siberian Sea is low (0.07 cc/m3) and is even more reduced in the central Arctic basin (Table V). Regional comparisons of biomass arc usual1.r. expressed in terms of unit volume, and the density of zooplankton is of the utmost significance for the nutrition of higher trophic levels. But with the great difference in depth between coastal and oceanic regions, the biomass beneath a unit area of sea surface is sometimes considered. Riley et al. (1949) compared the production beneath a square metre of sea surface for coastal areas south of New York, for the semitrcpical Sargasso Sea area, and for the mixed continental slope water between. Riley found that the inshore water showed its typical greater richness; the mean ratios for the volumes of zooplankton of the three areas: coastal, “slope”, and tropical waters, were approximately 10:4: 1. Oceanic plankton also appears to have a generally lower organic content. Despite the greater depth of oceanic areas and the much greater crop fluctuations near shore, especially in coastal boreal waters, Riley’s investigations generally confirm the original view that tropical waters are usually poorer in zooplankton biomass than temperate waters, especially inshore areas. Grice and Hart (1962) provide a more recent comparison for approximately the same region. They investigated the zooplankton of the upper two hundred metres of water between New York and Bermuda and confirmed the richness of the coastal areas. In numerical abundance, the ratio between coastal, “slope” and Sargasso Sea waters averaged some 22 :4: 1. By volume, the same comparison yielded ratios of approximately 50:3:1. Their results confirmed the very much greater seasonal fluctuations in neritic waters (approximately x 30) as compared with the subtropical Sargasso waters (approximately x 4). Although in coastal regions virtually the whole column of water from surface to bottom was sampled, but only the upper 200 meixes in oceanic stations, the greater richness of coastal waters is still evident. The volume in the coastal area exceeds that of most boreal northern Atlantic regions. The very low quantity found for the Sargasso Sea is similar to the values suggested for subtropical Pacific and Australian oceanic regions (Table V). Despite the low biomass of zooplanktoil in trol ical waters, apart from areas of upwelling or divergence, it has been suggested, notably by Cushing (1959a and b), that in tropical oceans in view af the more rapid utilization and regeneration of nutrients the system of plankton production may be more efficient even though gross production is much lower

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J. E. G . RAYMONT

than at high latitudes. The standing crop of phytoplankton is small and as the different members of the zooplankton in tropical waters tend to breed at different periods of the year, there is always a fairly ateady grazing population and the phytoplankton never blooms excessively. TABLEV Comparison of Volumes of Zooplankton from Different Oceanic and Coastal Regions _ _

-

~~

. _

Plankton volume (cma/ma) Region

Winter ~~~~

Summer

Authority

~~

Northern Atlantic - Iceland Faroes, Greenland Coastal shelf, north-eastern U.S.A.

0-84*

0.2-0.3

~ _ _ _ _

0.7-0.8 ~

iand

sears ~ (1939) ~

0-5-0-6

North Sea English Channel

0-1

Laptev and eastern Siberian Sea Central Arctic Basin

0.07 0.01

___

Sea of Japan Okhotsk Sea Bering Sea

0.03-0.5

____

1.0 Zenkevitch (1983) 1 -&3 *O 1 *5-2 *5

Pearly Mean ~

~~~

Barents Sea Australian oceanic waters Australian shelf waters

0.14

Zenkevitch (1963)

0.02-0 *05 0.1

Australian inshore waters

>0.2

Subtropical Pacific

<0.05

Equatorial Pacific

0.1

Boreal northern Pacific

0.5-1-0

New York- Bermuda Coastal waters Slope waters Sargasso waters

1 *07 0.27 0.02

Most of smaller copepods not included owing to mesh size.

Trantor (1982)

Russian data quoted by Tranter (1982)

Grice and Harb (1962)

l

~

T H E PRODUCTION O F MARINE PLANKTON

177

The relationship between the phytoplankton and the zooplankton therefore approaches a steady state; continuous grazing releases excretory material which is rapidly remineralized, and the nutrient concentration remains very low as it is continuously utilized. The opposite condition is seen in colder waters where typically an enormous early burst of phytoplankton is followed by very heavy grazing, but frequently there is a considerable time lag between the increase in phytoplankton and the rise in the zooplankton herbivores. Only when the crop of phytoplankton has been sufficiently reduced does new regeneration take place. This concept of the very efficient use of primary production in warmer waters has been supported more recently by the work of other investigators. For example Menzel and Ryther (1961) have found that off Bermuda the zooplankton uses almost 100% of the production of algae. Grice and Hart (1962) suggest a remarkably efficient utilization of the phytoplankton in Sargasso waters, the herbivores showing far greater diversity of species than in neritic and. in boreal waters. Presumably the herbivores are more specifically adapted to utilize the various types of food efficiently; they perhaps have very specialized food requirements. Grice and Hart also call actention to the balance between herbivores and carnivorous groups in the zooplankton. In warm subtropical waters about half the zooplankton is herbivorous as against 65yo in neritic boreal areas. Two predominantly carnivorous groups (the chaetognaths and siphonophores) were also much more important in warm tropical waters in respect to the zooplankton as a whole than in the coastal areas. I n tropical waters therefore, not only is the herbivorous plankton utilizing the phytopbnkton as efficiently as possible, but it would appear that the herbivore population is kept in delicate balance with the carnivorous forms. In coastal and boreal waters there may be an excessive production of herbivorous plankton following a phytoplankton outburst. This may account in part for the sudden great swarms of salps which Grice and Hart observed in the more neritic areas. Steemann Nielsen (196213, 1963)has pointed out that in warm oligotrophic waters the herbivores mush search out their food and the greater depth of the euphotic zone will make greater energy demands on the zooplankton for the food obtained. Since less of the food aseimilated is presumably available for growth and reproduction, it is likely that the zooplankton will be longer-lived. The ratio between the standing stock and the rate of production for both herbivorous and carnivorous plankton animals will vary, but it will tend to be higher in oligotrophic areas than in the nutrient-richer wihxs of temperate and higher latitudes. I n these typically richer regions any factors which allow phytoplankton growth to start more slowly, and so allow the zooplankton to begin grazing down the phytoplankton crop, will prevent

178

J . E . C,. R A Y M O N T

the enormous burst, of phytoplankton typical of high latitudes. Steemann Nielsen believes that such “explosions” of phytoplankton occur only if a very rapid burst of algal growth precedes the reproduction of the zooplankton. Thus with particularly good light conditions and the rapid stabilization of the upper water layers, the rapid algal bloom typical of neritic areas may get ahead of zooplankton growth. More generally the relationship between phytoplankton and zooplankton is probably more stable. This “wastefulness” in production at higher latitudes may be only apparent; material not consumed or only partly digested by the zooplankton may be used effectively by other members of the marine eco-system. Vinogradov (196213)has suggested that excessively rich algal crops may also supply food to deep layers through extensive vertical migrations of the zooplankton. Although some bathypelagic zooplankton may feed on detritus, many will be filter feeders migrating periodically towards the surface. When such plankton descends again their faeces and their bodies may be preyed on by zooplankton of the mid-water strata. The total biomass of the intermediate layers may thus be greater since these can be made up not only of filter feeders which migrate but of predators and detrital feeders. The amount of detritus descending to deeper levels is probably very small and is relatively resistant, so that the biomass of zooplankt,on at great depths is much reduced. In the deep sea as in oligotrophic shallower layers there is presumably a delicate balance between the herbivorous and carnivorous population. At high latitudes the breeding, especially of herbivorous copepods, is largely influenced by phytoplankton outbursts though Heinrich (1962) states that some copepods breed before the phytoplankton outburst. Grainger (1959) suggests that while the herbivorous copepods at high latitudes breed essentially near the time of the major phytoplankton growth and show enormous fluctuations in population, the carnivorous forms do not show nearly as great numerical changes seasonally and may breed at different times of the year. This is perhaps borne out by the observations of Dunbar (1946, 1962) on chaetognaths and amphipods; for example, Sagitta elegans arctica appears to have a very long spawning period (July to February) in Arctic waters and the spawning time does not depend on food availability.

c. RATE O F ZOOPLANKTON PRODUCTION So far discussion has been limited to the standing crop of zooplankton; estimation is difficult and our knowledge is limited. But estimates of tfhe rates of production of zooplankton are even more difficult. One of the earliest attempts was that of Riley (1947). Over the region of Georgea Bank, Riley proposed that the size of the herbivore population (H)

T H E PRODUCTION O F MARINE F’LANKTON

179

which made up the bulk of the zooplankton a t a time t might be expressed by the equation:

H - H e(A-R-C-D)t t 0 where A = rate of assimilation of food by herbivores R = herbivore respiration rate C = rate of consumption of herbivores by predators D = herbivore death rate.

An estimate of the rate of assimilation may be deduced indirectly from the phytoplankton density and the known grazing rates of copepods. Over the period of the spring increase, however, allowance must be made for excessive grazing by the copepods. Riley assumed a maximum limit for assimilation equal to 8% of the animal’s weight per day. As regards herbivore respiration rate, laboratory experimental results may be used. Thus the respiration of Calanus gives an indication of the loss of matter due to respiration, due regard being paid to the effect of temperature. Riley uses the seasonal changes in the population of Sagitta elegans, which he regards as the main zooplankton predator on Georges Bank, to estimate the rate of predation. A constant was determined statistically for the amount of matter consumed per unit predator, and predation was considered proportional to the niimbers of Sagitta. The herbivore death rate (D) which includes such things as natural death, dilution, etc., was also deduced statistically.

v

\ E

-

Observed zoopbmkton popJlalion 0- 4

(b) 20 -

Colculaled popdolion

-

V

10 -

‘%n

P’

/’ +Feb

Mnr

Apr

May dun

Jul

plug

k p Oct

Nov Dec

FIG.12. (a)The rate of growth of the zooplankton on Georges Bank. (b) Calculated end observed seasonal variations in zooplankton demity on Georges Bank; (from Riley, 1947; reprinted from “Plankton 5nd Productivity in the Ooeene”, Pergemon Press).

180

J. E.

a. RAYMO NT

Figure 12a shows the rate of change of a population of zooplankton obtained by Riley using the various coefficients calculated. An approximate integration of the curve may be obtained by employing mean value for the factors in the equation over short time intervals. This theoretical curve has been fitted to the field data for Georges Bank there is a considerable measure of agreement between the actual and theoretical curves (cf. Fig. 12b). Cushing (1959a) used a mathematical model to assess the production of Calanus and other small copepods as the herbivore plankton in the North Sea over a period of six months. He deduced the rate of increase of the algae from the light energy available at various depths during the six months (cf. p. 167), and estimated the grazing rate from the minimal food requirements necessary for maintenance, reckoning also the rate of increase of the herbivorous copepods. His analysis of this rate of increase is especially interesting as he obtained his data from the egg production of Calanus in relation to food concentration. Marshall and Om had already shown that egg production appears to be a function of food concentration. Cushing estimated the percentage mortality for juvenile stages of Calanus and the mortality of the adults for various weekly periods between January and June. The production of Cabnus and of other herbivores over the six-month period is shown in Fig. 13. Cushing’s results suggested that the copepods were undernourished during the first months of the year, but they fed excessively over t,he main period of phytoplankton production. This apparent “wastefulness” of production in boreal waters has already been noted. Details of the rates of production of zooplankton must, however, depend on a far wider and more accurate knowledge of the biology and especially of the physiology of plankton animals. Even our knowledge of breeding cycles of zooplankton is limited; we know fairly accurately the breeding cycles of a few species of copepods, of a few euphausids, some amphipods and sagittae. Most of these are boreal species; knowledge of the breeding of tropical plankton is especially lacking, and deepsea plankton is virtually unknown as regards its breeding habits. Since zooplankton is so difficult to keep in the laboratory the effect of various environmental factors on reproductive rate, especially the effect of food supply, is almost unknown. The work of many investigators, notably Marshall and Orr’ (1956), dealt with the stimulating effect of food on reproduction in Calanus. Marshall (1949) also suggested that abundant diatoms increased the production of other copepods. Barnes (1957) indicated a stimulating influence of phytoplankton production on the liberation of cirripede nauplii. Edmondson (1962) demonstrated that the density of phytoplankton was related to successful reproduction of copepods and other animals. Work on bivalve larvae, summarized

T H E PRODUCTION O F MARINE I'LANKTON

181

by Loosanoff and Davis (1963), alao indicates the importance of an adequate food concentration for the rearing of various species. While such observations demonstrate repeatedly the importance of food supply on egg and larval production, we do not have detailed and accurate knowledge of the precise operation of this factor. The tank 1.'

0.

0.0

L

x 0 .-

Y

c

Y

5"

0.00

0.000

i

0.0000

FIQ.13. The theoretical production of algae, and of Calanm and "other copepods" as mg wet weight per litre for the period January to June; (from Cushhg, 1969; reprinted from "Plankton and Productivity in the Oceans", Pergamon Press). 0

182

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a . RAYMONT

culture of zooplankton with fertilization experiments (e.g. Raymont and Miller, 1962) has also not yielded precise data on the rate of zooplankton production in relation to phytoplankton crop. Investigations by Reeve (1963) have made an important contribution in dealing with the efficiency of utilization of phytoplankton, even though the species studied (Artemia) is not a marine plankton animal. Our knowledge of the metabolism of zooplankton animals is excessively limited, though Conover (1962) has maintained Calunus hyperboreus for considerable periods of time and has been able to relate feeding to activity, and to respiration, and to make some estimates of efficiency and growth. A survey of our knowledge of aspects of metabolism, including utilization of food, excretion, and respiration (Raymont, 1963) reveals that data on maintenance and growth requirements and even of the metabolic food reserves of zooplankton are very 1imit)ed(cf. Raymont et al., 1964). Investigations of the metabolism of plankton have been handicapped because of the difficulties of culturing zooplankton species in the laboratory. Although it is possible to obtain egg production from Calanus Jinmarchicus and C. hyperboreus, and to rear various stages, so far the culture of successive generations has eluded us. Jacobs (1961) made an important contribution in growing Pseudodiaptmus coronutwr in the laboratory through several generations, using phytoplankton aa food, but this copepod is not a truly planktonic species. The most important recent advance is that of Zillioux and Wilson* (unpublished) who bred Acartia tonsa through five successive generations using phytoplankton cultures as food. Continuation of such experiments should allow the medium and the food requirements of planktonic animals to be accurately defined, as with the work of Provasoli and his colleagues (e.g. Shiraishi and Provasoli, 1959) on the nonplanktonic copepod Tigriopw. Only then can we study adequately the factors affecting the metabolism and growth of plankton animals. Meanwhile mathematical models help us to appreciate the problems and point the way to future research.

D. THE FEEDING OF ZOOPLANKTON The trophic relationships of animal plankton species is a complex problem. Perhaps the copepods are best known for their food requirements and of these Calanus has been particularly studied. An excellent summary is included in the work of Marshall and Om (1955): a wide variety of diatoms is utilized as food, from the large Coscinodiscus and Ditylum to the smaller species such as Skebtonema and Nitzmhia closterium. Dinoflagellates such as Peridinium, Gymnodinium, md Prorocentrum are also widely eaten, but there is some selection; for I a m greatly indebted to the authors for permission to use the unpublished data

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example, Ceratium is apparently not taken. Sinall nanoplankton flagellates can also be consumed, though these must probably exceed 2-3p diameter; a small species such as Nannochhis may not therefore be retained. Marshall and Orr have also studied the problem of the suitability of phytoplankton species as nourishment, using oviposition as a criterion. Thus, while all diatoms appeared to be useful as food, only some flagellates were satisfactory. For example, diets of Dicrateria, Hemiselmis and Chlorella apparently did not contribute to egg production. Beklemishev (1954) found that the copepads Calanus spp. ,Metridia spp., and Eucalanus consumed mainly diatoms in northern Pacific waters; larger cells were definitely crushed by tbe mouth parts. I n more southern latitudes, more flagellates, dinoflagelltrtes and coccolithophores were also eaten, and this was probably true during the summer months in more temperate waters. With small copepods such as Pseudocalanus, Parmalanus, Tenma, and Acartia, the diet appears to be rather similar, mainly diatoms and certain flagellates (cf. Gauld, 1951; Raymont, 1959; Raymont, 1963), but differences exist. Thus Conover (1956) has suggested that although Acartia feeds on a wide variety of phytoplankton, the setae are rather coarse so that Acartia tends to be a ‘‘wasteful” feeder. More interesting differences arise however with species such aEsCentropages, Labidocera and Anomalocera which appear to be at least partly carnivorous. Anraku and Omori (1963) confkm that certain calanoid species differ in their feeding habits. They examined the mou1;h parts of the calanoids and made feeding experiments using diatoms, animal food (Artemia nauplii), and a mixture of the two. Results showed that whereas Calanus Jinmurchicus was essentially herbivorous, Acurtia tonsa, Centropages hamatus and Centropages typicus were essentially omnivorous, with Centropages apparently preferring animal food. LabicEocera was almost entirely predatory, and this applied even more strongly to Tortanus discaudatus (cf. Kaymont, 1963). Gauld (1964) agrees that Anomalocera and Labidocera are essentially carnivorous, and that Centropages, Temora and Acartia take some animal food. This problem of differences in the food eaten, even in one group of zooplankton animals, applies particularly to deep-living speoies. Thus Beklemishev found that deep living copepods such as Caidius and Uwtanus consumed large diatoms, and Conover (1960) has shown conclusively that Calanus hyperboreus, though a deep-living species, is essentially herbivorous. On the other hand, other deep-water species such as Bathycalanus and Eucheirella are in all probability partial carnivores, and Euchaeta, Scottocalanus, Megacalanus, and Valdiviella, amongst others, are almost certainly carnivores. Perhaps even essentially herbivorous species may take some animal food when food h3 scarce.

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Although a species such as Calunus appears to feed on a wide variety of phytoplankton there may be some selection. Harvey (1937) found that the copepod selected Lauderia in preference to Chaetoceros or Nitzschia. Mullin (1963) tested 4 species of Calunus on 8 different food species of phytoplankton. The larger-celled species were selected; from a mixture of 5 food species, the smaller nanoplankton algae contributed less than 6% to the diet. Petipa (1959) claims a considerable degree of food selection for Acartia spp. from the Black Sea. Less is known of the diet of other groups, but among the euphausids Euphausia superba (Barkley, 1940) appears to be exclusively a herbivore, feeding on diatoms, probably selecting the smoother celled, smaller species. On the other hand, species of Thysanoessa and Meganyctiphanes are believed by Einarsson (1945) to be essentially detritus feeders or carnivores. Work in the Clyde sea area (Macdonald, 1927; Mauchline, 1959) suggests that Meganyctiphanes is largely a filter feeder in the smaller stages, while the larger older forms are mainly carnivorous on copepods and on other zooplankton; some detritus appears to be taken. Some mysids filter phytoplankton effectively, and in shallow water may live on bottom material and detritus. Bathypelagic species are usually regarded as mainly carnivorous though some detritus is probably eaten. Ostracods were also thought to be filter feeders, but Cannon (1931; 1940) has shown that whereas Cypridina is a filter feeder, the large Gigantocypris mfilleri is apparently carnivorous. Loosanoff and his colleagues have investigated the food of bivalve larvae, especially those of Crassostrea and Venus mercenaria (Loosanoff and Davis, 1963). Food for young larval molluscs must be of suitable size; usually algal cells greater than lop in diameter cannot be ingested, but size is not the only factor. Thus bacteria and certain flagellates will not promote good growth in oyster larvae. Davis (1953) showed that 9 species of bacteria and 1 species of flagellate failed to produce growth, although 5 other flagellate species (Dicrateria, Hemiselmis, Isochrysis, Chromulina and Pyramimonm) all gave good growth. The requirements even changed with the age of oyster larvae. The larvae of Venus mercenaria appear to be able to grow on Chlorellu and even on some bacterial cultures which are unsuitable for oyster larvae. However, for many bivalve larvae a mixture of Momchrysis and Isochrysis appears to be most suitable (cf. also Walne, 1963). The specific food requirements of cirripede larvae have also been investigated. Early work suggested that diatoms and flagellates might be utilized, but the work of Costlow and Bookhout (1967, 1958) indicated that algal (Chlanzydomonas)food needed to be supplemented with a little animal (Arbacia eggs) material. Moyse (1963) has recently added

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a more detailed study of the food requirements of different species of barnacles. Ohlorella and Dunaliella were valueless apparently for all species. Balanus balanoides was successfully reared on diatoms (Skeletonema, Ditylum, Asterionella), but not on flagellate diet. On the other hand, Chthamalus could be reared on severd flagellate species, but diatoms were not utilized. Most fish larvae, though they may take a small amount of phytoplankton food in early stages, feed mainly on zooplankton. Cod larvae feed on euphausids, decapod larvae, and other crustaceans; occasionally they take the larvae of other fishes (Wiborg, 1948a and b, 1949). Most investigators have emphasized the importance of copepods as food for larvae of fishes, and both Marak (1960) and Wiborg emphasize the question of size selection. However, there may be a greater degree of selectivity. Shelbourne (1963, 1957, 1962) showed that while small copepod nauplii were taken by larval plaice, the appendicularian Oikopleura was the most important constituent in the diet. Ryland (1964) has recently confirmed the overwhelming importance of both Oikopleura and Pritillaria as food for larval plaice. Except for fish larvae, our knowledge of the food habits of carnivorous zooplankton is particularly fragmentary. Pelagic heteropods are known to feed on copepods but to a large extent on chaetognaths. Medusae and ctenophores are known to feed on copepods, on sagittae and on fish 1arva)e.The ctenophore Beroe feeds on Pleurobrachia;apparently in Russian waters it feeds exclusively on Bolinopsis. The siphonophores are an exclusively carnivorous group feeding on such zooplankton as copepods and other crustaceans, but recently, in Florida waters, Bayer (1963) ha:3 observed that Velella, Porpita, and even Physalia are themselves eaten by the snail Janthina. Although our knowledge is limited, the complexity of the zooplankton food net is quite extraordinary. Our knowledge of the diet of bathypelagic plankton is far less. Most deep-sea plankton has been regarded as filtering out detritus particles, or being carnivorous on other plankton. Vinogradov (1962b) has pointed out that small particles will decompose fairly rapidly during their descent into the deep layers and , probably only the resistant non-assimilable fraction remains. The problem of how far bacteria might add to the food of zooplankton has been investigated to some extent, mainly with surface plankton animals, chiefly copepods and bivalve larvae. I11 general, bacteria seem to be unimportant. I n any event, in really deep water most microbiologists suggest that the bacterial population is very much reduced; there is doubt whether it could add significantlj to the diet of the larger zooplankton. It is possible that bathypelagi c plankton (copepods, mysids, and decapods) could filter off Radiolaria and Foraminifera occurring in the deeper water layers (cf. Vinogrsdov, 1962b).We do not

I

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know the specific requirements of these protozoans, but some Radiolaria might consume bacteria. Murray (1963)suggests that Foraminifera can feed on dead material and possibly on detritus and bacteria, though living phytoplankton appears to be preferred. However, the recent work of Freudenthal and his colleagues (unpublished),* using labelled food cultures, shows that planktonic Foraminifera prefer Nitzschia and some flagellates; bacteria although ingested apparently do not contribute to the nutrition. Vinogradov (1962b) suggests that zooplankton from intermediate depths by extensive diurnal vertical migrations obtains food from the upper water layers. Faecal pellets produced by this migrating plankton may assist with the nutrition of the plankton of the deeper layers. Apart from these coarse filter feeders, the majority of the deep-sea plankton will be carnivorous.

E.ALTERNATIVE FOOD SOURCES FOR ZOOPLANKTON The k d i n g s of Bernard, Wood, and others that various Protophyta may occur in the deep layers of the ocean, far below the euphotic zone, implies that these plant cells may also serve as food for deep-sea zooplankton. However, the amount of food available to deep-sea plankton must be extremely limited. There is little doubt as Zenkevitch and Birstein (1956) have suggested that deep-sea plankton is very reduced in density. Vinogradov (1962a) has commented on the extraordinarily rapid reduction of biomass of zooplankton in really deep water. At high latitudes, for example, he suggests that the biomass below 6 0001 metrea is only l/lOOOth that of the uppermost water layers. Although Vinogradov believes that few deep-sea animals feed mainly on detritus, this may be an important accessory food. Investigations, especially summarized by Krey (1961), suggest that detritus can account for a very large fraction of the total organic suspended matter; this is true even of the surface layers where the contribution from living plankton may be expected to be high. I n deeper water the actual quantity of orgmio matter is much lower, but the proportion of detritus may reach almost 100%. I n a later study, Krey (1964) shows that despite considerable fluctuations in the amount of suspended matter, there is a marked tendency for the amount to fall with depth and in very deep water extremely little material is present. This Krey attributes partly to the eating of material by organisms in the upper layers, but above all to the mineralization processes occurring in deep water. The fraction of living material in the total suspended matter shows, as would be expected, 8 remarkably sharp fall in really deep water. Although the very small amount of suspended material in deep waters

* I em much indebted to the authors for permission to use their data.

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may be used by filter feeding animals, there is in relative terms a far greater amount of dissolved organic material (of. Duursma, 1961).Putter (1909, 1925) suggested that this dissolved malker might be used as food by marine animals, but direct experiment indicates that even if metazoans can absorb such substances, the gain in energy will be negligible. But small protozoans might utilize dissolved organic material effectively. Apart from relatively large planktonic protozoans such as Radiolaria and Foraminifera, there may be a considerable population of very small protozoans, particularly ciliates, in the seas. If such ciliates could feed on the dissolved matter, they in turn could serve as the base of a food chain leading to metazoan bathypelagic plankton. Heterotrophic bacteria are certainly able to use dissolved organic material, and in forming particulate living substance, they could serve as food for Protozoa, or in turn, for Metazoa. Elventhough Metazoa may not filter bacteria directly, a food chain through larger Protozoa could build up a useful food supply in deep water. The problem, however, largely turns on the density of heterotrophio bacteria in deep-water layers. Plating techniques and direct counts can give markedly variable assessments of the bacterial population. Moreover it is almost impossible to separate bacteria quantitatively by filtralion; a considerable proportion of the bacteria will pass even very fine filters and thus comparisons of the amount of particulate organic matter left on the filter and of the so-called “dissolved” organic maliter passing through the filter cannot give a correct assessment of the bacterial population. To a large extent bacterial substance will be included in the “dissolved” organic fraction. Earlier observations summarized by Zobell (1946) suggest that deep water has relatively small populations of bacteria. Kriss (1963), however, indicated that even in deep-water layers there may be considerable populations of heterotrophic bacteria, especially in tropical waters, which Kriss considered richer in organic material. The recent investigations of Sorokin (1964b) throw doubt on these rich populations of heterotrophic bacteria in deep water. Even a limited heterotrophic bacterial population, in providing particulate material for higher trophic levels, would be of great advantage in deep water. Parsons and Strickland (1962) have attempted an assessment, and have assumed a value of 0.1 mg. per m3 as the standing crop of microheterotrophs. Assuming a growth rate similar to the phytoplankton, they obtain a production equivalent to about 0.5 - 1% of that due to photosynthetic organisms. But bacteria can exist through the whole column of water, and even though their denriity is much reduced at deeper levels, their contribution to the production of particulate living matter may not be inconsiderable. Another possible source of particulate food for the zooplankton in the

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oceans appears from the recent investigations of Baylor and SutcliBe (1963). They observed that particulate organic matter may be formed in sea water when active foaming occurs from the dissolved organic matter. Riley (1963b) also discusses the adsorption of dissolved organic matter onto the surface of bubbles to form particles. Such particles consist not only of organic aggregates, but have interstices which may then trap bacteria and even plankton and inorganic material. Bacteria and protozoans may use this substrate and in turn these particles may serve as food for zooplankton. Riley has shown that this organic aggregate material may be an important accessory food source in inshore waters. How far such material may be formed in deeper water, where presumably bubbles are absent, is uncertain. Whatever particulate material is present could presumably serve as a surface for the adsorption of dissolved organic material. Thus the detritus may not be only relatively non-assimilable matter.

F. ZOOPLANKTON - QUANTITATIVE FOOD REQULREMENTS There are several suggested routes, by which the reservoir of dissolved organic matter in the oceans might be transformed into particulate material, but there is little possibility yet of any quantitative assessment. Indeed, even the quantitative particulate food requirements of individual species of zooplankton are but poorly known. Few species have been accurately studied, and most investigations have centred round assessing filtration rates in filter feeders, or in measuring respiration rates to estimate metabolic requirements (cf. Raymont, 1963). An indication of the quantitative dietary needs of zooplankton arises from work on copepods, chiefly Calanus. Despite considerable variations in filtration rate recorded by investigators, a mean rate of 70 cm3/Calanus/dayappears to be generally acceptable. Experiments by Marshall and Orr (1955) using phytoplankand W, however, have suggested rather lower ton food labelled with 32P values. With rates of the order of 70 cm3/day, the average phytoplankton crop in temperate waters should be sufficient to cover maintenance requirements. But at times of the year phytoplankton is scarce and it seems unlikely that all the herbivorous plankton will find enough food, not only for maintenance, but for growth and reproduction. However, we may be misled by thinking of herbivores as automatic filterers. Several workers have suggested that food may be actively sought, and Cushing (1959a)has proposed from his “encounter feeding theory” that considerably greater quantities of food may be secured. Gauld (1964) points out that some copepods (Acartia, Centropages, Temora, Pseudocalanus and perhaps Calanus) can feed by a sweeping movement of the maxillae (“scoop net feeding”) as well as by the usual filtration method.

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The amount of food collected by these two methods may be very different, and the extent to which each meclianism is used depends in part on the type of food available. Carnivorous copepods (Anomahera, Labidocera) use the sweeping movements of the maxillae to secure their prey and this mechanism is also used by partly carnivorous species such as Temora and Centropages. Cushing ( 1964) believes that considerable superfluous feeding occurs with herbivorous copepods such as Calanus (cf. Beklemishev, 1962). Active reproduction is limited to such periods of excessive feeding. Even so, a considerable quantity of food is “wasted”. Cushing believes that very high grazing rates are typical of Calanu-s, but when there is extensive searching for limited food, egg production ceases. Petipa (1959) believes tihat the average dietary requirements of Acartia in the Black Sea, amounting to 4% of body biomass per day, cannot normally be met without the inclusion of a considerable amount of zooplankton food. Animal food plays a particularly important part during periods of activt: reproduction. The investigations of Corner (1961) and of Cowey and Corner (1963) tend to show that sufficient food material for Calanus is present in sea water. They analysed the total amount of particulate matter in the water and then related this to the maintenance requirements. During winter, they suggest that Calanus needs to filter only 30 cm3/day, and in summer some 50 cm3/day. Marshall and Orr (1964) have listed the amounts of phytoplankton organic matter itnd the total particulate organic matter in different marine areas. Although the quantities in coastal waters are relatively high and appear to be sufficient for the requirements of copepods, the amounts in open oceans and in deep water are very much lower and would certainly seem to be inadequate for herbivorous zooplankton. Even in inshore waters the seasonal variation in total particulate organic matter is not well known. Marshall and Orr suggest that while during a spring diatom increase a great excess of food is present, it is doubtful whether in winter the amount available would cover requirements. The food requirements for a number of copepod species based on respiration rates are given. Some of the daily requirements appear to be very high; moreover far more food will be required for growth and reproduction. Further detailed metabolic studies are needed before we can measure these additional food requirements. A comparison of the metabolic needs and the body reserves for some zooplankton, however,has suggested that the requirements may be exceedingly high (Conover and Raymont, unpublished; Anraku, 1964).

VII. CONCLUSION Primary production in the oceans is mainly dependent on phytoplankton, though in shallow coastal waters the important contribution of the Q.

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benthic microflora and macroflora has probably been underestimated. Oceanic areas a t low latitudes may show, over short periods, high rates of primary production owing to temporary nutrient enrichment, but in general the low level of the major plant nutrients (nitrate and phosphate) in tropical and subtropical areas, with the permanent thermocline restricting vertical mixing, markedly limits annual productivity, despite the much greater depth of the illuminated zone. I n temperate and sub-polar regions, although production rates vary markedly over the year owing to the great seasonal differences in depth of light penetration, the greater nutrient concentration leads to increased annual production. At high latitudes, very high rates of production may hold for short periods, but the time of abundance tends to be short. Productivity in the Antarctic is high; in the highest Arctic latitudes, however, the annual production is very low. Upwelling areas in lower latitudes show greatly increased production. The effect of temperature on productivity is essentially indirect since its main influence is on the stabilization of the upper water layers. In a few areas salinity differences may also assist in stabilizing the upper water layers and thus may affect production. The establishment of a seasonal thermocline sharply limits production but the drop in phytoplankton crop in temperate and higher latitudes during early spring is more often due to grazing than to nutrient lack. The effect of a discontinuity layer in reducing replenishment of nutrients from deeper layers has its main effect on phytoplankton production during the summer period. The direct regeneration of nutrients within the euphotic zone is therefore of primary importance in production over the summer period at higher latitudes; it is always of great significance at lower latitudes. Although trace elements and organic substances are required by many marine algae, there is little evidence for believing that decreased concentrations of these substances affect total production, except perhaps temporarily in some tropical oceanic areas. The varying amounts of such materials between inshore and offshore waters may, however, influence the composition of the phytoplankton population. I n general, areas of high primary production have large standing crops of algae; the temporal variations in crop, especially at higher latitudes also usually parallel the changes in production, except that heavy grazing may reduce the crdp over summer. High densities of zooplankton are found only in regions of richer phytoplankton; a sparse distribution of algal cells involves the herbivorous zooplankton in excessive searching for food so that less energy is available for growth and reproduction. Some degree of “wastefulness” in the grazing of herbivores on the phytoplankton is likely at higher latitudes and is more generally true at all latitudes in neritic regions. The “wastefulness” arises mainly from

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the blooms of phytoplankton and the growth of zooplankton being somewhat out of phase. Provided the blooming of the phytoplankton is not too accelerated, however, the “wastefulness” is not excessive and in any event the partly used phytoplankton crop serves as food for deeper living zooplankton and for the benthos. Oceanic depths have a much reduced zooplankton population. The main limitation would appear to be the amount of particulate orgahic matter available as food. While the vertical migrations of the zooplankton to different levels in the oceans carries organic particles such as faecal pellets to greater depths where they can be used by the deeper filter-feeding zooplankton, the nutritive vitlue of such particles is probably not very high. Protozoa, especial1.y ciliates, feeding on the relatively much greater quantities of dissolved organic matter in the deep oceans, either directly or via bacteria, Sorm a second food source for filter-feeders. Some bathypelagic planktonic species may feed directly on bacteria but the density of micro-organisms in the open oceans is probably never high. Organic aggregates can be formed from dissolved organic matter in the oceans and this material may serve as another source of food for the zooplankton. At moderate depths in certain warmer seas the deeper-living phytoplankton may also form a subsidiary food supply. Carnivorous species are always prominent in deep-sea zooplankton populations; they appear to be capable of feeding on a wide variety of planktonic animals. The precise nutritive requirements are known only for very few species of zooplankton, mainly Culanus. I n inshore waters phytoplankton production is more than sufficient for zooplankton growth and reproduction over the spring and summer; during winter the total quantity of particulate organic matter is probably also sufficient for maintenance requirements, if it is assumed th,at all such organic matter can be assimilated by the animals. The requirements of oceanic and especially of deep-sea zooplankton species art? virtually unknown, and the amount of particulate matter in the open oceans, especially at great depths, appears to be very limited. Any clear ,assessmentof the production of oceanic zooplankton must await metabolic studies on oceanic species.

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Abbott, B. C. and Ballantine, D. (1957). J . Mar. 13iol. Ass. U . K . 36, 169-189. Toxin from Gymrwdinium venqficum Ballantine Allen, E. J. andNelson, E. W. (1910).J . Mar. Biol. .tiss. U . K . 8,421474. On the artificial culture of marine plankton organism. Anderson, G. C. (1964). fimnol. & Oceumgr. 9,284-302. The seasonal and geographic distribution of primary productivity 08 the Washington and Oregon coasts.

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Anraku, M. (1964). Limnol. & Oceunogr. 9, 195-206. Influence of the Cape Cod Canal on the hydrography and on the copepods in Buzzmda Bay and Cape Cod Bay, Massechusetta. I1 Respiration and feeding. Anraku, M. and Omori, M. (1963). Limnol. & Oceunogr. 8, 116-126. Preliminary survey of the relationship between the feeding habit and the structure of the mouth-parts of marine copepods. Ansell, A. D., Raymont, J. E. G., Lander, K. F., Crowley, E. and Shackley, P. (1963). Limnol. & Oceanogr. 8, 184-206. Studies on the maas culture of Phaeodactylum. 11. Ansell, A. D., Coughlan, J., Lander, K. F. and Loosmore, F. A. (1964). Limnol. & Oceanogr. 9, 334-342. Studies on the mass culture of Phaeoo!m%ylum.IV. Antia, N. J., McAllister, C. D., Parsons, T. R., Stephens, K. and Strickland, J. D. H. (1963). Limnol. & Oceanogr. 8, 166-183. Further measurements of primary production using a large-volume plastic sphere. Austin, T.S. and Brock, V. E. (1959). Int. Ocean. Congress Prepints, A.A.A.S. Waahington 130-13 1. Meridionalvariations in some oceanographicand marine biological factors in the Central Pacific. Barker, H. A. (1935). Arch. Mikrobiol. 6, 157-181. The culture and physiology of marine dinoflagellates. Barkley, E. (1940). 2eit.fiir Fischerei der Hilfswissen. 1 ( l ) ,65-156. Nahrung und Filterapparat des Walkrebschens Euphausia superba Dana. Barnes, H. (1957). Anned Biologique 33 (1-2), 67-85. Processes of restoration and synchronisation in marine ecology. The diatom increase and the spawning of the common barnacle, Balanus balanoides (L). Bayer, F. M. (1963). Bull. Mar. Sci. Gulf Caribb. 13, 4 5 6 4 6 6 . Observations on pelagic molluscs associated with the siphonophores Velella and Physalk. Baylor, E. R. and Sutcliffe, W. H. (1963). Limnol. & Oceanogr. 8, 369-371. Dissolved organic matter in seawater as a source of particulate food. Beklemishev, K. V. (1954). Zool. J . Inst. Oceanol. A d . Sci. U.S.S.R. 33, 12101229. Feeding of some common plankton copepods in Far Eastern Sees. Beklemkhev, C. W. (1962). Rapp. Proc. Verb. Cons. Perm. Int. Explor. Mer. 153, 108-1 13. Superfluous feeding of marine herbivorous zooplankton. Belser, W. L. (1959). Int. Ocean. Congresa Preprints, A.A.A.S. Washington, 908-909. Bioassay of organic materials in sea water. Belser, W. L. (1963). “The Sea”, Vol. 2 (M. N. Hill, ed.), Ch. 9, 220-231, “Bioassay of trace substances.” New York and London: Interscience Publishers. Bernard, F. (1939). J . Conseil int. Explor. Mer. 14, 228-241. g’tude sur lea variations de fertilit6 des eaux m6diterran&nnes. Bernard, F. (1953). Deep Sea Res. 1, 34-46. RBle des flagell6s calcaires dam la fertilit6 et la s6dimentation en mer profonde. Bernard, F. (1963). I n “Marine Microbiology” (C. H. Oppenheimer, ed.), Ch. 22, 215-228. Density of flagellates and Myxophyceae in the heterotrophic layers related to environment. Springfield, Ill.: Thomas. Bernard, F. and Lecal, J. (1960). Bull. I&. Oceanogr. Monaco. No. 1166, 1-59. Plancton unicellulaire r6colt6 dans l’oc6an Indien par le “Charcot” ( 1950) et le “Norsel” (1955-56). Bigelow, H. B. and Sears, M. (1939). Mem. Mua. Comp. Zool. (Harvard) 54, 183-378. Studies of the waters of the continental shelf, Cape Cod to Chesepeake Bay. 111.A volumetric study of the zooplankton. Bigelow, H. B., Lillick, L. and Sears, M. (1940). Tram. Am. Phil. SOC.31, 140191. Phytoplankton and planktonic protozoa of the offshore waters of the Gulf of Maine. Part I. Numerical distribution.

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The Dynamics of a Field Population. of the Pine Looper. Bupalus piniarius L (Lep., Geom.)

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H. KLOMP

Department of Zoology. Agricultural University. Wageningen. Netherlands

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I Introduction 207 A. The Area of Investigation ......................................... 208 B The Lifecycle of the Pine Looper ................................... 209 C The Pine Looper aa an Object for Populatior. Studies................. 211 I1 Methods of Measuring Density........................................ 211 A Density of Eggs and Larvae ....................................... 211 B Density ofNymphs 220 C Density ofPupae ................................................ 223 D Density ofMoths................................................. 229 E The Dispersion of Nymphs, Pupae. and Moths....................... 233 I11 Annual Routine Rearings............................................. 233 A Rearing ofEggs .................................................. 234 B Rearing ofLenrae ................................................ 237 C Rearing of Pupes ................................................ 240 D Rearing ofMoths ................................................. 240 IV Annual Variations of the Reproductive Rate ............................ 240 A The variability of Fecundity Within One Generation .................242 B The Variability of Fecundity Between Generations................... 268 267 V The Composition of Life Tables ....................................... VI The Analysis of the Causes of Fluctuation .............................. 273 A The Pattern of Fluctuation ........................................ 273 B Key-fector Analyeis 276 VII The Analysis of the Causes of Regulation............................... 286 A . The Incidence of Regulation....................................... 286 B Density Dependent Fecundity ..................................... 288 C DensityDependent Mortality ...................................... 289 294 D Delayed Density Dependent Mortality.............................. VIII Final Considemtions................................................. 299 Acknowledgments 303 References............................................................... 303

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I . INTRODUCTIOK In general it can be stated that in the field of population dynamics three main problems deserve special attention; these, briefly stated (see also Wilbert, 1962; Klomp, 1962), are: 1 . By and large the numbers of an animal in a particular habitat 207

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fluctuate irregularly. This raises the question of the causation of density fluctuations. 2. Although fluctuations do occur, with some exceptions the density of such a population changes within relatively narrow limits. It is often stated that this is due to regulation, i.e. high densities cause mortality and emigration to exceed reproduction and immigration, and low densities induce the reverse effect. These density-governed reactions form the central problem in many population studies. Nevertheless, especially in field populations our knowledge of the relationships which stabilize numbers is still very scanty. 3. The density of any one species is often stabilized at different levels when in different types of suitable habitats. This must be due to an environmental influence on the relation between regulating factors and density. The study of this problem is a comparative one, and it will be the last stage to be solved, and then only after a thorough analysis has been made of the co-action of factors affecting reproduction, mortality and migration.

The present paper is devoted solely to the first two problems; the third being left out of consideration because the investigations reported here apply only to one area. Our aim was to analyse the variability of numbers of an insect, and the relations between density and factors affecting mortality and reproduction. Therefore, we measured the density of all stages of the insect, its reproduction, and the influence of as many mortality factors as possible. A.

T H E A R E A O F INVESTIGATION

The study has been carried out in a plantation of Scots pine (Pinua sylvestris), in the north-western part of the National Park “De Hoge Veluwe”, near Otterlo, province of Gelderland, the Netherlands. The area is situated on flat preglacial sands and the trees were 45 years old and 10 m high in 1950, when the investigations were begun. The size of the plantation is 20 ha (approximately 50 acres), but the observations were all performed in the central part of it, hereafter referred to as the study area, the size of which is 6.8 hectares. This area is divided in six blocks by narrow paths (Plate 1 and Fig. 5 ) . The sands in the study area are covered with a litter layer of 3-5 cm thickness, which is nearly completely overgrown with moss, with some patches of grass and blueberries. It is a pure stand of Scots pine; other trees and shrubs are lacking. The growth of the trees is slow and their density normal with a fairly good closure between the crowns. A characteristic view of it is given in Plate 1.

PLATE1. Study area in the National Park “De Hoge Veluwe” 25 km north-west of Arnhem.

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DYNAMICS O F FIELD POPULATION OF PINE LOOPER

B. THE LIFECYCLE

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OF THE P I N E LOOPER

The geometrid, Bupalus piniarius L., chosen as an object for this study, is univoltine (Fig. 1). The moths emerge from the litter in MayJune over a period of nearly five weeks. This emergence has a daily periodicity, the moths appearing between 7 and 9 hr. The males start appearing some days earlier than the females. Immediately after having reached the surface the adults search for an object, e.g. a small protruding stick, which enables them to hang upside down and freely expand the wings to their full size. One or two hours later, depending on temperature, the insects take flight. The females soon settle down in the tree crowns, whereas the males take part in a tumbling courtship flight, exhibited around the crowns during the morning hours, i.e. shortly after the emergence of the females. The function of this flight can be interpreted as a search for virgin females. Copulation usually take place in the crowns, and 10-20 hours later the females start egg deposition. The eggs are deposited on the needles in clusters of 2 to 25. After each act of oviposition the moth has a period of rest, and- before resuming the laying act again - a short flight is performed as a result of which the nearly 180 eggs of one female are more or less randomly distributed on the crowns of several trees. The total number of eggs of one female is laid within 8-14 days, the lifetime being highly dependent on temperature. Normally, the last females t o emerge die about mid July. After its natural death the oviduct of the female may still contain up to 10 mature eggs with fully developed chorion; in the ovarioles, a large number of oocytes in all stages of development is always present. The first instar larvae hatch about 20 days after oviposition. They bite a hole in the chorion and leave it, but do not eat it, so that the empty egg shells are still present on the needles some weeks after hatching . The young larvae disperse by crawling and soon afterwards start to eat, making small grooves in the needles. The growth of the larvae is slow, passing through five or six instars from 1,he beginning of July up to mid October. During this period there is ctn enormous increase in size, the body length increasing from 3 mm immediately after hatching, up to 40 mm when fully grown. The larvae descend to the litter from the beginning of October up to mid November. They simply fall from the twjgs on to the moss cover and normally penetrate into the litter layer with@ 10-15 minutes, during which period they crawl around, presumably in search of a suitable place for penetration. The larvae which are ready to descend are

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DYNAMICS OF FIELD POPULATION O F P I N E LOOPER

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easily recognizable because their segments are more pronounced (Fig. 1). This stage will be called “nymph” (= pre-pupa) in this paper. The nymphs normally enter the upper layer of the litter and make a small chamber lined with silken threads in which they pupate. The pupae enter diapause, which is broken by low winter temperatures, after which they are reactivated by rising spring temperatures (Schoonhoven, 1963). For more details on the bionomics the reader is referred to Escherich (1931).

c. THE P I N E LOOPER AS AN OBJECT FOR POPULATION STUDIES The pine looper, also named the bordered white, was suggested as a suitable object for this study by the late Prof. L. Tinbergen. His starting point was that a long-term study of the factors affecting reproduction and mortality requires a habitat as stabble as possible, and as already suggested by Varley (1963), forests am very well suited in this respect. Secondly, the non-patchy distribution of this insect enables the assessment of density with reasonable statisticid accuracy. Finally, this species is by far the most numerous of the bigger insects living on pine trees, and hence can be collected in all stages in sufficiently large numbers for rearing purposes (Klomp, 1962, Fig. 16).

11. METHODSOF MEASURINQ DENSITY Density has been assessed in the egg, larvd, nymphal, pupal, and adult stages of the insect. The methods used are quite different for the stages living on the trees (egg and larva) and 1;he others. Nevertheless, we were able to express all density data in nnmbers/m2. For eggs and larvae this has been done indirectly via the amount of shoots, for the others directly by counting the numbers/m“ ground surface. These methods will be described briefly for the various stages.

1. Methods

A.

DENSITY O F EQQS AND LIARVAE

The assessment of the density of the tree-living stages involved a much more complicated method than those used for nymphs, pupae, and adults because density had to be expressed in numbers per unit of ground surface t o enable a direct comparison of the density of different stages of the insect. The method used is based on the following formulation.

R m =Rs x B m

(1)

where R m = mean number of eggs or larvae per m2, i.e. the number in an imaginary column with a brtse of 1 m2 and an unlimited height.

212

H . KLOMP

1,= mean number of eggs or larvae per shoot. grn = mean number of shoots/m2,i.e. the number present in the column just mentioned. (a)Mean number of eggs or larvae per shoot. N , is estimated by taking samples of twigs cut off the trees. When larval density is measured each sample is composed of twigs cut from six trees. These trees are selected at random by going criss-cross through the study area, sampling the tree which is nearest whenever 50 steps have been taken. The successive trees are numbered 1-6 and are sampled in three sacks of cloth in the order 1-4, 2-5 and 3-6 (Fig. 2). Hence, in each sack the twigs of two trees are mixed. It takes half a day to collect a sample of this size. When egg density is measured two sacks are normally used, and four trees are sampled. A ladder is carefully placed in the tree, and the sack which can be hooked on with open mouth to the branches (Fig. 2) is placed in the lower part of the crown. Then a large number of twigs are cut off with great care and collected in the sack. The twigs are cut off at the older leafless parts and from all levels in quantities proportional to the size of the crown (Fig. 2). If the sample is used to estimate egg density the parts of the twigs bearing needles are cut in pieces of about 5 cm and these are thoroughly searched and any eggs found are collected. If the sample is used to estimate larval density the sacks are successively placed in a container which is gradually filled with carbon dioxide to anaesthetize the larva which can be shaken off the twigs onto a cloth spread over the ground. The effectiveness of this treatment is checked by repeating the whole procedure. The larvae collected are stored in ethyl alcohol. I n the twig mass of each sack the number of yearling shoots is counted. Pine trees produce new shoots at the tops of nearly all twigs once a year in June (Fig. 2). These shoots can be recognized when fully grown by the more light-coloured needles and the absence or smaller amount of algae. These characteristics can be used up to May of the following year. The number of shoots present in a sack is used as an index of the size of the sample. If their number/m2 were known, it would be possible to calculate the density of eggs and larvae, provided some conditions are fulfilled (see p. 217). It takes two persons one whole day to handle a sample composed of three sacks plus the counting of the shoots. As an example, some 1964 results are given in Table I. These show the variability of sample size (column 4) and of larval density (column 6 ) . The results obtained on three successive days can be pooled to calculate a mean density.

DYNAMICS O F FIELD POPULATION O F PINE LOOPER

213

FIG.2. Sampling of eggs and larvae. A. The sack. I:. The twigs are cut off a t the naked branches thus sampling needles of all year classes. The numbers refer t o year of growth. C. Diagram of a tree, showing the sector in which the branches have been cut off and collected in the sack. D. Study area with the rosition of six trees sampled on one day in three sacks.

(b) Mean number of shoots/m2.sin can be estimated as:

s, where and &

=

T x Bt

= mean

number of trees/m2,

= mean

number of shoots per tree.

can be estimated with adequate accuracy, by counting the number of trees occurring in about 175-200 plots of 5 :< 5 m.-Figure 3-A shows the distribution of these plots in the study area in 1954. Figure 3-B gives the frequency distribution of the number of trees per 25 m2 plot. H

214

H . KLOMP

TABLEI Data of 6 Twig Samples Taken in the Summer of 1954 to Estimate Larval Density 1

2

Sample Sack 90 91 92

92a 93

94

1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2

3

3

Date 9 Aug. 10 11

8 Sept. 9

10

5 4 Number Number of of shoots larvae 2 336 2 529 2 552 2 036 2 012 2 418 2 280 2 401 2 608

55 64 59 32 90 53 77 22 74

2 046 2 720 2 274 2 786 1986 2 163 1959 2 741 2 828

54 61 85 74 56 56 37 66 49

6 7 Number of larvae

per ma

per shoot 0.0236 0.0253 0.0231 0.0157

b" = 0.0251

/

J

0.0219 0.0338 0-0092 0.0282 0.0264 0.0224 0.0374

w, = 11.6

\

0.0189 0.0241 0.0173

& on the other hand is very variable as a result of an extreme variability of tree size. Moreover, only a limited number of trees can be cut down to count the number of shoots present. To avoid this difficulty we looked for a relation between the number of shoots per tree (St)and the size of the tree, expressed in the circumference of the trunk (C). This relation proved to be: log St = a

+ b log C

(3)

The parameters a and b vary year by year, and therefore have to be estimated annually. To achieve this about 46 trees whose trunk memurements were known, were felled each year to count the number of shoots present in the crowns (see Fig. 4). The values of a and b are estimated by a linear regression calculation.

216

DYNAMICS OF FIELD POPULATION OF PINE LOOPER

1 a Y

2 I0 rh

rb

70 TRUNK CIRCUMFERENCE (em)

FIG. 3. Measurement of the number of shoots/m*. A. The distribution of 177, 26 ma plots in the study area in 1954. B. T h e frequency distribution of the number of trees/ 26 ma plot in 1964. From this histogram the value Ip crtn be computed as indicated in the figure. C. The frequency distribution of the tnmk circumfe_rence of 811 tm meesured in the 177 plots shown in A. From this histogram the value C can be computed. See the text. The mean number of shoots/ma (8,) might be approximated as follows. The relation (3) also holds for the mean values: __ log St = a b log C (4) and according to (2) : log 8, = log F + log St,

+

which is approximately:

log 8, = log

and consequently, according to (4):

-

T + log St, --

+ + b log C

log 8, = log ! i ' a

The value of 8, computed in this way is biased because there is a difference between the mean logarithm and the logarithm of the mean of a variable. Mathematical considerations showed that the bias can be mbstantial.

We proceeded from the relation (3) by substituting for C the mean trunk circumference, 8,of 800-1 000 trees measured annually in all plots of 26 m2 referred to above (see frequency of trunk circumference in Fig. a), resulting in log Bt = a + b log C' (5)

and then according t o relation (2) B, can be computed.

216

H . KLOMP \

1.5

1

LOG

C

FIQ.4.The relation between the logarithm of trunk circumference (C) and the logarithm of the number of shoots (st)present in the crowns of 45 trees felled in November 1954. The regression function is log St = -0.312 2.346 log C.

+

As an example, the computation of B, in 1954 will be given. According to (Z), (3) and (5) we have to estimate: 1. the mean number of trees/m2, 2. the mean size of the trees 6 (trunk circumference between 1-50and 1.60 m; eye level) b log C. 3. the parameters of the relation log St = a i. I n 177 plots of 25 m2 806 trees were counted, i.e. 0.1821 treeslma (See Fig. 3-A, B). ii. The trunk circumference of 806 trees has been measured. Figure 3-C shows the enormous variability. proved to be 38.21 cm in 1954. iii. 45 trees were felled in November 1954 and the number of shoots counted on each tree. The data are plotted in Fig. 4. The parameters appeared to be a = -0.312 and b = 2.346. Hence, according to (5)

+

c

log St and

=

-0.312

+ 2.346 log 38.21 = 3.40054 St

=

2 515

DYNAMICS O F FIELD POPULATION OF P I N E LO O PER

217

From relation (2): B m = 0.1821

x 2 515

= 458

shoots

(c) The mean number of eggs or larvae/m2.Finally, we have to compute the mean number of larvae/m2. Having estimated the mean numand the mean number of shoots/m2 (8,) ber of larvae per shoot (gs) larval density can simply be derived according to relation ( 1 ) . As already stated on p. 212 this relation can be applied only when certain conditions are fulfilled. These conditions will now be discussed. First, the eggs of Bupalus are deposited on the older needles, probably because new shoots are very small and the needles are too short during the period of oviposition. After hatching, the larvae disperse and can be found later on needles of all ages, i.e. both 3n yearling shoots and on older twigs. Nevertheless, we expressed density as a number per yearling shoot (cf. Table I), meaning the eggs or larvae occurring in a mass of needles (of all year classes) corresponding i;o one yearling shoot. This is permissible only if the twigs are cut off i L t the older leafless parts (cf. p. 212). Secondly, a t the top of a tree the shoots are very long and stout and bear quite a number of needles. I n the lower part of the crown there are small shoots formed. Consequently, per unit of weight, the number of shoots a t the top is much fewer than a t the base of the crown, with intermediate values in the middle. This means that the twigs sampled must be taken from all levels of the crown itnd in proportional quantities (cf. p. 212). If the bottom part of the crown is overcut, then the number of shoots in the sample will be too high and its size overis based on all levels of the crown. It estimated, because the value proved to be extremely difficult to verify exactly the correctness of this aspect of sampling, because of the irregular growth of the branches. Therefore, control has been by sight only, trjing to cut off all the twigs occurring in a definite sector of the crown (Fig. 2 ) . Finally, the method may be biased because yearling shoots fall off during the period between sampling and measuring the value of B m . Sampling has been carried out from June up to the beginning of October, the felling of trees to determine b m has normally taken place in November, in a few years during September or 0ctol)er. On the lower branches some shoots may lose all their needles and drop off. The quantity of such shoots in three successive years was:

s,

5.3 shoots/m2. 1954 during the period 29 June-27 October 1955 during the period 29 June-19 November 7.0 shoots/m2. 1956 during the period 8 July-25 October 13.4 shoots/m2.

which comprised 1, 1.5, and 2.5% of the shoots present. These relatively

218

H. KLOMP

small quantities have been neglected in the computations of l m r d density. It is evident after these comments that the density can indeed be expressed in numbers/ma according to relation (1). As shown in Table I the mean number of larvae per shoot in 1954 on 10 August and 9 September is 0.0251 and 0.0252, respectively. Where S m amounts to 468, larval density appears to be 11-5 and 11.5, respectively. The calculation of a confidence interval for the estimate of the number of eggs or larvae/m2 has been made by the Department of Mathematics of the Agricultural University, Wageningen. The ultimate result, the 96% confidence interval, can be formulated as follows: where 1 = the mean number of eggs or larvae/m2.

t

=Student’s stochastic, the size of which depends on the number of degrees of freedom, and the latter again on the number of samples taken.

1, = the estimated mean number of specimens/ma. = the

s

standard deviation of

Wm.

I n August 1954 B m amounted to 11.6 (Table I), t = 2.31 with 8 degrees of freedom, and s = 1.74. Consequently, the 95% confidence interval equals 7.5-15-5 larvae/m2. I n other years s is about equal to 16% of also.

m,

2. The Density of Eggs After larvae have hatched, the empty and transparent choria remain attached to the needles for a considerable period but rarely for more than a year. Such choria will be covered by algae, and can readily be distinguished from freshly deposited eggs of the current year. Thus, egg density can be estimated after the last eggs have been laid. The last eggs are deposited about a fortnight after the emergence of the last moths, which was determined from counts of emerging moths in the field (see p. 229). Sampling normally fell in the period 6-20 July, with some variations as a result of the prevailing spring temperatures. Searching samples for eggs is very time-consuming (cf. p. 212), and therefore sample size or number had to be relatively small. In most years two or three samples (from eight or twelve trees) were taken, containing an amount of 8-10 000 shoots, being roughly equivalent to 20-26 m2 ground surface. In Table I1 the full results of a year with high and a year with low density are presented to give the reader an idea of the variability of

DYNAMIOS OF FIELD POPULATION OF P I N E LOOPER

219

TABLEI1 Reeults of Egg 8ampling in 1951 (High Density) and 1953 ( L mDensity)

Sample Sack

Number Number of of Date shoots eggs

32

1 2

1217 1217 1617 1617

09

1 2 1 2 1 2

2916 2916 317 317 017 617

31

70 71

1

2

836 738 1649 1197

372 684 893

2 160 2636 2 668 1892 2 279 2 662

34

Number of eggs per mr

per 3hoot

0.445 0.791 Re= R, = 0-677 0.4946a 0.4946 x 276= 136 ~

0.016

A 0.0140 x 460 = 6.3 28 43

0.012 0.017

/,I..

a. Standard deviation of mean 0.0690 (CoefBcient of variation 14F b. Standard devistlon of mean 0.0016 (Coemcient of variation 11

sample size and egg density between sacks. I n Table I11 the overall results of the estimates of egg density are given and these data are used in the analysis of the dynamics of the population (p. 267).

3. The Density of Larvae The first sampling for larvae is normally not carried out before the first half of August. Then, if weather is favourable, three samples me taken on successive days (Table I).At this time of the year the larvae are mainly in the second and third instar (see Fig. 11). If samples were taken earlier, many of the small first instar larvae could be missed. A similar sampling programme is carried out during 26 August to 10 September (Table I), when most are fourth instars (Fig. l l ) , and again in the period of 25 September to 10 October, when they paas through the last larval stage (Fig. 11). The estimates of density gained in these three periods of sampling will be referred to hereafter as the August, September, and October density. The variability between sacks within one sampling period is shown in Table I. The mean densities for August arid September (see Table I) together with the comparable results of all other years, are presented in Table IV. Finally, in Fig. 10 the complete density data of eggs and larvae are illustrated for years with low, intermediate, and high density.

220

H. K L O MP

TABLEI11 Results of Estimating Egg Density Mean number of eggs/shoot Year

fl*

1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964

0.1206 0.4945 0.1063 0.0140 0.1332 0.0732 0.1090 0.0509 0*0110 0.0532 0.0663 0.1323 0.2138 0.1019 0.0911

Mean Mean Coefficient number of number of of shoots/m2(a) egg_s/m2 variation 8 m

315 275 348 450 458 45 1 532 432 493 451 422 (461)b 463 (461)b (461)b

N m

%

38 136 37 6.3 61 33 58 22 5 -4 24 28 61 99 47 42

14 15 11 11 22 12 17 7 34 7 15 18 17 9 11

a. The coefficientof variation of this quantity varies year by year between 5 and 6%. In 1954, for instance, it is 5.3% giving a 95% confldence interval of 412 < Sm < 504. b. During the years 1961, 1963, and 1964 the number of shootslm' was not actually determined. The values given are means over 1953 and all later years.

B. DENSITY OF NYMPHS Nymphal density could be assessed by sampling the individuals falling off trees. For this purpose we used an apparatus which can best be described as a stoppered funnel (see Fig. 5 ) . The insects falling into the funnel slide down along the smooth walls and are killed within some minutes in rainwater which has collected in the closed point of the funnel. Superfluous water leaves the funnel through small holes in the wall a t 15 cm from the point (Fig. 5-A). During the years 1953-58 inclusive, about 50 funnels were placed in the study plot, each with an effective catching surface of 1 m2 (diameter 113 cm). From 1959 onwards about 100 funnels with a catching surface of 1/2 m2 (diameter 80 cmj were used. These funnels were placed in rows (see Fig. 5-B). Prior to 1959 they were 20 and later 10 steps apart, and their distribution was independent of the structure of the crowns. If the last step of a set of 10 or 20 happened to be very close to a trunk, the funnel was placed so as nearly to make contact with the trunk, the distance between funnel circumference and trunk being about 5 cm. This occurred with less than 3% of the funnels.

221

DYNAMICS O F FIELD POPULATION O F P I N E LOOPER

TABLEIV Results of Estimating Larval Density Mean number of larvae August Year

Per shoot

1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964

0.0302 0.0887 0.0046 0~0100 0.0251 0.0308 0.0284 0.0042 0.0073 0.0129 0.0178 0.0570 0.0536 0.0397 0.0141

Septemb,sr

per me 9:5 24.4 1-6 4.5 11.5 13.9 15.1 1.8 3-6 5 -8 7.5 26.3 24.8 18.3 6.5

Per shoot 0.0244 0,0814 0.0037 0.0101 0.0252 0.0266 0.0229 0.0019 0.0044 0.0082 0.0154 0.0556 -

b

0.0397

0.0080

per me 7 -7 22.4 1*3 4.5 11.5 12.0 12-2

0.8

2 -2 3.7 6.5 25.6 18.3 3 -7

October Per shoot 0.0273 0.0713 0.0036 0.0102 0.0197 0.0164 0.0164 0.0019 0.0051 0.0064 -

a

-

a

0.0320 0-0271 0.0050

per ma 8 -6 19.6 1-3 4.6 9 -0 7-4 8.7

0.8

2.5 2.9 -

-

14.8 12.5 2 -3

a. In 1960 and 1961 the October density has not heen estimated. b. In 1962 the moths emerged extremely late due to low spring temperatures. As a result of this the Brst samples could not be taken before 20 August. Therefore,the Septembersampling was cancelled; the October Sam ling was normal as a result of an accelerated growth of the larvae. For numbers of shootslm' see Tabfe 111.

The funnels were checked every other day, exceptionally daily, during the period of about the 1 October to 20 November, and the nymphs were collected (Fig. 5-C). See Fig. G-A for frequency distribution, and mean density computed at the end of the sampling period. Density estimates obtained by this method may be biased for various reasons. Firstly, some of the descending larvae may crawl down along the trunks of trees (Escherich, 1931). We never observed this behaviour, and we strongly doubt the correctness of this statement. The power of locomotion, characteristic of geometrid larvae, is partly lost in nymphs and the latter execute slow and clumsy mol-ements. Secondly, larvae escaping from the funnels or taken by predators would introduce an error. Not however if they fell into water and were inaccessible to predators. Thirdly, fully grown larvae sometimes fall off trees, but they could be distinguished from nymphs (cf. p. 211). The last question concerns the significance of the estimated means. These estimates are best expressed by the 95% confidence intervals of the means and this requires the frequency distribution of the number E*

222

H. KLOMP

A

NUMBER OF NYMPHS COLLECTED ON DATES GIVEN ON THE ABSCISSA

L C

TO

11

13

15

17

19 21 OCTOBER

23

25

2;

29

31

2

4 6 8 NOVEMBER

10

FIG.6. Assessment of nymphal density. A. The funnel used to catch the domending nymphs. B. T w o examples of the distribution of 100 funnels over the study area. In some yeara slight modifications of these patterns were used. C. Number of nymphs collected deily in 62 funnels of one m* each, in the autumn of 1964.

DYNAMICS OF FIELD POPULATION OF PINE LOOPER

223

of nymphs per funnel. This was obtained by fitting the observed frequency distribution against the Poisson series and negative binomial. Figure 6 shows that both distributions agree fairly well with the observed distribution. In &B(the Poisson series) P(r = x) = e - n p npx,’x!, where E(3) = np = 0.73 and 4.2 for 1967 and 1962, respectively. In 6-C(the negative binomial) P( g = x) = (k+$-l)px(l p)-k-x, where E(x) = kp = 0.73 and 4.2 for 1967 and 1962, respectively, and var (g)= kp(1 p) = 1.08 and 7.2 for 1967 and 1962, respectively.

+

.

+

To study the dispersion of nymphs we used the coefficient of dispersion defined by Fisher (see Milne, 1964). This is the quotient of variance and mean, c = $/it, which amounts to unity when the distribution is random, and is more than unity when the objects are aggregated or underdispersed. If we sample from a Poisson distribution, the stochastic c has a normal distribution, with mean = 1 and variance s% = 2n/(n - l)a.Thus, if the estimated value of c is outside the ran,ge 1 f 2sC,then the probability of the observed distribution being random is less than 5%. If then the objects ,are underdispersed. 21/{2n/(n c>1 As shown in Table V (columns 1-6) in all years studied the coefficient of dispersion is more than unity and, moreolrer, in 8 out of 12 years its value is outside the range. Consequently, th13 nymphs are more or less aggregated, and it is to be expected that the negative binomial gives a better fit. The negative binomial distribution has been fitted to the observed distributions each year, by taking E(g) = i i = (zxi)/n, and var (x) = s$ = { zx; - ( 1xr)2/n}/(n- 1). Two examples of this distribution are given in Fig. 6-C. The “goodness of fit” of these results were tested by the chi-square method (Table VI). It shows that in 1 out of 11 cases there is a significant deviation (level of significance a = 0.05) where we can expect this to occur once in 20 cases. Consequently, the agreement is satisfactory. The mean of a sample taken from a negative binomial, provided the sample is sufficiently large, has approximately a normal distribution; therefore, where the sample size is more than 50, the 95% confidence limits can be given by two times the standard deviation of the mean: it f 2sz - (see Table V, columns 7 and 8).

+

.

c. DENSITY

O F PUPAE

During the winters 1950-51 to 1953-54 inclusive, pupal density was assessed in December, i.e. shortly after pupation, and in April, i.e. just prior to emergence. I n later years only the April census was made, because winter mortality of pupae proved to be very low, and moreover,

224

H . KLOMP

1957

30--

20-

10-

4 962

A

M €AN 1.2 1'12 SQM. VARIANCE 7.2

MEAN 0.73ISO.M. VARIANCE 1.08

- ST. DEV. of -

ST.DEV. of MEAN:0.27

MEAN: 0.15

n

0

2

8

4

6

L

6 6 10 12 ? L 16 FUNNEL OF '/2 S 0 . M .

10

12

14

16

W

rn

I

'h

20

-Ih

C

2oi

10

0

2

NYMPHS

PER

FIQ.6. A. Frequency distributions of descending nymphs in a year with low density (1957; 51 funnels placed in the study area, each one m* surface), and in a year with high density (1962; 100 funnels placed in the study area, each 4 me surface). Soe Table V, B. Poisson distributions with the same means as in A. C. Negative binomial distributions with the same means and variances ES in A. See the text a d Table VI for fitting the graphs C to A.

TABLEV

Means, Variances, Dispersion, and Confidence Intervals of Nymphal Density 1

2

3

Year

Number of funnels

Mean number of nymphs/m2

1953 1954 1955 1956 1957 i95S 1959 1960 1961 1962 1963 1964

52 52 52 52 51 60 99 99 98 100 97 89

2.54 3 *46 3-23 4.13 0.73

.'a*- , 1

0.968 1.828 3.1 18 4.188 4.298 0.818

4

5

6

7

8

Variance

Coefficient of dispersion

95% Range of coefficient of dispersion

Standard deviation of mean

Confidence intervals

3-67 5 -43 4-55 6.78 1.08 2.06 1.18 2.03 4.29 7 *24 6 -92 0.97

14 4 1-57 1*41 1*64 1*48 i*i2 1-23 1.12 1-38 1.73 1.61 1.20

0.60 - 1.40 0.60 - 1.40 0.60 - 1.40 0.60 - 1.40 0.60 - 1.40 3.59 - i . 4 i 0.71 - 1.29 0.71 - 1.29 0.71 - 1.29 0.72 - 1.28 0.71 - 1.29 0.70 - 1.30

0.27 0.32 0.30 0-36 0.15 A on V.&W

0.11 0.14 0.21 0.27 0.27 0.10

2.01 - 3.07 2.84 - 4.12 2.64 - 3.86 3.42 - 4.85 0.43 - 1.02 11 1 -?t* - Y0 .Y0%. 0.74 - 1.17 1.53 - 2.10 2.70 - 3.53 3.66 - 4.70 3.73 - 4.85 0.61 - 1.01

.

226

H. KLOYP

TABLE VI

Goodness of Fit for the Negative Binomial to the Obeerved Distributions

of Descending Nymphs

Year 1963 1964 1966 1966 1967 1968 1969 1960 1961 1962 1963 1964 (1) N

=

(ii) P

=

Degrees of freedom Chi-square N-3 0-78 0-48 2.96 1-34 0.96 2.22 1-17 2.34 1.12 3-82 9-76

0.50

1 2 1 2 0 1 1 2 3 4 4 1

P 0-30-0*60 0*70-0*80 0*06-0~10 '

0-60-0.70 -

0.10-0.20 0-20-0-30 0-30-0.60 0.70-0.80 0.30-0-60 0.02-0.06 0.30-0*60

number of claasea entering into the calculation of xE after lumping to avoid expected numbers less than 8. probabilit that the observed distribution haa been sampled from a negative binomial pop.& tion distrliution with the same mean and variance.

the remnants of pupae killed by predators during the winter were still present and could nearly always be recognized in April. The data in Table V I I show that the differences between the two censuses were usually small. I n most Aprils 24 ma were searched for pupae. This is a time-eonsuming procedure taking 7 to 10 days for two persons. Each square is TBLE VII Cmpar&on of December and April Censua of Pupal Density, in the # a m Winter Mean number of pupae per mr

Winter

December

April

Difference

1948-49 1949-60 1960-61 1961-62 1962-63 1963-64

2.4 (14) 3.3 (14) 6.9 (16) 3.6 (19) 0.64 (11) 3.0 (24)

3.1 (14) 2.6 (7) 6.4 (24) 3.6 (18) 0.73 (22) 3.0 (24)

+O-7 -0.7 -0.6 +0.1 0.09

,

+

+o*o

(1) T h e data from 1048-40 and 1044.50 were collected by L. Tinbergen in hls area of observation at Hulshorst (see Tinbergen 1060). (ii) The numbers In brackets indicate the number of m' searched for pupae.

DYNAMICS O F FIELD POPULATION’ O F P I N E LOOPER

227

dug out and moss and litter are spread on a cloth in small quantities and examined carefully. The litter is then piit back into the square and covered with moss, which recovers within one to two months. The 24 squares are in diagonal rows in the study area (see Fig. 7).

!-I

B

0

FIG.7. Assessment of uuual densitv. A. Exanule of the determination of the uosition of a maplot which is tiorbughly eeirched for pupae. The square is situated immediately in front of the thirtieth step of a walk in a straight line, independent of crown structure and the presence of trunks. B. The distribution of 24 m*plots in the study area. Each year the plots are situated approximately along the mme diagonals.

To study the dispersion of pupae we made use of the coefficient of dispersion (c). Table VIII shows data for intact pupae in April and columns 1-6 indicate that in 2 out of 14 cases c has a value smaller than unity. Thus there was still a tendency to aggregate, but only in 4 out of 14 cases is c outside the range of 1 f 25,. This signifies that the pupae were evidently less aggregated than i;he nymphs. Therefore, the Poisson-series have been fitted t o the observed distributions by taking E(x) = S. Figure 8 shows that the fit is very close in some years, as was to be expected after the results of the above analysis with the coefficient of dispersion (the goodness has been tested with the Xa-method). The results (Table IX)show that in 1 out of 13 cases the observed distribution deviates significantly from the Poisson distribution.

TABLEVIII Means, Variances, Dispersion, and Conjdence Intervals of Pupal Density in April ~

4

5

6

7

8

Mean number of pupae/m2

Variance

Coefficient of dispersion

95% Range of coefficient of dispersion

Standard deviation of mean

Confidence intervals

5 -42 3.57 0.73 3.00 3.00 2-58 1-87 0.12 0.87 1.13 2-25 3.38 5.04 4-63

8-28 5.91 0.78 4-70 5.22 3.83 1-80 0.11 0.81 1.68 4.11 7 -03 13-35 6.86

1-52 1*66 1.07 1*57 1.74 1.48 1.08 0.92 0.93 1*49 1.83 2.08 2.65 1*48

0.398 - 1.602 0.294 - 1.706 0.368 - 1.632 0.398 - 1.602 0.398 - 1.602 0.398 - 1,602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602 0.398 - 1.602

0.57 0.57 0.19 0.44 0-47 0.40 0.27 0.02 0.18 0.27 0.41 0 -54 0.75 0.53

4.28 - 6-56 2.43 - 4.71 0.35 - 1-11 2.12 - 3.88 2.06 - 3.94 1.78 - 3.38 1.13 - 2.21 0.08 - 0.16 0.51 - 1.23 0.59 - 1.67 1.43 - 3.07 2.30 - 4.46 3.54 - 6.54 3.57 - 5.69

1

2

3

Year

Number of m2

1951 1952 ,1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964

24 18 22 24 24 24 24 24 24 24 24 24 24 24

?

DYNAMICS O F FIELD P O P U L A T I O N O F P I N E LOOPER

229

0.12/SO.M.

10

2 3 W u >

5

0 1

:i

e (L

0

2

.

4

6

8 0 2 PUPAE PER SQ.M.

I

6

8 1 0 1 2 1 4

10

5

'Ol

C

1 1 2

PUPAE PER SP.M.

FIG.8. Top graphs. Distribution of the number of pupite/m* in years with low, intermediate and high density. Bottom graphs. Poisson distributions with the same means as in the top graphs, given for comparison. In 1958 and 1951 the pupae are approximately randomly dispersed; in 1961-they are under-digpersed. See the text and the Tables VIII and IX.

The mean of a sample taken from a Poisson distribution has approximately a normal distribution. Therefore, the 95% confidence limits can be given by twice the standard deviation of the mean: Z & 292- (see Table VIII, columns 7 and 8).

D. D E N S I T Y O F MOTHS In 1951 and 1953 the emerging moths were caught in wooden traps, constructed in the form of a pyramid with a ground surface of 1 m2.

230

H . KLOMP

TABLEIX Goodness of Fit of the Poisson Series to the Observed Distributions of Pupae in April

Year

(1) N (11) P

-g

1951 1952 1953 1954 1965 1956 1957 1958 1959 1960 1961 1962 1963 1964

Degrees of freedom Chi-square N- 2 0.34 2 -09 0.35 6.30 3 *04 4 *62 0.33 0.21 1-00 1.01 3.32 7.71 13.02 7.80

3 2 1 3 3 2 2 0 1 1 2 3 4 4

P

>0.90 0.30-0.50 0.50-0.70 0 *05-0 '10 0.30-0.50 0.05-0.1 5 0.80-0.90 0-25-0.35 0.30-0.50 0.30-0.50 0.05-0.10 0.01-0.02 0.05-0*10

number of c l a y entering into the calculation of x' after lumping to avoid expected number8 lees than 3. . robability that the observed distribution hss been sampled from a Polsson population dtstrlution with the same mean.

The pyramids were randomly placed in the wood just prior to the start of the emergence of adults and were examined every other day. The results obtained by this method, especially those of 1953, must be considered with some reserve because they are probably biased to an unknown extent as a result of the settlement of ants and spiders in the traps which preyed upon the moths. In all other years a different method was used, in which the emerging moths were counted in 40-60 wholly open squares scattered randomly throughout the study area. These 1 ma squares were only marked with small sticks. The moths were thus able to cross the borders freely before settling down to stretch their wings. The counts were made daily during the whole period of emergence and only in the early morning when the fresh adults rest for some time (see p. 209). Figure 9 (top graphs)"gives examples of the observed frequency distributions of moths for years with low, intermediate, and high density. Dispersion has again been studied using the coefficient of dispersion (Table X). Columns 1-6 show that in 6 out of 14 cases c has a value smaller than unity. Moreover, only in 1 out of 14 cases is c outside the range of 1 f 2s,. This indicates that the emerging moths are randomly distributed. This is corroborated by the fit of the Poisson series

TABLEX Means,Variances, Dhpersion, and ConJidence Intervak of Moth D e d t y in MayJune 1

2

3

Year

Number of m8

Mean number of moths/ma

n 1951 1952 1953 1954 1955 1956

26 60 52 40 48 48

1958 1959 1960 1961 1962 1963 1964

60 40 40 40 40 40 40

1357

40

-

X

2-71 1-28 0.10 1-05 1-42 1-52 0.90 0.10 0-48 0.58 1-50

2-13 1*08 0.83

4

5

6

7

8

Variance

Coefficient of dispersion

95% Range of coefficient of dispersion

Standard deviation of mean

Confidence interval of mean

x

S ; :

2 -46 0.99 0.09 1-13 1.40 1*57 i .22 0.09 0.51 0.71 2.92 2-11 1-52 0.87

0.91 0.78 0.89 1.08 0.99 1.03 i .3fj 0.92 1-06 1.22 1*95 0.99 1.41 1-05

0.42 - 1.58 0.63 - 1.37 0.60 - 1.40 0.54 - 1.46 0.58 - 1.42 0.58 - 1.42 u s 5 4 - 1.46 0.63 - 1.37 0.54 - 1.46 0.54 - 1*46 0.54 - 1.46 0.54 - 1.46 0.54 - 1.46 0.54 - 1.46

0.31 0.13 0.04 0.17 0.17 0.18 0-17 0.04 0.11 0.13 0.27 0.23 0.20 0.15

* 2sx

2.09 - 3.33 1-02 - 1-54 0.02 - 0.18 0.71 - 1-39 1.08 - 1.76 1.16 - 1.88 0.56 - 1.24 0.02 - 0.18 0.26 - 0.70 0.32 - 0.84 0.96 - 2.04 1.67 - 2.59 0.88 - 1.48 0.53 - 1.13

232

I

H . KLOMP

25 -

20-

IS-

1957

1962

O.~O/SQ.M.

2.l/SQ.M.

5-

-

>V

L 2

MOTHS

CL

I5l 10

5

10-

5

Ib 2

4

PER SQ.M.

0

2

4

0

2

4

25-

IJ.

-

20-

15-

15-

20

10-

5-

-

h

5

h ?

2

MOTHS

L

ER SQ.M.

FIQ.9. Top graphs. Distributiqn of the number of moths/m* in years with low, intermediate and high density. Bottom graphs: Poisson distributions with the same means aa in the top graphs, given for comparison. See the text and the Tables X and XI.

to the observed distributions (Table XI, and Fig. 9). Where this fit could be tested with the X2-method no significant differences could be shown to exist. Even in 1961, where cis outside the 95% range (Table X), there is no significant deviation with the Poisson distribution.

DYNAMICS O F FIELD POPULATION OF P I N E LOOPER

233

TABLEXI Goodness of Fit of the Poisson Series to the Observed Distributions of Emerginq Moths

Year 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 (i) N

=

(ii) P

=

Degrees of freedom Chi-square N -2 1.83 1.13 0.02 2-18 1.00 2.92 1.01 0.02 0.11 3.71 3.81 3.36 1.18 0-34

2 2 0 2 2 2 1 0 1 1 2 3 2 2

P 0.30-0.50 0.50-0.70 0-30-0.50 0.80-0.90 0.20-0.30 0.30-0.50 -

0.70-0.80 0-05-0.1 0 0 10-0 -20 0.30-0-50 0 -50-0 -70 0.80-0*90

-

number of classes entering into the calculabion of chi-square, after lumping to avoid expected numbers less than 3. probability that the observed distribution has been sampled from a Poisson population distribution with the same mean.

E.

THE DISPERSION OF NYMPHS, P U P A E , A N D MOTHS

It has been shown in the foregoing paragraphs that the dispersion of the successive stages of the insect shifts from being more or less aggregated to a, random distribution. The aggregation of nymphs is most plausibly explained by the composition of the micro-habitat where they live before descending, i.e. in the crowns of the trees. The crown-layer has a good closure, but is nevertheless heterogeneous as a result of occasional small gaps between the crowns of different trees. The funnels were distributed quite independently of the structure of the crowns (cf. p. 220), and as a result, both the frequency of funnels with a low and a high number of nymphs increases. This results in a good fit to the negative binomial distribution (Fig. 6). The crawling movements of the nymphs disperse the insects to a small extent before entering the litter to pupate, and still later the more intense movements of the moths immediately after emergence and before settling down for wing-stretching cause a random dispersion of’the adults. 111. ANNUALROUTINEREARINGS High numbers of eggs, larvae, and pupae were collected annually in the study a.rea, and reared to investigate survival. I n this way, the

234

€ RLOMP I.

percentage parasitism was established and the proportion affected by disease determined. The latter value, it is true, cannot be transferred directly to the field population, but by comparing the rearing results of different years a relative measure of the health of the insects can be gained.

A.

REARING OF EGGS

As reported (p. 212) egg density was determined by way of twig sampling. The eggs were classified as “hatched”, “parasitized”, “unfertilized”, “empty”, or “dead”. The green, unhatched eggs present in the samples were reared, and then classified. The data over three years with high, intermediate, and low density are presented in Table XI1 and the summarized results for all years are presented in Table XIII. The eggs may be infected by one species of parasite, Trichogramma embryophagum Htg., such eggs turn black during development, and are readily recognized. The sampling dates guarantee that all, or nearly all, of the unhatched host eggs found in the samples are older t h m 2 days. Based on the results of some preliminary experiments it was originally assumed that Trichogrumma does not infect host eggs older than two days (under summer temperature conditions). Therefore, at the beginning of this study it was thought that all samples provided an unbiased estimation of the percentage of eggs infected in the field. Later experiments showed that the parasite is able to oviposit successfully in host eggs in which development has progressed. This implies that, the values obtained at the beginning of the sampling period may represent too low estimations. Therefore, such values were eliminated where this was the case, as for instance in 1951 (see Table XII). As demonstrated by Laing (1937) Trichogrammu is adapted for infecting egg batches and nearly always parasitizes the whole batch. This can lead to an abnormally high percentage of parasitism when egg density is so low that the number of batches per sample is small. Thus, in 1958, sample 138 contained seven batches, one of which consisted of eight infected eggs, resulting in an overestimation of the fraction parasitized (see Table XII). Unfertilized eggs colour deep green, and dent gradually after about 10 days. It appears that such eggs are occasionally deposited by fertilized females in a batch’ of normal eggs. Empty eggs include all those eggs whose content is partly or wholly absent without a visible perforation of the chorion. The shell of empty eggs usually becomes indented. The category “embryo dead” comprises all eggs in which the embryo dies during development due to unknown causes, and those in which the fully developed first instar larva fails to leave the chorion through the hole actually made by the larva.

TAE- XII

-

S m Read& of the Sampling and the Rearing of Eggs 1951; high density; cf. Tables 11 and 111

Sample number and date Categories of eggs unhatched hatched parasitized unfertilized empty embryo dead SUm

R

510 409 116

4 1

876 159 4 1

1040

1040

-

%

S

R

84.2 15.3 0.4 0.1

365 299 280 2 10 -

587 354 3 12

956

956

-

-

% I

61.4 37.0 0.3 1.3

-

S

R

159 726 506 4 31 8

833 556 4 32 9

1434

1434

Summaryof samples

33

16 July

12 July

5 July

S

32

31

30

20 July

% -

-

58.1 38.8 0.3 2.2 0.6

S

R

11 344 231 3 32 5

351 235 3 32 5

626

626

31-33

%

R

56.1 37.5

1771 1145 10 76 14

-

0-5 5.1 0.8

-

% 58.7 38.0 0.3 2-5

0.5

3 016

1956; intermediate density; of. Table I11

Sample number and date Categories of eggs unhatched hatched parasitized unfertilized -PtY embryo dead SUm

Q..-----

117 I 9 July

S

R

-

147 19 68

158 76

1

1

-

-

-

-

235

235

% 67-2 32.3 0.5 -

S

R

%

-

102 118 78

217 81

71.6 26-7

4 1

4 1

1-3 0.3

303

303

-

-

-

S

R

59 87 30 2 7

126 49 2 8

185

185

-

-

-0

"I

UuuU*cb.J

118 I 12 July

117 I1 9 July

samples

118 11 12 July

% 68.1 26.5 1.1 4.3

-

S

R

80 154 77 1 6 1

220 87 2 8 2

319

319

117-118

%

-

69.0 27.3 0.6 2.5 0-6

R 721 293 4 21 3 1042

% 69.2 28-1 0.4 2.0 0.3

1968; low density; cf. Table 111 Sample number and date

138 8July

23 9 8

-

unhatched hatched parasitized unfertilized empty embryo dead

-

-

Sum

40

40

30 9 1

140 14 July

139 10 July

-

76.0 22.6 2.6

-

-

6 20 1

27

9 = number of egga 88 found in the samples; R = number after rearing of unhatched eggs in glass tubes; % = peroentages of preceding column R. See the text.

26 1 1

27

-

-

-

-

-

-

92.6 3.7 3.7

29

29

29

-

29

Summaryof samples 138-141

141 15 July

-

100

-

-

4

33

-

1

-

36

-

-

-

1 1

38

38

-

94-7

-

-

2.6 2.6

-

120 10 2 1 1

134

-

89.6 7.5

1-5 0.7

0.7

DYNAMICS OF FIELD POPULATION OF P I N E LOOPER

237

The survival and mortality rates given in Titble XI11 have been computed by adding the numbers per category occurring in the appropriate samples (cf. Table XII). Thus the lowest number of eggs upon which the rates are based amounts to 134 in 1958. For that year the standard deviation of the survival rate is: s

=

.\/{P(lOO - P)/n} = .\/{89.6(100

-- 89.6)/134} = 2.6,

and the confidence interval is (89.6 f 2 x 2.6). I n 1953 the standard deviation is of the same order. In all other years it is noticeably smaller because nearly all numbers of eggs amounted to 500 or more. Thus in 1951:

s

=

.\/{58-7(100 - 58*7)/3010}= 0.9.

B.

REARING O F LARVAE

In most years 100-300 larvae were collected and reared in jars in an insectory. These rearings were far from uniform. Firstly, there was some variation in the period of sampling, which sometimes fell in mid August, but sometimes was as late as mid September. Secondly, larvae were collected in various ways. In some years all larvae found in the twig samples were reared, viz. in 1950 and 1951, when they were not yet shaken off the twigs (cf. p. 212). I n others they were obtained by shaking the crowns of several trees scattered through the study area. Thirdly, the number of larvae per jar varied year by year, and it appears that the density in the jars had a significant el€ect on larval mortality. Another objection which can be raised against the usefulness of rearing larvae was the fact that the primary cause of death could not always be established. Some larvae were found dead and covered by mould, but this does not necessarily mean that a fungal disease was the primary agent killing the insect. Other larvae stop taking in food and after some days die and shrivel up. The cause of this disease is unknown. In 1955 and 1956 many larvae died from a cytoplasmic polyhedral virus (Smith and Rivers, 1956). Very exceptionally larvae died as a result of their inability to strip the old skin off the abdominal segments. A survey of the rearings is given in Table XIW. This shows that parasitic mortality also occurs. There is one braconid (determined by Dr. G . E. J. Nixon, British Museum (Natural History) as Apanteles caberae, Marshall, 1885), which is present in most years in low numbers. I n 1963 it parasitized about 10% of the laxvae. The parasitic tachinid Strobliomyia Jissicornis (Strobl.) (determined by Dr. F. van Emden, British Museum (Nat. Hist.), occurred only in 1954 and 1955, being very numerous in 1954. The data on “numbers diseased” in Table XIV do not represent the incidence of disease in the field since the concmtration of larvae in jars

TABLEXI11 Estimates of Survival and Mortality Rates of Eggs Categories of eggs hatched parasitized unfertilized empty embryo dead

Totals

1950

1951

1952

1953

1954

1955

1956

1957

1958

1959

1960

1961

1962

1963

1964

63.0 37.0

58.7 38.0 0.3 2.5 0.5

39.6 59.4 0.3

81.9 11.9 2.0 2.5 1.7

48.0 46.6

68.4 28.1 0.2 1-9 1.4

69.2 28.1 0.4

21.8 69.2 8-7 0.3

89.6 7.5 1.5 0.7 0.7

69.1 20.8 0.3 4.0 5.7

69.4 26.8

66.0 22.3

2.3

9.0 2.7

77.3 15.9 3.5 1.9 1.4

63.7 22.8 3.0 9.7

0.8

40.7 40.7 0.6 17.2 0.8

643

134

489

526

659 1016 1 1 7 3

484

-

-

378 3016

0.7

-

999

177

0.7 3.6

1.1

962

2.0

0.3

577 1 0 4 2

0.8 0.8

-

The line “Totah” givea the numbera of egga collected in the fleld earnplea. The ratea are expreaaed in % of thwe totals.

TABLEXIV Results of the Rearing of Larvae Collected in the Study Area

Diseased Polyhedrosis mouldedOr Incomplete ecdysis Parasitized Apanteles Ol..^LlJ^...

U U I

.."--

"ucwfrry'u

Nymph

Totals

) ] ] 22

29

46

)

9

50

36

-

9

1

-

3

16

13

10

14

33

22

21

2

1

1

-

-

1

3

-

-

-

-

2G

1

3 i

-

21

-

-

5

-

-

24

-

140

107

52

128

246

215

163

262

154

209

154

162

136

100

158

318

286

174

290

193

256

194

2

5

13

340

H . KLOMP

may have influenced the occurrence of disease. This does not apply to deaths caused by parasites and those results have been used for further analysis of the population dynamics (p. 267).

c. R E A R I N G O F P U P A E As reported on p. 226, pupal density was assessed in April of each year by searching through 24 m2of litter which yielded 15 to 120 pupae. Such numbers are too low to provide a reliable estimation of the pupal mortality rate and therefore further pupae were collected by searching less accurately through litter lying outside the sampling squares and on localities scattered throughout the study area. By this means some hundreds of pupae were collected and reared in 0.37 litre glass jars containing a small amount of litter with not more than seven pupae per jar. The sexes were separated and grouped into classes of 0.1 mm pupal diameter (for reasons see later). The breeding results are given in Table XV. Pupae which putrefied have been deducted from the original numbers. In 1963, of 418 pupae 12 putrefied (see Fig. l 2 ) , thus 406 pupae were reared and are shown in Table XV. The percentage parasitism represents an unbiased estimate of pupal infection in April because no parasites leave their hosts before the middle of May. However, the adults of Cratichneumon nigritarius, which emerge and fly in the second half of May, infect pupae of the pine looper which have still to emerge. Consequently, the ultimate pupal mortality due to parasites will be higher than indicated in Table XV. We have no data bearing on the increase of the percentage parasitism, but it is probably low in most years since the parasite is rare. Both mortality from putrefaction and furtker infestation by the ichneumon can be assessed indirectly (see p. 272). All other parasites infect host larvae. For more details on their ecological significance see p. 294.

D.

REARINQ O F MOTHS

Moths have been reared in great numbers in most years to measure adult fecundity. (See next chapter for results.)

IV. ANNUAL VARIATIONS OF

THE

REPRODUCTIVE RATE

The mean fecundity of the moths expressed as mean number of eggs deposited, showed significant variations year to year. These variations have been analysed and will now be described. First we shall consider variability of fecundity within one generation, then secondly, the annual changes in fecundity.

T A B L EX V Results of the Rearing of Pupae Collected in the Study Area in April 1951

N

%

Moths Eucarcelia rutilla Blondelia nigripes Cratichneumon nigritarius Poecilostictus cothurnatus Heieropelma calcator Anowmlon biguttatum

258 22 6 13 1

85.4 7-3 2.0 4.3 0-3

2

0.7

Number of pupae reared

302

Total

_

Yo parasitism

-

1952

N

1953

%

139 57.6 84 34.8 13 5.4 0.8 2 1 0.4 2 0.8 24 1

14.6

Moths Eucarceliu rutillu Bloiulelia nigripee Cratichneumon nigritarius Poecilostictua cothumzatus Heteropelm calcator A n d o n biguttatum

75 30 7 5 38 2 1

Number of pupae reared

158

Total

yo parasitism

1956

%

N

%

N

%

N

YO

80 41 5 1

199 67 8 17 6 -

67.0 22.6 2 -7 5.7 2.0 -

173 71 9 14 25 2 3

58-2 23.9 3.0 4-7 8.4 0.7 1.1

359 129 11 4 15 1 5

68.5 24.6 2.1 0.8 2.9 0.2

218 55 11 17 41 2 13

61.1 15.4 3.1 4.8 11.5 0.6 3.6

5

-

1

60.1 30.8 3.8 0.8 3.8 0.8

_

133

297

297

1960

1961

1.0

524 41 *8

33 -0

40.0

1959

357 31.6

1962

N

Yo

N

Yo

N

%

N

Yo

N

%

47 *5 19.0 4 -4 3.2 24.0 1.3 0.6

143 37 12

57.7 14.9 4.8

167 52 32 1 3 1

64.0 19.9 12.3 0.4 1.1 0.4 1.9

193 66 30 1 1

66.3 22.7 10.3 0.3 0.3

226 37 27 17 3 1 5

71.5 11.7 8.5

24 1 89 64

5.4 0.9 0.3 1.6

5 4 3

59.4 21.9 15.8 1.2 1-0 0.7

_

21.4

3

1.2

_

248 52 *5

5

261 42 -3

29 1 36.0

316 33.6

406 28 -4

39.0

1963

YO

53

1957

N

~

N

1955

N Y O

42.2

1958

1954

1964

N

%

104 40 79

36.6 14.1 27.8 1.8 16.5 1.1 2.1

5

47 3 6 284

40-6

63.4

242

H . KLOMP

A.

THE VARIABILITY O F FECUNDITY WITHIN ONE QENERATION

Many studies on insects have shown that adult fecundity is highly dependent on the degree of development of the fat body in the larvae.

\

JULY

1962/63

A U G.

OENSITY OF 0 EGGS Q LARVAE I 0 LARVAE AUG.-OCT. x NYMPHS

SEPT.

OCT.

NOV.

-

APR.

JUM

Fro. 10. Survivorship curves showing the decrease of numbers from the egg to the moth

stage, at high, intermediate, and low density. The numbers plotted have been taken from

the Tables 111, IV, V, VIII, and X. The density of first instar larvae (larvaeI) has been taken from the life tables (see Section V).

DYNAMICS OF FIELD POPULATION O F PINE LOOPER

243

Therefore, it is logical to start this analysis of fecundity with the study of larval growth, then to assess the effects of larval growth on pupal size, and finally study the relation between pupal size and adult fecundity. 1. Larval Growth The eggs are deposited in May/June and the bulk of the larvae hatch in the second half of the latter month. Then there is a slow growth up to mid October. The head capsules were measured (for method see Klomp, 1968) and Fig. 11 shows the 1957 results. From the first instar to the nymphal stage there was a steady rise in variability which has been ascribed to several causes. These causes aim partly genetic, and can be attributed to sex as well as to genetic difixences within the sexes; they are partly environmental, arising from factors which induce a variable number of larval instars, and from differences in microhabitat and an effect of larval density on size. Differences in sex were studied only in the nymphal stage and exclusively in the years 1956, 1957, and 1958. The difference between mean head capsule-widths of females and males were: 2-105-1.957 = 0.148 mm in 1956; 2.242-2.078 = 0.164 nim in 1967; 2.252-2.079 = 0.173 mm in 1968. The effect on size of other genetic differences is difficult to analyze because the various genotypes cannot be separated probably because of the great number of genes involved coupled with environmental effects superimposed upon gene action producing continuous variation (see later, p. 248). The bottom graph of Fig. 11 suggests that t$e larvae have 7 instars, but this is incorrect. I n rearings in 1957, where the development of individual larvae was checked, about half of the insects had five whilst the others had six instars. Both these groups are represented in the histograms 1, 2, and 3, which are clearly separate units, compiled exclusively of larvae in the fist, second, and third instar. Histogram 4 is trimodal due to the fact that 4a and 4c represent the fourth and fSth instar of individuals which had six instars, and 4b represents the fourth instar of individuals with five instars. Consequently, histogram 6 , representing the final larval instar, is composed of two groups: individuals pupating at the end of the fifth, and those pupating at the end of the sixth instar. Individuals which have six instag give pupae of larger size than those with five instars. Thus, this difference contributes to size variation in the final larval instar. We have no evidence concerning the environmental factors influencing the number of larval instars. According to the evidence obtained from other species both temperature and nutrition may have rtn

244

H. KLOMP

IF

JULY 16-3l

- --AUSUST 16-31

1030

20

0 YI 20

-

SEPT.l-15 d

35

LO

15

-

5

a

10

15

10

b

c SUMMARY

25 30 16 41 WlmW OF H E A D CAPSULE (MICROMETER

15 UNITS)

SO

FIQ.11. Results of measurements of the width of the head capsule of larvae collected in the field in 1957 (Both sexes included). The majority of first instar larvae (histogram 1) originated from eggs collected in the field and reared in the laboratory. The measurements after 15 October are those o f nymphs collected in the funnels described on p. 220. The bottom graph is a summgry of the others. The numerals 1, 2, and 3 indicate the histograms of the first, second and third larval instar; 5 denotes the final instar; 4a-c are explained in the text. One micrometer unit = 0.045 mm.

effect (Weber, 1954; Wigglesworth, 1953). The fraction of individuals passing through six instars varies from year to year (see p. 258). The other environmental effects on size will be discussed in the next section.

DYNAMICS OF FIELD POPULATION 'OFPINE LOOPER

245

2. Pupal Size (a) The Variability of Pupal Size in the Field. The great variability of larval size in the last instar is reflected in the size of the pupae (see Klomp, 1958, Fig. 4). This variation has been studied annually from random collections in the study area in April (see p. 240). Their sex was established according to the method described by Escherich (1931), and both males and females were measured (for method, see Klomp, 1968) and grouped into classes of 0.1 mm. These groups were reared. Figure 12 gives the results for April 1963. The non-par.witized pupae (graphs B) are larger than parasitized ones, both in males and females. This difference is not statistically significant in all years, but as a consequence

601MALES

n

FEMALES 211

0 6

-7

-10 NUMBER I

E

3.5

3.7

3.9

L.1

-

11

L.3

_ _ _ ~

L.5

3.9

- , . L.1

L3

PUPAL DIAMETER I N m m

h

L.5

L.7

L.9

5.1

5.3

FIQ.12. Histograms of pupal diameter in April 1963. A. Totals. B. Nonparaaitized pupae giving rise to moths. C. Pupae parasitized by hchinids. D. Pupae parasitized by ichneumonids. E. Putrefied pupae. I

246

H . KLOMP

of its recurrent incidence in successive years (with two exceptions only) it can be considered as real (see Table XVI). We shall concern ourselves only with the variability of non-parasitized pupae. The possible causes having been commented on in the section on larval growth. TABLE XVI Differences of Pupal Size Between Non-parasitized and Parasitized Pupae in Both Sexes Year 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 Mean

Males 0.06 mm 0.02 0.06 0-06 -0.02 0.04 0.03 0.08 0-04 0.16+ 0.05

+

Females 0.05

0.05 -0.03 0*13+ 0.10 0.09 0.08+ Oslo+ 0.07 0.07 0.17+ 0.08

min

+

+

+ = difference is aigniflcant according to t-test. Figure 12 shows that male pupae are much smaller than female pupae. This difference is of the same order each year and always highly significant. Also, within the sexes pupal size varies considerably. This variability may be due to genetic and environmental effects, and was tested as follows. ( b ) Experiment on Size Variability. Let us consider the frequency distribution of pupae (Fig. 12-B) and confine our attention firstly to those specimens showing extreme measurements. If we assume that variability in the pupal population is mainly genetic, the extreme classes “small” and “large” will be composed of “genetically small” and “genetically large” individuals respectively, both classes having most of the environmental variability included. If we assume on the other hand that variability in the pupal population is mainly environmental, then the extreme classes will be genetically similar, but “small” will include especially specimens which have been influenced disadvantageously, and “large” those individuals which have advantageously been influenced by the environmental factors. If the first hypothesis is correct then the offspring of small a n d large pupae reared under the same environmental conditions should show great differences in size on the average. If the second applies, then the

D Y N A M I C S O F FIELD POPULATION O F P I N E LOOPER

247

progeny of the two extreme classes of pupae should be about the same size. Pupae of the size frequencies shown in Fig. 12-B were grouped into three superclasses: small (a), medium, and large (b). The ranges and means of the extreme classes (a) and (b) are given in Table XVII. TABLEXVTI Ranges and Means i f Pupal Diameter of Specimens Used in an Experiment (cf. Fig. 12, graph B ) Piipal diametei. in mm Males Superclass

range

Females mean

range

mean ~~

a. small

b. large

up to 4.1 inclusive 4.5 and larger

4-06

4-53

lip

to 4.5 inclusive

5.0 and larger

4.37 6-05

After emergence the adults of the superclasses a and b were paired in intra-class combinations in cages each contsining one pair of moths. After copulation the females deposited their eggs readily on pine twigs in the cages. These eggs were collected and distributed in several petridishes. The dishes which conta,ined, let us say, a-eggs (deposited by small females) were alternated with those containing b-eggs and placed in an outdoor insectary until the larvae hatched. Within some hours after hatching the larvae were transferred to glass jars of 0.37 1. volume containing small pine twigs of uniform length as food and closed with a copper-gauze lid. They were reared until after pupation, then the pupae were collected and measured. The food was refreshed every 10 to 14 days and the number of instars of the larvae determined from the head capsules found on the bottom of the jars. As will be discussed later (p. 264) pupal size in the field appears to be dependent on larval density. To study the effect of this factor simultaneously in one experiment, both the a- and b-larvae were reared singly and in couples, resulting in four categories of jars. These jars, amounting to a total number of 162 at the beginning of the experiment were randomized and placed on a big table in a n outdoor insectary. The mortality in these jars was very low especially in the singly reared ones as shown in Table XVIII. This ta.ble suggests i~ more pronounced mortality among the larvae reared in couples, but this is misleading since the death of one specimen of a pair automatically meant that the other had to be disregarded.

248

H . KLOMP

TABLEXVIII Number8 of Larvae and Pupae in an Experiment

Category

Initial number of jars

Initial number of larvae

a. single a. in couples b. single b. in couples

54 27 54 27

54 54 54 54

Final number of pupae measured males

females

totals

24 22 26 28

28 22 26 16

52 44 52 44

( c ) Results of the Experiment. The pupae obtained were measured and grouped into classes of 0-1 mm. The results are given in Fig. 13 and the means and standard deviations summarized in Table XIX. It is shown that both in males and in females there are larvae with five and larvae with six instars. I n the single rearings the number of larval instars of each individual pupa could be established. Where there were two larvae per jar this was possible only when both larvae passed through the same

F;;mG:k 4.0

4.2

44

4.6

i ; ~F

4.8

E

M

4.6 L8

A

L

5.0 5.2

k

5h

5.6

5.8

a.lN COUPLE 0 W

(z

3

In

L.6

4.6 5.0 5.2 5.4 5.6 5.8 PUPAL D I A M E T E R IN rnm

FIG.13. Histograms of pupd diemeter of speckem reared in jars during lervel development. See the text.

TABLEX I X Results of an Experiment Carried out to Analyse the InJEuence of Several Factors on Larval &&h Males Fivs httbIX3

Category a

single

4

n

sx 8.

a in couples

4

n sf 8%

b

single

4

n

sx

sl! b

in couples

d

n

sx

Sij

4.45 21 0.13 0.028 4.33 22 0.14 0.029 4.66 24 0.14

Six instars 4-60 3

4.60 2

U'UZLI

4.34 24 0.18 0.036

Instars unknown

Pup1 Size

Females Five Totala

hStal'S

4.47 24 0.14 0.029 4-33 22 0.14 0.029 4-56 26 0.14 0.028 4-37 28 0.19 0.036

5-14 17 0.12 0.030 4.82 14 0.10 (is026 5.24 17 0.18 0.042 4.96 12 0.17 0.050

4 = mean pupal diameter in mm. n = number of pupae measured. sf = standard deviation. sz = standard deviation of the mean. The values given In this column refer to the frequency distributions portrayed in Fig. 13.

..

and

Six instars 5.19 11 0.20 0.061 4-96 8 0.13 0.046 5.47 9 0.22 0.075

Instam unknown

Totala 5.16 28 0.16 0.030 4.87 22 0.13 0.027 5-32 26 0.22 0.043 5.01 16 0.21 0.082

250

H. KLOMP

number of instars. Where one larva with five and one with six instars occurred, as it did four times in category “b in couples” pupal diameter could not be identified with the larval growth type because the individuals were not marked (see Table XIX). Moreover, it must be realized that the first instar larvae in the second and fourth category were coupled independently of sex. Thus part of the 22 males occurring in “a in couples” have grown up with males, the others with females. The sexes could not be distinguished before the pupal stage. It is suggested in Table X I X that the fraction of la,rvae passing through six instars is greater in the females than in the males. This has been tested with the XP-methodby pooling the data of the first three categories. I n the category “b in couples”, half of the eight individuals with an unknown number of instars had five, but it cannot be ascertained how these four individuals are distributed among the sexes. The data to be tested then are as follows five instars 67

males females X* =

19.1

,

six instars 5

28 degrees of freedom 1 , P < 0.001 48

This shows that the number of larval instars is related to sex in this experiment. This point needs no further consideration since it has no bearing on the other results (differences of pupal diameter are all studied within the sexes).

If the difference between “small” and “large” pupae of the field population is purely environmental then the offspring of these two categories when reared under the same conditions should be similar (see p. 246). To test this we compared the mean pupal diameter of “a single” with “b single” and that of “a in couples” with “b in couples”. The differences between these categories are as follows (cf. Table XIX): b-a single males females

4.56- 4.47 = 0.09 5.32- 5.16 = 0.16

b-a in couples 4.37 - 4.33 5.01 - 4.87

z=

0.04

= 0.14

Student’s t-test shows that these differences with one exception are statistically significant. The probability of getting the difference of 0.04 in the group “males, b-a in couples” amounts t o 0.40. The comparisons were made between total numbers of pupae, i.e. the individuals with five and six instars were added within categories. This can be justified because conformable differences between categories occurred when only individuals with five instars were considered. Moreover, an effect of an interaction with the number of six-instar larvae could be excluded, because six-instar pupae were greater than five-instar pupae on the average (see p. 2 5 2 ) , and in the b-categories the numbers of the former were lower than in the corresponding a-categories in three out of four cases (cf. Table XIX).

To evaluate the results they have to be compared with the differences in pupal diameter of the parental groups or superclasses used in the

D Y N A M I C S O F FIELD POPULATION O F P I N E LOOPER

25 1

experiment and originally collected in the field. The differences between these groups (“b large” minus “a small”) are as follows (cf. Table XVII). males females

4.53- 4.05 = 0.48 5.05 - 4.37 = 0.68

It is evident that the differences between the parental groups are much more pronounced than those between the means of the b and a categories in the experiment, in which the effects of environmental variability were eliminated. This suggests that pupal variability in the field is largely environmental. This raises the question of what factor is responsible for the variation. As remarked earlier (p. 247) field evidence riuggests that larval density may be an important factor affecting larval growth and, hence, pupal size. Now the larvae in the crowns of the trees are more or less randomly distributed, and consequently there will be some variation in density from place to place. Thus, if larval density has a noticeable effect, in principle this factor might contribute to pupal variation within one year. The influence of larval density can be studied by comparing the groups “single” and “in couples” both in the a and in the b categories of the experiment. The differences of pupal size between these groups are as follows (see Table XIX): a single - a in couplos 4-47 - 4.33 := 0.14 males 5.16 - 4.87 := 0.29 females b single - b in couples 4.56 - 4.37 == 0.19 males 5.32 - 5-01 == 0.31 females Again the comparisons are made between total numbers of pupae, i.e. fiveinstar and six-instar pupae taken together. This is the most logical comparison because the total effect of density will be expressed in the overall numbers of pupae. I n this case, however, it is worthwhile analysing the effect in more detail. In Table X I X pupal size is also given for fivo- and six-instar individuals separately. If we make the comparisons between the categories “single” and “in couples” for the five-instar pupae only, then the results are the same aa for total numbers of pupae, and the t-test shows that the differences are highly significant. If we consider the six-instar individuals, which is only possible among females in the a-category, then the difference is conformable and, again, significant. Consequently, the effect of density is expressed in the size of the five-instar pupae as well as in the diameter of the six-instar individuals. I n addition, however, there is some evidence that the fraction of six instar pupae in the category “single” is greater than in t,he category ”in couples”. This is shown in Table XX, in which the categories “a” and “b” and the sexes have been added. Although

252

H . KLOMP

TABLEXX The Number of Pupae in an Experiment with Five and Six Instars During the Larval Stage ~~

Category a a

+ b single + b in couples

~

Number of pupae Five instars S i x instars 79 76

x’ = 3.31; deg. of freedom :1; P

25 12

= 0.08.

not significant a t the 5% level, the low probability of 0-08 strongly supports the hypothesis that there is an effect of density on the number of instars, and this is of importance, because it means that the hormonal complex of the insects is affected by the interference. In the meantime, the higher proportion of six-instar pupae in the categories “single” has its consequences for the mean pupal diameter in the group “total” of Table XIX. I n this table mean pupal size is greater in the six-instar than in the five-instar individuals within all five categories in which the two types occur. Under the hypothesis of equal size this result has a probability of 2 x (1/2)5 = 0.06. Moreover, in those categories where the number of six-instar pupae is so high that Wilcoxon’s test can be applied (females of “a” and “b single”, and “a in couples”, see Table XIX) the chance of equal meane is beyond the critical level in the last group. This strongly suggests that within categories six-instar pupae are greater than five-instar ones. Therefore, the higher proportion of the former in the categories “single” will by itself contribute to a more pronounced difference in total mean pupal diameter between “single” and “in couples”.

( d ) The In$uence of Larval Density. The above data show that the influence of larval density on pupal size is considerable under experimental conditions. Consequently, this effect may well be responsible for part of the pupal variability in the field. There is one point, however, which casts doubt on this view. Two larvae per jar, as used in the experiment, represent a higher density than any mean larval density experienced in the field. This raises the question as to whether larval density in the field is high enough to influence larval growth in a measurable way. It will be shown later, when discussing the variability of mean pupal size in various years, that growth is indeed affected at densities much below that used in $he experiment. Summarizing we can say that within each sex, pupal size in the field is partly dependent on the genotype, and partly but more significantly on environmental factors influencing larval growth. Of the latter, larval density may well be an important component. The relation between larval density and larval growth calls for an explanation. We can state with certainty that competition for food can be excluded as a causative process both in the experiments and at the

DYNAMICS OF FIELD POPULATION O F P I N E LOOPER

253

highest larval density experienced in the field. Food has always been present in excess. The causation of the interference among larvae is now under study by Mr. P. Gruys of the Institute for Biological Field Research, Arnhem, Netherlands. In one of the Annual Reports of that Institute he has suggested that growth is inhibited by mutual contact between larvae (Gruys, 1963, p. 26).

3. Adult Fecundity The fecundity of individual moths is rather variable within each year as illustrated by the following ranges 1954 1958 1963

153-266 eggs 161-299 eggs 117-267 eggs

These numbers have been determined with females reared from the pupae collected in the field in April (see p. 240). Individual females were caged in an outdoor insectary each with a male, the pairs being composed independently of pupal size. After mating the females readily deposit the bulk of their eggs on the needles of a pine twig placed in the cage, retaining only 0-10 in the oviduct as they do in the field. These eggs have been included in the data on fecundity. Immature eggs without chorion which were always present in the ovarioles after death were excluded. The variation of fecundity proved to be related to pupal diameter. This was readily shown because pupae were reared per mm diameter classes and the females caged separately. Thus for each female the size of its pupa and its fecundity were known. The relation is shown in Fig. 14. The coefficient of regression is of the same order of size for all years studied, and always differs significantly from zero. It indicates that fecundity increases by 100 eggs with an increase of 1 mm size on average. This relationship has already been shown to exist in the same species by several other authors quoted by Klomp (1958). Figure 14 shows that the great variability of fecundity within one pupal diameter class makes pupal size a poor index of aduli; fecundity. This might be the result of several causes, but the only ont: we checked was the variability of egg size. Egg size has been determined by measuring the greatest diameter of the egg. (For method see Klomp, 1958.) An index for the mean egg size of an individual female was obtained from the arithmetic mean of the diameters of all or of the majority of the eggs laid by her. Undoubtedly egg weight would have been a more logical index and less timeconsuming in its determination than mean egg diemmeter. But a suitable balance was not available and the less appropriate index had to be used. Later we were I*

254

H . KLOMP

260

..

J I951

///yy :A/

210Iz

0 z

220-

3

-

u

W

./ / . - ;

200-

180-

160-

I

,

,

,

'/ ,

4.5

,

,

:

,

,

;

5.0

,

,

,

,

,

5.5

,

PUPAL DIAMETER (mm)

2601963 210-

220-

g

-

200-

n 2

-

a

1BO-

160-

I20 1

4% 4

50

0

5.5

4

P U P A L DIAMETER (mm)

FIG. 14. Relation between pupal diameter and adult fecundity in two years. The regression functions of fecundity on pupal size are y = - 189.7 79-5 x and 37 = -342.1 109.9 x. The means a r e indicated on the regression lines by crosslets. The 1964 graph shows 95% confidence limits of the regression line. Each dot represents a female moth.

+

+

DYNAMICS O F FIELD POPULATION O F P I X E LOOPER

255

able to show that maximum egg diameter is highly correlated with egg weight, showing that diameter at any rate can be used as an indel for weight or volume.

The mean egg diameters of individual females have been plotted over fecundity in Fig. 15 within the pupal diameter c1a:ises 4.6-5.0, for the year 1963. Graphs for the extreme pupal size classes have not been composed because of the low numbers within these classes (see Fig. 14, bottom graph). Figure 15 shows that in two out of five pupal classes egg size decreases significantly with an increasing fecundity; in two other cases (pupae 4.6 and 5.0) the evidence strongly suggests such a decrease; only in one case (pupa 4.9 mm) there is no indication of declining egg size, but as appears from Fig. 14 the fecund females fail in this series. I n other years the conformable relationships are very similar to those of 1963. All the evidence together proves that within cne pupal size-class fecundity and egg size are correlated. This is diagrammatically illustrated by graph A of Fig. 16. It can be derived from this diagram, that addition of the graphs shown in Fig. 15 must result in an overall negative correla6ion between fecundity and mean egg diameter. This is shown for 1963 in Fig. 17. The regression coefficient of the relation shown in Fig. 17 amounts to -0.0058, and deviates significantly from zero (P = 0.025). Similar calculations have been performed for the years 1954, 1955, 1957 and 1958 and the regression coefficients were respectively -0*0008(43), -0.0019(66), -0.0030('74) and -0.0028(27) (number of females studied in brackets), which deviate from zero in the year 1957 (P = 0.05) only.

For all years that such an overall regression coefficient of mean egg size on fecundity has been computed, its value is smaller than may be expected from the corresponding relationships within one pupal size class (cf. Fig. 15 with Fig. 17). This is because the egg size increases with an increase of pupal diameter. This is diagrammatmally illustrated in Fig. l&B, and the actual data for 1963 are shown :m Fig. 18. The regression coefficient of the relation shown in Fig. 18 amounts to 0.422, but does not deviate significantly from zero (P = 0.22). I n other years the corresponding coefficients are positive as well, and amount to 0.953( 1954), 0-389(1955), 0-571(1957), 0*882(1958), and 0*502(1959). Tke fact that all values computed are positive makes it very probable that the egg diameter increases with an increase of pupal diameter. Under the hypothesif that no relationship exists there is an equal chance for getting positivb and negative values. The probability of having six equal values then amounts to 2 x (1/2)O = 0.03. Moreover, the regression coefficient deviates significantly from zero in the year 1954 (P = 0.007).

As already shown in the paragraphs on pupal size (p. 252) part of the variability of the pupae is genetic. It is logical to assume that an

“Z

256

H. KL OM P

PUPAL D I A V E T E R L.bmm

21

130

170

150

.

2 2-

21-

210

190

. ..

P z 0.06 230

250

270

* .

4.7mm P = 0.03

* .

20I

..

.

.

*

LSmm P z 0.01

K

W

IiO

l9 W

150

170

’

190

210

230

230

1

270

W

*I

P = 0.60 0

.

21

20-

FIQ.16. Scatter diagrams showing the relation between fecundity and mean egg diameter (in micrometer units) in 1963,within the pupal diameter classes 4.6 to 5.0 (cf. Fig. 14). Each dot represents a female moth. The probabilities given for the scattering, are b d on the hypothesis that there is no relation between fecundity and eggdiaineter (tested with Kendall’s rank correlation method).

DYNA4MICS O F FIELD P O P U L A T I O N O F P I N E LOOPER

257

I

I

T

PUPAL 0 IAM ETE R -+

-

PUPAL DIAMETER--

FIQ. 16. Diagrams showing the relations between pupal diameter, fecundity, and egg size of nine female moths, which have three by three t i n e s the same pupal diameter. A. Egg size (indicated by the size of the dots) is not relai,ed t o pupal size. 13. Egg size increases with an increase of pupal size.

accumulation of genes having a posit,ive effect on pupal size is also expressed in the size of the moths and in the size of the eggs produced. The fact that large pupae give rise to large moths has already been demonstrated by Klomp (1958). And the evidence given here shows that large moths produce large eggs on the average. The relations found are at first sight self-contradictory. Both fecundity and egg size are positively correlated with. pupal size (Figs. 14 and E

. .

23-

Y

I - Y

-4

I 22P

-

w

21-

u w 2

<

w

I

20-

.

.

FIG.17. Relation between fecundity and mean egg diameter (ih micrometer units) in

1963. This graph is a summary of the graphs given in Fig. 15. Each dot represents a female moth. The regression function of egg-diameteron fecundity is y = 22.4 - 0.0058X.

H . KLOMP

258

"1 *

a Y

-

.

.

*

i i

. 0

.

z 20u -4 5

FIQ.18. Relation between pupal diameter and mean egg diameter (in micrometer units) in 1963. Each dot represents a female moth. The regression function of egg diamet,eron 0.422 x. pupal diameter is y = 19.25

+

18), but nevertheless there is a negative correlation between fecundity and egg size (Fig. 17). As shown above, this results from the fact that the variability of fecundity within each pupal size class is negatively correlated with egg size (Fig. 15).

B.

THE VARIABILITY OF FECUNDITY BETWEEN GENERATIONS

After having studied the causes of the intra-generation variability of fecundity, we will now direct our attention to the annual differences in the number of eggs produced. For reasons given in the foregoing section we again begin with the variations in larval growth, then study the effects of this on pupal size, and conclude with the annual variations of adult fecundity.

1. Larval Growth Larval growth has been studied from 1954 onwards, by measuring the width of the head capsule of larvae collected in the field (see p. 243 and Fig. 11). The results of various years have been summarized in Fig. 19. The ultimate size of the larvae expressed as the mean head width of the last stage (histogram 5 in Fig. 11) varied in different years (see Table XXI) over the range 45-1to 48.6 units and the difference between these extremes is highly significant (t-test; P < 0.001). Another variable of growth is the proportion of larvae with six instars. The trimodal histogram of "instar" 4 in 1957 has already been explained in the foregoing section (p. 243). 4a represents the fourth instar of larvae with six (so called six-instar larvae), and 4b that of larvae with five developmental stages (so called five-instar larvae). A comparison of the surfaces of the histograms 4a and 4b shows roughly that 50-60% of the larvae had six stages in that particular year.

TABLEX X I Some Data on Larval Density, Larval Growth, Pupal Size, and Adult Fecundity, Arranged According to Larval Density Mean head width last larval instar Rough estimate (mean of of proportion histogr. 5, of six-instar Fig. 19) in larvae in yo micr. units

Mean pupal diameter (mm)

Generation

Larval density

1

2

3

4

5

6

7

8

9

1961-62 1951-52 1962-63 1963-64 1956-57' 1955-56 1954-55 1950-51 1960-6 1 ?981 $9 1953-54 1959-60 195%59 1952-53 1957-58

26.0 23.2 19.8 18.3 13.9 12-2 11.5 8.6 7 -0

24 1.7 2.4 1.7 2.2 1-8

0-10 0- 10 0-10 0-10 5-20 0-10

45 *4

20-40 J+60 80-100 20-40 56-60

47.1 45.8 47.1 48 *2 48.6

4.33 4.11 4-29 4.27 4.27 4.30 4.30 4.31 4.38 4.45 4.39 4.49 4.37 4.40

4-82 4.59 4.80 4-83 4.69 4.77 4-83 4-91 5.01 5.01 4.94 5.22 5 -03 5.13

168 136 18!.

3 .O 4 -2 3 -9 3.3

4.51 4-29 4.52 4.47 4.46 4.52 4-50 4.48 4.69 4.68 4.63 4.77 4.62 4.68

c: .n

U "

4.5 4.1 2 -8 1-4 1.2

-

4.3

45 -8 45.1 45.5 46.1 45.8

-

Totals (parasitized pupae included)

Males Females (non-parasit- (non-parasit- Mean ized pupae ized pupae adult only) fecundity only1 -

Stand. dev. of histogr. 4 (Fig. 19) in micr. units

161 166 172 19.5 -

20.5 192 210 178 216

a. larval density expressed as mean number per ma over the period 28 July 10 September. The data presented here deviate slightly from those given by Klomp (1958). due to the fact that the mean has been computed over a longer sampling period. b. 1 micrometer unit = 0.045 mm.

260

H. KLOMP

50*

-

"L I0

20

30

LO

lg5? 50

MICROMETER UNITS

FIG.19. For explanation see facing page.

DYNAMICS O F F I E L D POPULATION O F P I N E L O O P E R

261

An increase in the proportion of six-instar larvae enlarges the surfaces of the histograms 4a and 40, as in 1959, where roughly 80-100~o of the larvae pass through six instars. An increase in the proportion of five-instar larvae, on the other hand, reduces the crurfaces of 4a and 4c, but enlarges 4b, as in 1958 and 1960 (where roughly 20-40% have six instars) and even more so in 1954 (where most probably no larvae have six stages). Thus, an approximate measure for the proportion of sixinstar larvae in the population is the standard deviation of histogram 4. The higher the proportion of these larvae the more individuals shift to the sub-histograms 4a and 4c and, consequently, the greater the standard deviation will be on the whole (Table XXI). The differences between the head widths of final five-instar and sixinstar larvae is small. This has already been noted (p. 252) and it is underlined by histogram 5 (Fig. 19), which is only weakly bimodal in years where both types of larvae are represented in significant numbers. TABLEXXII The Mean Widths of the Head Capsules of the First and the Last Larval Instur in Various Years, Arranged -4fter the Sizc: of the Pormer First instar

Last instar

Year

Head width

St. dev. of mean

Heid width

St. dev. of mean

1960 1961 1963 1958 1959 1955 1957 1962 1956

9 -52 9.64 9.68 9-71 9.80 9.80 9.83 9.84 10.11

0.044 0.021 0.025 0.022 0.023 0.031 0.01 1 0.022 0.040

47.,1 45 .-4 45.1 48.2 47.1 46.1 48.6 45.8 45.5

0.15 0.13 0.1 1 0.16 0.20 0.16 0.21 0.16 0.12

All values expressed in micrometer units. 1 unit

= 0.045 mm.

FIG.19. Histograms of the width of t.he head capsule of larvae in various years, arranged according to larval density (see Table XXI). The first instar has been measured in half micrometer units; all later instars in whole units. 1 unit = 0.045 mm. The numbers measured have all been reduced to 100 per instar. This has no complicationswhere there are five clearly separated instars, such as 1955 and 1961. Where the histograms are not separated, half the number of the least frequent class are allocated to each instar. Where histogram 4 is obviously bi- or trimodal: as in 1959 and 1957, it involves more than one instar, but it is considered as one group for comparative purpoijes. The sex of the larvae is unknown, but as a result of the high numbers measured and i t sex ra$io of about 50%. each histogram can be taken to consist of approximately equal numbers of males and females. Note the steady shift in the size of the last instar going from the top to the bottom of the figure (see Table XXI, column 5). See the text for further explanation.

262

H . KLOMP

But this bimodality may well be the result of differences between the sexes (see Fig. 20). If we now ask the question as to the causation of the size variability we will first state that there is no correlation with the size of the first instar larvae. The size of the latter, it is true, is rather variable and there are statistical differences between years, but it is not simply related to the ultimate size, as shown in Table XXII. Consequently, the remarkable annual variation of the last instar must be the result of factors operating after the egg stage.

40

20

n w

K

I:

!:I 3

LO

-

A

1956 TOTALS

40

r

E

1956 MALES 55

1956 FEMALES

In

> 2

50

L5

40

A 45

50

L5

50

55 1958 MALES

55 1958 FEMALES

w

m

I

LO

2

LO-

2 0-

L5

50

- --

55 1958 TOTALS

WIDTH O F HEAD CAPSULE (MICROMEfER UNITS)

FIG.20. Histograms of the head widths of nymphs in two years, to show the difference between the sexes and the resultant weakly bimodal distribution of the totals. The histograms of the totals do not entirely coincide with the relevant ones of Fig. 19 because in the latter larvae in the final instar have been added (cf. Fig. 11). No data for other years are available.

DYNAMICS O F F I E L D POPULATION O F P t N E L O O P E R

263

A possible cause of variability in size and in the proportion of sixinstar larvae in the field would be the ever-changing weather. We did not study this factor. The influence of weather 011 growth may be expected to be rather complicated. The slow growing larvae are exposed to the weather for a period of about three months, and as shown by Schwenke (1953),the various instars have different temperature optima. Moreover, temperature and light may be supposed to have an effect on the number of instars, but we are not informed a,bout the mechanism determining this number. To appreciate the influence of the weather, it is necessary to know more about the precise effect of separate physical factors on the growth of this species, and at present our knowledge is entirely insufficient in this respect. It appeared, however, that the above variation is correlated with density. This is shown for the ultimate size of the larvae in Fig. 21 and in Table XXI. High larval density is correlated with small size of head

1

8 LARVAL

12 I6 a0 DENSITY (NUMBERS PER

-

sa.cN.)

24

28

FIG. 21. Correlation between larval density and the size of fully grown larvae, mainly nymphs. The numerals refer to years. See Table XXI (columns 2 end 6) and Fig. 19. See the text for the abnormal position of the 1984 point.

capsule in the last larval instar. The relation is :most pronounced in densities up to about 12 larvae/m2, whereas at higher densities head width decreases only little, if at all. The 1964 data were unusual because abnormally high September temperatures induced an inhibition of larval growth especially in the fourth and fifth instar. The proportion of six-instar larvae was correlated with larval density. This is shown in Table XXI and in Fig. 22. In this case also, the correlation is most pronounced in the low range of densities, whereas at numbers higher than 12/m2 the standard deviation is independent of density, probably because all individuals have five instars (cf. Fig. 19). The question must be raised as to whether these relations are causal. In the experiment (pages 246 to 252) it was shown that the presence of

264

H. KLOMP 5,

I d

4-

=

3-

eI? 8

a57

a59 as8

*64

em

2

e55

d 2-

em

e6L e56

<

m a

a 61

u)

1

FIG.22. Correlation between larval density and the proportioil of six-iwtw larvae in the population. The numerals refer to years. See the text and Table XXI, columns 2 and 3.

two larvae per jar suppressed both the size of the larvae and the proportion of six-instar individuals, and it is attractive to attribute both the field and experimental results to the same cause: growth inhibiting contact between larvae (see p. 253). However obvious, this supposition needed further experimental corroboration, which was provided by Gruys (Klomp and Gruys, 1965), who showed that conformable differences in mean size are obtained between individuals of relatively small artificial populations with various densities, inhabiting similar groups of pine trees of the same wood in one year.

2. Pupal Size It was shown by Klomp (1958) that within one generation larval size was correlated with pupal diameter. This would imply that mean larval size in different years would be correlated with mean pupal diameter (see Fig. 23). From the relations found it follows that pupal

i4L a5, a@ a55 a56

45

MEAN HEAD 46 WIDTHL7 I LAST LARVAL LBI INSTAR 49 1

FIQ.23. Correlation between larval size and pupal diameter. The numerals refer to years (autumn). See Table XXI, columns 6 and 6.

DYNAMICS OF FIELD POPULATION OF P I N E LOOPER

265

diameter will be correlated with larval density, a:3 illustrated in Fig. 24 for both males and females. I n the former the effect of density is much less pronounced than in the latter, which is in accordance with the results of the experiment described earlier (see p. 251). As in the larvae, the growth inhibiting effect of density is particularly evident in the low range, and again appears to be slight or absent at densities higher than 12 larvae/m2 (cf. Figs. 21 and 22).

3. Adult Fecundity It was shown (Fig. 14) that within a generation, fecundity is highly correlated with pupal diameter (means indicated by crosslets). As said

\

MALES

053

LL-

43-

W

I

4

.58

FEMALES

L.9-

in.5j\

L.7-

L61

a56

m51

i

8 12 16 20 LARVAL DENSITY (NUMBERS PER S Q H.)

U

28

Fro. 24. Correlation between larval density and pupal size. The numerals refer to yeam (autumn).See Table XXI, columns 2, 7, and 8.

266

H . KLOMP

on p. 253 the means of fecundity represent the number of eggs deposited plus those few mature eggs present in the oviduct after death. To gain an estimate of the number of eggs laid by females in the field the mean number retained by the females under natural conditions must be subtracted. This number averaged 3.8 for 85 females found dead in the field at the end of the egg-laying period. Therefore, the fecundity figures given in Table XXI are those gained in the cage experiments, of which Fig. 14 gives two examples, but in all years decreased by 4 eggs. The data on fecundity (Table XXI) is plotted against mean pupal size (Fig. 25) to show a high correlation. This means that the annual mean fecundity will be correlated with larval density as is shown in

*I

050 054

200

051

0 60

I

180

2

059

063

160

057

056

053

055 06*

,

I

~ . 7 LB L.D 5.0 SJ M E A N PUPAL DIAMETER ( m m )

1.6

5.2

FIQ.25. Correlation between mean pupal diameter (females)and mean adult fecundity. The numerals refer to years (spring). See Table XXI,columns 8 and 9.

\

059160

z 3 0 L.. w

w <

061162 160-

058t67

I

"Oi

a51t.52

I

L

8 12 16 20 LARVAL DENSITY (NUMBERS PER

2L

sa.M.)

7

28

FIQ. 26. Correlation between larval density and mean adult fecundity. The numerals refer to years. See Table XXI, columns 2 and 9. Kendall's rank correlation method r h w s that the relation is sign5cant (P = 0.019). The regression function is y = 204 -2.02 x.

DYNAM IC S O F FIELD POPULATION

OF

rnm

LOOPER

'707

Fig. 26. Mean fecundity decreases with an increase of larval density and, consequently, the reproductive rate is density dependent in the sense of Varley (1953). From the viewpoint of density regulation this result is of paramount importance, and its significance will be discussed later (pp. 288 and 297). Summarizing this chapter on annual variations of the reproductive rate very briefly, we can state that differences of population density of larvae between years cause differences in the intensity of mutual contact among the individuals. A t high densities the relatively high frequency of contact causes an inhibition of larval growth, resulting in a low fecundity of the moths in the following spring.

v. THE COMPOSITION

O F L I F E TA13LES

To have a general survey on density, fecundity and mortality the data concerned have been arranged in life tables (Table XXIII). The columns in these tables are indicated by the usual s*ymbolsE, 100 q, and d, respectively representing the density in nurnbers/m2, the mortality in yo, and the mortality in numbers/m2. The bold type numerals in column E are direct density estimates from Tables 111,IV, V, V I I I and X; those in column 100 q are the mortality rates obtained by the rearing of the insects detailed in Tables XIII, XIV and XV. The sex ratio figures in 100 p-column are an exception to this rule. They represent the percentages males in the April collections of pupae (p. 240). All other numerals in columns 1 and 100 q are concerned with indirect measurements, such as differences between successivc: density estimates, or previous density estimates multiplied by survival rates. This is more clearly elucidated below. There is again one exception, namely the mortality or emigration index of the moths. This index if3 computed according to the method explained in the bottom part of the life tables. As shown it is based on the difference between the expected and the actual densities of eggs, being an index for the fraction of females which did not deposit their total potential quantity of eggs. .Q number of these females certainly died prior to the deposition of the Grst batch, others after having laid a smaller or larger proportion of their potential production. The difference between expected and actual egg densities may also be caused by an emigration surplus but the females show little flight activity, and I am inclined to attach little or no value to migration in general. True, the males leave the study area regularly during their courtship flight, but measurements showed that the,y entered the area in the same numbers. I am not informed about movements during the night (see also p. 293).

TABLEXXIII Life Tabla Stage

Month

Mortality fector

1

-

Miscellaneous

JdY

hNaS

August

Miscellaneous

Pprasites Miscellaneous

.

Pupae

Dec.

Oct

Total Misselleneous Miscellaneous

Winter predation Miscellaneous April

June

Moths 99

Sex ratio (% 33) Moth mort. index

Mean fecundity Expected BEE8

d

38.0 3.3

61.7 4.5

56.2

136

1

1952-63 1OOq

d

59-4 1.o

22.0 0.4

37

0.7 0.4

1.1

-

-

- -

60.4

22.4

18-1

60.4

14.6

80

15

24.4

69.5

55.6

8.2

2.0

22.4

0.9

19.6

8.6

)31*4

)

5.4

2 -7

2.7

-

-

-

12.5

2.8

12-5

2.8

)82.1

3*5 8.5

0.6

14.6

36-3

0.8 1.9

49.9

2.7

54.0

1.6

1.2

3.6

1-3

I

1.3

X

196 = 234

136

1*3

89.3

13.4

18.8

0.3

2 so 0.02 - - - -

]

50.8

0.66

0.64 2.2

42.2

0.08 0.73

4.5

13.5

40 *O

0.7

0 .o

4.5

0 -0

0.0

4.6 2 *5

45.6

3 .O

2.1

0 .o 2 .o 0 so 33.0

1.o 0.9

--

46.6

- -

30.0

63.9

2.3

86.6

0.63

63.0

1*9

53.2

0.69

55.5

0.06

53.1

0.58

0.04 0.33

0.61 X 136 = 52

1.1

0.52 11.3

0.005

178 0.04 X 1 7 8 == 7.1

46.6 5.4

28.4 3.3

52.0

31.7

60.3

17-5

-11.5 11.5

0.0 13.3

1.5

8.7

1.0

22.0

2.5

0.62

3.5

61-1

6.5

5.7

0.2

6.1 3.0

0.2 0.1

3 -0

41.8

10.0

1.3 0.3

51.8

1.6

56.1

0.79

68.6

0.42

-1.4

0.61 43.0

205

9 *o

0.06

0.8

0.10

d

3.3

21.7

1.5

61

1954-56 1ooq

- -

3 .O

0a 0 0 .o

1

29

0.29 0.34

54.9

0.50

6.2

1.6

16.1

0.61 41.9

1.2

11.9 6.2

6 -3

41.3

--

195

d

--

7 ’ 7 ) 9.6

5.9

1953-54 1ooq

14.0

9 -5

-

1

-

Parasites Miscellaneous Total

1951-52 loop

37.0

Miscellaneous

Nov.

Moths

-

1

14.0

24

Sept.

L-aS Iv-VI Nymph8

Pupae

d

-

Total

Larvae I

11-111 Larvae 111-Iv

1960-61 1ooq

X

0.22

205 = 107

172

0 . 6 1 x 172 = 105

T A E I .XXIII ~ -oontinned

Stage

Month

Eggs

JdY

Mortality factor

Trichogrammu Miscellaneous

I

1955-56 1OOq

33

Total hNaS

1 JdY

Larvae 11-111 LaNW 111-IV

Miscellaneous Sept.

13.9 12.0

Parasites Miscellaneous Total

Nov.

Pupae

DW.

Oct. Miscellaneous

7.4 3.2

2 *6

Parasites Misceiianeous Total Motha

June

Moths 99

Sexratio(% 3 3 )

58

16.3 1.6

31-6

10.5

30.8

17.9

38.2

8.6

62-3

24.9

13.7

1.9

1.2

0.1

4.5 -4.6 38.7

12.2

56.8

4.2

15-6

0.5

1*5

3.1 0 .o

0.08 0 .o

31-6

Moth mort. index

4.1

1*8

1-7

19.2

2 *9

7 *3

0.9 2 *6

21.3 28.6

-

52.9

4.6

56-1

2.3

3.5

5.6 0 .o

0.1 0.0

0.82 6.26

-

39.0 7 .C

0.67 6.13

42.4

1.10

46.6

0.80

65.3

0.83

48.1

0.43

0.90

0.47

166

0.67 x 166 = 111 53/111 = 0.477

161 0.47 22

69-2 9.0

15.2 2.0

78.2

17-2

62.5

3.0

55.6

1.0

0.0

0.0

8.8

0.07

82.2

0.60

5.4

54/76 = 0.711

]

7.5 2.9

d

0.73

0.12

3 $6 2.2

7.7 0.0

0.01

52.5

0.06

0.0

1.8

1.o

0.87

10.4 25.0

1.2

0.10

16.7

0.02

55.3

0.06

0.48

38.9

1.4

0.0

0.0

28.0

0.70

44.4

0.80

216

0.04 x 216 = 8.6 3.2/8.6 = 0.372

20.8 10.0

5.0 2.4 -~ 7.4 30.8 65-1

10.8

36.2

2.1

121.6

0.8

34.5

1.0

36.8

0.70

4.2 0.9

0.05

5.8 3 *7

1.9

1*2 12.0 1.0

0.12

42.3

44.6

0.37 0.02 0.39

56.5

0.27

0.01

1.1

0.58

0.01

36.0 LO.'?

0.40 0.!2 - _ _ 46.9 0.53 52.3

0.30

48.1

0.13

0-28 45.5

0.01

d

2 *9

0.21 37-2

1OOq

16.6

23

- -

1 24

0.41 0-16 0.57

2.5

0.8

5.4

1OOq

4.8

1.8

0.33

x 161 = 76

1

- -

0.8

1969-60

1958-59

0.04 71.1

0.32

d

0.13

iir.8

47.7

58

8.7

1957-58 1OOq

4.8

40 15.1

1 22

28.1 2 *7

0.67

Mean fecundity Expected eggs Actual eggs Mort. index of moths

d

9-3 1-2

2.7

April

Pupae

1956-57 1OOq

37.5

Miscellaneous Winter predation Miscellaneous

1

28-1 3 *5

22.5 Miscellaneous

August

Larvae Iv-VI Nymph

d

0.10

210

192

0.21 x 210 = 44

0.28 X 192 = 54

20144 = 0.455

26/54

24

28

=

0.481

TABLEX X I I I - continued Stage

Month

Eggs

July

Mortality factor Trichogramlna Miscellaneous

I

1960-61 lOOq

28

Total Larvae I

July

Larvae 11-111 Larvae 111-IV

August Miscellaneous Sept.

7.5 6.5

Parasites Miscellaneous Total Oct. Nov.

Pupae

Dec.

Miscellaneous

-

April

Total Moths

-

June

99

8.6

2 a3

61.4

11.9

13.3

1.o

0 .o

0.0

14.6

2.9

Sexratio(% 8 8 ) Moth mort. index

Mean fecunditv

0.07 0.01

33.6

0.77 0.03

34.9

0.80

47.0

0.71

0.79 61

26.3 25.6

-

34.2

13.7

2.7

0.;

1.7

74.3

155

15.9 6.8

15.7 6.7

] 3 *4

22.7 24.8

14.8

2.7

28.4

0.04 0.06

9.7

0.97 0.33

38.1

1.3

59.2

1.2

- 2 *1

1.1

31.1

0.27

2.6

37.9 __ 40.5

10.0

43.2

8.4

34.5

2.9

0.54 47

10.7 6.3

36.3

17.0

12.5 8.6

0 .o

40 *6

38.0 78.6 50.8

2 .O 1.9

3.9

0.83

0.56

39.0

11.7

0.0

0.0

94 22.4 31.8

1.7 4.1

31.2

3.9

43.0

3.7

6.1 0 .o

0.3

5.8

634

-

18.9

2.9 0.87

82.3

3.77

47.5

0-39

45.5

0.20

0.44

X

0.28 -

181 = 98

175

0.44 42

1964-65 1OOq d 40.7 18.6

17.1 7.5

59.3

24.9

62.0

10.G

43.1

2.8

- 17.1

0.50 4.6

I 42

4.9

52.0 181

22.8 13.5

18.3

0.54

169 0.86 x 168 = 114 99

-

9.1 5 .O

d

18.3

5.5 0'29

1963-64 1OOq

47

67.5

0.43 19.0

1

30

20.18

8.4

43.6

0.48

X 196 =

d

77

0.86 60.6

1962-63 1OOq

99

22.3 11.7

3.5 2 *9 0.6

1

13.6 7.1 _ _ _ _ 34.0 20.7

1*3

0.79

196

d

6.2

1*3 1*5

1961-62 1OOq

40

36.1

Parasites Miscellaneous Moths

30.7

2.3

Winter predation Niscellaneous Pupae

7.5 1.1

3.6

Miscellaneous

1 61

26.8 3.9

19.4

Miscellaneous

Larvae IV-VI Nymphs

d

X

175 = 77

6.5 3.7

6.6

31.2

0.24 1.2

37-8

1.4

30.4

0.7

- 2.3 1.6

D Y N A M I C S O F FIELD POPULATION O F PI-SE LOOPER

27 1

By chance the density estimate of a particular stage may turn out to be higher than that in an earlier stage. Examples of this have already been given in Tables IV and VII, and are more frequent in the life tables. Thus in 1953-54 nymphal density was estimated to be 2.5, whereas one month' later pupal density appeared to be 3.0. Such chance effects may even occur in sitiiation!3where by the application of direct measurements mortality factors could be shc wn to operate. Thus in 1951-52 pupal density in April amounted to 3-6/mL,in D'xember to 3.5. Nevertheless 2.2% of the pupae collected in April had been killed, in the main by predators during the previous winter. Similar!y, in 1957-58 the small difference between the density measurements of pupae in April and of moths in June suggests a relatively low mortality rate in that interval of time, but the rearing of pupae proved that more than 5094 of them were parasitized. Another source of inaccuracy is caused by rounding off. Thus, in December and April 1959-60, pupal density was estimated to be 1-19 amd 1-13, respectively. The size of the confidence intervals shows (Table VITI) that t,liere is no sense in presenting the estimations with an accuracy of two decimril places, taliusresulting in 1.2 and 1.1 specimens/iii', respectively. The wint,er inortality o f pupae as measured in April can only account for a difference of 0.06, which might be rounded off to 0.1 specimen/m'. Finally, larval density was not measured in Oc!t,obcr 19C.O and 1961 (Table IV), and nymphal density not measured in 1950, 1951, and 1952 (Table V). Pupal density in December was measured directly only t o 1!h53 inclusive (p. 223). Fecundity was not measured in 1961 and 1964, but determined by interpolation in Fig. 25. Larval parasitism due to Apanteles was not rtssessed in 1953, 1957, 1958, and 1959 (p. 237 and Table XIV).

One point which is cleady brought to light in bhe tables is the incompleteness of the analysis, as shown by the recurrent use of the word miscellaneous. It indicates mostly that the mortality is due to unknown causes, and in addition that several non-separable factors operate simultaneously. All cases in which the term is used will be considered briefly.

( a )Egg Mortality. The miscellaneous mortality lisited in the life tables is specified in Table XI11 and discussed on p. 234. ( b ) First Instar Larval Mortality. This mortality rate is computed as a difference between the July and August densitieri. The former value results from the product of the egg density and the riurvival rate of eggs; the latter is a direct estimate made by sampling trees in the study area. The mortality of the tiny larvae is nearly alwa,ys very high, but is difficult to measure directly because dead specimens shrivel up, leaving extremely small head capsules, which are hardly detectable amidst all other debris. The causes of their deaths can be manifold, but are probably mainly abiotic. A possible biotic factor is a spider, Xysticus audax. This thomisid searches for prey on the needles and it readily accepts first instar caterpillars as food.

1

272

H. KL OM P

(c) Mortality of Later Larval Instars. During the first half of August mortality is a t least partly due to the same factors as in the first instar. Later, birds come into consideration, especially in September when the larvae are of an attractive size, and not only flocks of titmice, but also migrants such as chaffinches and bramblings, will occasionally hunt in the crowns. These predators most probably also account for most of the losses occurring after the October census, because nymphal density is considerably lower than larval density in many years. I n some years (1955 and 1956) a polyhedral disease also plays a significant role (see also Table XIV). ( d )Mortality of Prepupae. I n nearly every year there is a big difference between nymphal density in November and pupal density in December. Predators hardly deserve consideration in this case, because the nymphs fall off the trees and disappear into the moss usually within minutes, and probably in most cases they descend during the night. When reared, nymphs sometimes fail to develop a normal pupal skin and die in the prepupal stage. We are inclined to assume that some of the losses in the field are due to this inability, but more precise information is wanted.

( e ) Winter Mortality of Pupae. Having once reached the pupal stage the insects generally survive the winter very well. When measured directly in the study area there is no mortality in a statistical sense, as shown in the first four years of our investigations. If a large collection of pupae is made in April, then a small fraction is nearly always damaged. (The only exception occurred in 1953.) Most of the damage is due to larvae of an elaterid, Athous subfuscus (which become active in March and April) as shown by the fact that the larvae are often found preying upon the pupae. They bite a hole between the segments of the abdomen, leaving a characteristic and recognizable cause of death which is apparent even after the insect leaves the pupal skin. A very low proportion of the pupae is diseased. They are either covered by mould and already dead, or still alive but with their abdominal segments stretched out and this results in death some weeks later. (f) Post-census Mortality of Pupae. The difference between pupal and moth density is nearly always striking. Most of the mortality is due to parasites which infect the larvae and kill the host at reactivation after hibernation. The parasitism according to species is given in Table XV. With one exception (1958) it cannot account for the total mortality occurring in this time interval. The additional mortality is computed in an indirect way from the difference between pupal and moth density estimates and after allowance for pupal parasites. It is due to various factors, two of which have

D Y N A M I C S OF FIELD POPULATION O F P I ~ Y ELOOPER

273

already been mentioned (p. 240), namely putrefaction and an ichneumon fly. However, the more important component of the complex is the elaterid larva. Its feeding stage is still active in May, and when numerous may destroy a considerable proportion of the pupae in the litter. Samples taken in the second half of May proved that this had occurred, certainly in 1953 and 1963. The life tables show in a relatively detailed manner the large losses which occur in the population. That the generatioi mortality must be necessarily high is obvious from the simple fact that one female produces some 200 eggs, and where the population density has no upward trend the total mortality can be expected to fluctuate around 99% (three examples are shown in Fig. 10). Though far from being complete, the life tables: are sufficiently detailed to provide us with an insight into the hazards faced by the population. Their presentation is essential because they contain all the basic material indispensable for a further analysis.

VI. THE ANALYSISOF A.

THE

CAUSESOF FLUCTUATION

THE P A T T E R N O F FLUCTUATION

The population density of the pine looper shows more or less cyclic fluctuations (see Fig. 27). Considering egg densities, it appears that the differences from generation to generation may be considerable. This is expressed in a meaningful way by the size of the population trend (R), being the quotient of densities of two successive generations (Balch and Bird, 1944). The extreme values occur from 1952 to 1953 and from 1953 to 1954, R being 0.17 and 9.7, respectively. This range approximates with those of other endemic pine forest insects, indicating that the type of fluctuation found in the pine looper is representative for pine caterpillars as a whole (Klomp, 1962). The question may be raised as to whether the pattern of fluctuation is a statistical reality. This point is considered in Fig. 28, where the 95% confidence intervals of pupal density in April are given (cf. Table VIII). It is evident that the population lows of 1953 and 1958 are highly significant. Moreover, the steady increase fiom 1959 toward 1963 is significant, as shown by the fact that the intervals of 1959 and 1961, and also those of 1961 and 1963 do not overhp. The pattern of fluctuation of pupal density is reflected in the pattern of moth density, and the latter again in that of egg density. Consequently, it seems safe to conclude that the population at least in broad outline behaved as portrayed in Fig. 27.

I

1950/51

1952/!S

1954/55

l95Ej/5?

1958/59 ' 1960/6( GENERATIONS (YEARS)

lQ&/.S

'

1961;/65

FIQ. 27. Fluctuations of density over 15 years of various stages of the pine looper. Densities connected by solid lines refer to independent field estimates; those connected by the broken line (larvae I) are indirect estimates, obtained from the product of egg densities and annual egg survival rates. Larval density (September) in 1962-63 was not measured directly (see Tables IV and XXIII).

I

,

4961

1963

1955

105?

1959

GENERATIONS

f961

(YEARS)

I963

FIQ.28. Changes in pupal density in April over 14 years, indicated by the shifts of the 95% confidence intervals presented in Table VIII. See the text.

DYNAMICS O F F I E L D POPULATION O F P I b - E L O O P E R

B. KEY-FACTOR

275

ANALYSIS

1. Generation Mortality and Age-interval Mortalities

To study the factors responsible for the changes in population density we adopted the key-factor method described by Varley and Gradwell (1960). I n this method total generation mortality (K), occurring from egg to moth stage, is compared with the suh-mortalities k,, k,, k, . . . . .) occurring in definite time intervals or, as we did, in the successive stages of the insect. To make an inter-generation comparison possible, mortality cannot be expressed as absolute numbers dying in the successive generations of a definite stage, but must be given as a relative index. This can be done in a meaningful way by taking the differences of the logarithms of the densities occurring prior to and after the incidence of the mortality. This is elucidated in Table XXIV, where the 19Ei9-60 generation is treated in full detail. The absolute densities from which we proceeded are given in the life tables. To facilitate the transfoymation of k-values to percentages for readers not yet familiar with the method, the relationship between the two measures is given in Pig. .

c2

100

k0

f ,,I

.

99.5L

90

T9

99.9

-

!i I60

8 -

a

g 20-

I

k-VALUE

FIQ.29. Itelation between k-value and percentage mortality.

It is shown in Table XXIV that the fraction of males is also treated as a mortality factor (k1J and is thus included in the analysis. This is meaningful because a fluctua.ting sex ratio will contribute to the causation of population fluctuation. Again, the fluctuating mean fecundity was treated similarly. Following Morris (1963a, p. 18) we considered this factor as operating at the end of the generation by the density of which its size was primarily determined (Section I V ) . We started from the 1957-58 generation having the highest mean fecundity (216 eggs per female), and considered all the other generations as having a reduced fecundity (k12).To incorporate the reduction as a factor in the

276

H . KLOMP

analysis, we computed the density of female moths (with a maximum fecundity) needed to produce just the numbers of eggs found per m2 in the next generation (moths, female 216 in Table XXIV; see also the relevant footnote to this table). TABLEXXIV Computation of k-values of Mortality Occurring in Generation 1959-60 ~~~~~~~

stage

Eggs Larvae I Larvae 11-111 Aug. Larvae 111-V Sept. Larvae IV-VI Oct.

Nymphs Pupae (Dec.) Pupae (Apr.) Pupae (“May”) Moths (June) Moths, females 1 Moths, females 2 Moths, females 2 16

Mortality factors

Egg mort.

L I-mort. L II/III-mort. L III/IV-mort.

L IV/VI-mort. Prepupal mort. Winter mort. Parasites Miscellaneous Sex ratio Female mort. Reduced fec.

~~

Log. Density density

24

1.38

16.6

1*22

5 *8

0.76

3 -7

0.57

2-9

0-46

1 -9

0.28

1.2

0.08

1.1

0.04

0.7

-0.155

0~ 5 8

k-values

k,

= 0.19

k,

=

k, = 0.18

-0.24

0-276

-0.56

0.142

-0.85

0.1308

-0.89

+ +. +

Larval

0.11 )mort. =

k2-@= 1.14

k,,

= 0.32

k,,

= 0.29

k,, = 0.04b

+

Qeneration mortality: E = 1.38 - (-0.89) = 2.27 = kl k, * * kll kl,. Density (of female moths 216) for maintaining steady state: 24/216 = 0.11. Generation mortality in steady state: K1 = log 24 - log 24/216 = log 216 = 2.33, being 99.64% (Fig. 20).

*. Theoretical density (of female moths with a mean fecundity of 216) computed as: (egg deneity next generation)/(maximum fecundity) = 281216 = 0.130. b. Can also be computed BS log (maximum fecundity) - log (actual fecundity) = log 216 - log 192 = 0.04.

Finally it is shown in Table XXIV how to compute the generation k-value corresponding with a steady state situation. This value (Kl) equals the logarithm of the maximum fecundity and amounts to 2-33. Values of k as presented in Table XXIV have been computed for all generations; they will be given in graphical form only. Firstly, in Fig. 30

DYNAMICS OF FIELD POPULATION OF P I N E LOOPER

I

1950/51

' 1952/55

' 4951j55

'

195d157

'

W&/S

W&

I%;,k53

'

377

IPG~/SI

Fro. 30. Comparison of the fluctuations of egg density with the fluctuations of generation mortality, expressed as K-value. K' indicates the value of K in the steady state. See the text.

the generation mortality graph is compared with the fluctuations of egg density. Quite logically it appears that the densitfy increases if K is smaller than the steady state value of 2.33, and conversely. The more K deviates from 2-33,the more pronounced is the densit'y change. Secondly, in Fig. 31, a comparison is made between the generation mortality and the sub-mortality graphs of eggs, larvae, pupae and moths, and with the fluctuations of the sex ratio and the reduction of fecundity. It will be evident that total generation mortality is largely controlled by the size of larval mortality. This is due to the fact that larval mortality fluctuates considerably, but moreover that the mortality rate is on a high level on the average. This will be evident from the following survey, where the ranges and the means of the age-interval mortality rates, the sex ratio, and the fecundity reduction rates are given. egg range 10-78y0, mean 38% 1arva 42-97y0, 90 Yo Pupa 22-85 yo, 60 Y O sex ratio 47-59y0, 53% males moth 11-71Y0, 47 % reduction of fecundity 0-37 yo, 16%

278

H . KLORlP K-VALUE

3.0 GENERATION MORTALITY (K) 2.5

2 .a

E ~ GMORTALITY

0.5

0.0

A

1.5

LARVAL

(k,)

MORTALITY ( L - k c )

1.0

0.5

PUPAL

MORTALITY

.. -' '

0.5 0.3

-

( kr k9)

4

0.4 0.2 0.5

0.0

REDUCTION

02

OF

lO&/Sl

FECUNDITY (kn)

/

0.0 a

1952153

'

195l1'/35

1956/57

1950)59

'

1964/61

19&/63

. rl

FIG.31. Comparison of fluctuations of age-interval mortalities, sex ratio and reduction of fecundity with the fluctuations of generation mortality.

worm by Morris (1963a, p. 35) of the fact, already pointed out by Morris (1957), that even small variations of a factor affecting a high

DYNAMICS O F FIELD POPULATION OF PINE LOOPER

279

mortality have a relatively large effect on generation mortality. Consequently, as demonstrated here, the effect of large variations of such a factor will be enormous. How close generation mortality is under the influence of larval mortality is shown in Fig. 32, where K is plotted over k,-k,. 0

b2 0

53

0

51 0

66 0

6z

0

51r

0

63 0

59 0

*i

0

61

0

60 0

50 0

58

L I

0.5 1.0 k-VALUE OF LARVAL MORTALITY

1.1

(k%- k6)

FIQ.32. Graph showing the influence of larval mortality on generation mortality. The numerals refer to years. See the text.

On the other hand Fig. 32 demonstrates that in some years generation mortality is higher than expected according to the relevant larval mortality. This proves to be due to various causes in different years. 1952 is a very extreme year, and as shown in Fig. 31 this is evidently the result of abnormally high egg and pupal mortalities. The former is caused by the egg parasite Trichogramma (Tables XI11 and XXIII), the latter by the larvae of the beetle, Athous suhfwcus (p. 273). I n 1957 the egg mortality due to Trichogranainais even Ihigher,(Tables XI11 and XXIII), but its effect on generation mortality is damped rather than strengthened by pupal mortality.

H. KLOMP

280

Two other years are worth considering, namely 1962 and 1963. Generation mortality is then also higher than expected according to larval mortality, and in both years this results from a high pupal mortality, but the causes differ. I n the 1962163 season the fraction of pupae killed by parasites is in the normal range, but the post-census mortality of pupae is high as a result of an abnormally high density of the larvae of the predatory beetle, Athous subfuscus. I n the 1963/64 generation, on the other hand, the parasites Blondelia and Poecilostictus cause a high pupal death rate (Tables XV, XXIII, and Fig. 31). Figure 31 further demoiistrates that generation mortality is not affected by the minor fluctuations of the sex ratio, and to an insignificant extent only by the density induced variability of the reduction of fecundity. The sex ratio is a factor on an intermediate level, but ha,rdly fluctuates, and can thus be expected to have no effect. Fecundity reduction varies more, but is ineffective as a result of the low level on which the fluctuations occur (p. 277). To sum up, it is shown that the fluctuations of the population density are primarily controlled by larval mortality changes, with occasional secondary effects of egg and pupal mortality superimposed upon them.

2. Age-interval Mortalities and their Contribution to Density

It can be objected that the conclusions reached in the foregoing section are supported only by a visual comparison of the graphs of Fig. 31. To meet this objection we applied the method of key-factor analysis described by Morris (1959, 1963b) to the same population data. This method starts from the fact that the density of a definite stage, e.g. egg density, is determined in succession by the egg density of the previous generation, the mortality of the eggs, the mortality of the larvae, the mortality of the pupae, and so on. To be informed about the effect of the separate components, the correlation between the egg densities of two successive generations is first studied, moving from the first to the last generation for which data are available. Secondly, to learn the effect of egg mortality, the correlation between the density of first instar larvae and the egg density of the next generation is studied, and so on. The quantitative formulatiojl of this method starts from the function Et+i = Et . sl.

where Et 8,

F

S,

. . . . . . s I 2 .F

egg density of generation t fraction surviving in the successive age intervals (s, = 1-p,, where pi is the fraction apparent mortality in the relevant interval) = fecundity (the maximum fecundity in this study, being 216 egg;gs/ female) =

=

281

DYNAMICS OF FIELD POPULATION O F P I N E LOOPER

To provide linearity and to stabilize variance, both the densities and the survival rates are converted to logarithms (Morris, 1963b). I n the analysis applied in this study the age interval mortalities and accordingly the survival rates are combined in the same groups as the k-values in Table XXIV. The contribution of Et to the size of Et+l is studied bj' plotting log Ettl over log Et (Fig. 33-A), and then the regression function log Et+i

=

b, log Et

+ I o ~ ( s , . s2. . . . . .

. F)

~ 1 2

can be computed, and the coefficients of regression (b,) m d correlation (r,) can be determined. The contribution of the mortality fluctuations in the egg stage to the annual changes of egg density r a n be analysed by plotting log Et+l over log (Et . s,), from which the regression function log Et+i = b, log(Et. 81)

+ log(s2.

63.

. . . . . 91,.

F)

can be computed, and the coefficients b, and r1 can be determined (Fig. 33-B). Similarly, the contribution of the mortality in the larval stage can be analyeed by the regression log Et+i = bl-6 log(Et

. S, . S, . . . . . . s6) + 1 0 g ( ~ ,. . . s,, . F)

giving b1-# and rl-&(Fig. 33-C), and so forth. The values plotted can be derived quite simply from the life tables, because in fact they all represent densities given in Table XXIII, column I ) . Thus . . sa) is the number of individuals surviving the larval stage, (Et . s1 . s z being 1-2 pupae in 1959/60, and the value plotted for this year in Fig. 33-C is log 1.2 = 0.08 (see also Table XXIV).

... .

The results of this analysis are presented in Fig. 33 and Table XXV. We have studied the effects of the mortalities in the successive ageintervals, and also those of the sex ratio and the variable reduction of fecundity. The effects of the different components of this complex of factors on the egg density of generation t 1 is expressed as their

+

TABLEXXV Results of Key-factor Analysis of Populatim Data

Component

log Et+i plotted over

Egg density of previous generation Egg mortality Larval mortality Pupal mortality Sex ratio Moth mortality Reduced fecundity

log Et log Et s1 log Et . s1 . . s6 log Et 9,. .sP log Et . s1 . . sl0 log Et . S, . . sll log EL. 5,. . s12

_-

.

-~

Coefficient of

correlation

--___

0.13 0.39 rl-@ = 0.85 rl-o = 0.95 rl-,, 0.94 rl-,, 0.99 rl-,? = 1.00 ro

r1

=

=

regression b, b, bl-e bl-9 b,-,, b,-,, b,-,,

=

0.13 0.38 = 0.76 = 0.85 = 0.84 = 0.96 =

=

1.00

282

€ KLOMP I.

1

1.5

- 0.5

LOG

Et

2

I/;

A

B

I .

LO6 E+.S, 1

0.5

-1

-as

15

1

LOO Et. 5, 0

0.5

Et+1

L O 6 Et . S q . i o

4.5

-1.5

-1

-1

-0.5

0

-0.5

FIQ.33. Regression diagrams for key-factor analysis. For further explanation see the text.

DYNAMICS O F FIELD POPULATION O F P I N E LOOPER

283

respective contributions to the gradual increase of the correlation coefficient. (The regression coefficient, which is an index of density dependence, will be discussed in the next chapter.) The size of r,, indicates that there is hardly any relation between the egg densities of successive generations (Fig. 33-A). Indeed, as shown in Fig. 27, the egg density can change generation by generation from an extremely high (1951) to an intermediate level (191i2),and in the opposite direction from a low (1953)to a high level (1954), thus giving quite a different picture from most of the forest insects studied by Morris (1959, 1963a, 1963b). The addition of the effect of egg mortality to the influence of egg density increases the correlation coe%cient to 0-3!1, and this improvement shows that this component supplies a clear, albeit not very pronounced contribution to egg density (Fig. 33-B). The correlation is much more improved when larval survival is plotted against egg density (Fig. 33-C), giving a coefficient of 0.85. This shows that the density of the next generation is m,%inlydetermined by the fate of this stage. Further improvement of the coefficient is due to pupal mortality, whereas moth mortality, and especially sex ratio and reduced fecundity have hardly any effect (Fig. 33-D-F). It will be evident that the addition of the final component, the reduction of fecundity, results in a correlation coefficienl; equal to unity, because of the fact that the values of log(Et . s1 . . . sI2) all equal log Et+l/log F = log Ettl/log 216 (Fig. 33-G). To sum up it is shown that the results of this quantitative analysis are in agreement with the conclusions reached by visual consideration of Fig. 31. Egg density is mainly determined by the numbers of insects surviving the larval stage in the previous generation. However, larval mortality is due to a complex system of factors oporating on the population in succession over a long period of time. WCIhave, therefore, to concentrate on a more detailed analysis of this complex.

3. Analysis of Larval Mortality As shown in Table XXIV, larval mortality is composed of five sub-

mortalities (k2-kE),which have been discussed on p. 271. From the life tables it appears that the densities needed to compute the k-values of the sub-mortalities have not been estimated completely annually. Therefore we joined k, and k, as juvenile mortality (including all of the larval mortality up to the end of August), and k, and k, as mortality of advanced larvae. Prior to 1955 k4-5could not be tieparated from prepupal mortality (kE),because of the fact that nymphal density was inadequately measured (1954)or not measured at all.

2 84

H . KL OM P

The k-values are presented in Fig. 34. It is shown that the agreement between total larval mortality and juvenile?mortality is reasonably good. The direction of change is opposite in 1961 only. When the mortalities of advanced larvae and prepupae are considered jointly (k4-,)there also seems to be a (less pronounced) relation. However, for the years that k4-, can be divided up in k4-5and k, neither of these components seems to bear any relation to the fluctuations of larval mortality. Thus, the visual consideration of Fig. 34 does not provide a clear insight into the contribution of the sub-mortalities to the causation of total larval mortality fluctuations, Therefore this question is studied again quantitatively with correlation analysis. L -VALUE 4 3

.

1.0

-

LARVAL

(4-ke)

MORTALITY

0.5.

*

4.0

@

1

l

1

1

1

JUVENILE

1

1

1

MORTALITY

1

(kz-k3)

0.5.

0.0.

*'.

,

1950

'

IB52

'

19'51

\--

'

49k6

-

lQk6

*

1960

'

-.

1%2'

FIG.34. Comparison of fluctuations of larval mortality in the juvenile, advanced, and prepupal stages wit,h total larval mortality.

DYNAMICS O F FIELD POPULATION O F P I N E LOOPER

285

Here we start from the fact that pupal density in December is determined in succession by the density of first instar larvae, the juvenile mortality, the mortality of advanced larvae and, finally, prepupal mortality. To be informed about the effects of these components we studied the correlation between pupal density and the relevant densities of the earlier stages of larval development. The results are presented in Fig. 35

1

0.5

2

1.5

Q

B LO6

1.

.

0

. 0.5

LOG

L,

N

1

FIG.35. Regression diagrams for key factor analysis. LI, L,, N, and P refer to the densities of first instar larvae, September larvae, nymphs and December pupae. The encircled points represent densities from 1950-54, which are lacking in diagram C, because nymphal density was not measured. (See text.)

286

H . KLOIII’

TABLEXXVI Results of Key-.fuctor diiulysis of Larval Density Fluctuations

Component Density of first instar larvae Juvenile mortality Mortality of advanced larvae Preptipal mortality

log P plotted over

log log lop log

LI

Ls N P

Coefficient of ~~

-

correlation

regression

0-65 0.87 0.94 1 *oo

0.73 0.8‘ 1 a35 1 -00

L I , L., N, and I’ refer to the densities of Hrst instar larvae. September larvae, nymphs, and pupae.

and Table XXVI. As appears from the differences between correlation coefficients first instar larval mortality supplies by far the greatest contribution to the size of the pupal population, whereas the effects of the mortalities of older larvae are small and about equal. First instar larval mortality appears thus to be a predominant component in the determination of the pattern of density fluctuation. This is because of the great variability in the high mean proportion of larvae which die. As already pointed out (p. 271) we are lacking information about the mortality factors involved, and as a result we do not in fact know why density fluctuates. I n general, we are inclined to attribute most of the fluctuations to the effects of weather, but in the pine looper, annual variations in viability of young larvae may well prove to be of equal or of greater importance (see p. 297).

V I I . THE ANALYSISO F

THE

CAUSESOF REGULATION

A . THE INCIDENCE O F REQULATION It has been stated by several ecologists, mostly on theoretical grounds, that the numbers in animal populations are regulated by density dependent and (or) delayed density dependent mechanisms. (For definitions, see Varley (1947) and Varley (1953).)The arguments used have been quoted by Wilbert (1962) and Klomp (1962) and will not be repeated at length. We will refer to Varley and Gradwell (1962) only, who observed that on oak trees several phytophagous caterpillar species fluctuate in numbers within relatively nmrow limits about different means, thus giving rise to what are called common and rare species in the same habitat. The authors deduced from these facts that density governed regulating mechanisms must be in operation, stabilizing each species a t its specific level of density. I n pine forests we observed quite similar conditions within a group of related plant-eating caterpillar

DYNAMICS OF FIELD POPULATION OF P I N E LOOPER

287

species including Bupalus, and reached the saime conclusion along similar lines of reasoning (Klomp, 1962). However, reaching this conclusion on theoretical grounds does not relieve us of the task of providing practical proof that regulation in fact operates in the Bupalus population under study, and especially to show how it operates. The incidence of regulatory processes in the Bupalus population can be demonstrated by the use of statistics. Therefcre we computed the regression of K-values of generation mortality on the logarithm of initial egg density for different years (Fig. 36). l'he coefficient of regression equals 0.87 and deviates significantly from zero (P = 0.01). 3.0 h

w 3

1

$

v Y -1

J

2.5

-

P

I

0.5

1.0

1.5

I

!LO

L 0 6 . € 6 6 DENSIT"

FIQ.36. Density dependent relationship between generation mortality (K) and egg density (Seetext).

This shows that there is a clear tendency for the gmeration mortality to be greater at the higher densities, i.e. generation :mortality is density related, being either density dependent or delayed density dependent. As already pointed out by Varley and Gradwell (1963), this statistical test is strictly speaking invalid, because the K-value is partly computed from the logarithm of egg density, and consequently the values plotted are not independent. However, the action of regulation is also demonstrated in Fig. 33-A, where independent estimations of egg density have been plotted. If it is assumed that no density related processes are operating, then there would be equal chances for Et+l to be

255

H . KLOMP

higher or lower than Et independent of the size of Et, and in that case the coefficient of regression of log Et+l on log Et tends to equal unity. As shown in Table XXV this coefficient is 0.13 only and deviates significantly from unity (P < O - O l ) , indicating that there is a strong tendency for Et+l to be smaller than Et a t the higher values of the latter, as a result of density related generation mortality. These facts make it appear extremely likely that the population of Bupalus is stabilized by one or more regulating processes, and in the following sections we shall have to give further consideration to the way in which these processes operate.

B.

DENSITY DEPENDENT FECUNDITY

In Chapter IV-B it was pointed out that larval density has an influence on larval growth through mutual interference. It was shown that high density inhibits growth, resulting in small pupae and giving rise to moths with a relatively low fecundity (Figs. 24 and 2 6 ) . The regression line in Fig. 26 shows that, on average, the fecundity decreases by 20 eggs when larval density increases by 10 individuals/mZ. Within the density range observed in the field this means a 25% overall reduction going from minimum to maximum density levels. At first sight this may seem to be considerable, but the power of regulation resulting from this reduction is small. This can be illustrated in various ways. One of these methods makes use of the effect of the density dependent factor (in this case fecundity) on the net rate of reproduction R ( = the index of population trend, being the quotient of successive densities of the same stage, e.g. Et+JEt), assuming for the sake of simplicity the resultant fraction (s) surviving the mortality factors to be constant. If we indicate the mean density level by p , and the deviations of this mean by up, then R roughly equals l / q a . This can be illustrated as follows. Let us assume the population to be in balance a t the mean density of Fig. 26 (p = 10 larvae/m'). Then the mean fecundity is 182, and consequently 8 = 1/182. If the population increases to 2p = 20, then fecundity decreases to 163, and R = 163 x 1/182 = 0.90 Z 1/+2. If density decreases to 1/2 p = 5, then fecundity increases to 193 and R = 193/182 = 1.06 Z 1/+(1/2).

This means that without 'the action of other density related mechanisms the population tends to approach asymptotically and slowly to the mean level as a result of the density governed fecundity, the suc~ ~ so on. cessive densities being e.g. 5p, 3 . 6 p , 2.513, 2 . 3 1~ .~ 9 and It might be supposed that the regulation of numbers in the Bupalus population is realized in this way, but that in the field the gradual return to the mean level is distorted by density independent variation of

DYNAMICS O F FIELD POPULATION O F P . N E LOOPER

289

rise to the irregular density fluctuations presented in Fig. 27. That this is not so is demonstrated by another method, which we have to consider next. In general, regulation might be expected to be in operation when the population declines after having reached a high level, or increases sharply after a very low level. The years in which this occurred are shown in Fig. 27, and Fig. 31 demonstrates that the density induced variability of fecundity in these cases is far from being a predominating factor in the complex of agents involved in the density changes. This strongly suggests that the population is under the control of additional regulating factors, and the proof of this will now be given. It was pointed out on pp. 287-288, that the coefficient of regression of log Et+l on log Et (Fig. 33-A) tends to be unit,y when numbers are wholly determined by density independent ageds. This coefficient proved to be 0.13 only, indicating strong density related action (see p. 288). In Table XXV it is shown that the gradual addition of the ageinterval mortalities gives a remarkable improvement to the regression coefficient, whereas adding the reduced fecundity increases the coefficient with a final 4% only. This proves that most ofthe regulation must be concealed in the mortality factors. Taking all the evidence together, it demonstrates that density dependent fecundity is of minor importance in the population dynamics of the pine looper. However, in a later section (p. 297) evidence is presented suggesting that the immediate cause of the fecundity reduction, namely the increase in the contact interference between larvae at the higher densities, has additional effects on the viallility of the insects, and these may well appear to be of primary significance in regulation. 8, giving

c. D E N S I T Y D E P E N D E N T MORTALITY The regulating agents said to be concealed in the mortality factors may be density dependent or delayed density dependent. We are concerned here with the analysis of the former category. In Section VII-D attention is particularly directed to the delayed processes.

1. Mortality in the Egg Stage Comparing Fig. 33-B with 33-A shows that there is a rise of the regression coefficient of 0.13 to 0.38 (Table XXV), if the effect of egg mortality is added to egg density. This suggests that egg mortality includes a source of compensatory reaction. To check whether this reaction is of the direct density dependent type we plotted k, over the logarithm of egg density, and it was found that k, increases slowly with

I

290

H . KLOMP

+

rising egg density (k, = 0.124 0.07 log E), but the regression coefficient does not differ significantly from zero. Egg mortality is mainly due to the egg parasite, Trichogramma, and if this parasite should operate as a delayed factor, a simple relation betveen k, and density cannot be expected. The k-value of the remaining miscellaneous mortality factors affecting the egg, which can be computed separately using the data of Table XPII, does not appear to be correlated with egg density either, and from this we conclude that in the egg stage direct density dependent mortality cannot be shown to occur.

2. Mortality i n the Larval Stage It is shown in Table XXV that the addition of larval mortality gives a remarkable improvement of the regression coefficient (cf. Fig. 3 3 4 and C), and this indicates that powerful regulation occurs in this stage. As already pointed out larvae are subjected to a complex system of factors operating in succession over a long period of time and, therefore, the density dependence in this system will be studied for the various age-intervals mentioned in Table XXVI. ( a )Juvenile Mortality. The improvement of the regression coefficient from 0.73 to 0-82 in Table XXVI indicates the possible existence of a weak density relationship (see also Fig. 35). The k-values of juvenile mortality (k2-3),when plotted over first instar larval density (LI), do not tend to increase with a rising density, and a direct density dependency of juvenile mortality can safely be excluded. ( b ) Mortality of Advanced Larvae. Table XXVI reveals an enormous increase of the regression coefficient when the density of surviving advanced larvae (nymphs) is plotted over pupal density (Fig. 35-B and C). This might indicate the occurrence of density dependence in this age-interval mortality. However, such an effect cannot make the coefficient exceed unity. That this occurs is due to the abnormally high prepupal mortality in 1957, while the density is then at its minimum (Fig. 27). This makes the relation to be inversely density dependent, resulting in the high value of the regression coefficient (Fig. 35-C). This inverse effect is also incorporated in the regression diagrams of Fig. 35-A and B because in all graphs pupal density has been plotted. It is much less obvious, however, because its influence is counterbalanced by the density related processes acting on the advanced larvae (see below). The exclusion of these processes results in a full expression of the inverse effect in Fig. 35-C. The mortality of advanced larvae proves to be density dependent. This is shown by plotting the relevant k-values (k4--6)over larval

DYNAMICS OF F I E L D POPULATION O F P I N E LOOPER

29 1

September density (Fig. 37-A). The regression coefficient (0.33) differs significantly from zero. To test this relationship further we computed the regression of nymphal density over larval September density (Fig. 37-B). As already stated, without density governed effects this should result in a regression coefficient equal to unity. Here, however, it is 0.68 and differs significantly from unity (confidence interval of regression coefficient b j=3 . s;, 0.46 < b < 0.90). As to the causation of this density governed mortality we can only make suppositions, because our field evidence with reference to this point is too scanty. Disease and predation by birds are the first agents to be mentioned. The response of birds would be functional in this case (Solomon, 1949; see also p. 2943, and might be due to the fact that the polyphagous predators concentrate on eating prey species which are temporarily numerous. An effect of this type has heen found by Varley and Gradwell (1963) in the winter moth, Operopiitera brumata, which are preyed upon by the larvae of a beetle and some mammalian predators. I n Dutch pine woods titmice with their varied diet concentrate on the more numerous prey species, thus giving rise to a density dependent predation over at least part of the density range of these species (Tinbergen, 1960; Tinbergen and Klomp, 1960). The density dependence of the mortality in this age-interval is more powerful than that of the fecundity. It can be derived that a density deviation up induces roughly a net rete of reproduction R z (see p. 288). As a result of this the population would also tend to apprciach asymptotically to the mean level, but moxe rapidly than under the sole influence of the density governed fecundity, the successive densities being e.g. 5p, 2.9p, 2.013, 1 . 6 ~ .. . . The question arises concerning the power of the combined regulatory effect of these density governed processes. This question can be approached roughly by the following reasoning. Both the mortality of advanced larvae and the fecundity are affected by larval density. Assuming that the population is in balance at the mean level (p. 288), being about 10 larvae/m2,then according to Figs. 26 and 37 the mean fecundity is 182 eggs and the larval mortality amounts to 64.5% (k4-5 = 0-43).Then R = 1 = 0.355 x 182 x s, and s = 0.0155, being the fraction surviving the other mortality factors. If the population increases to 293 = 20, then fecundity decreases to 163, larval mortality increases to 72% (kdP5= 0.53), and R = 0.28 x 163 x 0.0155 = 0.71 1/42. If the population declines to 1/2p = 5, then fecundity increases to 193, larval mortality decreases to 53.5% (k4-5 = 0.32), and R = 0-465 x 193 x 0.0155 = 1.39 1/+J(1/2).

l/Ta

292

H . KLOMP

I.>,

h-r. 0.5 0

0

05

I

LOG L s

1.5

FIG.3 i . A. Density dependent relationship between the mortality of advanced larvas (k,--6) and larval September density (Ls)(k4-5= 0.08 0 . 3 3 log Ls). €3. The relation between nymphal density (N) and larval September density (log N = -0.08 0-68 log L*), (See text).

+

+

Consequently, if we indicate the deviation of the mean level by ap, then R roughly equals 11.\/a, and this results in a rather rapid approach to the mean level, the successive densities being e.g. 5p, 2.3p, 1*5p,. . . . The combined effect of the two density governed processes so far found operating in the populrtion, and density independent variability superimposed upon it, might at first sight result in the pattern of fluctuation observed. However, when the population declines sharply after having reached a high density, it is not the mortality of advanced larvae which is predominating (Fig. 27). This suggests that there are still other regulating processes operating, and this supposition is supported by the results of the following analysis. The regression of larval September density (log Lt,,) on the same

I .

0

0.5

1

LOG L t

.

15

FIQ. 38. Regression diagrams for key-factor analysis. A. Larval September density (Lt,,) plotted over larval September density of the previous year (1954 to 1964 inclusive). B. Larval September density plotted over the number of larvae surviving the mortality of advanced larvae ( = nymphal density) in the previous year (1954 to 1964 inclusive). (See text).

DYNAMICS OF FIELD POPULATION OF I"NE LOOPER

293

density of the previous year (log Lt) results in a regression coeficient of 0.38 (Fig. 38-A). If the former is plotted over the product of the latter and the fraction of advanced larvae surviving (log Lt . sPp5 = the logarithm of nymphal density), then the coefficient iricreases to 0.52 only (Fig. 38-B). This suggests that a good deal of density governed reactiqn must be present in other components, and the weak density induced, variability of fecundity alone cannot account for this. (c) Prepupal Mortality. If the k-values of prepupal mortality (k,) are plotted over nymphal density there proves to be 110 relation.

3. Mortality in the Pupal Stage

The results of the regression analysis shown in Fi,z. 33 and Table XXV suggest that pupal mortality includes a weak density related factor. I n principle this can be both delayed and direct density dependent, because the mortality is partly determined by parasites operating mostly in the preceding summer, and partly by predators (and disease), which are especially active in the period March to June. I n this section the possible occurrence of density dependent factors hits been studied only. The parasites are considered in a later sub-chapter. There proves to be no relation between total pupal mortality (k,-J and pupal December density. Nor is there any relation between the k-value of non-parasitic mortality and pupal density. From these results it is concluded that there is no direct density dependent effect included in this age-interval mortality.

4. H t a l i t y in the Moth Stage As explained on p. 267 the index of female moth mortality is related to the fraction of females which did not deposit their total quantity of eggs due to pre-senile mortality or emigration. When the k-value of this index (kJ is plotted over moth density, then the regression coefficient turns out to be 0.12, but it does not differ significantly from zero. Therefore this factor cannot be considered as being density dependent. Hence, if there is a night movement of females (cf. p. 267) then its intensity is most likely not affected by density. 5. conclusion Summarizing the results of this analysis we ca:n state that density dependent mortality factors were found operating among advanced larvae only. The regulating power of the density governed relationship appeared t o be insufficient, even in co-operation with the density induced variability of the fecundity, to account for the total density related action shown to be present. Therefore, it is most likely that in

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addition one or more delayed density dependent factors have a compensating influence on numbers.

D.

D E L A Y E D DENSITY D E P E N D E N T MORTALITY

1. The Role of Parasitoids Many years ago it was pointed out by Howard (1897) and Howard and Fiske (1911) that insect parasites must play a significant part in the dynamics of the populations of their hosts. These assertions were based mainly on field observations showing increasing percentages of infected hosts when the latter approached infestation levels. These statements later attracted the attention of Nicholson (1933) and Smith (1935). The former has demonstrated in an arithmetic theory, which was later also mathematically formulated (Nicholson and Bailey, 1935), how host and parasite should interact to result in oscillations around fixed levels of density. The first condition to be fulfilled is the synchronization of host and parasite generations. Secondly, according to this theory, when host density increases the parasite population meets more favourable conditions for oviposition, because of an increasing chance of finding a host. This phenomenon, resulting in a higher effective fecundity of the parasite, has been referred to afterwards by Solomon (1949) as being the parasite’s functional response to host density. The result of this response is that notwithstanding the increase of host density the fraction of hosts infected remains about constant, assuming an invariable parasite density. The third starting point of the theory is the assumption that the functional response gives rise to an increase of the numbers of the parasite in the next generation, a phenomenon afterwards indicated by Solomon as the parasite’s numerical response to host density. According to the theory, this rise in parasite density results in a higher fraction of hosts being infected in this new generation, independently of the density of the host. Consequently, the density dependent reaction expressed as an increased percentage mortality is realized one generation after the increase in host numbers which initially put the system into action. Therefore, Varley (1947) has indicated this type of parasite response as being delayed density dependent. This theory of Nicholson>has been criticized on several points. One of the objections levelled against it is the ever-increasing amplitude of the oscillations (Varley, 1947), which are in fact never observed under natural conditions. Tinbergen and Klomp (1960) have presented some models showing that these oscillations can be damped by the introduction of a density dependent factor into the host-parasite system. Varley and Gradwell (1962) have suggested that in the winter moth, Operophteru

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brumata, and its tachinid, Cyzenis albicuns, such oscillations might be damped by density dependent predation occurring in the pupal stage during hibernation. There is as yet very little evidence supporting the theory of Nicholson. Such evidence should comprise field-collected da,ta on the functional and numerical responses of the parasites over a series of successive generations, and material of this kind can in most cases be obtained only by the application of time-consuming sampliiig techniques. Morris (1959, 1963b) has shown that parasites are responsible for most of the density variability in some forest insects, which makes a regulatory influence of parasites appear likely. Other evidence in favour of a regulatory effect of parasitoids is provided by the results of some biological control measures. I n these cases the introduction of a specific parasite has resulted in a stabilization of the density of the pest at a level far below the economically intolerable one. Strictly speaking this fact does not, however, provide proof of regulation by parasites (Klomp, 1962, p. 105). Thus it is clear that there is great need for a be1;ter understanding of the part played by insect parasites in natural populations. Therefore we will consider the parasites of the pine looper in some detail.

(a)Egg Parasites. There is one species infecting eggs: Trichogramma embryophagum (Table XIII). This species is polyphagous and has 5 to 6 generations per year on different hosts in succetsion (Klomp, 1956). This implies that it is not synchronizcd with eii$er of its hosts and cannot be delayed density dependent with reference to the pine looper, because the numbers of the parasite are not only determined by the density of this host species, but also by the numbers of the others. ( b ) Larval Parasites. So far two species have been met infecting and killing the larval stage: a tachinid, Strobliomyia fissicornis, and a braconid, Apanteles caberae (Table XIV and p. :!37). These parasites have no regulatory significance. The tachinid occurred in 1954 and 1955 only. I n the years studied the braconid never infected more than 9% of the larvae, and there is no indication of a numerical response to increases of host density. ( c ) Pupal Parasites. Of the species listed in Tab113XV, Cratichneumn is said not to be synchronized with Bupalus (Thdenhorst, 1939). The adults emerge in May and the females of the first generation fly in May and June, infecting pupae of Bupalus, which at the time have not yet emerged, and some alternative host species. I n addition, the fraction of pupae parasitized by this species never exceeded 6p/,, and consequently it needs no further consideration from the viewpoint of regulation.

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The other species, all infecting host larvae, are most probably all synchronized with the pine looper. Two of these, Heteropelma and Anomalon, are so rare that they do not occur in the extensive samples in several years (Table XV), and hence can be left out of consideration. The fractions of pupae infected by the remaining species are presented in Fig. 39, together with the density fluctuations of the host larvae, which is the stage attacked by the adult parasites. Neither the tachinids Eucarcelia and Blondelia, nor the ichneumonid Poecilostictus shows a clear numerical response to changes of host density. Eucarcelia has a maximum infection rate in 1951 when larval host

-

PER CENT: PARASITISM

I

.- .

TOTAL PUPAL PARASITISM

is51

1953

195s

a

.

49s

1959

.

.

1961

.

-

3%3

FIG.39. Fluctuations of September larval density and the percentages of parasitized pupae. The fractions of pupae infected in April of the years 1951, 1952, etc. have respectively been plotted over 1950, etc., because the April values are representative for the activities of the egg-laying adult parasites in the previous summer (see Table XV).

DYNAMICS OF FIELD POPULATION O F P I N E LOOPER

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density is very high. I n 1952, parasitism by this species slightly de creases, whereas theoretically a considerable increase was to be expected as a response to larval host density in 1951. Earlier, in a preliminary discussion of the significance of this parasite (Klomp, 1959), I did suggest that part of the deviations from expectation might be due to a shortage of sunshine during the period of activity of the fly. However, it is clear that in later years the parasite did not react to large changes of host density either (see Fig. 39), and weather cannot be held responsible in these cases. The other tachinid, Blondelia, was relatively ineffective up to 1958, and then started increasing slowly in numbers. This increase may possibly be the result of a numerical response to the simultaneous growth of host density, but then the question is still unanswered why the parasite did not react to changes of host density in carlier years. The fluctuations of Poecilostictus cannot be explained satisfactorily by a numerical response to host density either. True, the high rate of parasitism in 1957 may be the result of the high host densities in the foregoing generations. Moreover, the slight and more pronounced increases of 1962 and 1963 may be the result of the high host densities in 1961 and 1962, respectively. However, such an increase of parasitism does not occur in response to the 1951 densit'y of the host, nor does the parasite react clearly to the sudden host, declines of 1952 and 1957. It might be argued that the low rate of 1959 is due to the 1957 fall of host numbers, but in fact this should have occurred in 1958. A regulatory influence on host numbers of one or more of the pupal parasites should necessarily find expression in the total fraction of pupae infected. The bottom graph of Fig. 39 demonstrates, however, that in general the overall infection rates fluctuate within relatively narrow limits, and the pattern of fluctuation does not suggest a delayed density dependent relationship. Instead it seems to be the result of irregular fluctuations of the individual parasite species occurring independently of the host's density.

2. The In$uence of Larval Density on the Viability of Eggs and Larvae in the Next Generation Having found that parasites do not play a demonstrable part in the regulation of numbers of their common host, we have to look for other possible delayed effects. I n the preceding chapters we have repeatedly argued that where the population declines after having reached a high level, or increases sharply after a very low level, this did not appear to be due primarily to the density controlled factors so far found operating. This question should now be considered more positively by stating

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H . KLOMP

what factors do cause the pronounced density changes. This can be demonstrated by Fig. 27. The steep fall in larval density from 1951 to 1952 is due to an extremely high egg and juvenile mortality in 1952, and a consequent low population up to the egg stage 1953 inclusive. This story is approximately repeated from 1956 to 1957, inducing the low egg density of 1968.

A very steep rise of egg density occurs from 1953 to 1954 and, albeit less pronounced, from 1958 to 1959. In both cases this increase of density is induced by high survival in the egg and juvenile larval stages (see also Figs. 31 and 34). These findings point to the existence of a relation between larval density in one year and the chances of survival of eggs and young larvae in the next. This has been studied in the graphs of Fig. 40. The regression calculations show that the coefficients of 0-18 and 0.31 have rather

.

a2

0.h

.

.

.

ah

.

.

.

.

0.6

Q.6

.

.

ae

68

.

.

.

.

4.0

.

.

4.0 LOG. M E A N LARVAL D E N S I T Y

0.4

'

-

1.2

.

.

.

1.h

.

.

1.2 4.k AUG.-SEPT.

FIQ.40. The relations between egg mortality (k,) and juvenile mortality (kZ+) on the one side, and larval density of the previous year on the other. The regression functions are k, = 0.08 0.18 X (log. density), and k2-$= 0.2 0.31 x (log.density).

+

+

D Y N A M I C S O F F I E L D P O l ’ U L A T I O N O F P I N E LOOPER

299

low, though not significant, probabilities (0.09 and 0-08,resp.). It is suggested by the great variability of the data, that other, and evidently very variable factors, have an additional effect on the survival of eggs and young larvae, and the first factor to think of is variation in weather. Another question which requires an answer concerns the causation of the relationship. It is obvious to revert to the influence of larval density on larval growth and adult fecundity (p. 266) that if density has an additional effect on the viability of the offspring, i.e. on the eggs and young larvae of the next generation, then the relationship could be explained. It will be evident from the results reached in the experiments discussed earlier in the paper (p. 246), that the question raised here can also be approached experimentally. This has been carried out by Gruys, and the conclusive results heavily support the hypothesis that in the field, larval density not only has an influence on larval growth and adult fecundity, but also on the viability of the offspring (Klomp and Gruys, 1965). Gruys showed that the extent to which the effect is expressed depends on the conditions of temperature and humidity, and this supports the view that the great variability of at least the juvenile mortality is due to weather influences. Egg mortality cannot be reduced to the same denominator, because in the field the egg parasite Trichogramma is the main source of the deaths. We have some slight indications, however, that host eggs of crowded parents are more successfully infected on the averagb than eggs of solitarily reared parents. All in all, several of the questions raised in this section are still unsolved, and the proposed answers provide no more than a working hypothesis for future investigations. They cannot be regarded as establishing a full explanation of how the number cd individuals in a pine looper population are regulated.

V I I I . FINALCONSIDERATIONS The study of the population dynamics of insects has progressed farther than that of any other animal group excepting perhaps the birds. Undoubtedly, the cause of this has partly to1 be looked for in the phenomenon that many insects are pests, thus making a study of the factors determining their numbers economically worthwhile. However, the great majority of phytophagous insect species never reach infestation levels and their numbers fluctuate far below the capacity of their food plants. It should be evident that improved knowledge of the dynamics of this group of species should be of great help in understanding the mechanisms which determine the high levels of the pests. Several theories have been put forward to explain the low population densities of most plant-eating insects. The oldest views state that the numbers of the insects are kept down through the delayed density

300

H . KLOMP

dependent action of predators or parasites. In spite of thorough research in this field this conception has never been definitely established. Another theory emphasizes the significance of an increase in the interaction between the individuals of a population with growing density, and the consequent deterioration of the physiological condition of the animals, giving rise to self-regulation (Chitty, 1957; Wynne-Edwards, 1962). However, the advocates of the former theory sometimes claim that, because of the low population density of plant-eating insects, direct competition, e.g. for food, can be excluded as a causative agent, and the influence of mutual contact interference can, in their opinion, be minimized for the same reason. This conception has definitely no general validity, as was pointed out recently by Kennedy and Way (1964), who cite several instances of interference at low density levels in various insects. It is therefore worthwhile to examine processes of this type to assess their importance for the regulation of insect numbers. The results of the present study clearly support the theory of selfregulation more than that of the parasite-predator thesis. It is true that the advanced larvae of the pine looper are subject to density dependent predation, but the regulatory effect of this relationship was not o f primary importance during the period of observation. I n addition, it was found that the larvae interfere a t densities far below the food capacity of the pine trees, thus giving rise to an inhibition of larval growth and a decreased fecundity at the higher levels. Moreover, there is strong evidence that in addition to the effects just mentioned, the viability of eggs and larvae of the next generation is affected disadvantageously, phenomena which show much agreement with those observed by Chitty (1955, 1957) in the vole, Microtus agrestis. If we assume for the moment that the numbers of Bupalus piniarius are regulated by this principle - the reader is reminded that the final proof for an influence of density on the viability of the offspring under field conditions has still to be provided - then at least two questions arise. The first is concerned with the fact that in Germany the pine looper is a serious pest. How can it reach such extremely high levels without being suppressed by the effects of the growing mutual contact between larvae? There is some evidence indicating that the inhibition of growth is intensified up to a maximum density. Above this level there seems to be no further decrease of pupal size, and the same may hold for the viability of the offspring. Further, the data available suggest that the density induced decrease of the viability is dependent on weather conditions and it might be that in the foci of Bupa1u.s infestations in Germany, the results of larval interference are suppressed by the prevailing weather at critical times, thus giving rise to infestations within two or three generations.

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The second question is concerned with the origin of a mechanism of this kind. It has been suggested by Wynne-Edwards (1962) that such mechanisms have evolved by natural selection of social adaptations, with the result that the disadvantageous effects of over-exploitation of the environmental resources are avoided. He 13tatesthat the type of selection operating at the individual level (i.e. on genotypes within the population) cannot be effective in eliciting the kind of social adaptations that keep the populations down at the optimum density levels. Living a t such levels is advantageous for the population and not so much for the individuals composing the population. Wynne-Edwards therefore introduces the concept of group-selection, a type of selection concerned with the viability and survival of the population as a whole. He does not, however, provide a model or mechanism by means of which group-selection can be understood to c,xert its differentiating effect. The present author meets difficulties in his understanding of the concept, however. The brief formulation of Wynne-Edwards: “ . . . when the short-term advantage of the individual undermines the future safety of the race [read “population” in this case], group-selection is bound to win, because the race will suffer and decline, and be supplanted by another in which anti-social advancement of the individual is more rigidly inhibited . . .” in my opinion explains next to nothing. No more can I appreciate the remarks of Brereton (1962) with reference to this point. He asks: “Can evolution work at the group level?” and answers: “There is evidence that it can, for how else could behaviour which is disadvantageous to the individual but of advantage to the group have evolved?” It is questionable in my opinion, however, whether the cases in which group advantage is ciaid to be involved have been interpreted correctly. Thus it might well be that, where low population density is considered to be advantageous for the group in avoiding over-exploitation, it is in fact of advantage for the individuals for some unknown reason to be spread out. Let us assume, for instance, that in the Bupalus population under consideration a genotype develops by mutation which is resistant with respect to the physiological suppression exerted by the other individuals in the population. This genotype will be at an adivantage and its proportion in the population will gradually increase, with the result that density ultimately surpasses the optimum level. I do not understand how group-selection is able to prevent such an “anti-social advancement”. I n my opinion it can be prevented only by being disadvantageous for the genotype. I n other words, the fact of being immune for mutual interference must have some disadvantageous effect for its possessor. How can the advantage of being immune be counteracted by a r*

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disadvantage of still greater effect? The answer to this question will necessarily be hypothetical, and is presented here merely as a suggestion. Herrebout et al. (1963) have shown that the larvae of the pine looper are highly camouflaged in their natural environment of pine needles as a result of their colour pattern and habits of resting and feeding. Moreover, they have given strong arguments in favour of the view that the fact of being camouflaged has functional significance, because it protects the insects against the attacks of enemies hunting by sight. Referring to evidence from the literature the authors point out that the effectiveness of the camouflage is increased by a solitary way of life: “the longer the interval between encounters of an individual enemy with specimens of the camouflaged prey, the more the experience gathered by the enemy in a previous encounter will have waned before the next takes place”. The same conclusion is reached by Brower (1958). Furthermore, by comparing the effectiveness of the camouflage of different pine inhabiting species, it was shown by Herrebout et al. that the species with the most cryptic colour pattern also showed the best adapted habits, and it was concluded that the different components of the camouflage tend to vary in the same direction and amount, as if being linked together. The pine looper appears to have reached the most perfect degree of concealment in both colour pattern and habits, and consequently it may also be expected to have developed a mechanism to keep the larvae separate and dispersed. This supposition is suggested by the fact that the larvae of gregarious and aposematic species (Diprion p h i , Neodiprion sertifer) have developed special behaviour patterns to keep the insects together (Prop, 1960). Having reached this point we will return to the mutual interference among larvae described in this paper. As reported earlier, the female moth deposits the eggs in batches ranging from 2 to 25, with an average of 6. Pine trees have a thin structure, with the twigs fairly well separated, and the pine looper larvae are rather inactive creatures. Consequently, the individuals of one batch might easily remain together for a considerable period, when they are not stimulated to disperse. This will be disadvantageous because enemies (birds) might readily learn that having found one larva, some more will be present in the immediate neighbourhood, and the predator might well develop a “searching image” for such prey species (Tinbergen, 1960). This supposition is further supported by the density dependent mortality of advanced larvae described earlier in this paper. It is suggested, therefore, that the larvae are athulated t o disperse by their encounters with other individuals; the higher the intensity of the mutual contact, the greater the dispersion, probably up to a maximum (cf. p. 263).

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Consequently, genotypes iminuiie for mutua 1 interference are not stimulated to disperse, and being a t a disadvantage will be selected against, notwithstanding the higher survival rates they have in other respects. This suggests that the functional significance of the mutual interference among larvae a t densities well below the immediate capacity of the food plant would be the dispersal of the individuals of one batch. The dispersal will only be effective, howevor, when the larvae can move to areas not yet occupied by the individua‘lsof other egg batches, i.e. when the density is not too high. It is therefore striking that the mechanism of dispersal seems to be so close1;y bound up with the mechanism regulating population density.

ACKNOWLEDGMENTS

My thanks are due in the first place to my assietants Mr. J. Kleinhout and Mr. B. J. Teerink, for their great help in the daily routines of the time-consuming ecological field work, for their -willingnessto visit the rather isolated study area a t quite “abnormal” moments of the day on bicycle or motorcycle in spite of wind, rain, or snowfall, and last but not least for their warm interest in the biological probleme we tried to solve in excellent co-operation. Further, I wish to express my sincere gratitude to the late Prof. L. Tinbergen and to Dr. A . D. VoQte, who raised my interest in the ecological problems of insect populations, and to Ir. J. H. van Tuil, Director of “Het Nationale Park De Hoge Veluvre”, who permitted me to work in the pine woods of the park. Finally, my thanks are due to Yeveral students and to the personnel of the National Park who helped me in more than one respect, and to Dr. M. R. Honer for correcting the English text. REFERENCES Balch, R. E. and Bird, F. T. (1944). Scient. Agric. 25, 65-80. A diseaae of the European spruce sawfly, Gilpinia hercyniae (Htg.). Brereton, J. Le Gay (1962). I n “The Evolution of L.ving Organisms” (G. W. Leeper, ed.), pp. 81-93. Evolved regulatory mechanisms of population control. Melbourne University Press. Brower, L. P. (1958). Am. Nat. 92, 183-187. Bird predation and foodplmt specificity in closely related procryptic insects. Chitty, D. (1955). I n “The Numbers of Man and Animals” (J. B. Cragg and N. W. Pirie, eds.), pp. 57-67. Adverse effects of population density upon the viability of later generations. Edinburgh: Oliver and Boyd. Chitty, D. (1957). Cold Spring Harbor Symp. Quant. Biol. 22, 277-280. Selfregulation of numbers through changes in viability. Escherich, K. (1931). “Die Forstinsekten Mitteleuropas”, Bd, 111. Berlin: Paul Parey Verlag. Gruys, P. (1963). “Annual Report 1962 of the Inst. Bid. Field Res.”, Arnhem.

304

H. KLOMP

Herrebout, W. M., Kuyten, P. J., and de Ruiter, L. (1963).Archs. nkerl. Zool. 15, 315-357. Observations on colour patterns and behaviour of caterpillars feeding on Scots pine. Howard, L. 0. (1897). Techih. Ser. Bur. Ent. U.S. 5, 5-57. A study in insect parasitism. Howard, L. 0. and Fiske, W. F. (1911).Bull. Bur. Ent. U.S. Dep. Agric. 91, 1-344. The importation into the United States of the parasites of the gipsy moth and the brown-tail moth. Kennedy, J. S. and Way, M. J. (1964).12th. I f i t .Congr. Ent. London. Intraspecific mechanisms in insect population regulation. Not published in the Proceedings. Klomp, H. (1956).Ent. Ber., Amst. 16, 117-120. Over het aantal generaties, de gastheerwisseling en de overwintering van Trichogramma embryophagum Htg. Klomp, H. (1958).A r c h . nkerl. Zool. 13, Suppl. I, 319-334. Larval density and adult fecundity in a natural population of the pine looper (Bupalus piniarius L.) Klomp, H. (1959).Proc. 15th. Int. Congr. Zool., London 1958, 797-800. Infestations of forest insects and the role of parasites. Klomp, H. (1962).Archs. nkerl. Zool. 15, 68-109. The influence of climate and weather on the mean density level, the fluctuations, and the regulation of animal populations. Klomp, H. and Gruys, P. (1965).I’roc. 12th. l n t . Congr. Ent. London 1964.The analysis of factors affecting reproduction and mortality in a natural population of the pine looper, Bupalus piniarius L. Laing, J. (1937).J . Anim. Ecol. 6 , 298-317. Host finding by insect parasites I. Milne, A. (1964).Bull ent. Res. 54, 761-795. Biology and ecology of the garden chafer, Phyllopertha horticola (L.). IX. - Spatial distribution. Morris, R. F. (1957).Can. Ent. 89, 49-69. The interpretation of mortality data in studies on population dynamics. Morris, R. F. (1959).Ecology 40, 580-588. Single factor analysis in population dynamics. Morris, R. F. (1963a).Mem. ent. SOC.Can. 31, 1-332. The dynamics of epidemic spruce budworm populations. Morris, R.F. (196313).Mem. ent. SOC.Can. 32, 16-21. Predictive population equations based on key factors. Nicholson, A.J. (1933).J . Anim. Ecol. 2, 132-178. The balance of animal populations. Nicholson, A. J. and Bailey, V. A. (1935).Proc. zool. SOC.Lond. 551-598. The balance of animal populations. Prop, N. (1960).Archs. nkerl. Zool. 13, 380-447. Prot,ection against birds and parasites in some species of tenthredinid larvae. Smith, H. S. (1935).J . econ. Ent. 28, 873-898. The role of biotic factors in the determination of population densities. Smith, K. M. and Rivers, C. F.”(1956).Parasitology 46, 235-242. Some viruses affecting insects of economic importance. Schwenke, W. (1953).Beitr. Ent. 3, 168-205. Beitriige zur Bionomie der Kiefernspanner, Bupalus piniarius L. und Semiothba liturata C1. auf biozonotischer Grundlage. Schoonhoven, L. M. (1963).Archs. nkerl. Zool. 15, 111-174. Diapause and the physiology of host parasite synchronization in Bupalus piniarius L. (Geom.) and Eucarcelia rutilla Vill. (Tach.).

DYNAMICS O F FIELD POPULATION OF P I N E LOOPER

305

Solomon, M. E. (1949). J . Anim. Ecol. 18, 1-35. The natural control of animal populations. Thalenhorst, W. (1939). 2. angew. Ent. 26, 185-208. Zur Biologie des Kiefernspannerparasiten Ichneumon nigritarius Grav. Tinbcrgen, L. (1960). Archa. nkerl. Zool. 13, 265-336. ‘The natural control of insects in pinewoods I. Factors influencing the intensity of predation by songbirds. Tinbergen, L. and Klomp, H. (1960). Arclzs. nderl. Zool. 13, 344-379. The natural control of insects in pine woods 11. Conditions for damping of Nicholson oscillations in parasite-host systems. Varley, G. C. (1947).J . Anim. Ecol. 16,139-187. The natural control of population balance in the knapweed gall-fly (Uropkoru juceufia). Varley, G. C. (1953). Trans. 9th. Int. Co,igr. Ent. 2, 210-214. Ecological aspects of population regulation. Varley, G. C. and Gradwell, G. R. (1960). J . Anim. Ecol. 29, 251-273. Keyfactors in population studies. Varley, G. C. and Gradwell, G. R. (1962). Pioc. 18th. Ant).Session Ceylon Ass. A d o . Sci. 142-156. The interpretation of insect population changes. Varley, G. C. and Gradwell, G. R . (1963). Proc. 16th. I ~ t tCoiigr. . Zool. Wash. 1, 240. Predatory insects as density dependent mortality factors. Weber, H. (1954). “Grundriss der Insektenkunde”. :ituttgart: Gustav Fischer Verlag. Wigglesworth, V. B. ( 1953). “The Principles of Insect Physiology”. London: Methuen and Co. Wilbert, H. (1962). 2. Morphol. Oekol. Tiere 50, 576-615. Uber Festlegung und Einhaltung der mittleren Dichte von Insektenpopulationen. Wynne-Edwards, V. C. (1962). “Animal Dispersion in Relation to Social Behaviour”. Edinburgh: Oliver and Boyd.

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Author Index Numbers in italics refer to the pages on which refermces are listed in bibliographies at the end of each article. .4

Aabye, Jensen, E., 123, 136, 203 Abbott, B. C., 141, 191 Adams, M. N. E., 137, 200 Alexander, J. E., 154, 194 Allee, W. C., 30, 40, 64, 81. 112 Allen, E. J., 137, 191 Allen, W. E., 136, 203 Anderson, G. C., 151,152, 159, 160,191 Andrewartha, H. G., 1, 2, 20, 28,42, 57, 58, 64 Anraku, M., 183, 189, 192 Ansell, A. D., 126, 132, 137, 192 Antia, N. J., 125, 133, 141, 144, 152, 192 Armsby, H. P., 79, 112 Armstrong, J. T . , 34, 64 Arndt, W., 23, 64 Atwater, W. O., 79, 112 Austin, J., 182, 201 Austin, T . S . , 136, 192 B Bailey, V. A., 294, 304 Baird, I. E., 131, 162, 159, 168, 202 Baker, J. R. 42, 64 Bakker, K., 42, 64 Belch, R. E., 273, 303 Ballantine, D., 141, 191 Barker, H. A., 137, 192 Barkley, E., 184, 192 Barnes, H., 180, 192 Bayer, F. M., 185, 192 Baylor, E. R., 188, 192 Beauchamp, R . S . A., 7, 8, 26, 28. 58, 64 Beklemishev, C. W., 189, 192 Beklemishev, K. V., 183, 192 Belser, W. L., 143, 144, 192 Benazzi, M., 45, 64

Benedict, F. (>., 79, 103, 112 Bennike, 8. A ., 2, 53, 64 Berg, K., 8, 17, 56, 64 Bernard, F., 143, 154, 157, 192 Berthet, P., 87, 90, 91, 112 Bertram, D. ;3., 26, 64 Bigelow, H. It., 135, 151, 161, 173, 176, 192 Birch, L. C., 1, 2, 20, 28, 42, 57, 58, 64, 82, 91, 112 Bird, F. T . , 2173, 303 Birge, E. A, 78, 112 Birstoin, J. A.., 169, 186, 205 Blair, W. F., 72, 112 Bogorov, B. 13., 136, 158, 193 Bolen, H. M., 43, 64 Bookhout, C. G., 184,194 Bornebusch, C. H., 78, 87, 91, 92, 112 Boycott, A. 13., 2, 21, 53, 61, 64 Braarud, T., 134, 135, 138, 149, 151, 156, 161, 193 Brereton, J. Le Gay., 301, 303 Brian, M. V. 57, 65 Brock, V. E., 136, 192 Brody, SamLel, 79, 84, 102, 112 Brongersma-Sanders, M., 141, 193 Brower, L. F., 302, 303 Browning, T . O., 2, 28, 42, 57, 64, 65 Bsharah, L., 157, 171, 193 Bumpus, D. F., 154, 158, 163, 175, 201 Burkholder, P. R., 157, 159, 193 Bursa, A. S., 134, 156, 193 Byers, G. W , 80, 101, 113 C Cannon, H. G., 184, 193 Carpenter, HI.E., 26, 65 Cassie, V., 145, 196 Chit,ty, D., 300, 303 Chodorowski, A., 8, 56, 65

307

308

AUTHOR INDEX

Clark, P. D., 82, 91, 112 Clarke, G. L., 160, 162, 172, 193 Clatworthy, J. N., 58, 66 Clowes, A . J., 136, 193 Cole, L. C., 73, 113 Collier, A., 141, 143, 193 Colman, J. S., 172, 201 Connell, C. E., 87, 95, 99, 100, 106. 114 Connell, J. H., 58, 65 Conover, R. J., 145, 151, 153, 182, 183, 193 Conover, S. A . M . , 135, 194, 201 Cooper, L. H. N., 122, 160, 161, 172, 194, 196 Corbet, G. B., 23, 25, 27, 65 Corcoran, E. F., 143, 154, 194, 198 Corlett, J., 151, 153, 194 Corner, E. D. S., 189, 194 Corwin, N., 159, 198 Costlow, J. D., 184, 194 Coughlan, J., 126, 132, 137, 192 Cowey, C. B., 144, 189, 194 Cragg, J. B., 2, 65 Crowley, E., 126, 137, 192 Curl, H., 132, 133, 137, 141, 143, 170, 194 Currie, R. I., 121, 129, 136, 194, 196 Cushing, D. H., 137,148, 154, 161, 162, 167, 175, 180, 181, 188, 189, 194

D Dahm, A . G., 4, 5, 6, 13, 23, 24, 65 Daisley, K. W., 144, 194 Davenport, L. B., 87, 95, 99, 100, 106, 114 Davis, C. C., 141, 196 Davis, D. E., 83, 113 Davis, H. C., 181, 184, 194, 198 Dawson, W. R., 84, 113 Debach, P. T., 57, 58, 65 Deevey, G. B., 161, 172, 194 Dempster, J. P., 44, 65 de Ruiter, L., 302, 304 Dice, L. R., 82, 113 Digby, P. S. B., 134, 153, 172,194,195 Dixon, M., 81, 113 Doeksen, J., 92, 113 Doty, M. S., 123, 147, 195 Droop, M. R., 139, 143, 144, 195, 200 Dunbar, M. J., 178, 195

Duursma, E. K., 140, 141, 142, 143, 187, 195

E

Edmonson, W. T., 2, 65, 180, 195 Efford, I. E., 23, 25, 28, 65 Einarsson, H., 184, 195 Elton, C., 26, 56, 65 Emerson, A. E., 81, 112 Engelmann, M. D., 76,95,98, 101, 106, 109, 110, 111,112 Escherich, K., 211, 221, 245, 303 Evans, F. C., 79, 82, 113

F

Farner, D. S., 84, 113 Fish, C. J., 151, 153, 172, 195 Fisher, L. R., 144, 194 Fisher, R. A., 42, 65 Fiske, W. F., 294, 304 Fleming, R. H., 162, 163, 195 Flint, W. P., 79, 114 Fogg, G. E., 125, 137, 141, 195, 197 Forrest, J. E., 27, 65 Foxton, P., 172, 173, 195 Funaioli, M. L., 5, 65 G Gaarder, T., 126, 127, 128, 195 Gauld, D. T., 137, 156, 162, 183, 188, 195, 196 Gentry, J. D., 95, 98, 100, 101, 106, 113 Gere, G., 84, 113 Gilbert, O., 57, 65 Gillbricht, M., 153, 195 GislBn, T., 4, 13, 23, 66 Golley, F. B., 78, 82, 83, 95, 98, 100, 101, 102, 106, 113 Gorham, E., 7, 8, 11, 14, 17, 66 Gradwell, G. R., 275, 286, 287, 291, 294, 305 Grainger, E. H., 178, 195 Gran, H. H., 126, 127, 128, 147, 153, 195 Greenly, E., 24, 66 Grice, G. D., 175, 176, 177, 195 Griffiths, J., 79, 114 Grontved, J., 119, 156, 195, 196 Gross, F., 137, 149, 156, 161, 196 Guys, P., 253, 264, 299, 303, 304

309

AUTHOR INDEX

Guillard, R. R. L., 134, 141, 142, 145, 153, 154, 157, 160, 196, 197 Gunter, G., 141, 196 Gunther, E. R., 136, 169, 196 Gurney, R., 21, 66

H Hairston, N. G., 57, 66, 78, 80, 101, 113 Halldal, P., 150, 156, 159, 161, 196 Hansen, V. K., 130, 172, 196, 203 Haq, S. M., 140, 197 Harby, A. C., 169, 196 Harper, J. L., 47, 58, 62, GO' Harris, E., 121, 152, 196 Hart, A. D., 176, 176, 177, 195 Hart,T. J., 134,136,147,151,153,161, 196 Harvey, H. W., 131, 143, 156, 160, 161, 172, 184,196 Rasler, A. D., 17, 66 Hayes, F. R., 53, 66' Hazen, W. E., 113 Heinrich, A. K., 178, 196 Hela, I., 136, 171, 196 Hentschel, E., 158, 170, 197 Herrebout, W. M., 302, 304 Hida, T. S., 171, 198 Hobart, J., 57, 65 Holling, C. S., 10, 35, 66 Hoffman, C., 152, 197 Holmes, R. W., 134, 136, 151, 153, 158, 161, 197 Hood, D. W., 140, 142, 197, 200, 202, 203 Howard, L. O., 294, 304 Hulburt, E.M., 134, 139, 140, 145, 153, 154, 157, 160, 197, 199 Humphries, C . F., 8, 56, 66 Hunter, W. R., 23, 27, 59, 61, 66 Hutchinson, G. E., 20, 41, 58, 66 Hyman, L. H., 34, 43, 66 Hynes, H. B. N., 2, 9, 23, 66 I Ichimura, S., 131, 202 It6, Y., 84, 86, 90, 113

J

Jacobs, J., 182, 197 Jeffries, H. P., 138, 197

Jenkin, P. M., 128, 129, 197 Jennings, J. B., 40, 43, 66' Jespersen, P., 169, 171, 197 Jewell, M. E., 2, 66 Johnson, M. W., 169, 173,197 Johnston, R., 140, 197 Jones. E. C., 147, 197 Jones, P. G. W., 140,197 J ~ R.F., ~ 131, ~ 199 ~ , jergensen, E. G., 141, 197 Juday, C., 78, 112 K Kain, J. M., 137, 197 Kanazaaa, A., 144, 197 Kendeigh, S. C . , 84, 113 Kennedy, C. R., 53, 67 Kennedy, J. S., 300, 304 Ketchum, B. H., 121, 137, 197, 198, 201 Kielhorn, W. V., 172, 198 Kimball, J. I?., 143, 198 King, J. E., 171, 198 King, J. R., 84, 113 Klem, A., 149, 193 Klie, W., 23, 67 Klomp, H., 57, 58, 67, 207, 245, 253, 257, 259, 264, 287, 291, 294, 295, 297, 305 Kohn, A. J., 34, 58, 67 Komhrek, J., 4, 67 Koyama, T., 140, 198 Kreps, E., 151, 153, 198 Krey, J., 18G, 198 Kriss, A. E., 117, 187, 198 Krogh, A., 142, 198 Kut,ner, M. B., 157, 203 Kuyten, P. J., 302, 304

138, 159,

211, 243, 273, 286, 299, 304,

1 Lack, D., 34 42, 58, 67 Laevastu, T., 136, 171, 196 Laing, J., 234, 304 Lander, K. F.,126, 132, 137, 192 Lanskrtya, L . A., 132,198 Larkin, P. A., 15, 53, 67 Lavoisier, A. L., 79, 114 Lea.vit,t,B. I$.,169, 198 Labour, M. V., 160, 161, 172, 196

310

AUTHOR INDEX

Lecal, J., 143, 192 Lender, T., 4, 5, 67 Lepori, N. G., 4, 5, 67 Leslie, P. H., 57, 68 Lewin, J. C . , 142, 198 Lewin, R. A., 142, 198 Lillick, L., 135, 151, 161, 192 Lillick, L. C., 145, 198 Lindeman, R. L., 75, 78, 83, 114 Linford, E., 182, 201 Lohmann, H., 156, 198 Loosanoff, V. L., 181, 184, 198 Loosmors, F. A., 126, 132, 137, 192 Lucas, C . E., 145, 198 Lund, J . W. G., 1, 67 Luther, A., 25, 29, 67

Macan, T.

M

2, 9 , 10, 12, 20, 21, 309 32, 43, 47, 53, 61, 67 McAllister, C. D., 125, 126, 133, 140, 141, 144, 152, 192, 199 MacArthur, R. H., 34, 42, 67, 78, 114 MacDonald, R., 184, 199 McFadden, J. T., 2, 68 Macfadyen, A., 1, 54, 67, 74, 82, 87, 91, 92, 93, 94, 109, 111, 114 Mackereth, F. J. H., 7, 17, G7 Mackereth, J. C., 47, 67 Mackintosh, N. A., 172, 199 McLaughlin, J. J. A., :134, 139, 142, 143, 200 McLeod, G. C., 132, 133, 137, 141,194 McNab, B. K., 87, 99, 100, 102, 114 McNaughton, I. H., 58, 66 Madden, J. L., 42, 69 Maddux, W. S . , 131, 199 Magagnini, G., 5, 67 Maguire, B., Jn., 23, 43, 68 Mann, K. H., 2, 10, 47, 53, 68 Marak, R. R., 185, 199 Mare, M. F., 162, 199 Margalef, R., 15, 68, 138, 199 T.9

Marshall, A. J., 114 Marshall, P. T., 128, 151, 199 Marshall, S. M., 137, 149, 156, 161, 180, 182, 188, 189, 196, 199 Martin, D. L.,41, 68 Mathews, H. M., 141, 152, 200 Mauchline, J., 184, 199 Melander, Hansen-E., 5 , 68

Melander, Y., 4, 5, 6, 68 Menzel, D. W., 131, 139, 144, 152, 163, 154, 159, 171, 177, 199, 200, 202 Mertz, D. B., 57, 68 Metcalf, C. L., 79, 114 Miller, R., 56, 65 Miller, R. S., 132, 182, 201 Milne, A., 40, 44, 57, 68, 223, 304 Min, H. S . , 141, 152, 200 Mirolli, M., 6, 8, 68 Le Moigne, A., 4, 5, 67, 68 Moon, H. P., 21, 68 Moore, H. B., 171, 200 Morris, I. G., 37, 7 1 Morris, R. F., 1, 68, 275, 278, 280, 281, 283, 295, 304 Morrison, P. R., 84, 114 Moyse, J., 184, 200 Mullin, M. M., 184, 200 Mundie, J. H., 17, 56, 68 Murray, J. W., 186, 200 N Nagel, W. P., 42, 69 Nelson, E. W., 137, 191 Newell, B. S., 140, 203 Nicholson, A. J., 41,42, 44,68,294, 304 Nielsen, C. O., 87, 88, 114 Northcote, T. G., 15, 53, 67 Nutman, S. R., 137, 156, 196

0 O'Connor, F. B., 87, 89, 114 Odum, E. P., 1, 68, 73, 87, 95, 96, 97, 99, 100, 106, 108, 114 Oguri, M., 123, 147, 195 Olsen, S., 11, 68 Omori, M., 183, 192 Orians, G. H., 42, 68 Orr, A. P., 128, 137, 149, 156, 161, 180, 182, 188, 189,196, 199 O'Rpurke, F. J., 25, 68

P Pantin, C. F. A.. 30, 68 Park, K., 140, 200 Park, O., 81, 112 Park, T., 57, 68, 81, 112 Park, T. S., 132, 203

AUTHOR INDEX

311

5 Sagar, G. R., 58, 66 Saijo, Y., 131, 202 Schoonhoveii, L. M . , 211, 304 Schmidt, K. P., 81, 112 Schmidt, O., 5 , 70 Schwenke, V f . , 263, 304 Sealander, J. A. Jr., 84, 114 Sears, M., 135, 151, 161, 173, 176, 192 Sears, P. B., 73 114 Sewell, R. B., 169, 202 Shackley, P., 126, 137, 192 Shelbourne, J. E., 185, 202 Shiraishi, K., 182, 202 Sieburth, J. M., 157, 159, 193 Sisgel, S., 93, 114 Hkellam, J. G., 58, 70 Slobodkin, ES.L., 77, 78, 82, 83, 98, 104, 114, 115 Slobodkin, I,. B., 78, 80, 113 Smalley,9. E., 95, 96, 97, 98, 106, 114, R 115 Rawson, D. S., 15, 53, G9 Smayda, T. J., 132, 134, 202 Ray, S., 143, 193 Smith, F. E., 78, 80, 82, 113 Raymont, J. E. G., 126, 132, 137, 149, Smith, H. S., 294, 304 152, 156, 161, 182, 183. 188, 192, Smith, J. B., 142, 202 196, 200, 201 Smith, K. M., 237, 304 Redfield, A. C . , 137, 138, 198, 201 Solomon, M E., 57, 70, 291, 294, 305 Reeve, M. R., 182, 201 Sorokin, J. I., 118, 160, 187, 202 Reid, D. M., 23, 6 9 Southern, R., 23, 70 Reid, J. L., 170, 201 Spaeth, J. P., 144, 200 Reynoldson, T. B., 4, 5, 6, 7, 8, 10, 11, Steele, J. H., 122, 131, 152, 154, 159, 14, 16, 17, 21,22, 23, 24, 25,26, 29, 167, 168, 202 32, 34, 35, 36, 37, 38, 39,40,41,43, Stmmann Nielsen, E., 117, 123, 124, 44, 47, 49, 50, 51, 53, 56, 57, 59, 60, 125, 130, 132, 136, 141, 149, 151, 61, 65, 68, 69, 70, 71 153, 156, 157, 158, 160, 162, 168, Richards, F. A., 138, 201 170, 17'7, 197, 202, 208 Richman, S., 82, 115 Steinbock, O., 27. 70 Riley, G. A., 134, 135, 144, 145, 148, Stephens, K., 125, 120, 383, 140, 141, 149, 150, 153, 154, 157, 158, 161, 144, 152, 192, 199 162, 163, 164, loti. 176, 175, 178, Stoinmel, H , 154, 158, 175, 201 179, 188, 201, 204 Strickland, J . D. H., 125, 126, 133, 140, Rivers, C. F., 237, 304 141, 142!, 144, 152, 187. 192, 199, Rodman, J., 140, 145, 19; 200 Root, R. B., 34, 70 Xundby, R. 4., 57, 68, C 5 Russell, F. S., 160, 161, 172, 196, 201 Sutcliffe, W. H., 188, 192 Ryer, G. A., 84, 114 Sverdrup, H. V., 136, 150, 203 Ryland, J. S., 185, 201 Swank, W. G., 95, 103, 106, 114 Ryther, J. H., 119, 122, 127, 129, 131, 134, 137, 139, 150, 152, 153, 154, 156, 157, 158, 159, 160, 171, 177, T 197, 198, 199, 200, 201, 202, 204 Talling, J. F., 20, 70, 128, 205

Parsons, T. R., 125, 126, 133, 140, 141, 142, 144, 152, 187,192,199, 200 Patten, B. C., 78, 83, 114 Pearson, 0. P., 85, 86, 87, 102, 114 Petipa, T. S., 184, 189, 200 Petrides, G. A., 95, 103, 106, 114 Phillipson, J., 87, 89, 90, 114 Pimentel, D., 42, 69 Pinter, I. J . , 135, 140, 142, 145, 200 Platt, R. B., 79, 114 Pomeroy, L. R., 141, 152, 200 Pontin, A. J . , 57, 69 Popham, E. J . , 34, 69 Prescott, J. M., 140, 200, 203 Proctor, V . W., 141, 200 Prop, N., 302, 304 Provasoli, L., 134, 135, 139, 140, 142, 143, 144, 145, 146, 182, 200, 202 Putter, A., 187, 200

312

AUTHOR INDEX

Tatsumoto, M., 140, 142, 202, 203 Taylor, M. C., 6, 8, 11, 25, 29, 40, 44, 51, 60, 70 Teal, J. M., 95, 97, 106, 115 Teixeira, C., 157, 159, 203 Templeton, J. R., 84, 113 Thalenhorst, W., 295, 305 Thienemann, A., 23, 24, 28, 70 Tinbergen, L., 226, 291, 294, 302, 305 Tordoff, H. B., 84, 113 Tranter, D. J., 140, 173, 176, 203 Tucker, D. S . , 11, 32, 54, 70 U uiiyott, P., 23, 24, 25, 28, 58, 64, 70 Utida, A., 58, 70 V Vaccaro, R. F., 122, 152, 159, 204 Van der Drift, J., 84, 91, 92, 113, 115 Varley, G. C . , 2, 70,211, 267, 275, 286, 287, 291, 294, 305 Verjbinskaya, N., 151, 153, 198 Vinogradov, M. E., 169, 178, 185, 186, 204 Vishniac, H. S., 144, 145, 204 W Waldbauer, G. P., 84, 115 Wallgren, H., 84, 115 Walne, P. R., 184, 204 Walton-Smith, F. G., 141, 196 Wangersky, P. J., 141, 143, 196, 204 Warwick, T., 27, 61, 6 6 Waterson, A. R., 27, 65 Watson, E. V., 27, 65

Wattenberg, H., 158, 197 Way, M. J., 300, 304 Weber, H., 244, 305 Weitz, B., 34, 70 West, G., 85, 86, 115 Whitehead, H., 26, 43, 70 Wiborg, K. F., 170, 172, 185, 204 Wickstead, J. H., 170, 171, 204 Wiegert, R. G., 83, 95, 100, 106, 115 Wigglesworth, V. B., 244, 305 Wilbert, H., 207, 286, 305 Williams, R. H., 141, 1 B G Williams, W. D., 2, 21, 23, 24, 26, 27, 32, 53, 59, 70 Williams, W. T., 140, 200, 203 Wilson, D. P., 33, 70 Wilson, W. B., 143, 193 Wimpenny, R. S . , 161, 204 Wit de, C . T., 58, 70 Wood, E*J. F . 9 11% 143, 157, 198, 204 Worthington9 B., 21$ 67 Wynne-Edwards, V. C., 41, 70, 300, 301, 305

*

Y Yentsch, C. S., 122, 152, 156, 158, 159, 198, 202, 204 Young, J. O., 6, 25, 29, 32, 33, 34, 35, 36, 37, 38, 39, 40, 43,44, 56, 59, 60, 61, 70, 71, Z Zenkevitch, L., 151, 153, 154, 169, 173, 174, 176, 205 Zenkevitch, L. A., 169, 186, 205 Zobell, C. E., 187, 205

Subject Index A Acartia, 183, 184, 188, 189 Acartia tonsa, 182, 183 Achaeta eiseni, 89 Aeshna cyanea (Mueller), 46 Africa, West, 136 African Elephant, 103 African Savannah, 103 Agabus didymus (Oliv.), 45 Agabus paludosus (Fab.), 45 Age and/or size classification, 82 Agricultural University, Wageningen, 218 Air moisture, 79 Alfalfa, 100, 101 Algae, 93, 97, 142, 147, 218 freshwater, 141, 146 marine, 123, 127, 128, 133, 134, 137, 138, 139, 140, 141, 143, 144, 145, 146, 157, 159, 160, 161, 180, 184, 190 microbenthic, 119 Allogalumna alatum, 110 Americas, the, 24, 153 Amphibia, 46 Amphipods, 178, 180 Ancylus lacustris, 35 Anglesey, 3, 10, 11, 12, 21, 22, 24, 27, 47, 48 Annelids, 34 Anomdocera, 183, 189 Anomalon biguttatum, 241, 296 Antarctic, 133, 136, 139, 147, 153, 157, 159, 161, 162, 172, 190 convergence, 157 waters, 130, 134, 157, 159, 169, 173 Ants, 98, 99, 230 Apanteles, 271 Apanteles caberae, 237, 239, 295 Aphytis, 58 Appendicularians, 161, 168, 185 Arabia, southern, 136 Arbacia, 184

Arctic, 132, 6 1 , 153, 159, 174, 175,176, 190 waters, 130, 134, 151, 153, 164, 155, 161, 169, 173, 178 Ard, Loch, 55 Ardunan, Loch, 55 Arklett, Loch, 55 Armagh, Comty, N. Ireland, 7, 16 Arnhem, The Netherlands, 253 Artemia, lK!, 183 Arthropoda, 35, 36, 37, 38, 80, 90, 91, 101 Asellus, 2, 21, 23, 27, 33, 35, 36, 37, 38, 39, 43, 47, 53, 54, 55, 56, 58, 59, 60, 61, 63 Assimilation rates, 76, 80, 90, 96, 97 Asterionella, 185 Athous subfTGscus, 272, 279, 280 Atlantic Ocean, 151, 158, 171 northern, 134, 142, 153, 157, 171, 173, 17&,175, 176 north-western, 158 southern, 158, 170 Atomic Energy Commission, Georgia, U.S.A., 99 Atomic fallout, 73 Australia, 140 seas, 140, 157, 174, 175, 176 Autotrophic bacteria, 117, 118 Azores, the, 171 Azov, Sea of, 155 B Bacillariopk yceae, 146 Bacteria, 52, 88, 92, 93, 117, 118, 120, 142, 144, 184, 185, 186, 187, 191 Balanus balanoides, 185 Baltic Sea, 143, 149, 156 Bangor, N. Wales, 41, 49, 51 Bardowie, Loch, 55 Bardsey, 3, 21, 27 Brtrents See., 153, 155, 173, 175, 176 Barra, 3, 2:'

313

31-4

SUBJECT I N D E X

Bathyealanus, 183 Bay of Biscay, 144 B&llocephah punctata, 4, 23 Bear Island (Arctic), 151 Beaumaris Reservoir, 37 Beech forest soils, 91 Belba, 110 Belgium, 90, 91 Benthic animals, 53, 190 Benthic plants, 118, 190 Benthos region, 118, 120, 191 Bering Sea, 174, 175, 176 Berkeley, California, 87 Bermuda, 153, 154, 157, 158, 160, 171, 175, 176, 177

Berod, 185 Biddulphia mobilieneis, 131 Bioenergetics, 79, 84, 86, 98 Biological Field Research Institute, Arnhem, The Netherlands, 253 Biomass estimates, 20, 41, 53, 54, 55,

56, 75, 80, 82, 90, 93, 101, 155, 158, 168,169,170,172,173,175,178,186 Bird energy budget, 85 Bird incubation, 85 Bird migration, 85 Birds, 23, 34, 58, 97 Biscay, Bay of, 144 Black Sea, 117, 118, 143, 160, 184, 189 Block Island Sound, 153, 161, 172 Blondelia, 280, 296 Blondelia nigripes, 241, 297 Blowflies, 42 Bluegram, Kentucky, 102 Bolinopeis, 185 Boreal waters, 127, 158, 171, 173, 175, 176, 177

“Bornebusch” approach (Energetics), 75, 82, 85, 87, 88, 95

Brachychthoniua jugatus, 110 Braconids, 237, 295 Bramblings, 272 Brazilian waters, 157 Britain, 2, 3, 4, 12, 21, 22, 23, 24; 26, 27, 28, 29, 34, 60

British Isles, 3, 23, 27, 94 British Museum (Natural History), 237 BupaJw piniarius L.,207 et seq.

Calanoids, 183 Cahnua, 161, 165, 179, 180, 181, 182, 183, 184, 188, 189, 191

Calcium, 12-14, 17, 18, 19, 20, 22, 23 Caldrtrvan, Loch, 55 Caledonian Canal, Scotland, 12, 22 California, U.S.A., 86, 87, 119, 136 Cambridgeshire, 60 Camilla, Loch, 16 Camisia, 110 Canada, 85 Canna, 26 Carbon dioxide production, 81, 84 Cardinal, Eastern, 84 Carnivore-herbivore ratio, 93, 98, 101 Carolina, South, U.S.A., 98 Carteria, 129 Cartesian diver apparatus, 81, 88, 90 Cattle, 103, 105 Centropages, 183, 188, 189 Ceratium, 134, 182 Chaetocerm, 128, 134, 184 Chaetognaths, 168, 177, 178, 185 Chaffinches, 272 Chaparral, 87 Chemistry of fresh water (Triclads), 2, 9, 21, 23, 29, 30, 54, 62

Chemosynthesis, 117, 118 Chile, 136 Chironmus. 36, 55 Chhmydomonas, 129, 184 ChloreUa, 132, 183, 184, 185 Chlorophyceae, 146, 155 Chlorophyll, 122, 123, 124, 130, 131, 132, 133, 155

Chlorophyta, 129 Chromulina, 184 Chrysomonads, 135, 140, 142, 145, 146 euryhaline forms, 135 stenohaline forms, 135 Chrysophyceae, 146, 155 Chthamalua, 185 Chukotsk Sea, 174 Churchill, Manitoba, Canada, 85 Ciliates, 168, 187, 191 Circumpolar Ocean, 153 Cirripede nauplii, 180

chum, 84

Clapper rails, 97

Caithness, 22

C

Clown dipterum, 36, 39

Clyde sea area, 135, 184

SUBJECT INDEX

Coccolithophores, 123, 137, 143, 156, 157, 183

Coccolithw, huxleyi, 135, 142 Cod larvae, 185 Coelenterata, 45 Coeihagrion puella (Linn.), 40 Cognettk, 89 Colemere, Shropshire, 37 Coleoptera, 45 College Pond, Bangor, 41, 49, 51 Colorado State University, 112 Columbia River, U.S.A., 151 Colymbetea f m c w , (Linn.), 45 Communities, trophic scheme analysis, 95-107

Competition, 252, 300, 302, 303 exploitation, 57 interference, 57 inter-specific, 44,47,48,50,51, 53, 56 intra-specific, 40, 41, 42, 47, 50. 53, 56, 62

Con, Loch, 55 Continent, the, 28, 94 Continental Shelf, 122, 159, 173, 174 Copepods, 161, 168, 172, 176, 178, 179, 180,181,182,183,184,185,188,189

Corixidae, 2 Coron, Lake, 48, 55 Coscinodkcw,, 128, 130, 182 CoscinoSirapolychorda, 128 Crabs, mud, 97 Crmsoetrea, 184 Cratichneumon, 295 Cratichneumon nigritariua, 240, 241 Crenobia alpina (Dana), 4, 23, 25, 26, 27, 28

Cricket, tree, 99 Cricosphaera carterae, 137 Crossbills, 84 Crotaphytua colhris, 84 Cryptophyceae, 146, 155 Ctenophores, 169, 185 Cullercoats, Northumberland, 12 Cu1troribu.h spp. (divergene), 110 Cura ( = Curteak)fomnanni, 43 Cyanophyceae, 146 Cyprk-lina, 184 cyzenk albicana, 295 D Damselfly larvae, 44

31 5

Danish fjords, 119 Danish forest soils, 91 Daphnk, 104 Decapods, 158, 185 Deciduous woods, English, 90 Decomposition cycle, 93 Deer, white-tailed, 103 “De Hoge Veluwe” National Park, The Netherlmds, 208, 303 Dendrocoelidae, 40 Dendrocoeluin lacteum (Mull.), 4, 5, 8,

11,13-15,19-22, 25, 28, 29,31-38, 40, 43-45, 51-53, 58-63 Denmark, 24, 88, 89

Density (Pirte looper), egg, 211-220 fluctuations, 207-208 independent and dependent mechanisms, 286, 289 larval, 21 !-220 methods clf measuring, 21 1-233 moth, 229-233 nymph, 220-223 pupal, 22::-229 Deronectes, 45 Detritus, 97, 127, 152, 155, 178, 184, 185, 186, 188

Diatoms, 119, 128, 130, 132, 134, 137139, 14!J-144, 155-157, 180-185

Dicraterk, 183, 184 Diges+,ion eificiency (Energetics), 82, 83, 93

Dinoflagellai,es, 132, 134, 142, 143, 144, 155, 182, 183

Dinophyceao, 146 Dipodomys, 84 Diprion pin;, 302 Dispersion (Pine looper), 233, 302, 303 Ditylum, 18S, 185 a u r a bicawlata, 36 Domesticated farm animals, 85 Dougalston, Loch, 55 Douglrts fir forest, 89 Dragonfly larvae, 44 Dug&, 21, 25, 28, 31, 32, 33, 36, 50, 53, 131 Dugeak gonocephah, 24, 28 D u g e s k lug.ubrk (0. Schmidt), 4-6, 11, 13-15, 19, 20, 22, 25, 29, 33-38, 41, 44, 45, 50-52, 58, 62, 63

37,

8, 31, 59,

316

STJBJI
Dugesia polychroa (0.Schmidt), 5 Dugesia tigrina (Girard), 4, 6, 24, 34 Dunaliella, 129, 144, 185 Dutch pine woods, 291 Dystrophic lakes, 32 Dytiscus marginalis, 44, 45 E Earthworms, 38, 92 Ecological efficiency (Encrgotics), 83, 101 Ecotone, salt marsh, 95-98 Egestion rates (Energetics), 76, 80, 85, 96, 101 Elaterids, 272 Elephant, African, 103 Ellesmere, 17 Emberiza, 84 Emigration (Pine looper), 208, 267, 293 Enchytraeidae, 35, 88, 89, 92 Energetics, 73-1 15 analysis, 75, 82 approaches, 74-78, 95, 101 efficiencies, 85, 101 historical considerations, 78-84 physiological studies, 84-86, 112 principles of, 108-112 terrestrial, 74, 79, 82, 112 trophic dynamic analyses, 95-103, 112 Energy, 77, 87 balance sheet, 77, 102 budget, 85, 95 consumption, 85, 88, 98 estimates, 77, 84, 85, 103 flow, 75, 87, 95, 97, 102, 118 maintenance, 75, 81, 86, 91, 93, 99, 105 metabolism, 85, 91, 93. 99, 105 units, 82, 85 utilization, 90, 91 values, 82 England, 21, 25, 27, 112 English Channel, 24, 122, 128, 156, 160, 174, 176 English deciduous woods, 90 Enzymatic processes (Plankton), 132 Ephemeroptera, 55, 56 Epizoic fauna (Triclads), 5 Equator, 136, 154 Erpobdella, 44, 45

Eucalaiaus, 183 Eucaycelia, 241, 296 Euchaeta, 183 Eucheirella, 183 Euglenineae, 146 Euphausids, 161, 168, 180, 184, 185 Euphotic zone, 125, 130, 131, 142-144, 151-154, 158-161, 164-167 Europe, 94, 134 north-western, 119, 153 Eutainas, 84 Eutrophic lakes, 7, 54 Exuviella, 130, 134

F Fair Isle, 3, 26 Farm animals, domesticated, 85 Faroes, 27, 173, 176 Faroe-Shetland Ridge, 135 Fecundity (Pine looper), 240 et seq. Fennosconia, 2, 34, 60 Fertilization Experiments (Zooplankton), 182 Field mouse, 87 Field sparrows, 99 Finlaggin, Loch, 21 Finland, 25, 29 Fish, 24, 44, 47, 53, 185 Fladen ground (North Sea), 122, 167 Flagellates, 119, 123, 132, 137,141-143, 156, 157, 168, 183-186 Florida Current, 154, 157, 171 Florida waters, 185 Food chains, analysis of, 95, 102, 108 Food webs, 108, 118 Foraminifera, 185, 186, 187 Friday Harbour, Washington State, U.S.A., 132, 135 Fritillaria, 185 Fungal disease (Pine looper), 237 Fungi, 92, 93, 118 G Gaetanus, 183 Gaidius, 183 Gammarus, 2, 23, 36, 38, 47, 54, 55 Garve, Loch, 22 Gmterosteus muleatus (Linn.), 46 Gastropoda, 23, 34, 36, 37, 38, 53, 55, 58, 63

317

SUBJECT INDEX

Gelderland province, The Netherlands, 208

Geometrids, 209, 221 George, E. S. Reserve, 101 Georges Bank (Gulf of Maine), 163,166, 178, 179, 180

Georgia, U.S.A., 96, 98, 99, 159 Germany, 24, 300 Ggantocypris miilleri, 184 alaucomys, 84 Goniaulax, 141 Gramnivores, 98 Grampian Mountains, 27 Grasshoppers, 95, 96, 97, 98, 99, 105 Great Belt region, 149 Greenland, 151, 153, 172, 176 Growth (Pine looper), 243-244, 258-

Heteropods, 185 Highland Fault, Scotland, 3, 12, 15, 21, 22, 27

Hirudinea, 4!i, 55 Homeostasis, 85, 87 Homeostatic mechanisms, 85 Homiothemi, 87, 95, 104, 105, 107 Hulshorst, 22 6 Human louse, 82 Humidity, 79 Husan, Koreit, 166, 167 Hydra oligactis Pallas, 45 Hydrobia, 59 Hydrobia jenkinsi, 35, 36, 39 Hydrobia (Pcdamopyrgua)jenkinsi, 27, 61

264

Growth (Plankton), 119, 121, 122, 125,

138-147, 150-153, 177-179, 182, 184, 187-189, 191 Growth (Triclads), 40-43 Growth rates, 80, 81, 85, 103 Gulf of Maine, 135, 145, 148, 158, 161, 164 Gulf' Stream, 172 Gun&, 30 Gymnodinium, 130, 141, 182 Gyrodinium, 130

I

Ice Age, 28 Iceland, 27, 156, 173, 176 Ichneumonids, 240, 245, 273, 296 Illinois, U.S.A., 85 Ilybius juliginosw (Fab.), 45 India, 157 Indian Ocean, 143, 157 Indian Ocean Expedition, 136, 171 Ingestion ratos (Energetics), 76, 80, 96, 101

Inshore waters (Plankton), 127, 135, 158, 159

H

Haliplus, 45 Harris, 3, 23 Harvestmen, 90, 92 Harvest mice, 85 Hawks, 86 Hebrides, Outer, 27 Heilin, Loch, 22 Helobdella stagnalis (Linn.), 45 Hemihenlea cambrensis, 89 Hemiptera, 46 Herniaelmis, 183, 184 Hempriggs, Loch, 22 Hendref, Lake, 55 Herbivore-carnivore ratio, 93, 98, 101 Herbivore-predator ratio, 93 Herbivores, 76, 90, 93, 99 Het Nationale Park De Hoge Veluwe, 303

Heteropelma, 296 Heteropelma calcator, 241

Institute of Biological Field Research, Arnhem, The Netherlands, 253 Ireland, 2, 5, 7, 12, 16, 17, 18, 21, 23, 24, 25, 27, 28, 59, 63, 171

Iris pseuducoc-w! (Linn.), 7 Islay, off west Scottish coast, 3, 12, 17, 21, 22, 216, 27, 32, 48, 49

Isle of Man, 3, 21, 26, 27 Isochrysis, 137, 184 Isotopes, 123

J Janthina, 185 Japan, Sea of*, 176 Japanese waters, 131, 176 Jelly-fish, 16!) Juncus moor, 94

K Kattegat, the,, 149

318

SUBJECT INDEX

Kendall’s raqk correlation method, 256, 266

Kentucky bluegrass, 102 Kinghorn, Loch, 16 Korea, 166 Kuroshio Current (Japan), 131 L

Labidocera, 183, 189 Labrador Sea,, 151, 153, 161, 172 Lake Maggiore, 6, 8 Lake O p e n , 30, 31, 32, 33, 55 Laptev Sea, 153, 173, 175, 176 Laderia, 127, 128, 184 Least weasel, 102 Leeches, 2, 9, 10, 47, 53, 56 Leningrad, 25, 29 Leverhulme Trust, 63 Lewis, 3, 26 Life tables, 77, 81, 82, 96, 101, 103 Light, effect on primary production (Plankton), 126-1 33 Limestone grassland, 94 Lindeman model (Energetics), 75-76, 77, 80, 83, 101, 104, 108, 112

Liochthnniua perpuaillus, 110 Lismore, 3, 21 Littoriw, 96, 106 Lizards, 84 Llyn Coron, 48, 55 Llyn Hendref, 55 Llyn Llygerian, 48 Llyn Mair, 32, 60 Llyn Mymbyr, 55 Llyn Teryn, 50, 55 Loch Ard, 55 Loch Ardunan, 55 Loch Arklett, 55 Loch Baxdowie, 55 Loch Caldarvan, 55 Loch Camilla, 16 Loch Con, 55 Loch Dougalston, 55 Loch Finlaggin, 2 1 Loch Garve, 22 Loch Heilin, 22 Loch Hempriggs, 22 Loch Kinghorn, 16 Loch Lochan, 55 Loch Lomond, 8, 12, 32, 54, 59, 60 Loch Menteith. 55

Loch Ross, 55 Loch Rusky, 54, 55, 56 Loch Ussie, 22 Lochan, Loch, 55 Lomond, Loch, 8, 12, 32, 54, 59, 60 London, Westfield College, 112 Long Island Sound, 135, 138, 144, 145, 153, 158, 161, 172

Lough Marlacoo, 16, 17 Lough Lowry, 16, 1 7 Lough Lurgan, 16, 17 Lough Shaw, 7 Louse, human, 82 Lowry, Lough, 16, 17 Lox& curvirostra sitkernis, 84 Loxia leucoptera leucoptera, 84 Loxodonta a f r k n a , 103, 106 Lumbricidae, 35 Lumbriculua variegatua, 35, 36, 61 Lurgan, Lough, 16, 17 Lusitanian fauna, 23, 24, 25 Lycosa psewloannulata, 84, 90 Lymnaea, 35, 59 Lymnaea pereger, 36, 38, 39, 54, 59, 61

M Macrobenthic plants, 119 Macrophytes, 144 Maggiore, Lake, 6, 8 Maine, Gulf of, 135, 145, 148, 158, 161, 164

Maintenance energy (Energetics), 75, 81, 86, 91, 93, 99, 105

Malham tarn, 17 Man, Isle of, 3, 21 Manitoba, 85 Marlacoo, Lough, 16, 17 Marquesas Islands, 147 Mathematical models (Zooplankton), 182

Mathematics Department, Agricultural University, Wageningen, 218 Mediterranean, the, 119, 143, 154, 157 Medusae, 169, 170, 185 Meerdael Forest, Belgium, 90 Megaculanwr, 183 Meganyctiphanes, 184 Melunoplua biliteratua, 99 Melanoplua femur-rubrum, 99 Menai Straits, 24 Menteith, Loch, 55

319

SUBJECT INDEX

Meroplanktonic larvae, 161, 168 Metabolism, 75, 83, 85, 86, 87, 88, 91, 93,99, 105, 141, 182, 189, 191 Metridia, 183 Mice, 85, 86, 87, 98 Michigan, 80, 98, 99 Michigan State University, 112 Microbenthic algae, 119 Microtus, 84, 87, 102, 103, 106, 300 Minnows, 46 Mites, 23, 28, 79, 81, 91, 101, 109 Mitopua morio, 89, 90 Monochry&, 184 Mortality (Pine looper), 205, 211, 237, 238, 240,267, 268,269, 270, 271 age-interval, contribution to density, 280-283 delayed density-dependent, 294-299 density-dependent, 289-294 egg, 271, 289-290 generation and age-interval, 275-280 larval, 271-272, 283-286, 290-293 moth, 293 prepupae, 272, 293 pupae, 272-273, 293 Mud crabs, 97 Mull, 3, 26 Mustella, 102, 106 Mymbyr, Lake, 55 Mysids, 168, 184, 185 N Naididae, 36 Nannochlork, 129, 137,144,146,183 N a n o p l d t o n , 165, 167, 182, 184 estimation of density, 156 National Science Foundation, 112 Natural history observations, 78 Nature Conservancy, 63 Nekton, 118, 120, 140 Nematoda, 79, 88, 92, 97, 98, 101, 1OC Neodiprion sertifer, 302 Nepa cinerea (Linn.),46 Netherlands, 218, 253 New England, U.S.A., 166 New York, 138, 170, 172, 175, 176 Newton Mere, Shropshire, 14, 15, 16, 19, 32, 37, 60 Newts, 43 Nitzschia, 130, 137, 142, 182, 184, 186 Northsea, 122,144, 166, 161, 167, 168, 174, 176, 180

North Uist, 3, 23, 26 Northumberland, 12 Norwegian Deeps, 144 Norwegian &a, 150, 156, 159, 161. 172 Notonecta gkzctca (Linn.). 46 Nympham, ‘I

0 Oak trees, 2.36 Odonata, 44, 46 Oeconthw niqricornis, 99 Ogwen, Lako, 30, 31, 32, 33, 55 Oikopleura, L85 Okhotsk, Sen of, 175, 176 “Old field” communities, 80, 87, 9% 103 Oligochaeta, 35, 36, 37, 38, 47, 58, 63 Oligolophua irklemur, 89, 90 Oligotrophic (lakes), 7 Oligotrophic (marine), 121, 123, 124, 157, 177, 178 Operophtera brumata, 291, 294 Oppia minutksima, 110 oppia Twva, 109, 110 Orchelimum, 95, 96, 97, 106 Oregon, U.S.A., 161 Oribatei, 90,91, 101, 102, 106, 109, 111, 112 Orkney Islands, 3, 26 Orthoptera, 99, 106 Ostracods, 184 Otterlo, The Netherlands, 208

P Pacific Ocea:n, 136, 158, 170, 171, 173, 174, 176, 183 Paracalanus. 183 Parasites (Pine looper), 233, 234, 239, 240, 241, 245, 268, 269, 270, 271, 272, 279, 280, 293-297, 300 Pam bomb calorimeter, 96. 99 Passer domesticus domaticus. 84 Passerculua tandwichensis, 99, 106 Pediculus humanua, 82 Peloribates curtipilus, 110 Peridinians, 134 Peridinium balticum, 134 Peridinium chattoni, 134 Peritrich, 49 Peromyscua, 87, 106 Peromyscua talifornicus, 87

320

SUBJECT INDEX

Peromyscus maniculatas, 87 Peromyscus polionotus, 99 Peromyscus truei, 87 Peru, 136 PIuzeocystis, 140, 157 Phaeodactylum, 144, 145 Phagocata vitta (Dug&),4, 11, 13, 14,31 Phalangiidae, 89, 90 Phenology, 78 Philaenus spumarius, 100, 106 Photosynthesis, 97, 118, 120, 121, 122,

123, 124, 125, 131, 133, 134, 150, 164 inhibition of, 128 Phoxinus phoxinus (Linn.), 46 Physalia, 185 Physiological studies (Energetics), 76, 78, 84-86, 87, 103 Phytophagous caterpillar species, 286, 299 Phytoplankton, 118, 120 annual production, 157-160 grazing by zooplankton, 160-168 primary production, 120-155 standing crop, 136, 147, 155-157

Pine looper (Bupalus piniarius L.), 207 et seq. Pinus sylvestris, 208 Pisces, 46 Plaice larvae, 185 Planariidae, 5, 6, 11, 37, 38, 40, 42, 54 Phnaria torva (Mull.), 4 Plankton, 53 marine, 117-205 phytoplankton, 120-168 standing crop, 155-157 zooplankton, 168-189 Plastic sphere technique (Plankton production), 125, 126, 141 P l a t y m o w , 129 Plecoptera, 55, 56, 61 Pkurobrachia, 185 Plymouth, 135 Poa pratemis, 102 Poecilostictw,, 280, 296, 297 Poecilostictw, cothurnatus, 241 Pogonmymnex badius, 98,99, 100, 101, 104, 106

Poikilotherms, 95, 104, 105, 107 Poisson distribution, 223,224, 227, 229, 230, -232, 233

Polar Basin, 173 Polar Sea, 159, 190 Pollution, 73 Polycelis, 8, 11, 12, 14, 19-21, 28, 29, 31, 32, 37, 52, 53, 58, 63

Polycelis felina (Dalyell), 4, 23, 24-28, 40, 48, 49

Polycelis hepta, 5 Polycelis nigra (Mull.), 4-6,

8, 12-14, 17,19-27,31-38,41,44,45,47-51, 53, 61-63 Polycelis tenuis (Ijima), 4-6, 12-14, 19-22, 24, 25, 31-38, 41, 44, 46, 47-51, 53, 56, 61-63 Pol ycentrops $avom.aculatus (Pictet ), 46 Polyhedrosis (Pine looper), 239, 272

Population dynamics (Pine looper), 207-305

Population regulation (Triclads), 40, 42 Population regulation (Pine looper), 208, 286-288

analysis, 286-299 Porpita, 185 Port Hacking, 174 Potamogeton, 7 Predator-herbivore ratio, 93 Predators, 83, 86, 90, 221, 226, 272, 280, 291, 293, 300

Primary production (Phytoplankton), 126-155

effect of light, 126-133 effect of nutrients, 135-138, 138-140 effect of salinity, 134-135 effect of temperature, 133-134, 147155

organic requirements, 140-147 stratification, 147-155 Procerodes ( = Qunda), 30 Production, estimation of (Energetics), 74, 96, 99, 100

Production of marine plankton, 117205

primary, estimation of, 120--126 phytoplankton, 120-155, 157-160 zooplankton, 178-182 Productivity (Energetics), 74, 86, 87, 106, 109

curve, 110 gross, 84, 100, 101, 102 net, 84, 101, 102, 109, 110

SUBJECT INDEX

Prokelisia, 97, 98, 106 Prorocentrum, 134, 141, 182 Protista, 118 Protophyta, 186 Protozoa, 168, 169, 186, 187, 191 Prymnesium, 141 Pseudocalanus, 183, 188 Pseudodiaptomus coronatus, 182 Pteropods, 161 Pupal size (Pine looper), 245-253, 264265 Pyrarnimonas, 184

Q Queen Elizabeth National Park, Uganda, 103 R Racoons, 97 Radio-active isotopes, 123 Radio-trscer experiments, 101 Radiolaria, 185, 186, 187 Rails, Clapper, 97 Rearing (Pine looper), 233-24@ Reithrodontomys megalotis, 86, 87 Reproduction (Pine looper), 208, 211 rates of, 240-267 Respiration (Energetics),74,76,89,98, 99,109 animal, 86, 93 bacterial, 93, 97 oxygen consumption, 75, 81, 84-86, 88, 90, 92 primary consumer, 97 rabs, 75, 80, 81, 86, 89, 90, 98, 100, 101 secondary consumer, 97 Respiration (Plankton), 120, 124 oxygen bottle method, 120, 121, 123, 125-128 Respiration (Triclads), 11, 32 Respirometer, constant pressure, 89, 96, 101 Rhantus bistriatw, (Bergst.), 45 Rhizosolenia, 133 Rhizosoknia styliformis, 138 Rhodomow, 144 Rhodophycem, 146 Rhysotritia ardua, 110 Rhum, 3, 22, 26 Richmondena cardinalis, 84

321

Rodents, 84 ROSS,Loch, 55 Ross and Cromarty, Scotland, 22 Rotifers, 2, :LO1 Royal Society, 63 Rudd, 44 Ruppia, 1 19 Rusky, Loch, 54, 55, 56 Russia, 25 Russian watms, 185

S Sagitta, 179 Sagitta elegaim arctica, 178, 179 Sagittae, 180, 185 Salinity, effect on primary production (Plankton), 134-1 35 Sdmo trutta forma farw (Linn.), 46 Salps, 161, 169, 170, 177 Salt marsh ecotone, 95-98, 100, 106 Sanday, 26 Sapelo Island, Georgia, 96 Sarga,sso Sea,, 131, 136, 139, 144, 153, 154, 157, 158, 171, 173, 175, 176, 177 Savannah River Plant, U.S.A. Atomic Energy Commission, Georgia, 99 Savannah, African, 103, 106 Scardinius erythrophthdmw (Linn.),44, 46 Scherloribatec levigatua, 109 Scherlom'battw pdlidwr, 110 Schroederella. 145 Scotland, 4, 12, 15, 17, 18, 21, 22, 49, 54, 59, 171, 173 Scots pine, 208 Scottocalanus, 183 See of Azov, 155 Sea o f Okhoi,sk, 175, 176 Seaweed, 110 Shew, Lough, County Armagh, N. Ireland, 7 Shetlands, 3, 23, 26 Shropshire, England, 11, 12, 14, 15, 16, 19, 59, 61 Siberia, 155, 173 Siberian Sea, 173, L75, 176 Silicoflagellaim, 139 Singapore Straits, 171 Siphonophoros, 169, 170, 177, 186

322

SUBJECT I N D E X

Skelebiwna, 130, 133, 134, 139, 141, 143, 144, 145, 182, 185 Skeletonems coatatum, 132, 138 Skokholm, 3, 21, 27 Snails, 61, 96, 185 Snowdonia, 11, 12, 14, 16 Soil buildkg process, Y2 metabolism, 92, 93 moisture content, 88 organisms, 92 Soils beech forest, 91 beech mull, 92, 94 beech raw humus, 92 Belgium forest, 91 coniferous, 89 Danish forest, 91 grassland, 92, 94 oak mull, 92, 94 rich mull, 92 raw humus, 92 spruce mull, 92, 94 spruce raw humus, 92 Solar radiation, 118, 127, 133, 166 South Georgia, 99, 159, 161, 162 Southern harvester ant, 98 Sparrows, 86, 98, 99 English, 84 field, 99 tree, 85 vesper, 99 Spartina, 96, 98 Spearman rank correlation (Energetics), 93, 104 Sphagnum, 13 Spiders, 84, 86, 90, 97, 230, 271 Spizellu arborea, 85 Sponges, 2 Sporozoa, 44 Spruce-budworm, 1 Standing crop yield, 54, 56, 76, 77, 98 estimates of, 82, 101, 155-157,,157160, 168-178 Stenohahe (brackish waters), 134 Stichowccus, 137 Sticklebacks, 43 St. Kilda, 26 Strathblane, 55 Strobliomyia, 239

h%obliomyia @aicornia (Strobl.), 237, 295 Suctobelba, 110 Sweden, 4, 24, 63 Synthesis (Plankton), 117, 118, 120, 125, 142

T Tachinids, 237, 245, 295, 296, 297 Tarsomids, 110 Tectocepheua velatwr (Mich.), 110 Temora, 183, 188, 189 Temperate waters, 127-128, 130, 148, 156, 159, 172, 183 Temperature, effect on life-cycles (Triclads), 6, 29 Temperature, effect on primary production (Plankton), 133-134, 141155 Terrestrial field studies (Energetics), 73-115 Teryn, Lake, 50, 55 Thahsia, 119 Thalmawaira gravida, 127, 128, 134 Thahaioaira nordenakioldii, 127, 128, 134, 137 Thuhaiothrix longisaima, 138 The Mere, Ellesmere, 17, 37 Thermo-regulation, 85, 105 Thomisids, 271 Thyriaoms ovata, I10 Thyaanoeaaa, 184 Tigrwpus, 182 Titmice, 272, 291 Tisbury Great Pond, 161 Tortanus diacauddua, 183 Tree cricket, 99 Tree sparrow, 85 Trhypochthonius (tectorum), 110 Tribolium, 57 Tribolium oastaneum, 57 Tribolium confuaum, 57 Trichogramms, 234, 268, 269, 270, 279, 290,299 Trichogramma embryophagum Htg., 234, 295 Trichoptera, 46 Triclads, 1-71 abundance pattern, 2, 6-19 changes in water level, 8, 29, 30, 31 dispersal, 21, 23, 24

SUBJECT INDEX

distribution pattern, &19 effect of water chemistry, 2, 9, 11, 21, 23, 29, 30, 54, 62

effect of weather, 28, 29-30 field methods, 6-12 food Of, 28, 34-40 historical aspects of distribution and abundance, 20-28 individual, 40, 56-62 lake-dwelling, 1-71 living places, 6-8, 29, 30-34 parasites, 41, 43, 44 predators, 34, 41, 42, 43, 44, 45, 47, 49

reproduction, 42, 43 sampling methods, 10 stream-dwelling, 6, 58 taxonomy, P 6 , 47, 61 total population, 15, 53-56 Triturus helveticus (Razoumowski), 46 Trophic dyhamic analysis (Energetics), 77, 95-103

Trophic efficiency model (Energet,ics), 83, 104, 107

Trophic levels, 76, 93-94, 95, 98, 107, 120

herbivore - carnivore, 98 Tropical waters, 124, 127, 130,131,133,

136, 137, 164, 157, 159, 171, 173, 177, 187 Tsetse flies, 34 Tubificidae, 35, 53 Tullgren extractor, 101, 102 Turnover rates (Energetics), 82

U Uganda, Queen Elizabeth National Park, 103 Uist, 3, 23, 26 Urbana, Illinois, U.S.A., 85 Urceolaria, 49 U.S.A., 85, 132, 134, 153, 173, 176 Atomic Energy Commission, Georgia, 99

Ussie, Loch, 22 U.S.S.R., 26, 173

V Valdiviella, 183 Vapour pressure, 79 Velella, 185

323

Venus mercenaria, 184 Vesper sparrows, 99 Voles, 102, 300 W Wadden, Sea, 143 Wageningen, The Netherlands, 218 Wales, 12, 15, 17, 18, 21, 24, 54, 59, 89 Warburg respirometer, 81 Washington State, U.S.A., 132, 151 Water chemistry, 2,9,21, 23,29,30,54, 62

Water lily, 7 Waters Antarctic, 130, 134, 157, 159, 169, 173

Arctic, 130, 134, 151, 153, 164, 155, 161, 169, 173, 178

boreal, 127, 158, 171, 173, 176, 177 eutrophig, 7, 54 inshore, 127, 135, 142, 143, 147, 148, 158, E 9 , 176, 190

offshore, 157, 158, 159, 176, 190 oligotrophic, 7, 121, 123, 124, 157, 177, 1'78

Pacific, 136, 158, 171, 173, 183 polluted estuary waters, 138, 157 stenohaline brackish, 134 subtropioal, 134, 136, 157, 171, 176 temperate, 127-128, 130, 148, 156, 169, 1'72, 183

tropical, 124, 127, 130, 131, 133, 136,

137, 154, 167, 169, 171, 173, 176, 177, 187 verticalexchange, 121,132,136, 159, 190 Weasel, blue-grass vole-least, 102 Welsh coast islands, 12 Weat Africit, 136 Western islands (Britain), 2, 21, 22, 23, 26, 27 WestfieldCollege,London, England, 112 Wheat, 86 White-tailell deer, 103 Wilcoxon's test, 252 Windermere, 7, 8, 12, 28, 32, 60 Winkler method, 120 Winter moth, 291, 294 Woods Holo, 122, 153, 156, 166

worn enchytraoid, 88, 89 nematodo, 88

324

SUBJECT INDEX

X XystiCua audax, 271

Y Yates’ correction, 8 Yeasts, 118 Yellow Flag, 7 Yorkshire, 12, 17 Z

Zapua, 84 Zooplankton, 118, 120, 145, 152, 168189

carnivores, 118, 167, 177, 183, 184, 185, 189

feeding of, 182-186 fertilization experiments, 182 food sources, 186-188 food requirements, 188-189 grazing of, 160-168 herbivores, 118, 161, 165, 177, 179, 180, 184, 189

rates of production, 178-182 standing crop, 168-178 Zostera, 119 Zygoribatula rostrata, 110