Evolutionary Dynamics of Forests Under Climate Change

Evolutionary Dynamics of Forests under Climate Change

Claire G. Williams

Evolutionary Dynamics of Forests under Climate Change

Claire G. Williams National Evolutionary Synthesis Center (NESCent) Suite A200, W. Main Street 2024 Durham, NC 27705-4667 USA [email protected]

ISBN 978-94-007-1935-4 e-ISBN 978-94-007-1936-1 DOI 10.1007/978-94-007-1936-1 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2011940207 © Springer Science+Business Media B.V. 2012 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

Evolution is the chief architect behind a forest’s response to climate change and, as such, deserves a place in the professional education of those who manage natural resources. So this book’s aim is to introduce students and other future managers to the evolutionary dynamics of forests and to show how these models can guide what to plant under climate change. Such an ambitious task is made easier with a case study and I have chosen the Lost Pines of Texas. The Lost Pines forest has been an integral part of American forestry education for decades because it illustrates how forest managers can use ready-made natural variation for the benefit of tree planting programs. An updated version of this same idea is needed now because most of the Lost Pines forest was lost to wildfire on September 6, 2011. Determining what to plant now is a top priority because the Lost Pines case study has long held a value is disproportionately large for its small size and it behooves us to examine why this is so. Already at the drought-prone edge of the Pinus taeda range, the Lost Pines area is likely to be the first of this eastern species’ populations to experience the harsh effects of climate change. Put another way, the Lost Pines population is vulnerable enough to serve as a climate change bellwether and thus instructive about what to plant under climate change. But first we must understand what was once here. The Lost Pines area in central Texas is one of the best-documented places in North America. Human artifacts at nearby Buttermilk Creek1 date back as far as 15,000 year before present (B.P.). After these early arrivals came the Clovis people, other paleo-americans and then, in more recent times, Native Americans tribes. Incidence of fire probably rose as a consequence of these early humans. Here too were Spanish explorers who ventured forth more than three centuries ago and they were the first to document the Lost Pines area so this forest is a naturally occurring phenomenon. Geological records became available for the Lost Pines area with the discovery of lignite, oil, natural gas and aquifers which now supply 88 oil fields,

1

Waters M et al (2011) Science 331:1599–1603. v

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22 natural gas reservoirs and large reserves of lignitic coal.2 Extractive wealth from the Lost Pines area continues to contribute to the science-led Texas economy. This wealth was transformed into research universities, space exploration, biomedical facilities, computing and now alternative energy. Most of this innovation is centered in Texas cities and these cities have now expanded until they are side-by-side with scientifically precise agricultural systems. Within this radius of scientific achievement, the Lost Pines area in central Texas can lay another claim: here evolutionary principles were first applied to tree planting programs. This idea was so successful in restoring forests in Texas during some long drought-prone years that it became the gold standard for tree planting programs worldwide. Defined here as managed evolution, these principles were translated into quantitative and population genetics. The new field of tree improvement got its practical start here in the Lost Pines area, through the efforts of Dr. Bruce Zobel and others. Since then, many scientists including the author have continued to optimize the genetic quality of seedlings for the largest tree planting program in U.S. history and they did so by applying these same evolutionary principles. As with its past, the future value of the Lost Pines area now looms large. At first glance, the regional scale of the Lost Pines case study might seem inconsequential to the increasingly global science of forests but this is not so. Regional scales actually matter more than global or even continental scales3 when it comes to making future climate change meaningful. Regional forecasts are not yet available but they alone link scientific abstraction to the scales of societal meaning,4 not the other way around. No two regions will be affected by climate change in the same way and thus resource managers must know how a region’s conditions are likely to change, not only what global temperatures will be on average. Meanwhile, a place-centered inquiry5 can fill the gap and perhaps later complement regional forecasts. The Lost Pines case study is the right place-centered inquiry for Texas. Highly vulnerable to climate change,6 energy-producing Texas has less than 10% forest cover. This forest cover of the Lost Pines and elsewhere serves to slow climate change effects7 although, as seen from the 2011 wildfire, it will also be more prone to loss. How can these losses be staunched? There is no easy answer given the rapid urban population growth projected for central Texas. Slated for a population over 70 million in coming decades, urbanization tends to reduces forest cover. Other forces are at work too. Houston and other central Texas cities are particularly

2

Dutton et al (2006). Schiermeier Q (2010) Nature 463:284–287. 4 Jasanoff S (2010) Theory Cult Soc 27:233–253. 5 NRC (2010) Adapting the impacts of climate change. National Academies Press, Washington DC, 272 p. 6 Schmandt J, North G, Clarkson J (2011) The impact of global warming on Texas, 2nd edn. University of Texas Press, Austin, 318 p. 7 Turner et al (2009) Nature 462:278–279. 3

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vulnerable to forest cover loss because they border on a hurricane-prone part of the U.S. coastline, the Gulf of Mexico. Regional forecasts for central Texas are likely to be among the most complex and idiosyncratic but already they also point to a loss of forest cover. The Lost Pines case study is germane here too because it was one of the densely few forested areas in the prairie-savanna matrix of central Texas. Forest trees, including Pinus taeda, are largely undomesticated at this time and this opens the option of managing allelic richness, or genetic diversity, more explicitly for forest planting programs. Managing genetic diversity now has the added precision of genomics data. Genomics refers to large-scale DNA sequencing databases and these databases are available for Pinus taeda in the public domain. Federal science agencies have amply funded genetic diversity studies at the DNA sequencing level for this important timber species and now this knowledge can now be translated into better seedling planting stock. Identifying adaptive variation at the DNA sequence level and then making this explicit for consumer seedling choices has not yet happened. Doing so would be ideal for replanting the Pinus taeda forests of the Lost Pines area. Timber-growing for the United States has moved offshore and so now the U.S. forestry community must revise its societal pact. The community has fissured into two schools of thought: molecular domestication versus managed evolution. Molecular domestication, as the more prevalent view, advocates that Pinus taeda programs take concentrate on modifying wood properties for a few highly selected genotypes which can be clonally reproduced in limitless numbers. If so, then the rapid molecular domestication of Pinus taeda and other temperate species would follow a similar path as domestication of maize, soybeans or cotton. This molecular domestication portfolio for Pinus taeda includes not only use of genomics data but also the use of recombinant DNA technology, i.e. inserting transgenes or genetic engineering. Of particular interest here is genetic modification of wood quality. This portfolio has also led to a new industry, i.e. companies which sell only forest tree seedlings and these use a different business model from those timber companies which once grow seedlings for their own land. A few seedling-sales companies have expanded into global markets at the same time that many state-run nurseries are closing. Presently, forest managers in Texas can still purchase forest tree seedlings from either state-run nurseries or private seedling suppliers but this situation has already begun to change in favor of private sales. Managed evolution, as the other school of thought, takes the longer view that managing more genetic diversity explicitly is the better choice for temperate forestry and that forestry’s technology portfolio has already diverged from maize and other annual crops. A number of factors such as longevity have already put forestry on that separate path. By making more genetic diversity explicit, managed evolution can imbue forest tree seedlings with a genetic quality which hedges against climateinduced losses. I assert here that managed evolution is the better choice for U.S. forestry’s societal pact and that this should guide what to plant in the drought-prone Lost Pines area now. Managed evolution, as coupled with genomics, has not been endorsed by either multinational timber companies or private seedling sales companies.

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A synthesis of this book’s content. The Lost Pines case study draws on knowledge from many disciplines but even so there are still gaps and contradictions which require careful examination. A theory or model can be upturned easily with a new experiment, new records or new fossil finds. Theories and models are simply placeholders for more knowledge, not facts. Thus the reader is encouraged to follow the line of reasoning for a particular hypothesis throughout the book before deciding what additional knowledge is needed. The following hypotheses serve to thread discussion. Predicting how the U.S. South’s planted pine forests will fare under climate change uses ecological principles. These, along with economic forecasts, have generated optimistic forecasts for Pinus taeda as a species. We can agree that this is one species will not become extinct. However, these forecasts have yet to be downscaled to a regional level and it is here that local forest cover losses are prone to occur. Having anchored these models to the Lost Pines as a real-life ecosystem illustrates some guiding principles for managing forests under climate change. Evolutionary dynamics models for forests require a frame which is distinctly different from ecological forecasting. Here, the species is treated as an aggregate of populations and the population, not the species, becomes the unit of response. A population is composed of individuals and these individuals response via the entire life cycle. When seen through this life cycle lens, a forest ecosystem now takes on more than its usual terrestrial dimensions: it acquires aerial and perhaps aquatic dimensions because pollen and seed dispersal must be included in how a population responds to climate change. The population’s raw material for change resides with its genetic variation and forest trees have unusually high levels of genetic variation within and among populations. How this genetic variation is shaped by selection, gene flow, random drift and even mutation contributes to evolutionary dynamics models. Evolutionary dynamics models for forests are explicit yet rarely integrated into climate change forecasting or considered with the realm of forest policy solutions. One reason might be that they are based on forest tree populations that lived and died several thousands of years ago, during Quaternary glacial cycles. Most forest tree populations during the Quaternary responded to past climate change either dispersing seed colonies elsewhere (migration) or by death (extirpation) although few local stands did persist in place. Charting these Quaternary forest responses has been shown to be useful to contemporary problem-solving even though forest cover losses to global warming in the future are not fully analogous to those under glaciation. Evolutionary dynamics models, with more still emerging, swing between (i) forest trees as long-lived yet transient generalists prone to migration or (ii) a more stationary past which includes local adaptation. These frame a dichotomy which continues to move the discussion about evolutionary dynamics models forward. Other models include repeated hybridization and introgression with close relatives. Repeated hybridization followed by strong natural selection under abiotic stress can tip the balance in favor of local adaptation and these changes typically occur with human disturbance. How might these models be advanced to the point that they can guide decisions or contribute to policy solutions? Many have wrestled with this question and the

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best answer so far is to tie evolutionary dynamics models to ecological realism. Ecological realism, or anchoring to a real ecosystem, does nicely link evolutionary principles to forest management as shown here with disjunct Pinus taeda population in central Texas known as the Lost Pines. This choice is challenging because no Quaternary glaciation occurred within the Pinus taeda range and this is an aggressive early-successional colonizer which is synanthropic, or well-suited to human disturbance and to the extent that it readily colonizes near and around the built environments. In particular, this species and its close relatives seeds into open gaps cleared by fire or storms but ultimately its migratory pace of Pinus taeda has been hastened most of all by a human activity: tree planting. More human activity than tree planting has shaped the present-day Lost Pines ecosystem so that its present state cannot be assumed to resemble its past yet its past determines which evolutionary dynamics models fit best. The past of the Lost Pines area could be reconstructed by sifting through a large number of historical and geological records and these temporal records proved vital in re-thinking the Lost Pines case study. The Lost Pines forest was completely cutover by 1880 but its species composition may not have been purely Pinus taeda at that time. A close relative, Pinus echinata, was also documented to be here in the primary settlement forest and to a lesser extent, in the post-settlement, or secondary forest. Putative hybridization between the two has been well-documented. The Lost Pines ecosystem is more complex than a disjunct Pinus taeda population and this complexity bears on what evolutionary dynamics model fit and what to plant now. Similarly, Lost Pines population has been widely believed to be reproductively isolated from the rest of the Pinus taeda range but this is not absolutely supported either. Historical documents suggest that pine islands once connected the Lost Pines to the rest of its range as recently as the middle of the twentieth century and before that, the gap’s distance tended to fluctuate. To this I add the conjecture is that the pine archipelago in central Texas might have been lost with ebbing of the Little Ice Age, which occurred circa 1850 and that losses due to this minor climate shift could have coincided with the agricultural clearing during settlement. As a consequence of these two factors, climate and clearing, many pine stands in the larger pine archipelago of central Texas may have disappeared without return. Similarly, the range has shifted in east Texas too. Those vast Pinus taeda forests today can be traced to East Texas tree planting programs because in 1900, the original range of this species was confined to only a dozen counties. To this fluctuating distance, forest biology findings adds more doubt to the idea that the Lost Pines population is reproductively isolated: a distance of 100 km does not pose an insurmountable barrier for windborne transport of live pollen. Not having been tested dispersal for the Lost Pines population directly, this is posed here as a hypothesis: HYPOTHESIS: The Lost Pines population is reproductively connected to the rest of its species range in East Texas Piney Woods. Likewise, geological records challenge other widely-held assumptions about the Lost Pines ecosystem. Quaternary climate change, in a global sense, altered the course of Texas Gulf Coastal Plain rivers and these events carved out a highly fragmented set of niches for Pinus taeda in central Texas. The Lost Pines forest can

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grow on Pleistocene geological formations along the Colorado River and these formations coincide with gravelly soils. These Pleistocene geological formations alone do not provide scientific proof that this Pinus taeda population itself is a relictual forest. This claim requires fossil evidence. So far, the only fossil evidence comes from the Boriack Bog pine pollen fossil data. With some reluctance, many assert that this pine pollen fossil evidence is not compelling proof that Pinus taeda forests have persisted since the Pleistocene on certain geological formations along the Colorado River so this too is presented as a hypothesis. HYPOTHESIS: Some lineages in the Lost Pines population originated from Pleistocene relictual populations in central Texas. This ambiguity about fossil evidence limits which evolutionary dynamics model can be fit to the Lost Pines case study. Neither of the generalized models, either the retreating edge model or the stable rear edge model, provides an exact fit to the Lost Pines particulars. To see why, consider that ideally, fossil evidence would be combined with DNA-based evidence from living forest tree populations. Without this evidence, DNA-based population surveys can suggest but not prove a theory specific to the Lost Pines population. Such is the case for the local paleoclimate model which starts with the tacit assumption that the Lost Pines is a Pleistocene relictual population. Accordingly, the Lost Pines population has a DNA signature consistent with one or more massive contractions sometime during the Quaternary and our conjecture is that extremely hot dry climate of the late Holocene was so severe that the population shrunk, or severely contracted downward to very small number of trees. If so, the local paleoclimate model could explain the drought-tolerant attributes of the Lost Pines population.8 This is not without its shortcoming. Its fossil evidence is sparse which means its DNA-based evidence is spatially ambiguous and its statistical methods are not temporally exact, especially in case of a species with historically large populations. This is posed as another hypothesis: HYPOTHESIS: Some lineages in the Lost Pines population severely contracted during prolonged hot, dry conditions of the late Holocene and thus survived conditions more extreme than those present now. What can be said is that Pinus taeda requires a steady water source, as its common name of loblolly (or colloquially speaking, a hog wallow) implies. It is conjectural to state that the Lost Pines forest in the low-rainfall area of central Texas receives supplemental water from aquifer-fed springs and seeps in the Bastrop area but this assertion is an important one which deserves closer study. Closest to the surface in Bastrop County, the Wilcox-Carrizo aquifer beneath the Lost Pines is formed from the same Eocene geological events as its lignite reserves.

8

Al-Rabab’ah M (2003) Evolutionary dynamics of Pinus taeda L. in the late quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p.

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These geologically-defined soils, often pocketed with seeps and springs, are thought to be among the few places that a pine stand could persist even if temperatures rose and water tables fell. HYPOTHESIS: Springs and seeps account for the persistence of the Lost Pines population in central Texas. If so, factoring these subterranean sources of water into the regional precipitation trends could improve the accuracy of bioclimate envelope (BCE) or aridity studies for Pinus taeda. These water sources, coupled with weathered Pleistocene soils, support one of the more original theories about the Lost Pines population which accompanied the local paleoclimate model so this too is presented as a hypothesis: HYPOTHESIS: The Lost Pines population is the source of western Pinus taeda population expansion at the end of the Holocene. That the Lost Pines population might have survived the Holocene so near the 100th meridian is hypothetical yet germane to gauging its chances of survival. Drought is likely to be worse in years to come and this will affect available water from the Colorado River. The Colorado River has highly vulnerable headwaters in the Southern Great Plains where future climate change effects will also be severe. Similarly, the Wilcox-Carrizo aquifer is slow to recharge thus there are concerns that this aquifer could be mined as cities around the Lost Pines area compete for this aquifer’s water. Springs and seeps could dry up. HYPOTHESIS: Scarcity of water will trigger large-scale losses to the Lost Pines forest planted now. While historical and geological records re-configured the Lost Pines case studies, this hypothesis points to what cannot be gained from applying evolutionary dynamics models. To wit, past death due to drought, fire or cyclones cannot be distinguished from death by other causes, i.e. pest and pathogen outbreaks. Also, managing genetic quality of a seedling can add resilience against abiotic stress for living trees but it offers no protection against catastrophic loss. In closing, managed evolution, or any model based on forest genetic composition, offers limited benefits. Such model assumes adequate genetic variation and that genetic variation itself cannot protect against wildfire or a declining water table. At best, it adds resilience when planting forests and that resilience can delay but not completely halt drought-imposed losses. Loss is the cohesive notion which winds through all evolutionary dynamics models. All future scenarios under climate change hold some measure of forest tree losses. Early losses begin when the population is stressed to its physiological limits at its home site and they progress until all individuals within this population have no more adaptive alleles within the reservoir of genetic variation. Short-term evolutionary processes do shape each population within its ecological context and this will continue to be the case for the Lost Pines population even after it is replanted. Pinus taeda planting programs, as the source of seeds, still have large reserves of genetic variation to draw upon but far too little is still known about its adaptive variation and that unknown is one of the wild cards for future forest management.

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In its simplest form, the Lost Pines case study illustrates how evolutionary principles can guide what to plant under future climate change. It does not focus on what is natural, what is rural or what elements set forests apart from human influence. Instead, the Lost Pines case study is presented from the start as a humandominated ecosystem. This coupled human-forest system is as dynamic as evolution itself and it is this odd entity that will dissemble under future climate change. To my thinking, future resource managers should incorporate evolutionary principles into planting programs but they also have a responsibility to explicitly manage against the expanding urban population’s drain on subterranean reserves of water and remain vigilant in retaining the right balance between forests and agriculture, recognizing that these are competing land uses at temperate latitudes. As for the recovery of the Lost Pines forest, nothing stays the same and there can be no return. Goethe said it best: “[Nature] is ever shaping new forms: what is, has never yet been; what has been, comes not again.”9 Managing the Lost Pines forests under climate change illustrates how a new pact between forestry and society can be forged and that the rubric of managed evolution is the right response under the rising uncertainty of climate change. Claire G. Williams

9

Quote from Johann Wolfgang von Goethe 1783 On Nature. From the translation by Huxley TH (1869) Nature 1:9.

Acknowledgements

Parts of this work have already been published in peer-reviewed scientific journals: American Journal of Botany, Molecular Ecology, Forest Ecology & Management, Heredity, Japanese Journal of Historical Botany, Nature Biotechnology, Canadian Journal of Forest Research and International Forestry Review. The book project started with two journal articles published with doctoral student Mohammad Al-Rabab’ah, now an associate professor at Jordan University of Science & Technology, and it took shape while working on an science diplomacy assignment in energy and environment at the U.S. State Department and finally came to a close at the University of Göttingen in Germany with a MWK travel grant from Lower Saxony. To my Texas colleagues: I am appreciative for your many contributions from start to finish. This project began science journalist Dick Stanley wrote about our research on the Lost Pines area in the Austin-American Statesman. His readers responded with useful commentary which led to archaeology, geology, aquifers and river terraces, the Houston toad, Clovis sites, Native Americans, bison, fire ecology, Goodrich Jones, and settler anecdotes. They took the time to write letters and email, to make phone calls, and to send invitations to meals, meetings, conferences and presentations. With their help, the Lost Pines forest took on a new interest which endured after departing my professorship at Texas A&M (1995–2004). This welcome was extended again a decade later: Professor Larry Gilbert at the University of Texas at Austin offered use of field research facilities and Professors Bonnie Jacob and David Meltzer and other colleagues at Southern Methodist vetted my formative ideas. Many thanks for this Texas welcome. To my North Carolina colleagues: I am equally appreciative to you for encouraging the completion of this project. In particular, I am indebted to Dr. Steve Anderson and the Forest History Society staff who provided resources and expertise. Likewise, the National Evolutionary Synthesis Center (NESCent) added in-kind support, library resources and expertise. The North Carolina State University’s D.H. Hill Library and its special collections provided access to the Bruce Zobel correspondence. Professor Peter White at the University of North Carolina’s Botanical Garden

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provided a public venue for this book in its latter stages. Truly, it takes a village to complete a book. Special thanks to Floyd Bridgwater for his many contributions, personal and professional, to this lengthy project. The two of us agree that this book should be dedicated to Professor Bruce Zobel (1920–2011) for many reasons. My appreciation also extends to many colleagues have supplied original research, expert advice, readings and lively discussions: these include Lisa Auckland, Robert Baker, Michael Blum, Robert Campbell, Fred Cubbage, Norma Fowler, Elizabeth Gillet, David Gwaze, Peter Kanowski, Gabriel Katul, Anna Kuparinen, Steve Jackson, James Lewis, William Lowe, Carol Lynn McCurdy, Victor Martinez, Corene Matyas, Cheryl Oakes, Andrea Piotti, Alan Pottinger, Elton Prewitt, William Platt, Humberto Reyes-Valdés, Megan Reynolds, Trina Roberts, Roy Plotnick, Ron Schmidtling, Philip Schoeneberger and Steve Vogel. Each of these experts provided compass bearings for this long search but I take sole responsibility for its synthesis. Claire G. Williams

Contents

Part I

Human Impacts on North American Forests

1

Climate Change ......................................................................................... 1.1 Introduction ...................................................................................... 1.2 Excess CO2 in the Atmosphere......................................................... 1.3 CO2 Integral to Life .......................................................................... 1.4 Not a Point-Source Pollutant ............................................................ 1.5 Long-Lived Molecule in the Earth’s Atmosphere ............................ 1.6 The Greenhouse Gas Effect .............................................................. 1.6.1 Other Greenhouse Gases ...................................................... 1.6.2 Measuring CO2 and CO2 Equivalents ................................... 1.7 More Than Greenhouse Gases ......................................................... 1.7.1 Climate Change Effects Are Regional ................................. 1.7.2 Hurricane Severity................................................................ 1.8 Loss of Forest Cover Accelerates Climate Change .......................... 1.9 Causes of Deforestation.................................................................... 1.10 U.S. South Forests ............................................................................ 1.11 Closing ............................................................................................ References and Related Readings ...............................................................

3 3 3 5 5 5 6 7 7 9 9 10 10 11 11 12 13

2

Predicting How Forests Will Respond .................................................... 2.1 Introduction ...................................................................................... 2.2 Pinus taeda Forests in the U.S. South .............................................. 2.3 Bioclimate Envelope (BCE) Models ................................................ 2.3.1 Lost Pines Anomaly ............................................................. 2.3.2 Predictions for U.S. Southern Pines ..................................... 2.3.3 Predictions for Pinus taeda in the U.S. South...................... 2.3.4 Predictions for Pinus taeda in Light of Seed Dispersal.................................................................. 2.3.5 Predictions for No-Analog Ecosystems ...............................

17 17 17 19 19 20 20 21 21

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2.4 2.5

Drawbacks to Bioclimate Envelope Predictions .............................. Evolutionary Dynamics Models ....................................................... 2.5.1 Population as the Unit of Response ..................................... 2.5.2 Genetic Variation as a Reservoir .......................................... 2.5.3 Measuring Genetic Variation................................................ 2.6 Past Climate Change Response ........................................................ 2.6.1 Local Persistence.................................................................. 2.6.2 Migration .............................................................................. 2.6.3 Extirpation ............................................................................ 2.7 The Role of Seed Dispersal .............................................................. 2.8 How Forest Respond ........................................................................ 2.9 Migration Rates ................................................................................ 2.10 Closing ............................................................................................. References and Related Readings ............................................................... Part II 3

22 23 23 23 23 24 24 24 26 26 27 27 27 28

The Lost Pines Narrative

A Forest Within a Prairie ......................................................................... 3.1 Introduction ...................................................................................... 3.2 The Lost Pines Area ......................................................................... 3.2.1 Bastrop State Park ................................................................ 3.2.2 Census Count ....................................................................... 3.2.3 The Lost Pines: Owners and Stakeholders ........................... 3.2.4 The Lost Pines: A Disjunct Population ................................ 3.2.5 Pinus taeda as Keystone Species ......................................... 3.2.6 Lost Pines:A Refugial Ecosystem ........................................ 3.3 Above Ground .................................................................................. 3.3.1 Low Rainfall and Prolonged Drought .................................. 3.3.2 Hurricanes, Tropical Storms and Ice .................................... 3.4 Beneath the Surface .......................................................................... 3.5 Regional Geography ......................................................................... 3.5.1 The Savanna-Prairie Matrix ................................................. 3.5.2 The Gap Between Lost Pines and Piney Woods .................. 3.6 Beyond the Matrix ............................................................................ 3.6.1 Austin and the Edwards Plateau ........................................... 3.6.2 San Antonio, Southern Texas Plains Mexico Border ........... 3.6.3 Coastal Plain and the Western Gulf Coast Basin Reference and Related Readings.......................................... 3.6.4 East to Houston, Piney Woods, and Louisiana Border ........ 3.6.5 North-Northeast to College Station, Dallas and Oklahoma Border .......................................................... 3.7 Closing ............................................................................................. References and Related Readings ...............................................................

35 35 35 36 40 41 43 44 44 45 45 45 47 48 48 49 50 50 51 51 52 52 52 54

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4

What Historical Records Add .................................................................. 4.1 Introduction ........................................................................................ 4.2 Early Human Activity in Texas .......................................................... 4.3 European Exploration ......................................................................... 4.3.1 New Spain .............................................................................. 4.3.2 Spain’s Military Road ............................................................ 4.3.3 Concerns Over the Louisiana Purchase.................................. 4.3.4 Moses Austin Petitions for a Land Grant ............................... 4.4 Settlement ........................................................................................... 4.4.1 New Spain and Mexico .......................................................... 4.4.2 The Republic of Texas............................................................ 4.4.3 The United States ................................................................... 4.4.4 The Confederate States of America ....................................... 4.4.5 Re-admitted to the United States ........................................... 4.4.6 Sargent’s Visit ........................................................................ 4.5 Managed Forests................................................................................. 4.5.1 Wasteful Logging Practices.................................................... 4.5.2 East Texas Piney Woods......................................................... 4.5.3 Early Reforestation................................................................. 4.5.4 Founding of the Texas Forest Service .................................... 4.5.5 Tree Improvement .................................................................. 4.5.6 A Role for the Lost Pines ....................................................... 4.5.7 Pine Islands in Central Texas ................................................. 4.5.8 Making Selections .................................................................. 4.6 Closing ............................................................................................... References and Related Readings ...............................................................

57 57 57 58 59 59 60 61 62 62 65 65 66 67 68 69 69 70 72 72 73 73 75 75 77 79

5

What Geological Records Add ................................................................ 5.1 Introduction ........................................................................................ 5.2 The Tale of Two Rivers ...................................................................... 5.2.1 The Colorado River of Texas ................................................. 5.2.2 The Brazos River .................................................................... 5.3 Geological Events............................................................................... 5.4 Wilcox-Carrizo Aquifer...................................................................... 5.4.1 The Lost Pines Forest and the Wilcox-Carrizo Aquifer ................................................................................... 5.5 Closing ............................................................................................... References and Related Readings ...............................................................

81 81 81 83 86 86 87

Part III 6

87 89 91

An Evolutionary Synthesis

Survivor of Past Climate Change Events ................................................ 97 6.1 Introduction ........................................................................................ 97 6.2 Taxonomic Classification ................................................................... 97

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6.3

Evolutionary Events ......................................................................... 6.3.1 Tertiary Period ........................................................................ 6.3.2 Quaternary Period .................................................................. 6.4 From Holocene Onward ................................................................... 6.5 Closing ............................................................................................. References and Related Readings .............................................................

98 98 100 107 107 108

7

The Pine Life Cycle ................................................................................. 7.1 Introduction ...................................................................................... 7.2 The Two Phases of the Life Cycle.................................................... 7.2.1 The Diploid Sporophyte Phase............................................... 7.2.2 The Haploid Gametophyte Phase ........................................... 7.3 Two Vehicles for Dispersal............................................................... 7.4 Pollen Dispersal................................................................................ 7.5 Seed Dispersal .................................................................................. 7.5.1 Colonization ........................................................................... 7.6 Evolutionary Consequences ............................................................. 7.6.1 Hybridization.......................................................................... 7.6.2 Serial Colonization ................................................................. 7.6.3 Sweepstakes Dispersal ........................................................... 7.6.4 Abiotic Stress Alters Seed Production ................................... 7.7 Closing ............................................................................................ References and Related Readings .............................................................

115 115 115 116 117 118 119 122 122 123 123 125 125 126 126 126

8

Short-term Evolutionary Processes ....................................................... 8.1 Introduction ...................................................................................... 8.2 Genetic Variation Protects ................................................................ 8.3 Forest Tree Populations Harbor High Genetic Diversity ................. 8.3.1 Gene Flow .............................................................................. 8.3.2 Locally Adapted Populations ................................................. 8.3.3 The Center-Periphery Model.................................................. 8.4 Evolutionary Models for Predicting Climate Change ...................... 8.4.1 Retreating Edge Model .......................................................... 8.4.2 Stable Rear Edge Model......................................................... 8.5 Evolutionary Dynamics Models: Experimental Findings ................ 8.5.1 Lost Pines: Retreating Edge or Stable Rear Edge? ................ 8.5.2 A Local Paleoclimate Model .................................................. 8.6 Closing ............................................................................................ References and Related Readings ............................................................

133 133 133 134 136 136 136 137 137 139 139 139 141 141 143

Contents

Part IV

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A First Approximation for the Future

9

Genetic Composition of the Planted Forest .......................................... 9.1 Introduction .................................................................................... 9.2 Forest Trees Are Largely Undomesticated ..................................... 9.2.1 Stage 1 Improved Seed Source......................................... 9.2.2 Stage 2 Early Domestication ............................................ 9.2.3 Stage 3 Semi-domestication ............................................. 9.3 Genetic Diversity as an Imperative ................................................ 9.4 Closing ........................................................................................... References and Related Readings .............................................................

151 151 152 153 153 154 155 156 157

10

Managing the Existing Forest ................................................................ 10.1 Introduction .................................................................................... 10.2 A First Approximation ................................................................... 10.2.1 A Scenario for Local Persistence ..................................... 10.2.2 A Scenario for Migration ................................................. 10.2.3 A Scenario for Extirpation ............................................... 10.2.4 Summarizing Scenarios.................................................... 10.3 Closing ........................................................................................... References and Related Readings .............................................................

159 159 159 160 161 162 163 164 167

Lexicon ............................................................................................................. 171 Index ................................................................................................................. 179

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Part I

Human Impacts on North American Forests

Michael Obersteiner (2009) Storing carbon in forests. Nature 458:151 Forests will take centuries to adapt to the disruptive processes that accompany climate change, making forest carbon stores vulnerable in the long term.

How might a forest fare over the next century under human-induced climate change? This driving question is addressed using a well-studied U.S. South species, Pinus taeda. This species and other pines have survived past climate change events over centuries, millennia and even millions of years so what is different about future climate change? Future climate change has no precedent. Rapid and abrupt, this type of climatechange has few signs of stabilizing over the next century. It is more complex than elevated levels of CO2 or global warming. Its complexity is greatest for temperate forests but regional forecasts are not yet available. Resource managers face a high degree of uncertainty about what type of forests to plant and how to best manage standing forests. Predictive models for future climate change are not yet scaled to regional effects at this time. Global circulation models show that climate change will be harsh at the westernmost edge of the Pinus taeda range, near the 100th meridian, and these models have been coupled with vegetation models to produce a number of large-scale forecasts. These forecasts show that, on the whole, U.S. South pine forests will migrate northward yet some parts of the Pinus taeda range have no forecasts and such is the case for the Lost Pines population at the westernmost edge of the species range. A finely-scaled dynamic model based on short-term evolutionary processes can serve as a complement to regional climate change forecasts and it can guide management practices. As shown by the Lost Pines narrative, a forest tree population and its life cycle together form the unit of response for future climate change.

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Chapter 1

Climate Change

1.1

Introduction

This chapter introduce how future climate change will affect forests and how forests in turn stabilize climate. This begins with a working definition for climate as weather data is collected over several decades or longer. Data are collected on synoptic meso-scale systems which shape wind direction, temperatures, precipitation patterns and for frequency of extreme events such as hurricanes or ice storms. Climate is a composite of statistical trends, both predicted and observed, and should not be confused with weather.

1.2

Excess CO2 in the Atmosphere

Atmospheric CO2 concentrations from the Industrial Revolution onwards have been rising sharply (Fig. 1.1; Stern 2006; IPCC 20071; Raupach et al. 2007). The world’s primary sources of industrial CO2 are coal-burning facilities although CO2 is also generated by naturally occurring sources such as volcanoes, earthquakes and deforestation. Industrial sources of CO2 are the primary problem and these have risen faster over the past two centuries2 than they have over the past 18,000 years

1 The IPCC is a committee of 2,500 scientists established in 1988 by the World Meteorological Organization and the United Nations Environmental Programme to provide objective assessment of human-induced climate change. 2 A disturbance is defined as a discrete event in time that causes abrupt change in an ecosystem. This means that a major change in climate within a 300-year interval over 10,000-year record qualifies as abrupt.

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_1, © Springer Science+Business Media B.V. 2012

3

4

1

Peak CO2 emissions must occur between 2000 –2015 This corresponds to a rise in global temperature 2.0 to 2.4 C -and to a rise in sea level 0.4 to 1.4 m Growth rate for global atmospheric CO2 for 2000-2006 was 1.93 ppm per year, highest since the start of the Mauna Loa continuous monitoring. Figures taken from IPPC Report November 2007 http://www.ipcc.ch/pdf/assessment-report/ar4

World CO2 emissions (GtCO2/yr)

140

Stabilization Scenario I: 450 ppm ceiling A pessimistic scenario

I :445-490 ppm CO2-eq II:490-535 ppm CO2-eq III:535-590 ppm CO2-eq IV:590-710 ppm CO2-eq V: 710-855 ppm CO2-eq VI:855-1130 ppm CO2-eq

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post-SRES range

60 40 20 0

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Climate Change

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Fig. 1.1 The target for atmospheric CO2 stabilization of 450 ppm ceiling is widely accepted although others, such as NASA scientist James Hansen asserts that this ceiling is considerably lower. This ceiling marks irreversible effects of global warming, i.e. melting of the polar ice caps, release of methane from clathrates, are predicted to occur if emissions exceed this ceiling. If so, peak CO2 emissions must occur before 2015. As shown here, this corresponds to a rise in global temperature 2.0–2.4°C and to a rise in sea level of 0.4–1.4 m. As of 2007, the growth rate for global atmospheric CO2 from 2000 to 2006 was 1.93 ppm per year, highest since the start of the Mauna Loa continuous monitoring (Source: IPPC Report November 2007 http://www.ipcc.ch/pdf/assessmentreport/ar4)

(Mannion 2006). Climate change records on geological time scales register no rise as steeply as this one. To understand how future climate change differs from past climate change,3 we must first understand more about its causal pollutant, CO2.

3 The mark of past climate change is omnipresent on the present-day landscape. To wit, presentday Texas was once part of the Western Inland Sea roughly 100 million years ago and this climate-induced event was instrumental in forming its oil, gas and coal reserves.

1.5 Long-Lived Molecule in the Earth’s Atmosphere

1.3

5

CO2 Integral to Life

Green plants including forest trees take up or sequester CO2 then give off oxygen O2 as part of photosynthesis, a process which converts sunlight into energy and thus sustains all life on earth (Mannion 2006). Tree growth is favored by elevated CO2 concentrations and faster tree growth means more carbon is sequestered in the shortterm (Luyssaert et al. 2007) but there are limits to how much CO2 can be taken up by forests.4 What CO2 is not sequestered by terrestrial ecosystems or by oceans becomes part of the excess of free floating CO2 molecules in the atmosphere. It is this execss CO2 acts as a pollutant and this pollutant has some novel characteristics.

1.4

Not a Point-Source Pollutant

The earth is sensitive only to its total CO2 burden. Excess CO2 concentration blankets the earth; it is not localized around its point sources. Unlike sulfur dioxide,5 CO2 concentrations are not localized, i.e. higher around its emission sources. This blanket of excess CO2 was first detected by continuously measuring the earth’s CO2 concentrations at a single location, the Mauna Loa station in Hawaii USA.6 This station, and other elsewhere, measured a rising CO2 excess which was not coming from Mauna Loa yet its steady rise could still be detected there (Keeling 2008). This provided the proof that the earth is indifferent – or agnostic – to the location of its point sources or even the type of CO2 emissions, coal burning or otherwise (Chameides and Oppenheimer 2007).

1.5

Long-Lived Molecule in the Earth’s Atmosphere

The other key feature is that CO2 molecules are long-lived. A molecule emitted today can persist for 50–100 years in the atmosphere. This means that CO2 emissions are measured not only as annual increase, or flux, but also in terms of a historical

4

Forests are not permanent. When they rot, die or burn, forest trees release, or emit, CO2 molecules. Point emissions of sulfur dioxide caused conifer forest dieback. 6 Rising CO2 inventory dates back to the 1950’s with continuous data from Mauna Loa, Hawaii USA providing the contentious yet convincing annual evidence that atmospheric CO2 concentrations were indeed rising. If CO2 had been measured only as often as surveys of the North Atlantic overturning circulation then it would have taken decades to obtain convincing evidence (Keeling 2008). 5

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Climate Change

inventory7 (Raupach et al. 2007). In the atmosphere, carbon exists as its oxidized form, CO2 and as such, atmospheric CO2 is part of the global carbon cycle. The present atmospheric CO2 increase is composed of anthropogenic emissions of CO2 and a major source of CO2 emissions is the combustion of fossil fuels, mostly coalburning, although aluminum smeltering, some forms of glass-making and cement production also figure prominently.

1.6

The Greenhouse Gas Effect

Free-floating CO2 and the other greenhouse gases are harmful because of the greenhouse gas effect. In simplest terms, CO2 is relatively transparent to the visible light from the sun which heats the earth by day but CO2 is opaque to infrared light (heat) so at night it blocks the heat that the earth’s surface which would otherwise re-radiated back into space.8 Excess CO2 in the atmosphere is a heat-producing pollutant because it traps heat from the earth’s surface. If the earth was a perfectly smooth sphere then this rising CO2 concentrations in its atmosphere would spell global warming but that is not the case: the earth does not have a smooth surface. The amount of trapped heat is not uniform distributed so the greenhouse gas effect does not strictly translate into global warming. A more complex response is introduced by the earth’s irregular features such as its oceans, its mountain ranges, its polar ice caps and even its vast areas of forest. Forests in particular have a complex biophysical relationship to excess CO2 inventory; evapotranspiration, sunlight absorption and reflectivity all vary depending on latitude and forest type (Table 1.1; Canadell et al. 2007; Bonan 2008). This complexity means that no two regions will be affected in the same way by excess CO2 concentrations. Future climate change is regional, not global.

Table 1.1 Carbon is cycled between atmospheric, marine, land-based biota, ocean-based biota and mineral reservoirs Distribution of annual CO2 emissions 1970–1999 1990–1999 2000–2006 Atmosphere 0.44 0.39 0.45 Ocean 0.28 0.27 0.24 Land 0.28 0.34 0.3 The largest fluxes occur between the atmosphere and terrestrial biota such as forests. Shown here are the fractions of CO2 emissions absorbed by terrestrial ecosystems including forested ecosystems and by oceans is incomplete. The largest fraction of CO2 emissions (.45% or 45%) remains in the atmosphere over the time period of 2000–2006 (Adapted from Canadell et al. 2007)

7

From this point forward, units for carbon flux calculations can be useful: 1 teragram (TgC) equals 1 million metric tons carbon or 1 megaton (Mt), 1 petagram (PgC) equals 1 billion metric tons carbon. In English units, 1 lb carbon dioxide, measured as carbon units, equals 3.6667 pounds carbon. 8 Swedish scientist Svante Arrhenius won a Nobel Prize for this discovery of the greenhouse gas effect.

1.6

The Greenhouse Gas Effect

7

Table 1.2 Six classes of greenhouse gases are long-lived and tend to be evenly distributed throughout the earth’s atmosphere Greenhouse gas classes Global warming potential (100-year time horizon) 1 CO2 CH4 21 N2O 310 HFC class 140–11,700 CF4 class 6,500–9,200 SF6 class 23,900 Of these, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) account for the largest proportion: 83.1, 7.6. and 7.4% respectively and occur in the earth’s atmosphere whether or not humans are present. The other three classes are manmade industrial pollutants which are rare yet potent GHG: hydrofluorocarbons (HFC), perfluorocarbons (CF4) and sulfur fluoride (SF6)

1.6.1

Other Greenhouse Gases

Carbon dioxide is one of several greenhouse gases (Table 1.2). Among these six classes, CO2 is by far the most prevalent, accounting for 83.1% of all greenhouse gases (GHG). It is also less potent than the other five GHG classes. Methane and nitrous oxide are part of the earth’s atmosphere whether humans are present or not. The other three GHG classes are more potent. These are synthesized by humans, or “manmade”. To wit, sulfur hexafluoride (SF) gas is one of these synthetic greenhouse gases (Table 1.2). Emitted in trace amounts, SF has a global warming potential which is 23,000 times greater than CO2. Note too that CO2 and the other five classes are expressed as carbon dioxide equivalents, also abbreviated as CO2e (Table 1.2). Even if one accounts for CO2 and its GHG equivalents, there is more to future climate change.

1.6.2

Measuring CO2 and CO2 Equivalents

Timelines for the advance of human-induced climate change have been constructed using earth systems models. Earth systems, or global circulation models (GCM), show that CO2 emissions must be stabilized before reaching a ceiling of 450 ppm (IPCC 2007). This ceiling (Fig. 1.1) corresponds to a 50% probability of exceeding 2° warming from the greenhouse gas effect.9 This scenario has been widely accepted but now there is growing reason to think that this ceiling is too high. 9 This is only one of the IPCC scenarios. All are based on projections of possible future emissions and these can be grouped into four scenario families known as A1, A2, B1, and B2. These emphasize globalized vs. regionalized development on the A vs. B axis and economic growth vs. environmental stewardship on the 1 vs. 2 axis. Three variants of the A1 are globalized, economically oriented scenarios which lead to different emissions trajectories: A1FI refers to intensive dependence on fossil fuels, A1T refers to alternative technology largely replaces fossil fuels, and A1B refers to balanced energy supply between fossil fuels and alternatives.

8

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Climate Change

2100 Greenhouse gas effect Excess CO2 Long-lived molecular half-life Soot, aerosols, pollutants

2040

Zone of rising uncertainty

2010

Fig. 1.2 A concept map for future climate change as forecast by Shell Energy Scenarios to 2050 (p. 40). Forests, whether standing or yet to be planted, will only stabilize or mitigate climate change if they are resilient and healthy. Climate adaptation for forests draws on evolutionary dynamics models

The ceiling measures excess CO2 and CO2e concentrations which will trigger irreversible changes. Included here is the melting of polar ice caps. Melting ice caps will cause a volatilization of methane-rich clathrates beneath the polar ice cap. Methane, or CH4, is a more potent greenhouse gas than CO2 (Table 1.2) so release of large-scale methane would register as an irreversible tipping point to the CO2 and CO2e balance for the earth’s atmosphere. To prevent this point of no return then CO2 emissions must peak soon. This cutoff date is the basis for the oft-cited statement that the world needs 60–80% reductions over 1990 emissions by 2050 but many other variables come into play: human population increase, energy consumption, forest cover losses and the accuracy of earth systems models. Now, in the year 2011, it is not clear what that path towards lower emissions will look like. Future climate change, as a largely regional problem without precedent, brings a rising uncertainty (Fig. 1.2). Consider that the growth rate for global atmospheric CO2 concentrations for 2000–2006 was 1.93 ppm per year, the highest since the start of continuous monitoring at Mauna Loa. This signals that we have entered a period of unusually sharp CO2 increases. Since 2004, global atmospheric carbon dioxide levels have risen from 280 to 377 ppmv (Stern 2006; Raupach et al. 2007) so now CO2 levels are already so high that even if industrial CO2 emissions halted today, the ecological consequences of long-lived excess CO2 concentrations blanketing the earth will continue unabated for centuries. Irreversible future climate change will already be manifest between years 2050 and 2100 (Fig. 1.1; IPCC 2007). This will occur first near the 100th meridian in North America. Western North America’s temperatures are predicted to rise 3.5–4°C

1.7

More Than Greenhouse Gases

9

under the assumption of moderate CO2 emissions scenarios (IPCC 2007; Cole 2009). Future climate change effects are already measurable within the continental United States (Parmesan 2006) and hence we have entered the zone of uncertainty (Fig. 1.2).

1.7

More Than Greenhouse Gases

CO2 and its equivalents will be accompanied by other pollutants and among these will be ozone precursors, volatile organic compounds, and black carbon (i.e. Kopp and Mauzerall 2010). All of these factors contribute not only to the complexity of human-induced climate change but also to a rising uncertainty about whether forests can thrive (Bonan 2008).

1.7.1

Climate Change Effects Are Regional

Human-induced climate change is rapid, more complex than elevated CO2 and global warming and it is regionally variable. Each region will experience its own customized plethora of climate change effects.10 Rain and snow are expected to fall in fewer, more intense events and these same events will also bring flooding or even prolonged dry periods (Parmesan 2007). While total precipitation might increase globally, some regions will be drier while others will receive more rain or snow than usual. Higher surface temperatures favor higher wind speeds, or turbulence. Greater surface drying from higher wind speeds in turn leads to more frequent thunderstorms. Thunderstorms are expected to bring heavier rains and higher wind speeds than usual. Future climate change brings several sources of uncertainty. Models for temperate forests bring the greatest uncertainty (Jackson 2008). The carbon uptake and release, or carbon budgets, are well-known but less is known about regional biophysical effects affecting climate. Other unknowns include how small-scale forests will fare (Loarie et al. 2009). One of the most critical questions is how forests influence precipitation.11 Removing forest cover in Brazil’s Amazon rainforests alters spring rains in Iowa by way of a phenomenon known as teleconnection (Avissar and Werth 2005). Similarly, how aquifers and other groundwater systems will be altered by climate change is not yet known either. Hurricane severity is expected to increase

10 Regional-scale effects of climate change for human-dominated have yet to be addressed in detail (Schiermeier 2010). 11 Forests and human activities within forests together influence climate. Forests can mitigate climate change but how these can be integrated for forest policy is stunningly complex, especially for the purpose of regional forecasting.

10

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Climate Change

but it is still debatable as to whether hurricane frequency will rise. Human-induced climate change holds a high degree of uncertainty for North America’s humandominated temperate latitudes.

1.7.2

Hurricane Severity

Of particular interest to North Americans is the hurricane-prone Gulf of Mexico. Hurricanes damage forests in the southern U.S. to such an extent that the damaged forests abruptly shift from a sink for CO2 uptake to a source of CO2 emissions (Chambers et al. 2007; Zeng et al. 2009). Consider that Hurricane Katrina in the Gulf of Mexico damaged 320 million forest trees (Chambers et al. 2007). Only 15% of destroyed timber could be salvaged so large quantities of woody debris was left behind. This debris attracted bark beetles, other detrimental insects and fungal diseases and these attacked both dead and live trees (Lugo 2008). Still more losses came from drying woody debris which served as fodder for forest fires. If ignited, the burning debris torches live trees (Chambers et al. 2007; Galik and Jackson 2009). Amplified by climate change, more severe hurricanes could bring dire consequences for the U.S. South’s richly timbered regions.

1.8

Loss of Forest Cover Accelerates Climate Change

More than 75% of the earth’s surface has now been modified by human activity over the past three centuries (Ellis and Ramankutty 2008) and forest cover loss figures prominently among this myriad of land use changes. Halting forest cover loss was chronic for decades until now, when deforestation is now recognized as a major contributor to greenhouse gas emissions (Table 1.1; Canadell et al. 2007). Fossil fuel emissions are clearly the culprit but deforestation too has added steeply to the rise of CO2 concentrations too. Slowing deforestation is a complex problem.12 Roughly 31% of the earth’s surface, or 4 billion ha, is now covered in forests (Goodale et al. 2002; Bonan 2008; FAO-FRA 2010). About 13 million ha of forest cover is being lost annually with losses are concentrated in the tropical regions of the Americas, Asia and Africa (Canadell et al. 2007). Not only forest deforestation but also forest degradation is hastening forest cover losses13 (Chazdon 2008). 12 The relationship between forest and climate change is highly interactive. These interactions have continental or even global ramifications (Avissar and Werth 2005). Strictly speaking, forests do not respond to climate change. 13 Forest trees offset anthropogenic carbon dioxide (CO2) emissions by removing CO2 molecules from the atmosphere via photosynthesis and converting it to wood. By slowing deforestation, forest policy can prevent CO2 molecules from entering the atmosphere.

1.10

1.9

U.S. South Forests

11

Causes of Deforestation

Amazon deforestation, now lessening (FAO-FRA 2010),14 can be traced to nation-building for one of the world’s fastest growing economies, Brazil. Here, forests are cleared for industrial-scale agricultural operations and for farm-to-market highways through these new agricultural corridors (Fearnside 2007). By contrast, the Congo Basin forest cover is increasingly lost to shifting food cultivation, human population increases, logging, and military conflict (Makana and Thomas 2006). Indonesia has had long-lasting peat fires which consume vast areas of its forests, adding further to atmospheric CO2 burden (Page et al. 2002). Most of the world’s forests are government-owned (Agrawal et al. 2008) and these provide a revenue stream during a financial downturn when there is little else to draw upon except the sale of logs and logging concessions. Related to this downturn are illegal logging profits and these too siphon off tropical forest cover. Forest cover losses worldwide are huge next to tree planting. Of the 4 billion ha of the world’s forest cover, only 187 million ha (5%) is planted forest and of this, only 72 million ha are managed for industrial wood (Cubbage et al. 2005). An even smaller fraction, about 25 million ha worldwide, is now classified as intensively managed planted forests (or IMPF)15 (Kanowski and Murray 2008). Deforestation is rapid within the borders of some equatorial countries now but its root causes are global. Losing forest cover loss is linked by global trade too. Strong market demand comes from the U.S. and other affluent developed countries, to losses due to exotic forest pathogens and pests spread by global trade and to widespread industrialization and urbanization which contributes to stifling atmospheric pollutants, soot and particulate matter. Globalization of trade takes its toll on forest cover too.

1.10

U.S. South Forests

This area, inclusive of the Lost Pines, covers nearly 216 million ha in 13 states. This is only 24% of the land area of the United States but it represents 60% of this country’s forests16 (Wear 2002). It too has had a history of rapid forest cover loss as part of nation-building. These are secondary forests, mostly planted on what was once agricultural clearings and cutover timber. Its forest cover has declined by 49% since

14

FAO-FRA. 2010. Global Forest Resource Assessment. FAO Forestry Paper. Rome. http://foris.fao.org/. 15 Intensively managed planted forests (IMPF) refer to many types of landholdings and a wide range of sizes. The largest of these (>10,000 ha) are held by companies, governments or even public-private partnerships. At the other end of the scale are independent landowners and even small growers (<10 ha). Note too that even the largest landowners have multiple management objectives: Brazil’s Veracel has planted 91,000 ha of pasture into forest plantations while leaving 100,000 ha for conservation. 16 U.S. forests store roughly 200 million metric (Mt) tons of carbon each year, offsetting roughly 10% of annual U.S. emissions caused by burning fossil fuels (Woodbury et al. 2007).

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Climate Change

the arrival of European settlers (Wear 2002; Chen et al. 2006) and most was cleared by American farmers between 1850 and 1910 (Kauppi et al. 2006). Nation-building in the U.S. South reached its zenith by the end of the nineteenth century but its deforestation did not peak until the first half of the twentieth century (Williams 1989; Houghton et al. 1999; Canadell et al. 2007). Over 89% of these forest lands in the U.S. South are privately owned. These managed forests assumed a new role as the national wood supply in the 21st century are few when logging in the Pacific Northwest’s national forests ceased but this is no longer the case; timber demand is now languishing in the U.S. South. Growing timber has moved offshore so many U.S. mills have closed. Reasons for replanting in the U.S. South’s forests are dwindling. Many forest landowners in the U.S. South now cut without planting because there are fewer U.S. mills and market demand has declined. Suburban housing and urbanization are now small but steady contributors to forest cover loss here; urbanization now accounts for 2% of the south central land area and 6% of its southeastern land area (Chen et al. 2006). Urban and suburban expansion, along with fewer mass public transit systems, are encroaching forested lands in the U.S. South. Urban sprawl is a chronic problem. The average American drives double the distance annually when compared to European drivers because U.S. cities are spread out across large areas.17 This means that the quality of urban mobility infrastructure bears directly on forest cover losses here in the U.S. South even though urban planners have taken measures to slow this. Together with agriculture, the built environment and its impervious surfaces are now replacing some of the U.S. South’s forest cover. How this figures into the future of U.S. forests under the threat of future climate change is not clear. How should managers slow forest cover loss in the U.S. South? This question has inspired many to propose market-driven policy solutions. These are classified as either (1) preventing CO2 molecules from entering the atmosphere (i.e. avoided deforestation) or (2) by removing CO2 molecules from the atmosphere (i.e. forest carbon offsets). Such forest-based policy solutions have surfaced repeatedly for international climate change cooperation but these forest-based18 solutions bring considerable controversy to the bargaining table (see Cannell 2004; Galik and Jackson 2009). In general, reaching accord on payment for ecosystem services poses no easy solution to the problem of climate change.

1.11

Closing

Future climate change has no precedent in past climate change so the next few decades bring a rising uncertainty. Slowing loss of forest cover can stabilize rapid climate change and this is true whether one lives in a developing or developed country. 17 18

From Signals and Signposts: Shell Energy Scenarios to 2050 (p. 40). Mitigation is defined as measures to reduce the pace and the magnitude of the changes in climate.

References and Related Readings

13

The question posed here is whether more forest cover will become a casualty of climate change but its answer must have regional solutions, not only those relegated to global governance, international negotiation or specific countries. Slowing losses to forest cover must be resolved on a regional scale. Quantity of forest cover is not enough. Sufficient quality of well-adapted forest cover is vital.

References and Related Readings Agrawal A, Chattre A, Hardin R (2008) Changing governance of the world’s forests. Science 320:1460–1462 Aitken SN, Yeaman S et al (2008) Adaptation migration or extirpation: climate change outcomes for tree populations. Evol Appl 1:95–111 Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. in the late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Al-Rababah M, Williams CG (2002) Population dynamics of Pinus taeda L. based on nuclear microsatellites. For Ecol Manag 163:263–271 Anderson L, Hu F et al (2006) Ice-age endurance: DNA evidence of a white spruce refugium in Alaska. Proc Natl Acad Sci USA 103:12447–12450 Angelsen A (2008) REDD models and baselines. Int For Rev 10:465–475 Arnold JEM, Persson R (2009) Reorienting forestry development strategies in the 1970s towards “Forests for People”. Int For Rev 11:111–118 Avissar R, Werth D (2005) Global hydroclimatological teleconnections resulting from tropical deforestation. J Hydrometeorol 6:134–145 Barnola J, Raymond D et al (1987) Vostok ice core provides 160,000-year record of atmospheric CO2. Nature 329:408–414 Birdsey E, Pregitzer K et al (2006) Forest carbon management in the United States, 1600–2100. J Environ Qual 35:1461–1469 Boer G, Flato G et al (2007) A transient climate change simulation with historical and projected greenhouse gas and aerosol forcing: projected climate for the 21st century. Clim Dyn 16:427–450 Bonan G (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449 Canadell J et al (2007) Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity and efficiency of natural sinks. Proc Natl Acad Sci USA 104:18866–18870 Cannell M (2004) Land sinks: the Kyoto process and scientific implications. In: Mencuccini M, Grace J, Moncrief J, McNaughton K (eds) Forests at the land-atmosphere interface. CABI Publishing, Edinburgh, p 281 Carslaw K, Boucher O et al (2010) A review of natural aerosol interactions and feedbacks within the Earth systeml. Atoms Chem Phys 10:1701–1737 Chambers J et al (2007) Hurricane Katrina’s carbon footprint on U.S. Gulf Coast forests. Science 318:1107 Chameides W, Oppenheimer M (2007) Carbon trading over taxes. Science 315:1670 Chazdon R (2008) Beyond deforestation: restoring forests and ecosystem services on degraded lands. Science 320:1458–1460 Chen H et al (2006) Effect of land cover on terrestrial carbon dynamics in the southern U.S. J Environ Qual 75:1533–1547 Cole K (2009) Vegetation response to early Holocene warming as an analog for current and future changes. Conserv Biol 24:29–37 Cole K, Fisher J et al (2008) Geographical and climatic limits of needle types of one- and twoneedled pinyon pines. J Biogeogr 35:257–269

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Cubbage F, Siry J et al (2005) Fast-grown plantations, forest certification and the U.S. South: environmental benefits and economic sustainability. N Z J For Sci 35:266–289 Cwynar L, MacDonald G (1987) Geographical variation of lodgepole pine in relation to population history. Am Nat 129:463–469 Davis M, Shaw R (2001) Range shifts and adaptive responses to Quaternary climate change. Science 292:673–679 Eckert A, Bower A et al (2010) Back to nature: ecological genomics of loblolly pine (Pinus taeda L.). Mol Ecol 19:3789–3805 Ellis E, Ramankutty N (2008) Putting people on the map: anthropogenic biomes of the world. Front Ecol Environ 6(8):439–447 FAO-FRA (2010) Global Forest Resource Assessment. FAO Forestry Paper. Rome Italy. http:// foris.fao.org/. Last accessed November 1, 2010 Fearnside PM (2007) Brazil’s Cuiabá-Santárem (BR-163) Highway: the environmental cost of paving a soybean corridor through the Amazon. Environ Manag 39:601–614 Fox T, Jokela E et al (2007) The development of pine plantations silviculture in the southern United States. J For 105(7):337–347, October/November Galik C, Jackson R (2009) Risks to forest carbon offset projects in a changing climate. For Ecol Manag 257:2209–2216 Godbout J, Jaramillo-Correa J et al (2005) A mitochondrial DNA minisatellite reveals the postglacial history of jack pine (Pinus banksiana), a broad range North American conifer. Mol Ecol 14:3497–3512 Goodale C et al (2002) Forest carbon sinks in the Northern Hemisphere. Ecol Appl 12:891–899 Gordon C, Cooper C et al (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168 Grainger A (2008) Difficulties in tracking the long-term global trend in tropical forest area. Proc Natl Acad Sci USA 105:818–823 Grainger A (2009) Towards a new global forest science. Int For Rev 11:126–133 Grimm E, Jacobson G Jr et al (1993) A 50,000-year record of climate oscillations from Florida and its temporal correlation with Heinrich events. Science 261:198–200 Hampe A (2004) Bioclimate envelope models: what they detect and what they hide. Glob Ecol Biogeogr 13:469–471 Heusser C (1966) Late-Pleistocene pollen diagrams from the province of Llanquihue, southern Chile. Proc Am Philos Soc 110:269–305 Hewitt G (2000) The genetic legacy of the Quanternary ice ages. Nature 405:907–913 Hocker H (1956) Certain aspects of climate as related to the distribution of loblolly pine. Ecology 37:824–834 Houghton R, Hackler J et al (1999) The U.S. carbon budget: contributions from land-use change. Science 285:574–578 IPCC (2007) In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contributions of Working Group I to the fourth assessment report of the intergovernmental panel on climate change. IPCC Fourth assessment report on climate change (http://www.ipcc. ch/pdf/assessment-report/ar4). Last accessed on September 9, 2011 Cambridge University Press, Cambridge, 996 p Iversen L, Prasad A (2002) Potential redistribution of tree species habitat under five climate change scenarios in eastern United States. For Ecol Manag 155:205–222 Iverson L, Prasad A (1998) Predicting abundance of 80 tree species following climate change in the eastern United States. Ecol Monogr 68:465–485 Jackson R (2008) Protecting climate with forests. Environ Res Lett 3:1–5 Jackson S, Lyford M (1999) Pollen dispersal models in Quaternary plant ecology: assumptions parameters and prescriptions. Bot Rev 65:39–75 Jackson ST, Overpeck JT (2000) Responses of plant populations and communities to environmental changes of the late Quaternary. Paleobiology 26(Suppl 4):194–220

References and Related Readings

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Jackson S, Weng C (1999) Late Quaternary extinction of a tree species in eastern North America. Proc Natl Acad Sci USA 96:13847–13852 Jackson S, Williams J (2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu Rev Earth Planet Sci 32:495–537 Jackson ST, Webb RS et al (2000) Vegetation and environment in eastern North America during the last glacial maximum. Quat Sci Rev 19:489–508 Jones A, Harrison R (2004) The effects of meteorological factors on atmospheric bioaerosol concentrations – a review. Sci Total Environ 326:151–180 Kanowski P, Murray H (2008) Intensively managed planted forests: towards best practices. Yale Forest Dialogue, New Haven, 69 p Kauppi P et al (2006) Returning forests analyzed with forest identity. Proc Natl Acad Sci USA 103:17574–17579 Keeling R (2008) Recording the earth’s vital signs. Science 319:1771–1772 Kirilenko A, Sedjo R (2007) Climate change impacts on forestry. Proc Natl Acad Sci USA 104:19697–19702 Kopp R, Mauzerall D (2010) Assessing the climatic benefits of black carbon mitigation. Proc Natl Acad Sci USA 107:11703–11708 Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 Ledig F, Rehfeldt G et al (2010) Projections of suitable habitat for rare species under global warming scenarios. Am J Bot 97:970–987 Lo Y-H, Blanco J et al (2010) A word of caution when planning forest management using projects of tree species range shifts. For Chron 86:312–316 Loarie S, Duffy P et al (2009) The velocity of climate change. Nature 462:1052–1057 Lugo A (2008) Visible and invisible effects of hurricanes on forest ecosystems: an international review. Austral Ecol 33:368–398 Luyssaert S et al (2007) CO2 balance of boreal, temperate and tropical forests derived from a global database. Glob Change Biol 13:2509–2537 Makana J-R, Thomas SC (2006) Impact of selective logging and agricultural clearing in forest structure, floristic composition, diversity and timber tree regeneration in the Ituri Forest, Democratic Republic of Congo. Biodivers Conserv 15:1375–1397 Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Marris E (2009) Reflecting on the past. Nature 462:30–32 Matyas C (2010) Associations between the size of hurricane rain fields at landfall and their surrounding environments. Meteorol Atmos Phys 106:135–148 McKenney D, Pedlar J et al (2007) Potential impacts of climate change on the distribution of North American trees. BioScience 57:939–948 McLachlan J, Clark J et al (2005) Molecular indicators of tree migration capacity under rapid climate change. Ecology 86:2088–2098 Montzka S, Dlugokencky E, Butler J (2011) Non-CO2 greenhouse gases and climate change. Nature 476:43–50 Obersteiner M (2009) Storing carbon in forests: a book review. Nature 458:151 Oren R et al (2001) Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere. Nature 411:469–472 Overpeck J, Bartlein P et al (1991) Potential magnitude of future vegetation change in eastern North America: comparisons with the past. Science 254:692–694 Page SE, Siegert F, Rieley JO, Boehm H-D, Jaya A, Limin S (2002) The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420:61–65 Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol Syst 37:637–669 Parmesan C (2007) Influences of species, latitudes and methodologies on estimates of phenological response to global warming. Glob Change Biol 13:1860–1872 Pearson R (2006) Climate change and migration capacity of species. Trends Ecol Evol 21:111–113

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Pearson R, Dawson T (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371 Premoli A, Kitzberger T et al (2000) Isozyme variation and recent biogeographical history of the long-lived conifer, Fitzroya cupressoides. J Biogeogr 27:251–260 Raupach M et al (2007) Global and regional drivers of accelerating CO2 emissions. Proc Am Philos Soc 104:10288–10293 Remington CL (1968) Suture-zones of hybrid interaction between recently joined biotas. Evol Biol 2:321–428 Rodbell D, Smith J et al (2009) Glaciation in the Andes during the Late glacial and Holocene. Quat Sci Rev 28:2165–2212 Roig F, Le-Quesne G et al (2001) Climate variability 50,000 years ago in mid-latitude Chile as reconstructed from tree rings. Nature 410:567–570 Running S (2008) Ecosystem disturbance, carbon and climate change. Science 321:652–653 Schiermeier Q (2010) The real holes in climate science. Nature 463:284–287 Stern N (2006) Stern review: economics of climate change. Cambridge University Press, Cambridge Turner W, Oppenheimer M et al (2009) A force to fight global warming. Nature 462:278–279 Wear D (ed) (2002) Land use. Southern forest resource assessment. USDA-Forest Service, Washington DC Williams M (1989) Americans and their forests: a historical geography. Cambridge University Press, Cambridge UK Williams M (2002) Deforesting the earth: from prehistory to global crisis. University of Chicago Press, Chicago, 689 p Williams J, Jackson S (2007) Novel climates, no-analog communities and ecological surprises. Front Ecol 5:475–482 Willis K, Araujo M et al (2007) How can knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies. Phil Trans R Soc Lond 362:175–186 Woodbury P, Smith J et al (2007) Carbon sequestration in the U.S. forest sector from 1990 to 2010. For Ecol Manag 241:265–278 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from 1851 to 2000. Proc Natl Acad Sci USA 106:7888–7892

Chapter 2

Predicting How Forests Will Respond

2.1

Introduction

Future climate change will bear little resemblance to the slow and gradual pace of past climate change (Fig. 2.1). Predictive models1 are founded on global circulation models (GCM).2 GCM such as the Canadian models or the Hadley Centre models predict future temperatures and precipitation patterns on large spatial scales; these can be coupled with several different vegetation models to forecast how forest species and other organisms might respond. These coupled models are coarse-grained, not regional, and this becomes apparent when reviewing a class of predictive models known as the bioclimate envelope (BCE). BCE are not without their drawbacks. To this informational void, evolutionary dynamics models add a complement which can guide forest management. Short-term evolutionary processes are neither slow nor gradual and they do provide fresh insights on a regional scale as shown by the focus on the U.S. South’s temperate pine forests.

2.2

Pinus taeda Forests in the U.S. South

Pinus taeda is the dominant species (Fig. 2.1). Its latitudinal range covers 10° of latitude, extending from Delaware (39° 21’ N) to central Florida (29°N) and its longitudinal spread is even greater, extending from the Atlantic Seaboard (75° W) to Bastrop, Texas (97° W). This range has an east-to-west aridity gradient which is seasonally variable (Eckert et al. 2010; Fig. 1.2). 1

Climate benefits of temperate forests are not fully understood yet but a good example is that conifer and hardwood forests in NC have lower surface temperature than grass fields or agricultural clearings (Bonan 2008). 2 GCM have coarse resolution with grid cell sizes ranging from 1° to 5° and these are insufficient for forecasting climate change effects at regional case.

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_2, © Springer Science+Business Media B.V. 2012

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Fig. 2.1 The Pinus taeda range extends across most of the southeastern United States and its range has a pronounced aridity gradient which increases from east to west. The aridity index was calculated as the ratio of precipitation to potential evapo-transpiration and none of the samples came from the Lost Pines area. At its western edge is the most extreme point. The aridity gradient has seasonal fluctuations (Figure from Eckert et al. (2010) and copyright permission is granted)

This vast range covers a total land area of 368,038 km2 (Al-Rababah and Williams 2002). Of this, more than 228,023 km2 occurs east of the Mississippi River Valley and the remainder occurs west of the Mississippi River Valley (Al-Rababah and Williams 2002). As for climate change predictions for the U.S. South, some readers might identify with economic predictions more readily than ecological ones. Economic models early on predicted an increase in the U.S. timber supply. Fixed-air carbon enrichment (FACE) experiments3 showed that elevated CO2 increased Pinus taeda growth to the extent that nutrients could become limiting (i.e. Oren et al. 2001). This increase in forest growth was defined as the “CO2 fertilization effect” and it translated into more standing timber in the short-term (Kirilenko and Sedjo 2007). The boost in forest growth was then balanced against with increased risks due to fire, insect attack, high winds and more severe weather events, all of which would damage fast-growing timber. Predictive models have since become more attenuated to the complexity of the forest-atmosphere interface.

3

Forests have long influenced climate and this is measured using free air CO2 enrichment systems (FACE) among others such as eddy covariance flux towers, satellite sensors, and accompanying mathematical descriptions.

2.3 Bioclimate Envelope (BCE) Models

19

The atmospheric models for North America area (Fig. 1.3) are originally based on the UK-based Hadley Centre model and the Canadian model (Boer et al. 2007; Gordon et al. 2000). These are some of the best-known earth systems models or general circulation models (GCM) for North America. Both give a coarse-grained approximation that show that climate change will be harsh within the interior of North America and that east Texas pine forests are predicted to shrink by 2100. Both carry a high degree of uncertainty for the western edge of the Pinus taeda range. Next, when GCM models are coupled with vegetation types, predictions can be based on bioclimate envelope (BCE). Note that BCE forecasts are a product of “scaling up” between fine-grained vegetation models and coarse-grained GCM. Migration is assumed to be the forest’s primary response to climate change and so BCE predictions for North America chart new northward range for a taxon. In no sense do BCE predictions accommodate the spatial scales needed for regional climate change forecasts.

2.3

Bioclimate Envelope (BCE) Models

In its simplest form, the present-day distribution of Pinus taeda or some other taxon is first mapped in its present climate-space using a set of variables such as temperature and precipitation. This is the climate change envelope, based on ecological niche theory, which predicts where forest tree species is likely to migrate under climate change. To do this, the taxon’s climate-space must be assumed to be its ecological niche and that the taxon is in equilibrium with its present climate-space. Its equilibrium climate-space is now shifted across map coordinates until it aligns with the future climate change scenario which most closely fits its climate space and this will be its new range. Northward range expansion is typically predicted for many Northern Hemisphere species as shown by three climate envelope models discussed here. The oldest Pinus taeda climate envelope model comes from a study reported by Hocker (1956). More comprehensive predictive models are readily available but this one illustrates a curious point about the Lost Pines of Texas.

2.3.1

Lost Pines Anomaly

From the start, Hocker (1956) simply sought to define the climate-space of Pinus taeda, not to predict how it might shift under rising CO2 concentrations. To do this, he first related the species’ range to climate variables, or measurements of local climate. The climate data came from 207 weather stations located inside and outside the species range and he looked for patterns using average monthly temperature, average maximum and average minimum monthly temperatures, average monthly precipitation and days of the last frost in spring and first frost in the autumn.

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Using this approach, Hocker (1956) derived a measure, or a discriminant function, which could describe climate conditions for each part of the entire Pinus taeda range with a single value. All station locations within the species range received, on average, a positive value while those outside the species range received a negative value. He found that Mississippi and Louisiana gave the highest values, ranging from + 0.84 to + 1.08 so here growing conditions are most favorable for Pinus taeda. The opposite was true in central Texas: here the discriminant functions were increasingly negative as one moved westward. Even the Texas weather stations inside the species range gave negative discriminant values. Weather stations near the Lost Pines area (30° 12’ N 97° W) had the highest negative values for the study and these values ranged between −0.23 and −0.36. How can Pinus taeda forests can persist here? The Lost Pines area falls outside the species’ bioclimate envelope and so its persistence4 appears to be an anomaly which cannot explained by climatic variables such as rainfall patterns or aridity. Hocker (1956) did not address this particular anomaly directly. Instead, he offered a generalized statement which proves insightful later for Chap. 5: “in instances when the calculated line falls inside the natural range, it is possible that the species occurs naturally beyond the calculated climatic limits as a result of modification of local climate by edaphic and/or topographic conditions.” The Lost Pines area appears be a climate envelope anomaly.

2.3.2

Predictions for U.S. Southern Pines

Migratory direction for forests in the U.S. South are northward based on fossil pollen data (Overpeck et al. 1991). To find the climate-space of the warm-temperate pines as a whole, Overpeck et al. (1991) correlated the pollen range with climate variables. As a group, warm-temperate pines were predicted to move 500–1,000 km north or northeast of their present ranges. A prediction for Texas is missing altogether.

2.3.3

Predictions for Pinus taeda in the U.S. South

Range expansion northward is predicted here too under future climate change. The future range for 80 forest tree species could be predicted under climate change by using standing timber inventory records in 2124 U.S. counties. This study’s predictions came from a wider range of climate-related variables such edaphic or

4

Adaptation now so has become one word with different meanings across disciplines yet all within the context of climate-related discussion. Adaptation is an evolutionary process but now it is also now a policy area, referring to policy solutions which consider how living species, humans included, will cope with hurricanes and extreme weather events which accompany human-induced climate change.

2.3 Bioclimate Envelope (BCE) Models

21

soil conditions and it accounted for potential evapotranspiration (PET). The result was a more conservative prediction of northward migration. Pinus taeda, along with 36 other forest tree species, is predicted to expand by a distance of 100 km also in a northward or northeastern direction (Iverson and Prasad 1998). This estimate is much lower than Overpeck et al. (1991)’s prediction of 500–1,000 km. How a forest tree species will actually shift its range is not addressed.

2.3.4

Predictions for Pinus taeda in Light of Seed Dispersal

Migration northward will be accompanied by a net loss in the species range. This predictive model differs from the other in that it makes seed dispersal explicit as the vehicle for migration. BCE predictions are compared based on the two extremes: no seed dispersal and full seed dispersal (McKenney et al. 2007). Under the full-dispersal scenario, Pinus taeda shifted completely into its future climate envelope. Here, migration registers as a net shift in the species’ range, not an range expansion. To do this, the latitudinal shift for the species was calculated by subtracting the mean center of the current climate-space from the mean center of the new climate-space as forecast. Pinus taeda was among those 25 North American forest tree species predicted to lose 57.2% of its present climate-space under the full-dispersal scenario. This loss corresponds to a dramatic five-degree reduction in its present-day latitudinal spread. The no-dispersal portends an even greater loss of 79.2%. Both models were tested across two different IPCC emissions scenarios (A2 and B2) (McKenney et al. 2007). This predictive study raised the question of no-analog ecosystems in the U.S. South (sensu Williams and Jackson 2007). No-analog ecosystems will be those which re-assemble elsewhere with a new composition of flora and fauna. If so, then future forests will be composed of forest tree species not currently indigenous (McKenney et al. 2007). Candidates are Mexico’s conifer forests but this conjecture seems doubtful now that Mexico’s own climate envelope predictions which show little if any northward migration of its conifer forests (Ledig et al. 2010).

2.3.5

Predictions for No-Analog Ecosystems

The guiding principal for no-analog ecosystem is that each species will respond in its own way to climate change; not all species together now will remain together. Some flora and fauna will be extirpated, others will persist and still others will migrate. In any case, present-day assemblages will not persist; between 4% and 48% of present-day analogs will predicted to be gone by the year 2100 and even if they do exist, they will have migrated elsewhere (Williams and Jackson 2007). This prediction spells new species invasions, displacements and death to flora and fauna now protected within intact ecosystems.

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Drawbacks to Bioclimate Envelope Predictions

The BCE approach is not without controversy and thus it has given way to better models which are less given to predictions within exact geographic coordinates (i.e. Loarie et al. 2009). One of most glaring problem is the assumption that a species as the unit of climate change response; this implies that populations within a species are not differentiated. Another problem with BCE is that it provides an incomplete description of meaningful variables. In many cases, non-climatic variables can be more important than climatic ones. Local landscape heterogeneity often trumps the influence of climate variables as a determinant of vegetation type (Lo et al. 2010). The Lost Pines population is a case in point because its climatic variables cannot fully explain its persistence in central Texas. Similarly, BCE models do not work if there are too little climate data (Ledig et al. 2010) and this is often the case for species or even disjunct populations which are at the highest risk of extinction. A more subtle problem with BCE is that climatic space implies that a forest tree species is in equilibrium with its home site and this is rarely the case (Chap. 8). This has been clearly illustrated for many small but highly most vulnerable conifer species in Mexico (Ledig et al. 2010). Yet another related problem is that BCE predictions are too coarse-grained for at-risk species or very small species ranges. All of these drawbacks call for a more finely-drawn means of predicting how a forest fares under future climate change (Fig. 2.2).

Windthrow, increased turbulence

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Forest ecosystem complexity increases with age while forest tree stems per unit area decrease with age Fig. 2.2 A diagram depicting forests at all stages under future climate change. Past climate change bears little resemblance to future human-induced climate change. Resolving how forests might fare under human-induced climate change can be directed at what to plant (a) and how to manage standing, older forests

2.5

Evolutionary Dynamics Models

2.5

23

Evolutionary Dynamics Models

Evolutionary dynamics models are scaled up from an organism’s life cycle, its evolutionary past and its present-day genetic variation patterns. Set into a proper ecological context, these form a natural complement to predictive models, BCE included, which are more coarse-grained and scaled downwards. Evolutionary dynamics models, if anchored to an ecosystem, take on a practical use: they can guide resource management decisions and they can bring fresh insights while developing regional climate change prediction.

2.5.1

Population as the Unit of Response

Evolutionary dynamics models are based on a population as the unit of response. Populations within a species are differentiated and because of this they show a range of adaptive response (Pearson and Dawson 2003; Hampe 2004; Pearson 2006). A population is the unit of response and this is consistent with past climate change response (Hewitt 2000; Davis and Shaw 2001; Aitken et al. 2008).

2.5.2

Genetic Variation as a Reservoir

This reservoir is shaped and re-shaped by the forces of mutation, genetic drift, selection and migration act. Genetic variation within an organism can be selectively neutral regions of its genome but a less-understood part of the genome are those regions which influence its response to environmental change, the adaptive regions. Genetic variation can be measured in numerous ways.

2.5.3

Measuring Genetic Variation

Genetic variation can be measured at the whole-organism level and this refers to the phenotype, a joint combination of a genotype and its environment. Genetic variation can also be measured or inferred using DNA-based5 sources. Analyzing DNA sequences at

5 DNA forms the building blocks of genes which, in turn, determine a tree’s traits such as its drought tolerance. DNA is present in all cells, both in trees and humans, and is identical in all cells. DNA sequence changes little if any over the lifetime of a tree. DNA can be obtained from any biological sample: bark, needles, embryos, maternal tissues in a seed or even sunken logs.

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the level of one or more populations leads to the concept of DNA signatures and these signatures act as a recording device, tracking population mergers, splits, contractions and expansions. The population’s particular pattern of DNA polymorphism spells out its historical response to past climate change. When coupled with fossil evidence, DNA signatures makes for a powerful new method of inferences about the past and these can be valuable for charting the uncertainty of future climate change. Evolutionary dynamics models are resolving at a rapid pace and this too is adding greatly to what is known about the nature of genetic variation and its role as a reservoir. Over time, available DNA data has shifted from biochemical and molecular markers to increasingly large amounts of DNA sequence data. Early on, these data were drawn from selectively neutral parts of the diploid genome but now DNA sequence data are now identifiable as parts of the adaptive parts of the genome, even for pines and other non-model organisms with large genomes. When individual DNA sequences are analyzed at the population level then evolutionary dynamics models, in theory and in practice, form the mathematical description of allelic composition. This verbal description is the basis for population genetics.

2.6

Past Climate Change Response

This starts with a simplified model: a forest tree population is subject to extreme environmental stress. Its response is progressive losses in which more and more of the population dies out. Some seeds might disperse and colonize elsewhere and if so then this is migration. Otherwise, the population dies out or extirpates.

2.6.1

Local Persistence

Progressive loss from climate change are generally assumed to be gradual (Box 2.1). Early on, a forest tree population persists locally through physiological tolerance, or phenotypic plasticity, to its home site’s conditions. Survival of individuals also depends on abundant genetic variation. Its few survivors finally die and this population no longer locally persists. But that is not its end. Its fate is now either migration of its offspring or extirpation.

2.6.2

Migration

If seeds from the distressed population have been dispersed elsewhere and if they germinated in a suitable habitat then migration has occurred (Box 2.2). Some selection for the better adapted trees may also have occurred as the population contracted and so some of these migrating seeds are better adapted then previous generations.

Box 2.1 Local Persistence of Fitzroya cupressoides The best example of local persistence comes from Chile’s Lake District where Fitzroya cupressoides populations have been persistent here for the past 50,000 years BP. This conifer is a site-specific endemic species and its populations have been subjected to the milder glacial cycles of the Antarctic (Heusser 1966; Rodbell et al. 2009). These isolated populations are thought to have survived within ice-free pockets along the slopes of the Andes Mountain range (Premoli et al. 2000). The oldest evidence comes from subfossil tree remnants which were unearthed by an earthquake in 1960 (Roig et al. 2001). Other accounts of local persistent populations include a Picea glauca population which persisted in Alaska during glacial cover (Anderson et al. 2006) and several North American forest tree species which also had one or more persistent population during glacial periods in the continental U.S. (McLachlan et al. 2005). These locally persistent populations would be a source of rapid re-colonization after the last glacier.6 As glaciers melted, these populations re-seeded the open, glacial-scraped landscapes around them, restoring the species’ previous range more rapidly than massive migration could have.

Box 2.2 Quaternary Migration Routes for Pinus bankisana A forest tree, as a sessile organism, does not actually migrate. Instead, its populations shift from one location to another via the complex seed plant life cycle. Forest tree migration is a slow process, one which requires many generations and thus millennial time scales. Perhaps the best example is the Quaternary past for Pinus banksiana in North America. Its massive migrations illustrate how glacially distinct populations would have migrated outside of vast glacial sheets then returned after the last glacier melted; this is a good example of the loss-and-renewal cycle. Its long-distance migratory routes across Canada, down to the Appalachians Mountains and perhaps as far south as Florida have been reconstructed using fossil pollen, macro-fossils and DNA-based assays on living populations (Godbout et al. 2005). This boreal conifer has a nearly transcontinental distribution across Canada. Its massive migration events closely correspond to Quaternary glacial cycle oscillations (Grimm et al. 1993; Godbout et al. 2005). When glaciers formed, Pinus bankisana populations migrated from eastern Canada as far south as Tennessee, Georgia or possibly Florida USA (Jackson et al. 2000) where this species coexisted with temperate and subtropical pine species (Remington 1968). This example also shows that massive migration is one response among many among populations within a species. One or more populations of Pinus banksiana were locally persistent among Canada’s eastern islands. Yet another population shows evidence of past hybridization with a closely related species, Pinus contorta. Massive migration, local persistence and even occasional hybridization with other species are among the population-level responses within a single species.

6

Locally persistent populations are the shortcut to recolonizing between glacial events.

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Box 2.3 Extinction of Picea critichfieldii The enigmatic extinction of Picea critichfieldii is the best documented evidence to date. This species once had a range in North America’s lower Mississippi Valley as determined by its fossil ovulate cones and needles. That this is a separate species is clear because its macro-fossils are distinctive from those belonging to present-day Picea species (Jackson and Weng 1999). Its range once extended throughout the lower Mississippi River Valley as far as western Georgia. By the end of the last glacier, its fossils disappear completely (Jackson and Weng 1999). The causes behind its extinction are not known.

2.6.3

Extirpation

If no offspring colonize elsewhere by the time that this population comes to its actual end. Now this population dies out, or extirpates (Box 2.3). A failure to disperse future colonizers elsewhere renders the population’s loss complete. Still, its extirpation is not extinction; after all, this population is one of several populations which make up a species. The loss of this one population might shift the entire species range but rarely does it mark the end of the species as a whole. If the population’s seeds colonize elsewhere, then its fate is open-ended. At some later time, if conditions improve, then this population might eventually re-colonize its homesite. As such, this response to climate change is an interlinking cycle of climate change response. Its three elements of persistence, migration and extirpation form different degrees of loss, or death. No two populations will go through this process in the same way. Each population within a species is differentiated from the others to a varying degree.

2.7

The Role of Seed Dispersal

Forest trees are sessile so they can only migrate via seed dispersal. This dispersal process is part of any seed plant’s complex life cycle. Forest trees, as seed plants, have a two-phase life cycle: the dominant sporophyte phase gives rise annually to the brief gametophyte phases. Of the two, the tree, as the sporophyte, gets more consideration but equally important is the gametophyte phase which is often overlooked because it is small, transient and has no corollary to the vertebrate life cycle. This life cycle meters the adult sporophyte’s migratory response. Both phases of the life cycle must function for one generation of forests to follow the next. These processes lead up to seed dispersal and colonization. Seen another way, without gametophytes, there can be no seeds and without seeds there is no future for any forest tree population in the case of natural regeneration. The following examples put these components together.

2.10 Closing

2.8

27

How Forest Respond

The Quaternary lasted nearly two million years ago and most of this time period was the Pleistocene epoch, a time when the earth’s climate grew cooler (Chap. 5). This led to a series of major ice ages. The Arctic ice cap was the source of vast, continent-sized polar ice sheets, or glaciers, which advanced and receded across North America’s higher latitudes. For lack of any better information on future climate change, evolutionary dynamics models draw heavily on how forest tree populations responded to Quaternary climate change. Most of the emphasis has after the last glacier melted, a time period over the past 20,000 years or less. These inferences can be made using temporal records along with fossil evidence and DNA polymorphism data.

2.9

Migration Rates

The emphasis on Quaternary glaciation has brought our focus to migration rather than local persistence but this is realistic assumption, as discussed in later chapters. Rather than asking how a forest might fare under future climate change, the question now changes to how rapidly might a forest tree population migrate? Empirical estimates for actual migration routes provide some alarming answers. Migration rates for forest trees in the late Pleistocene are crudely estimated to be roughly 1 km year−1 from or 100 km per century (e.g. Pearson 2006) but most estimates are lower (10–50 km per century; Iverson and Prasad 1998). An oft-cited example is Pinus contorta which moved 2,200 km over 12,000 years which is a rate of 18 km per century (Cwynar and MacDonald 1987). Among the slowest rates is Pinus edulis which migrated only 43 m year−1 (Cole et al. 2008). All point to the over-riding concern that migration rates for forest tree populations might be too slow to keep with the rapid advance of human-induced climate change.

2.10

Closing

How human-induced climate change will affect U.S. South’s temperate Pinus taeda forests has given way to a number of important predictions. The U.S. South will benefit from having more timber in the short-term. Southern pine forests, including Pinus taeda, will expand its range northward or perhaps migrate northward with a net loss in the size of its range. None of these climate change predictions apply to the western edge of the species range in central Texas. In fact, the persistence of the disjunct Pinus taeda population at the western edge of the range cannot be easily explained with climatic variables.

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2 Predicting How Forests Will Respond

Evolutionary dynamics models serve as a complement to climate change forecasting; these are process-oriented biological models which are driven by shortterm evolutionary processes. The population is the unit of response and any response to climate change requires the entire life cycle for generations. Given these caveats, one can now proceed with more finely drawn insights as to a particular forest tree population’s chances of locally persisting, migrating or dying out. Evolutionary dynamics models are largely founded on how forests responded to past Quaternary climate change. Even so, evolutionary dynamics models might offer a practical framework for guiding resource managers on what to plant or what to expect for older, standing forests and this is shown using the Lost Pines narrative.

References and Related Readings Agrawal A, Chattre A, Hardin R (2008) Changing governance of the world’s forests. Science 320:1460–1462 Aitken SN, Yeaman S et al (2008) Adaptation migration or extirpation: climate change outcomes for tree populations. Evol Appl 1:95–111 Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. in the late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Al-Rababah M, Williams CG (2002) Population dynamics of Pinus taeda L. based on nuclear microsatellites. For Ecol Manag 163:263–271 Anderson L, Hu F et al (2006) Ice-age endurance: DNA evidence of a white spruce refugium in Alaska. Proc Natl Acad Sci USA 103:12447–12450 Angelsen A (2008) REDD models and baselines. Int For Rev 10:465–475 Arnold JEM, Persson R (2009) Reorienting forestry development strategies in the 1970s towards “Forests for People”. Int For Rev 11:111–118 Avissar R, Werth D (2005) Global hydroclimatological teleconnections resulting from tropical deforestation. J Hydrometeorol 6:134–145 Birdsey E, Pregitzer K et al (2006) Forest carbon management in the United States, 1600–2100. J Environ Qual 35:1461–1469 Boer G, Flato G et al (2007) A transient climate change simulation with historical and projected greenhouse gas and aerosol forcing: projected climate for the 21st century. Clim Dyn 16:427–450 Bonan G (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449 Canadell J et al (2007) Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity and efficiency of natural sinks. Proc Natl Acad Sci USA 104:18866–18870 Cannell M (2004) Land sinks: the kyoto process and scientific implications. In: Mencuccini M, Grace J, Moncrief J, McNaughton K (eds) Forests at the land-atmosphere interface. CABI Publishing, Edinburgh, 281 pp Chambers J et al (2007) Hurricane Katrina’s carbon footprint on U.S. Gulf Coast forests. Science 318:1107 Chameides W, Oppenheimer M (2007) Carbon trading over taxes. Science 315:1670 Chazdon R (2008) Beyond deforestation: restoring forests and ecosystem services on degraded lands. Science 320:1458–1460 Chen H et al (2006) Effect of land cover on terrestrial carbon dynamics in the southern U.S. J Environ Qual 75:1533–1547

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29

Cole K (2009) Vegetation response to early Holocene warming as an analog for current and future changes. Conserv Biol 24:29–37 Cole K, Fisher J et al (2008) Geographical and climatic limits of needle types of one- and twoneedled pinyon pines. J Biogeogr 35:257–269 Cubbage F, Siry J et al (2005) Fast-grown plantations, forest certification and the U.S. South: environmental benefits and economic sustainability. N Z J For Sci 35:266–289 Cwynar L, MacDonald G (1987) Geographical variation of lodgepole pine in relation to population history. Am Nat 129:463–469 Davis M, Shaw R (2001) Range shifts and adaptive responses to Quaternary climate change. Science 292:673–679 Eckert A, Bower A et al (2010) Back to nature: ecological genomics of loblolly pine (Pinus taeda L.). Mol Ecol 19:3789–3805 Ellis E, Ramankutty N (2008) Putting people on the map: anthropogenic biomes of the world. Front Ecol Environ 6(8):439–447 Fearnside PM (2007) Brazil’s Cuiabá-Santárem (BR-163) Highway: the environmental cost of paving a soybean corridor through the Amazon. Environ Manag 39:601–614 Fox T, Jokela E et al (2007) The development of pine plantations silviculture in the southern United States. J For 105:337–347 Galik C, Jackson R (2009) Risks to forest carbon offset projects in a changing climate. For Ecol Manag 257:2209–2216 Godbout J, Jaramillo-Correa J et al (2005) A mitochondrial DNA minisatellite reveals the postglacial history of jack pine (Pinus banksiana), a broad range North American conifer. Mol Ecol 14:3497–3512 Goodale C et al (2002) Forest carbon sinks in the Northern Hemisphere. Ecol Appl 12:891–899 Gordon C, Cooper C et al (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168 Grainger A (2008) Difficulties in tracking the long-term global trend in tropical forest area. Proc Nat Acad Sci USA 105:818–823 Grainger A (2009) Towards a new global forest science. Int For Rev 11:126–133 Grimm E, Jacobson G Jr et al (1993) A 50,000-year record of climate oscillations from Florida and its temporal correlation with the Heinrich events. Science 261:198–200 Hampe A (2004) Bioclimate envelope models: what they detect and what they hide. Glob Ecol Biogeogr 13:469–471 Heusser C (1966) Late-Pleistocene pollen diagrams from the province of Llanquihue, southern Chile. Proc Am Philos Soc 110:269–305 Hewitt G (2000) The genetic legacy of the quaternary ice ages. Nature 405:907–913 Hocker H (1956) Certain aspects of climate as related to the distribution of loblolly pine. Ecology 37:824–834 Houghton R, Hackler J et al (1999) The U.S. carbon budget: contributions from land-use change. Science 285:574–578 IPCC (2007) In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt, KB, Tignor M, Miller HL (eds) Contributions of Working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 996 p Iverson L, Prasad A (1998) Predicting abundance of 80 tree species following climate change in the eastern United States. Ecol Monogr 68:465–485 Iversen L, Prasad A (2002) Potential redistribution of tree species habitat under five climate change scenarios in eastern United States. For Ecol Manag 155:205–222 Jackson R (2008) Protecting climate with forests. Environ Res Lett 3:1–5 Jackson S, Lyford M (1999) Pollen dispersal models in Quaternary plant ecology: assumptions parameters and prescriptions. Bot Rev 65:39–75 Jackson ST, Overpeck JT (2000) Responses of plant populations and communities to environmental changes of the late Quaternary. Paleobiology 26(Suppl):194–220

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Jackson S, Weng C (1999) Late Quaternary extinction of a tree species in eastern North America. Proc Natl Acad Sci USA 96:13847–13852 Jackson S, Williams J (2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu Rev Earth Planet Sci 32:495–537 Jackson ST, Webb RS et al (2000) Vegetation and environment in eastern North America during the last glacial maximum. Quat Sci Rev 19:489–508 Jones A, Harrison R (2004) The effects of meteorological factors on atmospheric bioaerosol concentrations: a review. Sci Total Environ 326:151–180 Kanowski P, Murray H (2008) Intensively managed planted forests: towards best practices. Yale Forest Dialogue, New Haven, 69 p Kauppi P et al (2006) Returning forests analyzed with forest identity. Proc Natl Acad Sci USA 103:17574–17579 Keeling R (2008) Recording the earth’s vital signs. Science 319:1771–1772 Kirilenko A, Sedjo R (2007) Climate change impacts on forestry. Proc Natl Acad Sci 104:19697–19702 Kopp R, Mauzerall D (2010) Assessing the climatic benefits of black carbon mitigation. Proc Natl Acad Sci 107:11703–11708 Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 Ledig F, Rehfeldt G et al (2010) Projections of suitable habitat for rare species under global warming scenarios. Am J Bot 97:970–987 Lo Y-H, Blanco J et al (2010) A word of caution when planning forest management using projects of tree species range shifts. For Chron 86:312–316 Loarie S, Duffy P et al (2009) The velocity of climate change. Nature 462:1052–1057 Lugo A (2008) Visible and invisible effects of hurricanes on forest ecosystems: an international review. Austral Ecol 33:368–398 Luyssaert S et al (2007) CO2 balance of boreal, temperate and tropical forests derived from a global database. Glob Change Biol 13:2509–2537 Makana J-R, Thomas SC (2006) Impact of selective logging and agricultural clearing in forest structure, floristic composition, diversity and timber tree regeneration in the Ituri forest, democratic republic of Congo. Biodivers Conserv 15:1375–1397 Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Marris E (2009) Reflecting on the past. Nature 462:30–32 Matyas C (2010) Associations between the size of hurricane rain fields at landfall and their surrounding environments. Meteorol Atmos Phys 106:135–148 McKenney D, Pedlar J et al (2007) Potential impacts of climate change on the distribution of North American trees. Bioscience 57:939–948 McLachlan J, Clark J et al (2005) Molecular indicators of tree migration capacity under rapid climate change. Ecology 86:2088–2098 Obersteiner M (2009) Storing carbon in forests: a book review. Nature 458:151 Oren R, Ellsworth D, Johnsen K, Phillips N, Ewers B, Maier C, Schäfer K, McCarthy H, Hendrey G, McNulty S, Katul GG (2001) Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere. Nature 411:469–472 Overpeck J, Bartlein P et al (1991) Potential magnitude of future vegetation change in eastern North America: comparisons with the past. Science 254:692–694 Page SE, Siegert F, Rieley JO, Boehm H-D, Jaya A, Limin S (2002) The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420:61–65 Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Ann Rev Ecol Evol Syst 37:637–669 Parmesan C (2007) Influences of species, latitudes and methodologies on estimates of phenological response to global warming. Glob Change Biol 13:1860–1872 Pearson R (2006) Climate change and migration capacity of species. Trends Ecol Evol 21:111–113

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31

Pearson R, Dawson T (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371 Premoli A, Kitzberger T et al (2000) Isozyme variation and recent biogeographical history of the long-lived conifer, Fitzroya cupressoides. J Biogeogr 27:251–260 Raupach M et al (2007) Global and regional drivers of accelerating CO2 emissions. Proc Am Philos Soc 104:10288–10293 Remington CL (1968) Suture-zones of hybrid interaction between recently joined biotas. Evol Biol 2:321–428 Rodbell D, Smith J et al (2009) Glaciation in the Andes during the late glacial and Holocene. Quat Sci Rev 28:2165–2212 Roig F, Le-Quesne G et al (2001) Climate variability 50,000 years ago in mid-latitude Chile as reconstructed from tree rings. Nature 410:567–570 Running S (2008) Ecosystem disturbance, carbon and climate change. Science 321:652–653 Stern N (2006) Stern review: economics of climate change. Cambridge University Press, Cambridge Turner W, Oppenheimer M et al (2009) A force to fight global warming. Nature 462:278–279 Wear D (ed) (2002) Land use. In: Southern forest resource assessment. USDA-Forest Service, Washington DC Williams M (1989) Americans and their forests: a historical geography. Cambridge University Press, New York Williams M (2002) Deforesting the earth: from prehistory to global crisis. University of Chicago Press, Chicago, 689 p Williams J, Jackson S (2007) Novel climates, no-analog communities and ecological surprises. Front Ecol 5:475–482 Willis K, Araujo M et al (2007) How can knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies. Philos Trans R Soc Lond 362:175–186 Woodbury P, Smith J et al (2007) Carbon sequestration in the U.S. forest sector from 1990–2010. For Ecol Manag 241:265–278 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from 1851 to 2000. Proc Natl Acad Sci USA 106:7888–7892

Part II

The Lost Pines Narrative

Heraclitus, Greek philosopher of Ephesus ca. 500 B.C. Out of all things there comes a unity, and out of a unity all things.

Francisco Ayala, Myth of Sisyphus (2010) The reductionist approach of biologists has enabled remarkable achievement by causing us to focus on just a few experimentally tractable organisms, but it also has tended to restrict our vision. There is much to learn about the many organisms that populate our planet, most in ways we can’t yet fathom…how do individuals organize themselves into incredibly complex communities?

The Lost Pines area in central Texas is a shady oasis complete with a river next to a Pinus taeda forest. Travelers have long been surprised to see this pine island rising out of its savannah-prairie matrix. Beyond this matrix are three fast-growing U.S. cities: San Antonio, Austin and Houston in addition to the hurricane-prone Gulf of Mexico. These complete the picture of the Lost Pines area as a complex human-dominated mosaic of temperate-zone land use. The Lost Pines narrative brings the right amount of realism necessary for showing how short-term evolutionary processes work and how they shape forest management decisions under climate change. More than a place, the Lost Pines area has an active network interested in conserving its forest. This oasis has long attracted human activity and this is one of these reasons that it has well-documented historical records. Its history brings forth important insights which bear on its future. The same is true for its geological records: the Lost Pines has fossil fuel reserves beneath its surface and so it has well-documented geological records which bring even more insights about its future. A resource-rich historical landmark, this secondary forest is now managed as a refugial ecosystem for the Houston toad. Perhaps least recognized among its many values is that the Lost Pines area marks a cradle of early innovation for planting programs. These programs were based on evolutionary principles and this was put to work for drought-prone Texas. From here this new concept of tree improvement matured into a precise scientific discipline which now used worldwide. Shaping the genetic composition of the forest

34

Part II

The Lost Pines Narrative

using the best available scientific knowledge opens the door to a range of new solutions. These solutions shape what to plant under future climate change. Early records show that pine islands here in central Texas might have been more widespread. The archipelago included more than Pinus taeda; nineteenth and twentieth century records indicate that two pine species were originally present: that Pinus taeda and drought-hardy relative, Pinus echinata. Lost Pines population is a true, naturally occurring disjunct population separated from the rest of its species range. It is disconnected to the rest of the eastward Pinus taeda range because it is bounded by a prairie-savanna matrix unsuited for pines. The prairie-savanna soils are too alkaline, too basic, as a rule to support either migration or expansion into the continuous range of this species. The good news is that its geological records show that the Lost Pines area has available water from a river basin’s terraces and from springs and seeps.

sdfsdf

Chapter 3

A Forest Within a Prairie

3.1

Introduction

The Lost Pines area is best known for its small Pinus taeda forest growing near the Colorado River of Texas. Surrounded by a savanna-prairie matrix, this forest is near croplands, pasture, dwellings and cities. The Lost Pines area serves admirably as a microcosm of how we, as Americans, use land in the twenty-first century. Highways zigzag through the forested area, connecting state parks to ranches, rodeos,1 suburban housing, malls and expanses of paved parking. These are prominent features of the newly urbanized American landscape and they are expected to expand even further over the next century, as Texas and its strong economy attract a disproportionate share of the world’s rising human population.

3.2

The Lost Pines Area

The Lost Pines area has a long-term conservation plan. Such plans are vital2 given that the proximity of the Lost Pines area to three fast-growing U.S. cities: Austin, San Antonio and Houston. Already part of a rural-suburban-urban continuum, the Lost Pines area is ideal for asking how a forest at the interface of prairies and cities might respond to human-induced climate change over the next century.

1

Bastrop’s rodeo draw people here too. See Engelhardt (2009). Two of the largest incentive programs for U.S. forest landowners once were the Conservation Reserve Program and the Forestry Incentives Program. Other options have been state or companysponsored reforestation programs or even forest certification. Sale of forest carbon sequestration rights was also well-developed for Texas where private landowners are rewarded based on the actual carbon that their forests stored; the Texas Forest Service is a third-party verifier for the Chicago Climate Exchange (CCX). 2

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_3, © Springer Science+Business Media B.V. 2012

35

36

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A Forest Within a Prairie

Fig. 3.1 A map of ecological regions (eco-regions) for Texas as defined by the U.S. Environmental Protection Agency (Griffith et al. 2004). The Lost Pines are located in map unit 33e

3.2.1

Bastrop State Park

This Pinus taeda forest is presently confined to the eastern part of Bastrop County, Texas with scattered stands in adjacent Lee and Fayette Counties (Figs. 3.1–3.2). Bastrop, the county seat, is the closest town and it borders on the Colorado River (Fig. 3.3) near Bastrop State Park which adjoins Buescher State Park (Figs. 3.4–3.5). Land ownership is split between private and public owners (Table 3.2). Of the two state parks, Bastrop State Park serves as the epicenter (N 30° 06¢ W 97°17¢) for the Lost Pines area (Fig. 3.5) and it serves to measure its relative distances from other landmarks (Table 3.1).

3.2

The Lost Pines Area

37

Fig. 3.2 A map of central Texas counties. The Lost Pines forest is mostly in eastern part of Bastrop County

Fig. 3.3 The Colorado River figures prominently in the present-day land use of the Lost Pines forest as well as its history. Here is a part of the river close downstream from the town of Bastrop near a kayak landing established by the Pines and Prairie Land Trust (Photograph taken by the author)

38

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A Forest Within a Prairie

Fig. 3.4 Bastrop State Park within the Lost Pines area of central Texas once included older, widely spaced Pinus taeda forests which accommodate hiking, golf and other recreation uses (Photograph taken by the author)

Fig. 3.5 A map of the Bastrop State Park, Buescher State Parks and the Stengl Biological Station. Here Pinus taeda stands have expanded within the past five decades

3.2

The Lost Pines Area

39

Table 3.1 Approximate distances between the Bastrop State Park area (B) and selected locations Approximate Distance* Latitude (W) Longitude (N) km (miles) Location Deg Min Sec Deg Min Sec Kilometers (miles) Bastrop State Park (B) 30 06 51 97 15 36 0 Dallas-Fort Worth Airport 32 53 48 97 02 16 306 (191) Buescher State Park 30 04 09 97 10 06 11 (7) Smithville 30 00 31 97 09 34 16 (10) Austin 30 16 02 97 44 35 48 (30) College Station 30 37 41 96 20 04 106 (66) Llano 30 46 29 98 42 02 153 (96) Houston 29 45 46 95 22 59 181 (113) Matagorda 28 41 27 95 58 03 200 (125) Freeport 28 57 15 95 21 35 224 (140) Dayton, Liberty County Texas 30 02 48 94 53 10 227 (142) Dinosaur Valley Park, Glen Rose 32 14 20 97 48 38 240 (150) Fastrill, Angelina County Texas 31 37 48 95 17 10 254 (159) Galveston Island 29 14 52 94 52 59 248 (155) Big Bend National Park 29 14 60 103 15 01 584 (365) Abilene 32 26 55 99 43 59 347 (217) Saltillo, Coahuila Mexico 25 25 37 100 59 00 630 (394) Monclova, Coahuila Mexico 26 54 37 101 25 20 547 (342) Mexico City, Mexico 19 25 37 99 07 39 1,189 (743) Distance (*) is conservatively estimated using straight-line distances with Google Earth™

The original part of Bastrop State Park (Fig. 3.4) was acquired by deeds from the city of Bastrop and from private owners from 1933 to 1935. The park opened in 1937 and since then it has acquired additional land area in 1979. The Pinus taeda coverage within both two state parks has increased from 25.5% to 37.2% coverage between 1949 and 1995 (Al-Rababah 2003). Bastrop State Park is one of two stateowned parks3 (Fig. 3.5). The other is Buescher State Park4 which had a few sparse pine stands and large spreading patches of trees which were naturally regenerated.

3

Both the Civilian Conservation Corps (CCC) and Works Project Administration (WPA) programs contributed greatly here during the Great Depression, planting forest seedlings and building infrastructure for state parks and national forests. 4 Buescher State Park, with an area of 462 ha, is located north of Smithville in Bastrop County. Between 1933 and 1936, Emil and Elizabeth Buescher deeded land to the state of Texas. Heirs deeded another portion and the rest of the park’s land area was acquired from the municipality of Smithville. The original park opened in 1940 with more land but some was deeded to the University of Texas.

40

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A Forest Within a Prairie

Box 3.1 USDA-Forest Service Forest Inventory Assessment (FIA) data for Bastrop County Texas. Pinus taeda has a lifespan of 300–400 years although timber harvest usually takes place after 35 years. Source: http://fiatools.fs. fed.us/fido/output.html (accessed 8/13/2010). Estimated Pine Count (FIA) for Bastrop County 19,993,184 Area (ha) Total 19,993 (FIA) Age structure 0–19 years 0 20–39 years 6,491 40–59 years 7,421 60–79 years 0 80–99 years 6,081 Ownership (ha) Total 19,993 State and Local Government 11,289 (56.46%) Private 8,704 (43.54%)

3.2.2

Census Count

The Lost Pines forest covers at least 19,000 ha (Box 3.1). Other estimates of its size tend to be higher; this area was estimated to be 26,876 ha using spatial imaging nearly a decade ago (Al-Rababah 2003) trees per ha as a minimum, this would suggest that a count closer to 27 million trees. A similar estimate of 21,463 ha5 was provided by the Texas Forest Service (Brown 1955). Similarly, Sargent (1884) stated that the Lost Pines forest occupied 36,400 ha in 1880. The Lost Pines forest has a large census population no matter which estimate is used. Two features distinguish the Lost Pines forest and its current management. First, the Lost Pines areas have more public ownership (11,289 ha) than private ownership (8,704 ha) and this explains why forest management objectives for the Lost Pines area are more diverse than timber-growing alone. Second, most of the Pinus taeda stands in the Lost Pines area are well past the timber harvest ages 25–35 years typical of this species (Box 3.1). Only 32.5% of the Lost Pines forest falls into the age class of 20- to 39-year (6,491 ha) as shown in Box 3.1. More of the trees belonged to the 40- to 59-year old cohort (37.1% or 7,421 ha) or the 80- to 99-year old cohort (30.41% or 6,081 ha) (Box 3.1). The latter is common in the two state parks which have large mature Pinus taeda forests but even so these Pinus taeda trees are not really old: this species has a lifespan of 300–400 years. 5 Here, Brown (1955) estimated that the Pinus taeda islands in Bastrop County were the largest with 56,675 acres but that Fayette County had 15,717 acres, Caldwell County had 3,783 acres and Lee County had 1,573 acres at this time.

3.2

The Lost Pines Area

41

Table 3.2 The Lost Pines community of owners and other stakeholders shapes its conservation plan Entity Name Purpose Federal U.S. Fish and Wildlife Safe Harbor Agreements Habitat Conservation Plans Houston Toad Recovery Plan U.S. Department of Interior Natural Voluntary cost-share programs for Resources Conservation Service land management State

Texas Parks & Wildlife Texas Forest Service Stengl Biological Station University of Texas

Education and outreach Park management Conservation easement funding; fire-fighting Comprehensive ecological research for the Lost Pines area

Civic

Boy Scouts of America

Manages Griffith League Ranch and Lost Pines Scout Reservation

Municipal

Bastrop County Heart of the Pines Fire Department

Economic development All-volunteer group educates about preventing fires

Non-governmental

Austin Bastrop County River Partnership Envision Central Texas

Education about river basin and its ecosystem Regional planning on 25- and 50-year timeframes Lower Colorado River Authority Water use authority recognizes role of forests in water quality Opportunity Bastrop County Economic development including recreational potential Pines & Prairie Land Trust Land conservation on 100 ha of privately owned pine habitat This community includes not only forest landowners but other natural resource management groups, universities, land trusts, government agencies and non-governmental groups

3.2.3

The Lost Pines: Owners and Stakeholders

The Lost Pines ownership, atypical of the rest of the Pinus taeda range,6 has a mixed forest ownership which works closely with a network of non-governmental (NGO) organizations, private landowners, civic groups, trust properties, conservation easements and state agencies such as the Texas Forest Service and the Texas Department of Parks and Wildlife (Table 3.2). Governance of some private lands has been ceded 6 Lost Pines’ private ownership is not typical for the larger Pinus taeda range: it has neither TIMOs (Timberland Investment and Management Organizations) nor REIT (Real Estate Investment Trusts). TIMOs owe their origins to the Employee Retirement Income Security Act (ERISA) passed by Congress in 1974. ERISA encouraged institutional investors to diversify portfolios to include timberlands. Even without a mill for their holdings, TIMOs manage for returns on timberland assets by buying and selling within short timeframes. TIMOs are chartered to hold a given property no more than 10 and 15 years, a period of time less than the rotation age of 25–35 years for Pinus taeda (Fox et al. 2007). Given this discrepancy, TIMOs are generally reluctant invest in silvicultural practices. The rise of the TIMO ownership group, along with the offshore departure of U.S. timber companies, has translated into a declining interest in forest research at universities and USDA Forest Service (Fox et al. 2007).

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A Forest Within a Prairie

Table 3.3 Forests and other shared commons are often represented by the social-ecological system (SES) criteria (Ostrom et al. 2007) and this has been approximated for the Lost Pines area in central Texas System Criteria Present-day Resource RS1-Sector Forest RS2-Clarity of system boundaries High RS3-Size Finite RS8-Storage characteristics Yes RS9-Location Suburban Resource Units

RU1-Resource unit mobility RU4-Economic value RU5-Size RU7-Spatial and temporal distribution

Trees Recreation Few large islands Closed, dense

Governance Systems

GS1-Government organizations GS2-Non governmental organizations GS3 Network structure GS4-Property rights system GS7-Constitutional rules GS8-Monitoring

Many Many Yes Yes Yes Spatial imaging

Users

U1-Number of users U3-History of use U7-Mental models U8-Dependence on resource

Many High Profits from recreation, tourism, property values Low

Related Ecosystems

ECO1 ECO2 ECO3

River Agricultural, suburban, urban Climate change

Interactions

I1-Harvesting levels by users I2-Information sharing among users I3-Deliberation processes

Minimum High Yes

Outcomes

O1-Social performance measures O2-Ecological performance measures

High Resilience Watershed stability

for management of endangered species; this along with conservation easements and the Safe Harbor Treaty shape the forest landowner’s directives under federal and state law. Human impacts on the Lost Pines area are myriad and these can be made explicit as a socio-ecological system (SES) (Ostrom et al. 2007; Table 3.3). The Lost Pines area is a socially constructed system in which human and forest ecosystems are tightly and inextricably linked. Other descriptions which fit are anthropogenic biome or a human-dominated forest ecosystem (Table 3.3). Under any of these definitions, the Lost Pines area is now highly vulnerable to one more human impact: near-term effects of climate change. Resource managers and owners of the Lost Pines forest lands depend on planted forests more than naturally regenerated ones. What is planted into any given year

3.2

The Lost Pines Area

43

Box 3.2 Afghan Pine: A Christmas Tree Species for Central Texas Afghan pine (Pinus eldarica) was introduced into the United States in 1960 and since then it has served as drought-tolerant Christmas tree species for central Texas farmers (Sen et al. 1994) although it does attract the occasional pest and/or pathogen problems. This introduction has been unusually successful given that most exotic pines introduced into central Texas. One explanation for its successful is that it has a widespread, scattered range from Azerbaijan to Pakistan and it is also synanthropic, owing its wide range to human transport along ancient trade routes (Ledig 1992).

depends on who is selling pine seedlings. The Lost Pines seedlings were once available to landowners through the Texas Forest Service nursery at Indian Mound but this is not currently the case.7 Instead landowners seeking pine seedlings for East Texas are referred to three private companies and two public agencies. Forest tree seedlings may still be purchased from the state’s west Texas nursery. During a recent visit, one landowner mentioned that he prefers to dig up seedlings volunteers within the Lost Pines area and transplant these on his land. As an aside, exotic pine species are occasionally planted (Box 3.2) although few survive the harsh climate of central Texas.

3.2.4

The Lost Pines: A Disjunct Population

Despite its drought-prone location, this eastern U.S. species requires a moist habitat. Its common name is loblolly pine and it originates from the species’ distinctively wet habitat. A loblolly refers to a low-lying mudhole or wallow and this is where European settlers spotted it. Originally a coastal species, early settlers saw it on swamp margins but since then its range has rapidly expanded. True to its name, Pinus taeda requires moist, but not saturated soils, for its survival. Pinus taeda forests in Texas has been described as growing on “low ridges of sandy, loamy textured soils interrupts the compact clays and silts with intervening depressions which are more or less swampy in wet times and broad shallow streamways, presenting a large area of rich alluvial land” (Bray 1904). Even more pertinent is that observation that Pinus taeda thrives where there is human disturbance and this species is especially well-suited to same sites as croplands. This response comes from the particulars of its life cycle.

7

Source for the Indian Mound nursery and its suggested seedling providers was accessed here: http://texasforestservice.tamu.edu/main/article.aspx?id=9562 accessed on March 15, 2011.

44

3.2.5

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A Forest Within a Prairie

Pinus taeda as Keystone Species

In recent years, Pinus taeda has been managed as a keystone species and this refers to “a species whose impact on its community or ecosystem is large and disproportionately large relative to its abundance” (Power et al. 1996). If the keystone species dies, then its entire ecosystems can degrade to the point of no recovery. Resilience for a keystone species provides a protective buffer for complex forest ecosystems under the threat of climate change. Such species lend resilience, or the ability to recover from disturbance, to forest ecosystems because these ecosystems are in a constant state of flux whether responding to incremental or catastrophic change. Here Pinus taeda forests provide shade and mitigate high summer temperatures. The shade and moisture from its pine cover support animals, insects, microbial communities as well as all manner of plants. This role of keystone species in a lowdensity setting is compatible with recreational uses such as golf courses, hiking and kayaking.

3.2.6

Lost Pines: A Refugial Ecosystem

A good example of the conservation ethic at the Lost Pines is the assisted migration program for endangered species. The best case to date is the Houston toad8 which is no longer indigenous to Houston. The toad now populates the Lost Pines area. This ethic is illustrated by this excerpt from the Houston Chronicle which ran at the height of a prolonged drought in August 2009 “roughly 1,000 Houston toads, raised from eggs at the Houston Zoo’s nursery, are scheduled to be released in Bastrop County with the next good rain.” The Houston Zoo’s intervention, began in 1978, is a partnership with a non-governmental organization (NGO), Environmental Defense. Together this partnership has raised more than 500,000 toads, an activity which serves as a strong indicator of the local conservation momentum. Adding more to the Lost Pines research momentum is the Stengl Biological Station, a part of the University of Texas campus which adjoins Buescher State Park near Smithville Texas (Fig. 3.5). This group conducts primary research on all facets of the Lost Pines ecosystem.

8 First amphibian granted protection under the U.S. Endangered Species Act, this toad was added to the IUCN’s Red List. Its census population is less than 2,500 and 95% of these individuals belong to a single subpopulation. Its largest population of over 2000 now lives in Bastrop.

3.3

Above Ground

3.3

45

Above Ground

The Lost Pines area is profoundly influenced by its weather and its climate,9 both of which are influenced by regional atmospheric systems and by proximity to the Gulf of Mexico.

3.3.1

Low Rainfall and Prolonged Drought

Precipitation at Bastrop reaches its maximum in spring and in fall. Its weather trends appears deceptively mild when one considers that its mean annual temperature for Bastrop fluctuates between 18.5°C and 22°C with a 60-year average of 20.1°C. In reality, these numbers are of little use when describing the area’s chronic shortage of rainfall, its history of prolonged drought and the unusual high frequency of tropical storms and hurricanes (Box 3.3). Central Texas has harsh weather and harsh climate for any forest tree species.10 Low rainfall is a chronic problem for Bastrop in summer where temperatures exceed 32°C more than 115 days a year (see review in Al-Rababah 2003). In the worst years, Central Texas has had scorching droughts that last for months, or even a year or longer. Precipitation records attest to its history of extremes: the annual mean rainfall was only 461 mm per year in the late 1950s yet this area had received as much as 1,428 mm of rainfall in 1940. These swings reflect erratic rainfall over Bastrop from storms off the Gulf of Mexico (Al-Rababah 2003).

3.3.2

Hurricanes, Tropical Storms and Ice

Lost Pines area is a wide, flat expanse which experiences extreme weather events from both southerly and northerly directions. From the southerly direction come tropical storms and hurricanes. The Gulf Coast (Table 3.1) is particularly prone to hurricane and tropical storms because maritime tropical air lofts from the Gulf of

9 A single weather event or a spell of unusual weather is not climate. It might be unprecedented yet still fall within normal range of climate variability. Consider that present-day Texas was once underwater as part of the Western Inland Sea roughly 100 million years ago as a consequence of climate and its change. Climate change has also been instrumental in forming the oil, gas and coal stores beneath the Lost Pines area and these originally came from long-dead marine life forms settling at the bottom of ancient seabeds or decaying swamp forests once composed of tree-like plants now extinct. 10 Climate change response is a dynamic process evident across Texas landscape even today. Land, sea, rivers and forests have all been affected by climate change over the course of millions, thousands and even in hundreds of years.

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Box 3.3 Describing Hurricanes and Their Classification Hurricanes, as tropical cyclones, severely impact structure and function of forests. In the Northern Hemisphere, these storms rotate about an eye, or center, in counter-clockwise direction. The storms slow as they make landfall but their wind shear brings extensive damage near the storm’s center and its accompanying rainfall can occur hundreds of kilometers from the storm’s center. All of this causes damage which is more explicitly described using the Saffir-Simpson system using a category scale of 1–5, shown here: Category 1 Hurricane: Wind speeds range from 119 to 153 kmh−1 (74–95 mph or 64–82 kt). No real damage to buildings but damage does occur to unanchored mobile homes and some poorly constructed signs. Windthrown trees, coastal flooding and minor pier damage are typical. Category 2 Hurricane: Wind speeds range from 154 to 177 kmh−1 (96–110 mph or 83–95 kt). Some damage occurs to roofs, doors and windows on buildings; far greater damage occurs to mobile homes. Flooding damages piers. Small craft in unprotected moorings may break from moorings. Some trees will blow over at Cat 2 winds (Oliver and Mayhead 1973; Vogel 1984). Category 3 Hurricane: Wind speeds range from 178–209 kmh−1 (111–130 mph or 96–113 kt). Some structural damage to small residences and utility buildings. Large trees are blown down, mobile homes and poorly built signs destroyed and flooding near the coast destroys smaller structures. Larger coastal structures are damaged by floating debris. Inland flooding tends to occur. Category 4 Hurricane: Wind speeds range from 211–250 kmh−1 (131–155 mph or 114–135 kt). More extensive curtainwall failures with some complete roof structure failure on small residences. Major erosion of beach areas. Inland flooding tends to occur. Category 5 Hurricane: Wind speeds 251 kmh−1 (156 mph and up or 135 + kt). Complete roof failure on many residences and industrial buildings. Some complete building failures with small utility buildings blown over or away. Flooding causes major damage to lower floors of all structures near the shoreline. Massive evacuation of residential areas may be required.

Mexico and its loop current into the south central US, acting as a genesis for storms (Box 3.3). These storms bring heavy rainfall farther inland to the Lost Pines area. The Texas Gulf Coast has among the highest hurricane return frequencies in the United States (Zeng et al. 2009; Fig. 3.6) and it has the largest exposed land area, roughly 9,600 km2 area in southern Texas, which is 55% of total of the high-risk U.S. coastal area (Zeng et al. 2009). At minimum, tropical storms and hurricanes from the Gulf bring much-needed precipitation into central Texas. Flooding and

3.4

a

Beneath the Surface

47

b

Tropical Storms

Hurricanes

N

N

return frequency 0.0350

return frequency 0.314 0.100

0.0100

0.010

0.0010 <0.0001

<0.001 0

500 1000km

0

500 1000km

Fig. 3.6 Return frequency for (a) tropical storms and (b) hurricanes is higher for the Gulf of Mexico coast than other parts of the United States. The Lost Pines area in Central Texas falls within the 1–10% return frequency for tropical storms and within the 0.1% return frequency range for hurricanes (Figure modified from Zeng et al. (2009). Copyright permission granted)

rainwater deluges are common during the peak of hurricane season in September but direct storm hits are rare for Bastrop County; its tropical storm frequency is estimated between 0.10 and 0.01 (Zeng et al. 2009) or one hurricane per decade or one hurricane per century, respectively. As shown in Fig. 3.6, its hurricane frequency is lower than 0.01 or less than one hurricane per century (Zeng et al. 2009). Another source of extreme weather comes from the northerly latitudes. These are ice storms and abrupt freezes known colloquially as blue northers.11 These northern cold fronts originate in the Canadian Arctic and they bring ice storms that bring transportation to a halt on highways and airport runways. More frequent than snowfall, ice storms pose an extreme weather event for central Texas.

3.4

Beneath the Surface

Many soil series dominate Bastrop County but the area near the largest pine island, near Bastrop State Park, is characterized by alfisol soils which belong to the AxtellTabor soil series12 (Soil Survey 1995). The Axtell series in particular accounts for

11

Bruce Zobel’s correspondence makes reference to the blue norther weather event in central Texas (Correspondence Box 3: 259.12): “Northers: cold weather fronts..They were brutal. Several times I went to work in short sleeves (75 F) to have it freezing (below 32 F) by the time I went home, the temperatures having dropped 30–40° in a few hours.” 12 1995 Soil survey of Bastrop County. USDA 1995 Soil Survey Geographic (SSURGO) Data Base: Data Use Information. Misc Pub. No. 1527, USDA Natural Resources Conservation Service, National Soil Survey Center, Wash DC. 83 p.

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70% of the pine forest soils in Bastrop State Park and the Axtell series is also typical of the pine-forested regions in east Texas and Louisiana (Chap. 5). The Bastrop area also has a myriad number of seeps and springs fed by an underground aquifer13 but these are notably absent from climatic variables which describe the rest of the Pinus taeda range (Fig. 2.1). Their locations have been documented in a comprehensive treatise on the springs and seeps of Texas (Brune 2002). Here he writes about a few of these springs and seeds within the town of Bastrop and its surrounds: “Fitzwilliam Springs (#3) is four kilometers southwest of Bastrop. Several springs at this location issue from terrace gravel on top of a bed of Wilcox sandstone five meters above the Colorado River bed on its left bank.” Another example: “Bastrop Springs (#2) is located at the end of Pine Street in the town of Bastrop flows from gravel at a rate of 0.31 liters per second (lps).” Here is a third example: “Burleson Springs (#1) is located four kilometers northwest of Bastrop. This springs flows from river terraces and gravels on the southwest side of the Colorado River.” These springs and seeps are thought to be vital to the local persistence of Pinus taeda in central Texas and they are plentiful in the Lost Pines area. The springs in the Lost Pines area do not have a constant flow rate from year to year (Brune 2002). To show this, Brune measured the same spring three times over the course of 18 years: (1) the spring flowed at a slow rate of 0.31 lps on March 2, 1953 which occurred during a drought, (2) on November 26, 1964 the spring’s flow rate was now 1.6 lps and (3) the third year was during a wet year was late summer, on September 27, 1975 and its flow rate was now 6.1 lps, a measure which was 20 times higher than its rate in 1953. Brune (2002) noted the groundwater moves so slowly that springs in sands may continue to flow for many months, or even years, without any rainfall in the recharge area (Chap. 5).

3.5 3.5.1

Regional Geography The Savanna-Prairie Matrix

First is the Southern Post Oak Savanna (33b), a type of oak savanna and next to this, running along a southwest-northeast axis is the Fayette Prairie, or Southern Blackland Prairie (32b), which is part of the Texas Blackland Prairies (32). The third and smallest eco-region, the San Antonio Prairie (33c) is northeast of the Lost Pines (Fig. 3.2).

13

Texas water law is significant; it maintains a rule of capture for groundwater as long as water source is not shown to be a subterranean river.

3.5

Regional Geography

49

Of these, the Southern Post Oak Savanna (33b) is a mix of post-oak (Quercus stellata) and other hardwoods, rangeland, pasture, and mesquite (Fig. 3.2). Most of its soil types are acidic but all have a dense clay pan (Griffith et al. 2004). Next is the Fayette Prairie (32b) which was once tallgrass prairie mixed with groves of oak and red cedar; now it is woodland, pasture and cropland (Fig. 3.2). A disjunct ecological region, this has fine-textured, clay soils covered with prairie vegetation. The fine-textured soils are vertisols, or waxy shrink-swell clays. These alkaline shrink-swell clays formed from Cretaceous shale, marl and chalk. Today pasture and cropland has now replaced prairie grasslands; much of this region has been converted to urban and industrial uses. This includes the vertisol-rich alluvium deposited by the Brazos River floodplain (32c). This deposition spreads into the Fayette Prairie near Washington and Grimes counties. Vegetation cover is often bottomland hardwoods: oaks, ash, pecan, elm, sweetgum, and eastern cottonwood (Fig. 3.2). The third eco-region is the San Antonio Prairie (33c) which refers to a narrow strip of grassland that runs 160 km on either side of the Old San Antonio Road (Fig. 3.2). This region has attracted dense settlement such that its present-day cover is a mix of woodland, pasture, rangeland, oil production, and some cropland. As shown in Fig. 3.2, the southwest eco-regions alternate in a parallel fashion between the Texas Blackland Prairies (32) and the East Central Texas Plains (33) which refers to oak savanna mentioned before. This parallel of prairie-savannaprairie-savanna runs sandwich-like runs from southwest to northeast direction at a slant. Lodged in the larger savanna filling of this odd sandwich is the Lost Pines region (33e) along with yet another type of prairie, the San Antonio Prairie (33c). The prairies and the oak savanna receive more attention when one traverses toward the northeast direction. None of these four surrounding ecological regions support pine forests. The Lost Pines area thus is a pine island surrounded by oak savanna and prairies. The pine forests and its savanna-prairie matrix are all ecological regions persist in spite of extreme environmental conditions.

3.5.2

The Gap Between Lost Pines and Piney Woods

The Lost Pines is separately by a distance of roughly 80–100 km from the rest of the Pinus taeda range in the east Texas Piney Woods but this distance is not fixed; it has shifted even over the course of recorded history. This gap is a portion of the savannaprairie matrix (see Chaps. 4 and 5). Note that the gap is not uniform but rather is highly heterogeneous. It is composed of alternating stripes of sediment-rich alkaline soil types which run along peninsular transects in the northeast-southwest direction. The gap is heterogeneous in other ways too. Its topography is dotted with soil mottling (Thornbury 1965, p. 67) or topographic undulations which range from 10 to 30 m in diameter; these mottles mark pockets of fine sand and silty loam.

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Soil mottling accounts in part for isolated pine or pine stand which dot the landscape of otherwise “pine-free” nature of the gap. Such soils can be suitable enough for pine seedlings if a good year brings enough rainfall but these wild seedlings often die within a decade or more before reaching reproductive age. Wild Pinus taeda seedlings, together with planted Pinus elliottii and Pinus taeda dot the landscape of the gap as windbreaks, highway vegetation, and homestead planting. Among these will be the rare Pinus eldarica (Box 3.3). Few pines thrive within the gap.

3.6

Beyond the Matrix

Beyond the savanna-prairie matrix are other ecological regions which are as follows: the Edwards Plateau (30), Southern Texas Plains (31), Texas Blackland Prairies (32), East Central Texas Plains (33), Western Gulf Coastal Plain (34) and South Central Plains (35) (Griffith et al. 2004). Although farther away than the savannaprairie surrounds, all bear on the long-term response of the Lost Pines to climate change.

3.6.1

Austin and the Edwards Plateau

In this direction is Austin, the state capital of Texas, named for founder Stephen F. Austin. It is home to the flagship campus of the University of Texas System. Austin is an expanding metroplex which is also the nearest urban neighbor to the Lost Pines at a distance of 57 km (Table 3.1). Austin has nearly 1.6 million people living at a density of 1,008 people per km2. This metroplex adjoins the fragile ecological region known as the Edwards Plateau (30). The Edwards Plateau (Fig. 3.2) refers to a vast limestone plateau characterized by rolling hills, a few mountains and a sparse network of streams. Savannas are dotted with juniper (Juniperus ashei), mesquite or oak groves (Quercus buckleyi, Q. fusiformis). The Edwards Plateau is also divided into four smaller Edwards Plateau eco-regions (Fig. 3.2). One of these four is the Semi-Arid Edwards Plateau (30d) which bears on the Lost Pines area and the Colorado River. Marking the transition zone between the oak savannas and the arid west Texas desert, this eco-region lies just the west of the 100th meridian, better known as the east-west continental divide for the United States. Here too are the headwaters of the Colorado River of Texas. The present-day annual rainfall averages only 510 mm so the Semi-Arid Edwards Plateau (30d) has a climate is too dry to support closed-canopy forests (Fig. 3.2). Once predominantly

3.6

Beyond the Matrix

51

grasslands, recent land-use practices have brought desertification and its presentday vegetation cover is shrubby (Griffith et al. 2004).

3.6.2

San Antonio, Southern Texas Plains, Mexico Border

In this direction is San Antonio, one of America’s fast-growing cities (Table 3.1). San Antonio is the seventh largest U.S. city with a population of 2.0 million people living at a density of 1,084 km2. Its rapid rise in human population has coincided with the loss of the city’s its forest canopy. San Antonio’s urban expansion is so recent so its present dimensions are sized for automobiles, not humans on foot. San Antonio, a city already notable for its sparse shade,14 lost 22% of its forested canopy to urban development between 1985 and 2002. The loss registers as 63,000 ha of full forest canopy, down from 81,000 ha. Miller (2007) describes how San Antonio’s sparse forest tree canopy lost out in this time period to “a concreted panoply of big box stores, strip malls, fly ramps and freeways”. Alliteratively stated, this concreted panoply now stands in place of forest canopy. Along the same southwest transect, past San Antonio, is the dry country of the Southern Texas Plains (31) which is also divided into four smaller eco-regions (Fig. 3.2). Farther on, the city of Laredo marks the U.S. border crossing into Mexico (Table 3.1). Adjacent is this border are Mexico’s states of Nuevo Leon and Coahuila and these figure prominently in the past sovereign ownership of the Lost Pines area. Neighboring Mexico is the world’s center of Pinus diversity where more than half of the world’s 110+ pine species are indigenous (Mirov 1967; Perry 1991; Farjon and Styles 1997).

3.6.3

Coastal Plain and the Western Gulf Coast Basin

Through here, the Colorado River of Texas meanders from Bastrop, to Smithville, LaGrange, Columbus and a host of other small towns before reaching the mouth of Matagorda Bay and the hurricane-prone Gulf of Mexico (Fig. 3.2). The Colorado River is one of nine river basins which form the Western Gulf Coast Basin (Thornbury 1965, pp. 62–65). From west to east, these rivers are the Rio Grande, Nueces, Guadalupe, Lavaca, Colorado, Brazos, Trinity, Neches, and

14 Land cover definitions are as follows: forests have 60% or more canopy cover, woodlands cover less than 60% but more than 25% and grasslands have 25% or less.

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Sabine. Note that the size of the alluvial valley and deltaic plain for each river is proportionate to the size of its flow. The Brazos River is one of the larger rivers which flows directly into the Gulf of Mexico so it is characterized by a broad valley and equally broad deltaic plains (Chap. 5). Lesser rivers such as the Colorado River have narrow valleys and commonly empty into estuaries or lagoons at the back of barrier islands (Thornbury 1965).

3.6.4

East to Houston, Piney Woods, and Louisiana Border

This direction passes near Houston, another one of America’s fastest growing cities (Table 3.1). Houston, the fourth largest metroplex in the U.S., has a population of 5.7 million people which live at a density of 1,300 people per km2. Along its western edge, the Piney Woods here are bounded by blackland prairies, an area where pine forests do not grow (Fig. 3.2). Pinus taeda dominates presentday forests but some of its other Australes relatives are also here. The same eastward transect goes through the East Texas Piney Woods (Fig. 3.2) intersecting towns by the names of Nacogdoches, Angelina, Fastrill and Cherokee Mound. These too figure in the history of the Lost Pines, east Texas timber industry and the Texas Forest Service (Chap. 4). The Piney Woods extends into other states, covering a total of 141,000 km2 in southern Arkansas, western Louisiana and southeastern Oklahoma.

3.6.5

North-Northeast to College Station, Dallas and Oklahoma Border

The due-north transect passes through Temple, Waco and on through the DallasFort Worth metroplex (Table 3.1; Fig. 3.2). The Red River separates Texas from Oklahoma. Another transect passes through College Station, the location of the flagship campus of the Texas A&M University System, once known as Texas Agricultural & Mechanical College. The Texas Forest Service is part of the TAMU System and it headquarters are located here, as part of this land grant campus. The director of the Texas Forest Service also serves as the state forester of Texas. Here too is the state’s climatology office and its chief scientist.

3.7

Closing

The Lost Pines area is a human-dominated forest ecosystem highly vulnerable to future climate change. The Lost Pines community attaches cultural, historical, geological, scientific and even commercial significance to its pine forests. Accordingly, its owners and stakeholders have formed a working network on behalf of good conservation policy

3.7 Closing

53

Fig. 3.7 A forest landowner in the Lost Pines area has bulldozed the name “LUECKE” into the landscape; this was accessed in Bastrop County Texas using Google Earth® software on May 5, 2010

and practice. This is necessary because Texas15 has sparse forest cover and so its other resources in the Lost Pines area must be factored into its forest management plans whether aquifers, lignitic coal deposits, natural gas or oil. No longer that trio of forest, river and prairie, this landscape has become a complex mosaic of competing land uses typical of the twenty-first century U.S. South temperate forest (Fig. 3.7). Pinus taeda serves as the keystone species of the Lost Pines ecosystem and thus its continued resilience can be managed to benefit of all concerned. Much is at stake here. How the Lost Pines and all other oxygen-producing forests at all latitudes survive – and adapt – to the plethora of effects which are already accompanying rising levels of carbon dioxide and its equivalents. Holding on to forest cover at the Lost Pines was a local concern to be outsourced and forgotten. Conservation practice (Fig. 3.8) uses a time scale of 25–50 years and this could be improved using longer timelines. Historical and geological records are brought into this present-day profile in the next chapters.

15

For an excellent and carefully annotated resource, the reader is referred the Handbook of Texas Online.

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Elevated greenhouse gases, soot, ozone and volatile organic compounds

Prairies Savanna Crops Pasture

Pine forest River basin

Crops Pasture Prairies Savanna

Urban Suburban

Aquifer & fossil fuel deposits

Fig. 3.8 Concept Map for the Lost Pines area as a human-dominated forest biome. The trio of landmarks: the pine forests, the river and the prairies are now part of a more complex mosaic which has pastoral and croplands, suburban housing and urban industrial, commercial and residential uses. Beneath its surface are more natural resources in the form of Wilcox-Carrizo aquifer and fossil fuel

References and Related Readings Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. in the late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Aten L (1983) Indians of the Upper Texas Coast. Academic publisher, New York Blum M, Valastro S (1994) Late Quaternary sedimentation, lower Colorado River, Gulf Coastal Plain. Geol Soc Am Bull 106:1002–1016 Bousman CB (1998) Paleoenvironmental changes in central Texas: the Palynological evidence. Plains Anthropol 43(164):201–219 Bray W (1904) Forest resources of Texas. USDA Bureau of Forestry, Government Printing Office, Washington D.C, 71 p Brown A (1955) The lost pines. Gulf Coast Lumberman Academic Publishers 42(August):28, 30 Brune G (2002) Springs of Texas. Texas A&M University Press, College Station Buckley SB (1866) A preliminary report of the geological and agricultural survey of Texas. Office of the State Gazette, Austin Burley J (2004) The restoration of research. For Ecol Manag 201:83–89 Davies C (1981) Policy implications of the banking of lignite leasing, Bastrop County Texas 1954– 1979. Econ Geogr 57:238–256 Dutton A et al (2003) Groundwater availability model for the central part of the Carrizo-Wilcox aquifer in Texas. Final Report for the Texas Water Development Board. The University of Texas at Austin, Bureau of Economic Geology, 295 p Dutton A, Nicot J et al (2006) Hydrodynamic convergence of hydropressured and geopressured zones, Central Texas, Gulf of Mexico Basin, USA. Hydrogeol J 14:859–867 Dynesius M, Jansson R (2000) Evolutionary consequences in species geographical distributions driven by Milankovitch climatic oscillations. Proc Natl Acad Sci USA 97:9115–9120 Engelhardt ESD (2009) Republic of Barbecue: stories beyond the brisket. University of Texas Press, Austin Farjon A, Styles B (1997) Pinus (Pinaceae) Flora Neotropica. The New York Botanical Garden, New York

References and Related Readings

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Fehrenbach T (2000) Lone star: a history of Texas and the Texans. De Capo Press, New York Fox T, Jokela E et al (2007) The development of pine plantations silviculture in the southern United States. J For 105(October/November):337–347 Griffith GE, Bryce SA, Omernik JM, Comstock JA, Rogers AC, Harrison B, Hatch SL, Bezanson D (2004) Ecoregions of Texas. U.S. Geological Survey, Reston Jackson S, Williams J (2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu Rev Earth Planet Sci 32:495–537 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: Milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Kennedy W (1841) The rise, progress and prospects of the Republic of Texas. Molyneux Craftsmen Inc, Fort Worth (1925) Kesselus K (1999) History of Bastrop county, Texas before statehood. Jenkins Publishing, Austin Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 Little E (1971) Atlas of United States trees, vol 1, Conifers and important hardwoods. USDA Forest Service, Washington, DC Ludlum D (1963) Early American hurricanes1492–1870. American Meterological Society, Boston Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Maxwell R, Martin J (1970) A short history of forest conservation in Texas 1880–1940. Stephen F. Austin State University School of Forestry, Nacogdoches, 61 McDougall A (2003) Did Native Americans influence the northward migration of plants during the Holocene? J Biogeogr 30:633–647 Meltzer D (1999) Human responses to Middle Holocene (Altithermal) climate of the North American Great Plains. Quat Res 52:404–416 Meltzer D, Holliday V (2010) Would North American Paleoindians have noticed Younger Dryas climate change? J World Prehist 33:1–41 Miller C (2007) Ground work: conservation in American culture. Forest History Society, Durham Mirov N (1967) The genus Pinus. Ronald Press, New York Moberg A et al (2005) Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 443:613–617 Nicot J-P (2008) Evaluation of large-scale CO2 storage on fresh-water sections of aquifers: an example from the Texas Gulf Coast Basin. Int J Greenh Gas Control 2:582–593 Oliver H, Mayhead G (1973) Wind measurements in a pine forest during a destructive gale. Forestry 47:185–194 Ostrom E, Janssen M et al (2007) Going beyond panaceas. Proc Natl Acad Sci USA 104:15176–15178 Parvin B (1982, January) Are the loblollies really lost? San Antonio Monthly 25–26, 56 Perry J (1991) The pines of Mexico and Central America. Timber Press, Portland Oregon Peterson M et al (2004) A tale of two species: habitat conservation plans as bounded conflict. J Wildlife Manag 68:743–761 Power M et al (1996) Challenges in the quest for keystones. BioScience 46:609–620 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Russell D et al (2009) A warm thermal enclave in the Late Pleistocene of the South-eastern United States. Biol Rev Camb Philos Soc 84:173–202 Sargent C (1884) Report on the forests of North America. U.S. Department of Interior, Census Office, Washington D.C Sen S, Magallanescedeno M et al (1994) In-vitro micropropagation of Afghan pine. Can J For Res 24:1248–1252 Sorensen CJ, Mandel RD et al (1976) Changes in bioclimate inferred from paleosols and paleohydrologic evidence in east-central Texas. J Biogeogr 3:141–149 Sylvia D, Galloway W (2006) Morphology and stratigraphy of the late Quaternary lower Brazos valley: implication for paleo-climate, discharge and sediment delivery. Sediment Geol 190:159–171

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Thomas C et al (2002) Extinction risk from climate change. Nature 427:145–148 Thornbury W (1965) Regional geomorphology of the United States. Wiley, New York Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Vogel S (1984) Drag and flexibility in sessile organisms. Am Zool 24:37–44 Waters M et al (2011) The Buttermilk Creek complex and the origins of Clovis at the Debra L. Friedkin site. Science 331:1599–1603 Zachos L, Garvie C et al (2005) Definitive locations of Paleocene and Eocene marine fossil localities, Colorado River, Bastrop County Texas. Tex J Sci 57:317–328 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from 1851 to 2000. Proc Natl Acad Sci USA 106:7888–7892 Zobel B, Talbert J (1984) Applied tree improvement. Wiley, New York, 505 p

Chapter 4

What Historical Records Add

4.1

Introduction

The Lost Pines narrative has a rich history which challenges implicit assumptions about species composition, present-day range and even its vulnerability to extreme weather events. More than a natural history, the Lost Pines area is also part of a history in scientific achievement. Here we find fresh and unexpected insights which are pertinent to how the Lost Pines area will fare under human-induced climate change over the coming century. The oldest records of human activity in North America are here in central Texas. Here roved the Clovis people, various paleo-americans and then Native Americans. Europeans arrived over three centuries ago and then came early Spanish explorers, settlers and, later, scientists. The unusual sight of a pine forest rising out of a prairie matrix inspired many a journal entry so there is no doubt that this forested area is a naturally occurring phenomenon. From these same records comes sparse evidence that this Pinus taeda forest might have been part of a larger pine archipelago scattered across a wider arc. Some evidence suggests that these scattered pine islands included Pinus taeda and Pinus echinata too. Although naturally occurring, this forest was completely cutover in 1880. The present-day Lost Pines area is populated by a secondary forest composed of both naturally regenerated and planted areas. Some of the pines in Bastrop State Park were seedlings when the first forest survey was completed here in 1880 and it is here that the scientific precision of tree improvement got its start.

4.2

Early Human Activity in Texas

Discovered in Buttermilk Creek, these artifacts date to 13,200 and 15,500 year BP and they belonged to humans who were here even before the Clovis people (Waters et al. 2011). For thousands of years, human foragers in Texas and other parts of the

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_4, © Springer Science+Business Media B.V. 2012

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Southern Great Plains faced radical climate-induced oscillations and this is evident from artifacts (i.e. Meltzer 1999; Meltzer and Holliday 2010). Native American tribes were living here long before 1600 (Aten 1983). These tribes practiced little to no agriculture1 or other clearing activities; instead they relied on fishing, hunting and gathering (Aten 1983). That pine forests2 were here is not certain. Open conifer woodland and prairies were prevalent at lower latitudes during glaciation, not dense forests (Toomey et al. 1993; Williams et al. 2001). Several Native American tribes had migrated to central Texas after 1600: among them were the Tonkawa, Lipan Apache and Comanche (Box 4.1). These tribes were drawn here by the prairies where bison and large game grazed, by the pine forest which provided shelter, fuelwood and small game and by the river which gave vantage for surveillance. Native Americans did not have a well-worn trading path through the pine forest which was later used by the Spanish for reaching their military outpost.

4.3

European Exploration

Spanish exploration of Texas (Table 4.1) began as early as the sixteenth century3 but it was not until 1691 that Spanish explorer Domingo Terán de los Ríos, a career military professional4 and his fellow traveler Father Manzanet, a Catholic priest, wrote about sighting pine islands along the Colorado River.5 Together these two, with their expedition members, travelled in search of a direct route between the east Texas missions and San Antonio de Bexar (Kesselus 1999; Brune 2002). They reached the banks of the Colorado River on June 26, 1691. This river, Terán de los Rios noted, flows all of the way to the Gulf of Mexico to Matagorda, forming a basin of tributaries (Table 4.1). Seeing the bluffs of the Colorado River, the explorer also mentions a pine forest to the east of the river and

1

In another part of the Pinus taeda range, the Eastern Woodland tribes along the Atlantic Seaboard developed agricultural systems (McDougall 2003) before the arrival of the Spanish. 2 Vegetation here and other parts of the present-day Pinus taeda range were part of a mixed parkland biome which has no modern analog (Russell et al. 2009; Williams et al. 2001). 3 An earlier but less exact account was noted when De Leon and Mazanet traveled in 1690 from Monclova, Coahuila Mexico. These explorers noted that the western edge of the eastern Texas pine forest was Houston County and that some “tall trees” grew in Fayette County which might have been the Lost Pines. 4 Domingo Teran de los Rios later became governor of Coahuila and of Tejas (Texas) in 1691. Spain withdrew its Catholic missions from east Texas in 1693 and subsequent governors did not reinstate Texas until 1716. 5 The lagoon described by Father Mazanet here is now known as Shipp’s Lake, an old ox-bow lake in a former channel of the river southeast of Smithville, now mostly filled with flood sediments.

4.3

European Exploration

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Table 4.1 The Lost Pines area has belonged to five countries or sovereign states in less than five decades Dates Sovereignty Events 1519 Spain Claim to Mexico 1821 Mexico Treaty of Cordoba 1936 Republic of Texas Texas Independence 1945 United States Admitted as 28th State 1861 Confederacy Secession 1870 United States Re-admitted to United States

prairies to the west. This same trio of landmarks: river, pines and prairies, would guide travelers through the Lost Pines area for centuries after them. The expedition are likely to have started down Colorado River at the Travis County line, paddled past what is now Bastrop then to Smithville where they crossed the river there (Brune 2002). Here Brune (2002) mentions that Father Massanet wrote: “…We crossed the San Marcos [Colorado] River in safety,… and stopped on the other side of the river in a level spot where there was good pasture for the cattle and horses. Near the river were many springs of cold water, But that of the river itself was very hot and muddy”. Here was a hidden landmark of the Lost Pines area: an abundance of natural springs and seeps.

4.3.1

New Spain

Terán de los Rios could not expand the Spanish missions westward. Among his obstacles were Native American attacks. Attempts to enslave or settle these tribes were unsuccessful and added to this problem was the failure to settle central Texas with imported Spanish settlers (Fehrenbach 2000). Many were lured from the Canary Islands, among other places, but these immigrants became cattle ranchers, not town builders. Settling interior of central Texas was a persistent problem for de los Rios and those New Spain’s governors who came after him.

4.3.2

Spain’s Military Road

By September 1795, more than a century after Teran de los Rios wrote about the Lost Pines, the Spaniards built a military road directly through the forest. This was part of the King’s Road, also known as the Camino Real or the Old Spanish Road (OSR). Native American attacks here forced Spain to post as many military troops in central Texas as it had in all of Peru (Fehrenbach 2000). This military outpost was one of many in this area. Here, small detachments of no more than 30 Spanish soldiers at any one time were stationed here in the Lost Pines area.

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Concerns Over the Louisiana Purchase

United States became a neighbor to New Spain and its possessions when it purchased Louisiana. This act created anxiety within New Spain’s governmental ranks and this became apparent with the capture of Zebulon Pike, well-known American explorer. Pike was captured by the Spanish on Feb 26, 1807 while searching for river headwaters. His captors took him to Santa Fe, New Mexico then to Chihuahua Mexico. Finally, he was released after American protest but this also meant that he had to be escorted across New Spain to the Louisiana border as a prisoner. On June 16, 1807, Pike passed through Bastrop and here he notes in his diary: “16th June, Tuesday – Marched early, and at eight o’clock arrived at the Red river [sic, as this was the Colorado]…in the afternoon passed over hilly stony land; occasionally saw pine timber.” Zebulon Pike briefly glimpsed the Lost Pines forest in 1807, thus providing one of the few records of the Lost Pines pine forest prior to 1880. To venture into the Lost Pines required courage. The forest was murky and unsafe, as mentioned here by this June 1828 account by naturalist Jean Louis Berlandier. He wrote: “The travelers who perambulate those regions scarcely ever come to rest in those pine forests (pinales), particularly if a storm is threatening… These large trees – whose roots are extremely short, not very widespread, and not very secure even in the most compact of terrain- fall with the slightest puff when they have chanced to grow in sandy soil. The large quantity of trunks lying everywhere, encumbering even the route, attest to how feebly they were attached to the soil...”.6 Berlandier’s view was shared by many settlers coming to Texas in search of land. The Lost Pines area was remote, it was primitive and it was too deeply inside Indiandominated territory. A few other accounts add more to what little is known about the Lost Pines forest at this time. William Kennedy (1841) wrote “Just above LaGrange, on the eastern side of the Colorado [River], about four miles from its bank, is a grove of excellent yellow pine, from two to four miles in width, which extends above the town of Bastrop”. His records confirm present-day range of the Lost Pines forest but then Kennedy then mentions pines as being present in Gonzales and Victoria countries, two locations which are outside of the present range of the Lost Pines (Fig. 4.1). Similarly, Ferdinand von Roemer, in his explorer’s account of Texas between 1845 and 1847, also mentioned the presence of pine forests on the barren hilltops between Bastrop and LaGrange (Fayette), Bastrop and Caldwell (Burleson), Bastrop (Bastrop) and also near Austin (Travis County) (Table 4.2). His notes add more locations outside the present-day range of the Lost Pines forest.

6 This concern of falling trees within the Lost Pines persists even now. In a hearing before the Texas Court of Appeals, Third District, Austin (Case No. 03-97-00609-CV) the appellant Theresa Felts sued Bluebonnet Electric Cooperative for damages caused by a falling tree. The accident occurred on September 9, 1993 when Felts and her two sons were traveling on County Road 139 off Highway 21 outside the town of Bastrop, Texas.

4.3

European Exploration

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Fig. 4.1 Early explorers prior to 1850 noted pine forests in many counties where they no longer grow. As mapped, this forms a pine archipelago which is larger than the three or four counties where the Lost Pines forests now grow

Table 4.2 Putative pine islands are located in Bastrop and Fayette; pine islands have been reported in nearby counties over the past three centuries County locations References Bastrop, Fayette Teran de los Rios (1691) Travis, Burleson, Bastrop Roemer (1845–1847) Gonzales, Victoria, Fayette, Kennedy (1825) Bastrop, Fayette Bray (1904) Caldwell, Brazos, Fayette, Lee, Freestone Brown (1955) Brazos, Fayette, Colorado, Bastrop Maxell and Martin (1970)

4.3.4

Moses Austin Petitions for a Land Grant

The age of settlement in central Texas began when the westward expansion of the land-hungry United States accelerated a banking crisis. The banking crisis, known as the Panic of 1819, brought financial ruin to many Americans because banks had over-collateralized land holdings. Many bankrupt individuals moved west to start again and among them was Moses Austin. Moses Austin, a resident of St. Louis, Missouri, had a vision of settling Texas with American settlers who would serve as loyal Spanish citizens. With this in mind, Moses rode on horseback from Missouri to San Antonio (known as San Antonio de

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Bexar or simply as Bexar) to present his request to Governor Martinez. Upon his arrival in Bexar, he was abruptly informed that foreigners, especially Americans, would not be welcome as settlers in Texas. Moses Austin left the governor’s office dejected and weary, now prepared for his long ride back to Missouri. But there in the courtyard, Moses Austin encountered an old friend who offered to intercede on his behalf (Kesselus 1999). Here was the self-styled Baron de Bastrop (Box 4.2) whom Moses had met in Kentucky more than 25 years before (Kesselus 1999). For a week, the Baron discussed the proposal with Spanish authorities and at the end of the week he brought good news to the waiting Moses Austin. On January 17, 1821 Governor Martinez approved the settlement grant7 and with this, Moses Austin took the good news back to Missouri. Riding through the winter on horseback, his health deteriorated and soon after his arrival in Missouri, Moses Austin died. On his deathbed, Moses Austin had asked his son Stephen to continue on the settlement. He, Stephen, agreed and so he too prepared for the same long journey to Bexar on horseback in order to secure permission for settlement. There Stephen met with the Baron de Bastrop and Governor Martinez and he secured permission. History did not favor this simple act (Kesselus 1999).

4.4 4.4.1

Settlement New Spain and Mexico

Before Stephen F. Austin could get the settlement started, Mexico declared its independence from New Spain in 1821. Present-day Texas and its Lost Pines area now belonged to the newly formed government of Mexico (Table 4.1). Stephen F. Austin was again obliged to obtain permission for a settlement again. He rode to Mexico City this time where he stayed for 14 months, from March 1822 to May 1823, in order to gain approval from Mexico’s new Congress. In time, Stephen F. Austin was finally awarded lands for settlement and he became an empresario.8 As such, he was well-rewarded for his trouble. This was an immense land grant: its boundaries went 26 miles (43 km) inland from Gulf of

7

Provincial Deputy Ambrosio María de Aldasoro to Texas Governor Antonio Martínez, Monterrey, January 17, 1821. Autograph letter signed, CN 10457, Béxar Archives at the University of Texas archives. “This official letter to Texas Governor Martínez relays permission for a group of “Missourians,” including Moses Austin, to settle in Texas.” 8 An empresario contracted with the Mexico government to settle a certain number of immigrants on land designed to him, allocated lands among the settlers and took responsibility for the characters of the settlers and provided order. In exchange, he would charge fees and received large tracts of land for himself.

4.4

Settlement

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Box 4.1 Three Major Native Americans Tribes Of these, the Tonkawa tribe was best known. Members of the Tonkawan linguistic group9 this tribe assimilated small groups of independent tribes whose numbers had dwindled and this had already taken place in southcentral Texas by the early eighteenth century. Another tribe was the Comanches; they represented a branch of northern Shoshones and their language belongs to the linguistic family Uto-Aztecan.10 By the early 1700’s some members of Comanche moved into central Texas where some occupied the area between the Colorado and Brazos Rivers. Fiction between Comanches and settlers was prolonged and intense so the Treaty of Medicine Lodge set up a reservation for Comanches, Kiowas and Kiowas Apaches in 1874 in the southwest Indian Territory between the Washita and Red Rivers. The third tribe, the Lipan Apache, have Southern Athabascan origins.11 By 1600’s two bands of this tribe had migrated to Texas, New Mexico and northern Mexican states and here they stayed, mostly in the Southern Great Plains region.

Mexico to the Old Spanish Road. The outermost boundary of this land grant was the Lost Pines area along with half of Bastrop County. The outermost boundary was so far from the Gulf that it was viewed as the least desirable area within the land grant and so it was the last to be claimed by Austin’s settlers (Kesselus 1999). Austin claimed a richly timbered land grant for himself which is now partly in Bastrop State Park. Early records suggest that there was already a town here named Mina, located at the junction of the Old Spanish Road and the Colorado River, while others state that this was not the case (Kesselus 1999). The town of Bastrop received its name from the Baron de Bastrop (Box 4.2) in honor of his assistance to Moses and Stephen Austin.

9

Tonkawa Indians of Oklahoma, Tonkawa Oklahoma. http://www.tonkawatribe.com/ Accessed on February 20, 2011. 10 Lipan Museum & Cultural Center is now located in Corpus Christi Texas. They migrated here in the 1600’s then split into two: one group stayed near the upper reaches of the Brazos River and the other near the upper reaches of the Colorado River. URL: http://www.lipanapache.org/ Accessed on February 20, 2011. 11 The Comanche Nation Complex is located in Lawton Oklahoma. URL: http://www.comanchenation.com/ Accessed on February 20, 2011.

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Box 4.2 Baron De Bastrop This was the assumed name of a New World émigré whose birth name was Philip Hendrick Nering Bogel. Born in Dutch Guyana, he had been raised in the Netherlands. A tax collector, Bogel fled to the New World when called to the courts of justice to answer on an embezzlement charge. There he assumed the name of Baron de Bastrop even though he had no claim to royalty but the name stuck as he thrived in his new position with the Spanish administrators of Mexico. The Baron leveraged his political position to Austin’s advantage, persuading Spanish officials to allow Moses Austin to establish a colony of 300 families in Texas. Later, he interceded on behalf of Stephen Austin who brought the first colonists. Now appointed land commissioner of the new colony, Bastrop formally issued titles for 272 of the 300 grants. His statesmanship grew until he was elected as Texas’ representative12 to the Legislature of Coahuila and Texas, created under the Mexico Federal Constitution in 1824.

Austin, as empresario, was charged with the political and legal responsibilities to his colony and so he chose his grantees with great care. Each of Austin’s carefully chosen settler families were allowed to purchase a full league of land, roughly 1,792 ha. That they become responsible settlers was a vital concern to Stephen Austin because he has held responsible for the conduct of all settlers and many would-be settlers were attracted to Texas at this time because Mexico and the United States had no reciprocal agreements for collecting debt or returning fugitives from the law. There was no shortage of those who wanted to settle in the interior of Texas. By late 1827, settlers had already claimed the best lands along the Brazos and Colorado Rivers. Settlers overcame their reluctance to move inland towards the Lost Pines area, arriving in great numbers between the years of 1830 and 1832. The settlement faced mounting problems. The Native American attacks continued and the newly independent Mexico was uneasy about its new immigrants and thus it unsettled in its decisions on how to best rule Texas from the state of Coahuila. In turn, Austin and his settlers grew increasingly uneasy with Mexico’s rapid administrative changes and its many new laws governing immigration. Finally, Austin’s colony decided to challenge Mexico’s claim and this successful change shifted the political boundaries of the Lost Pines for a third time.

12 It follows that the Bastron de Bastrop, as a representative to the legislature of the newly created state of Coahuila and Texas from 1824 until his death in 1827, was unwavering in introducing legislation favorable to the cause of immigration. That Anglo-American settlers were immigrants to Mexico is a point often overlooked by those unfamiliar with Texas history.

4.4

Settlement

4.4.2

65

The Republic of Texas

By 1835, the newly formed Republic of Texas included the Lost Pines area as part of its sovereign boundaries (Table 4.1). By 1837, slaves and cotton had been introduced to Bastrop County13 in 1837. The towns and its surrounds14 were growing rapidly, drawing on only source of timber anywhere nearby: the Lost Pines forest. Logging this isolated tract of timber was hastened with the arrival of the steam mill. Among many such operations was the Bastrop Steam Mill Company was started in 1838. Higgins Mill, operated by Jacob Higgins and Abner Cook, followed suit in 1840 (Easton 1947). Settlers saw the timber as a resource, not a barrier to farm and pasture clearing. The cotton economy and other agricultural endeavors of these settlers usually flourished with the rains from hurricanes and tropical storms which moved inland from the Gulf of Mexico. Rarely did hurricanes travel up the Colorado River but the notable exception was the Matagorda Hurricane of 1854 (Ludlum 1963, pp. 162–163). On September 17–18 of that year, hurricane-force winds struck Matagorda, destroying nearly all of its buildings before moving up the Colorado River to the town of Columbus. From there, the large, slow-moving storm passed just east of Columbus. Rainfall in such excess did little good for farmers; entire crops of cotton were blown down to such an extent that not even a single bale could be harvested after this storm (Ludlum 1963). Rainfall could be spare or torrential here in central Texas but travelers and settlers alike found another more reliable water source: natural springs and seeps. Burleson Springs, located 4 km northwest of Bastrop, flowed from river terraces and gravels on the southwest side of the Colorado River and this attracted many. The stagecoach which traveled between Bastrop and Austin stopped and later this was the site of a water-powered grist mill by the 1840s (Brune 2002).

4.4.3

The United States

The Republic of Texas now joined the United States as the 48th state (Table 4.1) but this decision was short-lived. By 1860, abolition was a contentious topic for Bastrop County but also a contradictory one: Bastrop County’s population had 2,248 slaves among its population of 7,006. Those who could vote voted against withdrawing from the United States, i.e. secession, yet also rallied for the Confederate cause. This was no easy decision.

13 Bastrop County was one of the 23 original counties of the Republic of Texas but it has since been redivided. Its original boundaries now include that all or even parts of 15 present-day Texas counties. In 1874 Lee County was the last county created and this was the last boundary change. From then on, Bastrop County has been its present size. 14 The town of Bastrop was vulnerable to Comanche raids between 1836 and 1841 and this led to various military assistance as well as a volunteer army.

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Frederick Law Olmsted, better known as the architect who designed New York’s Central Park, was among those who took an interest in this paradoxical situation at Bastrop. A staunch abolitionist, Olmstead rode horseback to central Texas to gather firsthand accounts of Texas slavery. He funded this long trip with a writing commission from a New York newspaper which was to later become the New York Times. Mindful of the landscape, Olmsted wrote about sighting of a pine forest near Bastrop: “We struck the Colorado at Bastrop – a village of considerable size and promise, Situated on the left river bank, and at the edge an isolated patch of pine timber, from which nearly all of the pine lumber used in Western Texas is taken.” From Olmstead’s notes it is clear that some of the Lost Pines was still standing prior to the Civil War in 1857 but that it was dwindling fast. Ultimately the county’s stance on slavery would swing its sovereignty once again. In 1861, the state of Texas joined the Confederate States of America (Table 4.1) and seceded from the United States, now known as the Union.

4.4.4

The Confederate States of America

As a member of the Confederacy, Texas was a vigorous supporter of the rebel cause. It supplied many troops throughout the Civil War to such an extent that it engaged in battle 1 month after Lee’s surrender at Appomattox in 1865. This led to the United States government to declare that Texas as a state of revolt. This declaration continued until 1866 at which time President Andrew Jackson announced peace between Texas and the United States. Texas then started the long process of re-admission back into the United States. Along with other U.S. South states, Texas remained under military rule for years while Congress voted for one state at a time. Texas was the last state to re-admitted. Its wait lasted 4 years, until 1870. Despite these difficult times, many were curious about the wealth of natural resources that Texas held. Professor Samuel Botsford Buckley was hired in 1866 to conduct the first geological and agricultural survey of Texas. He carefully noted the Lost Pines area, providing the most thorough account of this forest prior to its complete cutover by 1880: “Although a large part of these pines have already been cut down, still enough remains to supply building material to many of the countries in the western and central part of the State” (Buckley 1866). Buckley did not anticipate the scope of national demand for pine timber. Even more relevant, Buckley continues, “There are two species of pine in Bastrop, viz.: Pinus mitis and Pinus taeda of the botanists, both of which make very good building material. The former is the most abundant.”15 Note that Pinus mitis is a synonym for Pinus echinata: Sargent (1884) lists Pinus mitis Michaux as any

15

The closest Pinus echinata specimen in any herbarium collection at the University of Texas or Botanical Research Institute of Texas (BRIT) is from Brazos County TX, collected by R.G. Reeves on Nov 11 1942 #1940 C at a location 4 km from Millican TX, as shown in the UT Herbarium collection.

4.4

Settlement

Table 4.3 Human population of Bastrop County (Sources: Online Handbook of Texas and the 2010 Census)

67 Year 1860 1870 1900 1910 1940 1960 1970 1980 1990 2000 2010

Human population 7,006 11,000 26,845 25,344 21,640 16,925 17,297 24,726 38,263 57,716 74,171

number of short-needled pine species so this can be assumed to be Pinus echinata because none of the other pines grouped under Pinus mitis are indigenous to Texas, Oklahoma or the western part of the Pinus taeda range. Even so, Buckley’s account is the most descriptive of the Lost Pines forest prior to its complete cutover by 1880.

4.4.5

Re-Admitted to the United States

Bastrop had now lost its slave-dependent cotton economy yet more people continue to move into the town. By 1870, Bastrop’s population had risen sharply to 11,000 people (Table 4.3). One explanation is the expansion of the railroad16 which required timber for its tracks, for its workers’ housing and for the countless towns which sprang up along its route. More than local demand, the railroad brought a transportation system which opened Bastrop and the rest of Texas to meeting national demands for its natural resources wealth. The American Midwest was now the nation’s new frontier and timber supplies there were scarce. Timber had to be imported and Texas ranked high among its proximal suppliers. The Atlantic Seaboard forests were already depleted and the vast pine forests of the Lake States were nearly depleted (Williams 1989) thus settlement of the Plains states opened new national markets for what had been a local supply of Texas timber. By 1875, railroads crisscrossed the east Texas timber belt and into the Bastrop area, loading what was thought to be an endless supply of timber. The railroads

16 The Houston and Texas Central Railroad organized on April 3, 1862 and it included a line through Bastrop County. Later the Colorado and Post Oak Island Railway connected the town of Bastrop in 1871. By 1887 the Missouri, Kansas and Texas Railway Company (MKT) was connected Bastrop and Taylor. The arrival of the railroad contributed significantly to Bastrop’s wealth before the end of the nineteenth century.

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opened up national markets for lumber and together they both placed undue pressure on Texas pine forests (Maxwell and Martin 1970). Influential Texas leaders would soon express public concerns over wanton logging waste and the looming prospects of a timber shortage and this would lead to managed forests. With the railroads came two time periods of peak prosperity for Bastrop: from 1880 to 1895 and again from 1905 to 1920. Until now, the town’s growth had been stymied because it lacked a good transportation system. Transportation on the Colorado River, a slow-moving shallow river, was not possible due to long-standing log jams and this had meant that the town’s trade had been restricted to local markers until now. Merchants within the town’s commercial district built stores and houses in the styles of Greek Revival and Victorian architecture, using their newfound profits from timber, coal and bricks. A timber famine did materialize but the Lost Pines forests were completely cutover.

4.4.6

Sargent’s Visit

Charles Sargent,17 director of the Arnold Arboretum at Harvard University conducted the first forest inventory for the United States. His survey included a map of Texas forest inventory but here, in place of the Lost Pines, was an area that he marked as being completely cutover. Three vital descriptions come from this visit: (1) the gap which separated the Lost Pines area from the rest of the eastward pine forests, (2) the Lost Pines forest, now cutover and (3) how southeastern Oklahoma, as another western edge of the Pinus taeda, once had scattered pine islands too. Sargent (1884, p. 542) noted his approach from the Brazos River. “The timber growth immediately west of the Brazos is stunted and scanty; large areas of grass land intervene between the scrubby woods until all at once ligneous disappears, and the seemingly boundless prairie, in gently undulating swells, expands before the view on all sides. Near the center of Milam county a belt of open post-oak woods from 20 to 25 miles in width is entered. It extends from Belton, in Bell county, southward to the upper confines of Gonzales county. Post oaks stand here from 20 to 30 feet apart, with black-jacks and blue-jacks between them, the trees being all of small size. The soil of these oak hills is of poor quality, sandy, gravelly, and more or less broken, arid, and devoid of vegetable mold.” Sargent continues on with this description of the edaphic gap where pine forests do not grow…“Taken as a whole, the country west of the Brazos River, except for the basin of the Colorado, is poorly timbered region.”

17 Charles Sprague Sargent was encouraged by U.S. Secretary of the Interior Carl Schurz who wanted a detailed analysis for the 1880 census on the nation’s available timber supplies. With this encouragement, the Smithsonian Institution hired Sargent to write what would become the Report which appeared in 1884.

4.5

Managed Forests

69

Next he wrote about the cutover Lost Pines area: “Toward the southern limit of this belt, near Bastrop; a tract of loblolly pine is found covering near four townships, or about 90,000 acres. During the last twelve years all of the useful timber on this isolated tract has been cut down. A second growth of pine, however, has sprung up, and is now growing vigorously under the fostering care of the owners of the land, and promises in a short time to afford a new supply of timber.” Sargent’s report of a complete cutover fits with the pine seedlings dotting the banks of Colorado River in the 1887 lithograph of Bastrop and its surroundings entitled “A Birds Eye View Painting” by Augustus Koch.18 Even though its timber was cutover, Bastrop’s prosperity grew with the discovery of its lignitic coal deposits at the end of the nineteenth century. Sargent (1884, p. 543) described similar pine islands in southeastern Oklahoma but he did not specify the species: “The forests of the Indian territory are confined to its eastern portion”…“:The extreme northeastern part of the territory contains numerous extensive open prairies, south of which a heavy body of forest composed of hardwoods, mixed on the high ridges with the short-leaved pine, extends southward into Texas, with a maximum width in the Choctaw nation of 60 miles.” He continues, making no distinction between pine species: “In the Cherokee nation, six considerable bodies of pine, varying from 10 to 30 miles in length and 2 to 4 miles in width occur on Spavina Creek, Illinois River, Salina River, Spring Creek, Bowman’s Fork, tributaries of the Grand River. A large body of pine occurs also 25 miles west of Reams, a station upon the Missouri, Kansas and Texas railroad. Smaller bodies of pine are also found, too, east of Reams and at Stringtown, where lumber is manufactured and shipped southward by rail into northern Texas.” Sargent notes that Arkansas, to the east, has a contrasting pattern, that its pine forests are continuous especially in Scott and Polk Counties and along the Cossatot River. Pine islands seem to be typical at the edge of the species range.

4.5 4.5.1

Managed Forests Wasteful Logging Practices

Dismayed by the wasteful logging practices in East Texas, W. Goodrich Jones, a Temple banker, launched a campaign at the end of the nineteenth century for a Texas reforestation program. His efforts were heard. By 1898, the Chief of the U.S. Bureau of Forestry visited Jones in Temple and asked if he, Jones, would survey the

18

The lithograph now belongs to the Bastrop Historical Museum.

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east Texas forests. Jones responded with a report that noted that 40% of every log was wasted and that more efficient use of the felled tree was possible. He urged state and federal governments to reign in timber cutting and to start a systematic tree planting program (Martin and Maxwell 1970). Conservation with an allowable cut and reforestation was his vision but this was not a professional forester speaking, this was a banker. In 1899 he successfully campaigned for Texas Arbor day which was to be February 22. His campaign had produced bill which was signed into law by Governor Sul Ross. To quote Jones “This great Pine belt acts now as a cooling agency and storage reservoir.” This idea of the forest as intricately tie to rainfall harked back to George Perkins Marsh and his persuasive treatise Man and Nature. Like Marsh, Goodrich Jones wrote an anecdote-filled oratory appeal. He decried the wholesale waste of the timber barons, drawing the demise of the buffalo as his analogy. Jones predicted that something far worse than timber famine would come and that this would be more akin to a change in rainfall patterns. The result would be a desert, not a forest, for Texas. By this time, Gifford Pinchot was rising on the national scene and he did much to encourage W. Goodrich Jones in his promotion of forest conservation in Texas. The two met in person when Theodore Roosevelt appointed Pinchot as the Chief of the U.S. Forest Service in 1905 then convened the White House Conference of Governors on forestry matters in 1908. There Roosevelt gave his famous speech warning of timber famine and, there, Goodrich Jones represented Texas, standing in for Governor Thomas Mitchell Campbell. Goodrich Jones ramped up his campaign to promoting tree planting. Early in November 1914, he called a meeting at the Carnegie Library in Temple, Texas. There he and the other attendees organized the Texas Forestry Association (TFA). TFA had the singular objective of creating a state forestry department and with it, a comprehensive forest conservation program. The group also drew up a model bill for the Texas legislature and they designated Goodrich Jones as the person to get the bill introduced and passed. And he did. Next Goodrich Jones proved an able leader for employing the first state forester. And here too he was successful. The bill for a state forester was signed into law by March 1915. Goodrich Jones personally ran the want ad in the June 1915 issue of Gulf Coast Lumberman for a state forester which advertised “Salary $3000 annually.” This was the start of institutionalizing managed forestry in Texas; a long succession of state foresters would follow.

4.5.2

East Texas Piney Woods

In 1904, east Texas was dominated by Pinus palustris or longleaf pine and its close relatives Pinus echinata and Pinus taeda were secondary species (Fig. 4.2). Pinus palustris was the predominant species on dry hills while Pinus taeda was a fringe

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Managed Forests

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Fig. 4.2 At the end of the nineteenth century, the original Pinus taeda range in east Texas occupied only a small 12-county area due east of Houston which covered roughly 18,000 km2. Copyright permission granted)

species which grew along the wetter lowlands or along the edge of swamps. Naturally occurring Pinus taeda in the Piney Woods had a narrow range just above hurricaneprone Galveston. Pinus taeda occupied a small 12-county area19 above Galveston which covered an area roughly 18,000 km2 (Maxwell and Martin 1970). Note that their map shows fewer than 12 counties (Maxwell and Martin 1970). Three particular

19

Those 12 counties were San Jacinto, Walker, Montgomery, Harris, Jefferson, Orange, Hardin, Grimes, Newton, Jasper, Liberty and Chambers (Maxwell and Martin 1970).

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points should be emphasized from Bray’s accounts of east Texas pine forests and its surrounds in 1904 and there were as follows: 1. East Texas range of Pinus taeda soils match those of the Lost Pines area; these contrast sharply with the alkaline vertisols typical of the flat wide Brazos River Basin. This vast expanse, described by Sargent, is the gap which separates the Colorado River Basin from east Texas Piney Woods. 2. The distance between the Lost Pines area and the east Texas Piney Woods is not fixed. In earlier maps, only Brazos County (which is intersected by the Brazos River) actually separates the two pine forests. 3. The early twentieth century range for Pinus taeda in Fig. 4.2 is right above the hurricane-prone Galveston area. Bray notes too, that a single storm the Galveston Hurricane of 1900, destroyed thousands of hectares of mature Pinus taeda stands. Emphatic as he writes that the hurricane has “uprooted nearly to the last tree”. Overlogging was not the only problem behind the worries about timber famine.

4.5.3

Early Reforestation

Goodrich Jones now went to work with Texas Forestry Association as his ally to lobby the state legislature for a forestry department at Texas A&M College. In a most unusual arrangement, the department would be headed by the state forester who would teach at the university. The state forester’s teaching requirement proved short-lived but this hiring arrangement did have a lasting consequence: the Texas Forest Service would remain located within a land grant university system. This placement elevated the degree of science literacy among its hires and ultimately made for a progressive research agenda Texas Forests.

4.5.4

Founding of the Texas Forest Service

The legislative momentum continued. Texas now sets land aside for its state forests. Eventually, the newly founded Texas Forest Service hires leaders who promote reforestation. Two nurseries produced one million seedlings annually (Maxwell and Martin 1970). The legacy of Goodrich Jones continues; managed forests and reforestation became the norm for Texas. Every day was now Arbor Day. Jones did not overlook Lost Pines area as evidenced by this speech to the McLennan County Historical Association in 1930: “In 1821, Stephen F. Austin and the early Texas settlers benefited by a strange freak of the great East TX pine forests. Oases of pine were found in Bastrop, Fayette and Colorado Counties…” These historical events in Texas had parallels elsewhere in the U.S. South but they tended to come later. Between the Civil War and World War II, large amounts of agricultural land in the U.S. South abandoned due to soil erosion, low crop prices

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and pest problems such as boll weevil infestations.20 By 1909, the U.S. South was producing more than 46% of all timber cut in the United States and these temperate pine forests competed poorly as agricultural land use prevailed.

4.5.5

Tree Improvement

Many events transpired to bring about this change within the Texas Forest Service. Professor Scott S. Pauley from the Harvard Forest in Petersham MA was an influential voice who convinced the Texas Forest Service make forest genetics integral to reforestation. Genetic quality mattered as much as quantity of forests and this called for a practical tree improvement program which would be built on forest genetics principles for the benefit of reforestation. It was not enough to plant forest trees; one had to match the right seed source to the site. Others in the U.S. South had come to the same realization and this term, tree improvement, was defined in its broadest sense to the application of Darwin’s evolutionary principles within a given silvicultural system (Zobel and Talbert 1984). This registered as a radical shift away from dysgenic logging and haphazard seed collecting. Initially government-led, nascent tree improvement programs matured into stable, long-term public-private partnerships which were later administered at U.S. universities. In a letter to a prospective job candidate, Bruce Zobel, on April 5, 1951, Texas Forest Service director Dr. A.D. Folweiler21 wrote “For a good many months, as a matter of fact for several years, I have been of the opinion that work in forest tree improvement should be done in the South. It has enormous possibilities”… Pauley’s ideas about forest genetics gained momentum elsewhere. On June 20, 1951, the Committee on Southern Forest Tree Improvement held its first meeting but Bruce Zobel, newly awarded a doctorate from the University of California at Berkeley, did not attend. He was on his way to Texas.

4.5.6

A Role for the Lost Pines

Bruce Zobel accepted the job at the Texas Forest Service at a starting salary of $4400 per annum on May 22, 1951. It took some time to get started but the job was to develop and supply a well-adapted seed source for industrial-scale reforestation.

20

The rise of a new United States Forest Service and the creation of a National Forest System also brought a sea change in attitudes towards forests and timber supplies. Reforestation programs were well underway by the 1950’s. But what species to plant and what the best source for seed and seedlings from that species? These were troublesome questions to be addressed on a vast geographic scale: more than 13 million acres needed reforestation, from Virginia to Texas (Wakeley 1954; Fox 2007). 21 Dr. A.D. Folweiler (1902–1986) was inducted into Texas Forestry Hall of Fame in Sept 2005.

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Table 4.4 Examples of selections made in the Lost Pines area GID Place Seedling year Selection age FA1-1 Fayette 1898 56 FA1-2 Fayette 1905 51 FA2-2 Fayette 1895 59 FA2F24-18 Fayette – BA1-1 Bastrop 1921 33 BA1-2 Bastrop 1907 45 BA3R13-41 Robertson – BA5-2 Bastrop 1885 69 BA3LH-1 Lavaca – BA5-1 Bastrop 1884 70 1-50 Bastrop 1909 46 BA2L20-21 Lavaca – BA3-1 Bastrop – D Bastrop 1914 41 E Bastrop 1907 48

Selection year 1954 1956 1954 1954 1952 1954 1954 1955

1955 1955

Original location and ages for a few of the Lost Pines accessions grafted by the Texas Forest Service elsewhere for the purpose of reforestation. These trees grew in naturally regenerated stands which would have been seedlings around the time of heavy logging in the Lost Pines in 1880. Many of these selections continue to provide experimental value for evolutionary studies

And this he did (Table 4.4). His early reports show a growing list of financial supporters. Among them are the Angelina County Lumber Company, Southern Pine Lumber Company, Temple Lumber Company and the Washington D.C.-based Charles Lathrop Pack Foundation. Bruce Zobel’s top priority was to take advantage of naturally drought resistant pines and this took him to the disjunct pine forests known as the Lost Pines. The Lost Pines area supplied the first selections for tree improvement. Bruce Zobel set up a coding system for his drought-hardy Lost Pines selections (see Al-Rababah 2003 for annotation and photographs of these selections). Several came from within the original perimeter of the Bastrop State Park; his meticulous descriptions read as follows: “Pt1 – Loblolly in Bastrop State Park, just north of water tank, Tree BAZ-1.” After selecting each tree, he would clip branch tips then graft these onto seedling stock located back at Fastrill. The Texas Forest Service had already established the archive at Fastrill, near their Indian Mound nursery and this is where Zobel grafted or planted Pinus taeda, Pinus echinata, Pinus palustris and Pinus elliottii. Grafting proved to be a quick yet effective method of multiplying and archive each selection made at the Bastrop State Park and its surrounds (Table 4.3). This fledgling effort in the Lost Pines area also provided a firsthand experience of the harsh central Texas climate. A Californian influenced by evolutionary biologist G. Ledyard Stebbins, Zobel was awed by the harsh climatic conditions of central Texas. He wrote “Vegetation in the Texas area had to be some of the toughest in the world and was adapted to these wild fluctuations in weather”. This tree improvement program at the Lost Pines grew until it became something which became known worldwide for its innovative contributions in theory and practice.

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This can be seen in Bruce Zobel’s report titled “Development of Drought-Hardy Strains of Loblolly Pine”. In it he writes: “Several approaches to this problem are possible. The first is to take advantage of nay naturally drought resistant strains already growing under severe conditions. Such conditions are found in the so-called “Lost Pine [sic]” area…” Here too in these archives is a map of the Arthur Temple Sr. Research Area. Texas Forest Service in Fastrill Texas with 72 acres. Lost Pines archive was established in 1956. Other pines, i.e. longleaf, shortleaf, slash, loblolly populations were planted there in 1953 (Table 4.4). Zobel, his colleagues, and his students worked tirelessly on making the Lost Pines selections into a reliable source of seedlings in Texas.

4.5.7

Pine Islands in Central Texas

Others at the Texas Forest Service working in the Lost Pines area captured public interest. Fire fighters used planes to spot fires and these pilots remarked at seeing a stepping stone pattern of pine islands between Bastrop and the East Texas Piney Woods (Brown 1955). In their accounts, they too recite counties which do not have pine stands now (Table 4.2). In this same interview, Bruce Zobel adds another unusual finding: he mentions seeing “one absolutely Pinus echinata” in the Lost Pines pine area (Brown 1955).

4.5.8

Making Selections

The same exact selections from the Lost Pines have now been archived elsewhere, outside the Lost Pines, Bastrop and central Texas. Bruce Zobel, Hans van Buijtenen and others at the Texas Forest Service selected trees then they clipped branch tips from each selection. These branch tips were grafted onto seedling stock at archives established in east Texas (Table 4.4). There, the grafted branch tip would grow into a full-sized tree crown and it would produce seeds and seedlings. New forests would be regenerated from these Lost Pines seedlings for nearly five decades. The move to reforest Texas was greater than the start of the Texas Forest Service, its ties to a major research university and more than the establishment of state parks. Managing forests for Texas became institutionalized at the federal level too. These new national forests included Angelina, Davy Crockett, Sabine, and San Houston National Forests. In 1980, these federal holdings came to a total of 665,034 acres in a land area of 1,730,939 acres. National parks were also established including the Big Thicket Nature Preserve (1974), Big Bend National Park (1944) and Guadalupe National Park (1972). Forest management in Texas continued to grow within the century after Charles Sargent and Goodrich Jones saw wasteful logging of the state’s original forests.

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Box 4.3 Walking Through the History of the Lost Pines Area Glimpses of this chapter’s events are still evident if the reader knows where to look. A short walk from the town of Bastrop to the Bastrop State Park begins on the banks of the Colorado River where Teran de los Rios and Father Manzanet paddled past. The early settlement is now marked by Fisherman’s Park on the river banks and behind that, the town of Bastrop is situated on a terrace above the river (Fig. 4.3). Once in the town, nearly nothing matches the lithograph “A Bird’s Eye of Bastrop” by Augustus Koch22 in 1887. As one of the few Texas towns founded under Mexico’s rule, Bastrop’s square layout is all that still adheres to the Spanish rules which laid out the town’s exact geometrical design and how each area would be used. Next is the town’s commercial district. Bastrop still has a historic district complete with Victorian, Greek Revival and early twentieth century houses, many of which are on the National Register. This attests to the wealth acquired after the railroad opened up national markets for its lumber, cotton, and cattle. Lignitic coal was discovered later nineteenth century and by 1920, Bastrop had mines and mining companies too. That Bastrop values its pine forest is still apparent in the business district where tree names now label banks, realtors, gift shops, restaurants and hotels: Loblolly Gift Shop, the Lost Pines Bank and the Lost Pines Conference Center number among them. Films, too, take names from this area. The film “Tree of Life” with Brad Pitt was made here. Continuing out of the town along Loop Road 150, one must cross Highway 21. This is actually the Old Spanish Road or the King’s Road built for Spanish military. At the town’s edge is the rodeo but the pine stands can be seen in the distance. The west entrance of Bastrop State Park comes into view, its telltale stone archway connecting to a perimeter of low stone walls. Within these walls is the original land grant of the Little Colony and parcels that Stephen F. Austin selected as his own. Here too, the Texas Forest Service pioneered an early tree improvement program which matured into a scientific discipline to meet the demand for a drought-hardy seed source. A couple of the original selections, only seedlings at the time that Augustus Koch saw them, can still be seen here in Bastrop State Park.

22 The lithograph has been annotated by the Amos Carter Museum with drop-and-drag-features which aid comparison. Accessed April 8, 2011. http://birdseyeviews.org/

4.6 Closing

77

Fig. 4.3 This 1929 topographic map of the town of Bastrop and its surrounds shows its uneven topography and it is this topography which brings springs and seeps to the surface in the eastern part of the county where the Pinus taeda forests are (Source: University of Texas Library. Copyright permission granted)

4.6

Closing

This is a chronicle starts with Spanish explorers, moves to Mexico’s independence and Anglo-American settlement and then to the institutionalization of managed forests. These pine forests have migrated within the time frame of recorded history but its political boundaries shifted faster. The political boundaries of the Lost Pines area changed more than five times within five decades (Table 4.1). The following findings bear on our search for how the Lost Pines forest might fare: (a) A pine archipelago. Some evidence points to a larger pine island archipelago in central Texas prior to 1850 and this coincides with the Little Ice Age (1300–1850 A.D.).23 Indeed, early accounts of Spanish explorers who first sighted the Lost Pines in 1691 would have seen this landscape part way through the Little Ice Age (Moberg et al. 2005). Over the next two centuries, reports from

23

Years before present (BP) starts backwards from 1950 A.D. so 1850 A.D. would be 100 years BP.

78

(b)

(c)

(d)

(e)

4 What Historical Records Add

explorers also coincide with Little Ice Age (1300–1850 AD) and this is consistent with other historical accounts (Rockman 2010) which was a long period of unusually a cool, moist climate conducive to pine expansion. With ebbing of the Little Ice Age around 1850, one might expect that pine islands would have expanded in this cool, moist climate. Much of these smaller pine islands might have disappeared with the warmer climate but they might have also been cleared for agriculture. One species or two? When Charles Sargent arrived, the area had already been completely cutover (Sargent 1884, p. 542). Historical accounts prior to Sargent’s visit can narrow the time period further. A small fraction of the Lost Pines was still evident in 1857 when Frederick Law Olmsted came through. Nine years later, in 1866, S.B. Buckley also mentions that “an abundance remained” so this hints that the Lost Pines cutover was not complete until after 1866. The remarkable part of the story is that the Lost Pines forest did recover, either in part or in full, without the benefit of forestry or foresters. This nextgrowth of the Lost Pines forest later provided some of the base population which was later selected as the foundation of a nascent tree breeding program. Historical records before and after the complete cutover challenges the assumption that the Lost Pines population is composed of a single species. Some evidence from nineteenth and twentieth century accounts suggests that both Pinus echinata and Pinus taeda are present the Lost Pines area but others dispute it. The evidence against this is also circumstantial. The USDA-Forest Service range maps for Pinus taeda (Little 1971, 1973) show a single species grows in the Lost Pines area. So little is really known about the Lost Pines forest prior to its cutover before 1880. Pine stands are transient across the drought-prone landscape. Seedlings and young saplings might thrive during a few years with higher than average rainfall but they are vulnerable to drought without supplemental water from the river or proximity to an aquifer-fed spring. If they die before they reach reproductive onset then the stands disappear. If so, pines are simply transient in this droughtprone western part of the range. Migrating range limits. Today, approximate distance between the Lost Pines and its nearest east Texas Pinus taeda population now is roughly 80 km to Colorado County but this gap has been larger and smaller over the course of history. Scientific achievements in forestry. The Lost Pines area was no exception when it came to the innovations swept up in the wave of U.S. science and technology programs which rose to prominence after World War II. This part of Texas might be better known for its NASA space program, for computational pioneering, oil drilling and biomedical innovations. These efforts were fuelled by its rich reservoirs of gas oil and coal. Texas parlayed its extractive wealth into a knowledge base which still sustains its twenty-first century economy despite its environmental disasters ranging from hurricanes and oil spills. Less recognized is its pioneering efforts in reforestation which started in the Lost Pines area. Even now, the best available science and technology is still restoring the drought-prone western edge of the Pinus taeda range.

References and Related Readings

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References and Related Readings Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. in the late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Aten L (1983) Indians of the Upper Texas Coast. Academic Press, New York Blum M, Valastro S (1994) Late quaternary sedimentation, lower Colorado River, Gulf Coastal Plain. Geol Soc Am Bull 106:1002–1016 Bousman CB (1998) Paleoenvironmental changes in central Texas: the Palynological evidence. Plains Anthropol 43(164):201–219 Bray W (1904) Forest resources of Texas. USDA Bureau of Forestry, Government Printing Office, Washington DC, 71 Brown A (1955) The lost pines. Gulf Coast Lumberman 42(August):28, 30 Brune G (2002) Springs of Texas. Texas A&M University Press, College Station Buckley SB (1866) A preliminary report of the geological and agricultural survey of Texas. Office of the State Gazette, Austin Burley J (2004) The restoration of research. For Ecol Manag 201:83–89 Davies C (1981) Policy implications of the banking of lignite leasing, Bastrop County Texas 1954– 1979. Econ Geogr 57:238–256 Dutton A, Nicot J et al (2006) Hydrodynamic convergence of hydropressured and geopressured zones, Central Texas, Gulf of Mexico Basin, USA. Hydrogeol J 14:859–867 Dynesius M, Jansson R (2000) Evolutionary consequences in species geographical distributions driven by Milankovitch climatic oscillations. Proc Natl Acad Sci USA 97:9115–9120 Farjon A, Styles B (1997) Pinus (Pinaceae) Flora Neotropica. The New York Botanical Garden, New York Fehrenbach T (2000) Lone star: a history of Texas and the Texans. De Capo Press, Cambridge Fox T, Jokela E et al (2007) The development of pine plantations silviculture in the southern United States. J For 105(7):337–347, October/November Griffith GE, Bryce SA, Omernik JM, Comstock JA, Rogers AC, Harrison B, Hatch SL, Bezanson D (2004) Ecoregions of Texas. U.S. Geological Survey, Reston Jackson S, Williams J (2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu Rev Earth Planet Sci 32:495–537 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: Milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Kennedy W (1841) The rise, progress and prospects of the Republic of Texas. Molyneux Craftsmen Inc, Fort Worth (1925) Kesselus K (1999) History of Bastrop County, Texas before statehood. Jenkins Publishing, Austin Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 Little E (1971) Atlas of United States trees, vol 1, Conifers and important hardwoods. USDA Forest Service, Washington, DC Ludlum D (1963) Early American Hurricanes 1492–1870. American Meterological Society, Boston Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Maxwell R, Martin J (1970) A short history of forest conservation in Texas 1880–1940. Stephen F. Austin State University School of Forestry, Nacogdoches, 61 McDougall A (2003) Did Native Americans influence the northward migration of plants during the Holocene? J Biogeogr 30:633–647 Meltzer D (1999) Human responses to Middle Holocene (Altithermal) climate of the North American Great Plains. Quat Res 52:404–416 Meltzer D, Holliday V (2010) Would North American Paleoindians have noticed Younger Dryas climate change? J World Prehist 33:1–41 Miller C (2007) Ground work: conservation in American Culture. Forest History Society, Durham

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Mirov N (1967) The genus Pinus. Ronald Press, New York Moberg A et al (2005) Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 443:613–617 Nicot J-P (2008) Evaluation of large-scale CO2 storage on fresh-water sections of aquifers: an example from the Texas Gulf Coast Basin. Int J Greenh Gas Control 2:582–593 Oliver H, Mayhead G (1973) Wind measurements in a pine forest during a destructive gale. Forestry 47:185–194 Ostrom E, Janssen M et al (2007) Going beyond panaceas. Proc Natl Acad Sci USA 104:15176–15178 Parvin B (1982, January) Are the loblollies really lost? San Antonio Monthly, pp. 25–26, 56 Perry J (1991) The pines of Mexico and Central America. Timber Press, Portland Power M et al (1996) Challenges in the quest for keystones. BioScience 46:609–620 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Russell D et al (2009) A warm thermal enclave in the Late Pleistocene of the South-eastern United States. Biol Rev Camb Philos Soc 84:173–202 Sargent C (1884) Report on the forests of North America. U.S. Department of Interior, Census Office, Washington, DC Sen S, Magallanescedeno M et al (1994) In-vitro micropropagation of Afghan pine. Can J For Res 24:1248–1252 Sorensen CJ, Mandel RD et al (1976) Changes in bioclimate inferred from paleosols and paleohydrologic evidence in east-central Texas. J Biogeogr 3:141–149 Sylvia D, Galloway W (2006) Morphology and stratigraphy of the late Quaternary lower Brazos valley: Implications for paleo-climate, discharge and sediment delivery. Sediment Geol 190:159–171 Thomas C et al (2002) Extinction risk from climate change. Nature 427:145–148 Thornbury W (1965) Regional geomorphology of the United States. Wiley, New York Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Chang 7:299–320 Vogel S (1984) Drag and flexibility in sessile organisms. Am Zool 24:37–44 Waters M et al (2011) The Buttermilk Creek complex and the origins of Clovis at the Debra L. Friedkin site. Science 331:1599–1603 Zachos L, Garvie C et al (2005) Definitive locations of Paleocene and Eocene marine fossil localities, Colorado River, Bastrop County Texas. Tex J Sci 57:317–328 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from 1851 to 2000. Proc Natl Acad Sci USA 106:7888–7892 Zobel B, Talbert J (1984) Applied tree improvement. Wiley, New York, 505 p

Chapter 5

What Geological Records Add

5.1

Introduction

The Lost Pines area is re-shaped by its geological records. Some records suggest where forest trees can and cannot thrive while others provide natural resource wealth. Geological records provide another kind of history too, one which is written on deeper time scales. These records attest to the constancy of past climate change. Past climate change is not measured by present-day climate or even weather records; it is measured as the geological events in relation to water. The chapter’s main message unfolds as the tale of two rivers and the story of its springs. The tale of two rivers starts with this clue from Hocker (1956) in Chap. 2: “it is possible that the species occurs naturally beyond the calculated climatic limits as a result of modification of local climate by edaphic and/or topographic conditions.” What is the modification that defines the gap between the Lost Pines forest and the rest of its species range?

5.2

The Tale of Two Rivers

With the arrival of the Quaternary’s Pleistocene epoch, the earth’s climate grew cooler and this led to a series of major ice ages (Mannion 2006). The Arctic ice cap became the source of the polar ice sheets, or glaciers, which advanced and receded across North America’s higher latitudes. As these glaciers spread south, they compressed temperature zones towards the equator. The first clue about the physical barriers for the Lost Pines forests comes from reconstructing Quaternary climate change events for two rivers: the Colorado River of Texas and its neighbor, the Brazos River. These river basins delineate suitable

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_3, © Springer Science+Business Media B.V. 2012

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Box 5.1 Is Lost Pines as a Pleistocene Relic? The widely accepted view of the Lost Pines’ geological past is summarized nicely by journalist Bob Parvin who described these events in an article for the San Antonio Monthly in January 1982 (pp. 25–26, p. 56): “It happened this way: throughout recent geological time, shallow seas laid down great swatches of muck and sand to form present gulf uplands. Polar caps expanded with periodic ice ages and the seas which contributed greatly to their volume would draw down. In such periods, world climate tended to be more under the influence of the great ice packs. Down in Texas, shivering but far from the glaciers, precipitation and runoff from ice flows were rearranging things. Great braided rivers floled to the gulf, carrying down the grit and rocks of highlands to use both as carving and land-building tools. What the previous seas had piled up, the river either whittled down, buried or swept away… Consequently, the ancestral Brazos drainage spread far out of its present-day banks and sluiced away most of the soil relationships between Central and east Texas pinelands. Only on an upraised chunk of sandy hills above the Colorado River did the loblollies hold out to memorialize the great curve that the gulf pine forests once made into Texas…[Eastern Bastrop County solid contains] vital combinations of sands and clays that play a part of loblolly survival…Usually, fine, shallowbedded sands resting above old marine clays of sandstone grow the healthiest trees. Under these conditions, ground water is “perched” or temporarily suspended nearer the surface so that short, thirsty roots of the loblolly pines can drink…Relict species, or remnant trees like these, were forced to adapt to unusual circumstances. In the case of Bastrop’s Pinus taeda, it took the development of thicker bark, fleshier needles, and fewer stomate [sic] openings to compensate for a drier and warmer climate. The southwesternmost piney woods get only two-thirds the rainfall averaged at the more easterly forests in Texas.”

edaphic conditions as well as barriers for present-day pine forests.1 As such, depositional fill along these two of the nine Texas rivers is only a small part of its geomorphology of the Texas Gulf Coastal Plain (Thornbury 1965, pp. 62–69) but it is the part which pertinent to explaining the edaphic gap. Parvin’s account (Box 5.1) points to past climate change and its geological consequence. This suggests that the edaphic gap between the Lost Pines population and the rest of its range can be reconstructed using geological events for the Colorado River and Brazos River basins.

1

The area between these two rivers is a geological anomaly. Of this, Thornbury (1965, p. 62) wrote: “The outcrop belt of Lower Cretaceous rocks between Brazos and Colorado Rivers is placed in the Central Texas Section of the Great Plains because its dissected plateau type of topography resembles more the Great Plains than the Coastal Plain…”.

5.2 The Tale of Two Rivers

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Gu

Fig. 5.1 The Colorado river of Texas showing its headwaters, the balcones escarpment, the bedrock-confined valley, the Quaternary alluvial plain and the Gulf of Mexico shoreline. The pine forests extend into the winding alluvial terraces between Bastrop and LaGrange (Reprinted from Blum and Valastro (1994). Copyright permission granted)

This search starts with what is similar between these two rivers. Both rivers originate in different areas of the drought-prone Southern High Plains and both flow through the Texas coastal plain into the Gulf of Mexico. Both run across a west-toeast precipitation gradient where annual rainfall ranges from 500 to 1,000 mm. Both had incisions triggered by climate change during global-scale glacial melting even though glaciers formed only at higher latitudes. As flow rates slowed, both river basins slowly filled with layered deposits (Blum and Valastro 1994; Sylvia and Galloway 2006). The differences between the Colorado and the Brazos Rivers tell the rest. The sandy, gravelly deposits of the Colorado River Basin provide the suitable soils for Pinus taeda. By contrast, the Brazos River has alkaline deposits which favor prairie and oak savanna rather than pine forests. Keep in mind that Beaumont-derived soils do not support pine forests and this matter most among the many distinctive differences between these two central Texas rivers.

5.2.1

The Colorado River of Texas

The United States does have two Colorado Rivers but only one runs through Texas and it is this river that runs next to the Lost Pines forest. The Colorado

84

5 What Geological Records Add

River (Fig. 5.1) runs northwest to southeast for a total of 1,387 km, starting in Dawson County, Texas (32° 44¢ 35″ N 101° 56¢ 18″). This long river flows through four distinct physiographic areas: (1) its fluvial headwaters, (2) narrow bedrock channels, (3) mid-river depositional terraces near Bastrop, and (4) its alluvial basin. Note too that it flows across a pronounced west-to-east precipitation gradient. The Colorado’s large fluvial system has a vast drainage area of 110,000 km2. Roughly 92% of this drainage area is located in the drought-prone Southern High Plains and the western Edwards Plateau (Blum and Valastro 1994). Here, the Colorado River receives only 510 mm of annual rainfall. Beyond its headwaters, the Colorado River is divided into two distinct parts (Blum and Valastro 1994). Here, where the river reaches the narrow bedrock channels of the Balcones Escarpment, annual rainfall rises to 810 mm. Typical of semi-arid climates, these soils support only xeric shrubby plant species. Brief storms often lead to rapid runoff and flooding through the rocky channels of this incised reach. Since 1938, flooding on the Colorado River has been controlled by a series of dams constructed above the Balcones Escarpment. Below the channel, east of Austin, the Colorado River widens into an alluvial reach rolling Pleistocene terraces and gravelly deposits (Fig. 5.1). It is here on the old terraces that the Lost Pines forest grows, most visible where the river winds through its alluvial channel. These terraces often have soils composed of fine sands, silt and clay. The pine forest soils correlate with moderately acid alfisols which developed over Quaternary deposits (Sorensen et al. 1976). Most of these Pinus taeda forests are concentrated on the higher terraces along the eastern banks of the Colorado River. These particular soils are characterized as gravel, sand, silt and clay with a pH range of 6.0–6.7 and they are not formed from recent deposits along the Colorado River. The alluvial basin of the Colorado River ends at Matagorda Bay and the Gulf of Mexico. This lower part of the Colorado River moves through 280 km of subtropical climate before it discharges into the Gulf of Mexico at Matagorda Bay. Along its course, the coastal basin takes on many landforms which range from prairies, marshes, swamps, barrier beaches to dense hardwood forests (Aten 1983, pp. 16–17). No pine forests grow here in this subhumid alluvial basin. The Colorado River’s present-day course began accumulating in the Last Glacial Maximum between 20,000 and 14,000 y BP (Table 5.1). Studies of its depositional fill begin with a base layer resting on Cretaceous or Tertiary strata which was formed at the Last Glacial Maximum between 20,000 years BP and 14,000 y BP. Incision of bedrock valleys occurred from 14,000 to 11,000 y BP. By ~ 11,000 years BP (Table 5.1). The Colorado River basin acquired extensive migrating lateral channels and valleys widening with depositional fill (Table 5.1). Holocene deposits of valley fill followed. Two of these notable events occurred between 5,000 and 2,500 BP and then again between 1,000 BP and now (Blum and Valastro 1994).

5.2 The Tale of Two Rivers

85

Table 5.1 Timing for valley incision and depositional fill occurred earlier for the Brazos river than for the Colorado river of Texas (Sources: Blum and Valastro 1994; Sylvia and Galloway 2006) Time period (years before present or y BP) Colorado river Brazos river 1,000 Layer of Holocene deposits 5,000–2,500 Layer of Holocene deposits 8,000–3,000 Upper valley fill dates 11,000 Start of depositional fill 11,000–14,000 Bedrock valley incision 15,000 Layer of LGM deposits 20,000 Pleistocene deposits 29,000 Pleistocene deposits 43,000–38,000 Pleistocene deposits 45,000–30,000 Massive valley incision

The Colorado River near Bastrop alternates between Pleistocene terraces and more recent depositional fill, most of which dates after Last Glacial Maximum, on through the Holocene (Table 5.1). Farther downstream, the Colorado River becomes increasingly alluvial (Blum and Valastro 1994). Louisiana, crosses the Colorado River only at its lower reaches, below those alluvial terraces which support pine forests.

Box 5.2 The Paleosoils Theory for the Colorado River This theory proposes that warm-temperate pine forests once grew upper terraces of the Colorado River (Sorensen et al. 1976). The upper Pleistoceneage terraces of the Colorado River clearly have clay-rich lateritic paleosoils well-suited to pine forests prior to the river’s Holocene depositional fill and these deep red clay B horizons were high in iron content might have supported pine forests in the Pleistocene. This theory fits in that pines readily colonize rough substrata whether glacial tills or ancient forest soils (Jackson and Williams 2004) and pine seeds could have colonize between the extreme weather events typical during this time period (Toomey et al. 1993; Blum and Valastro 1994; Sylvia and Galloway 2006). There is no supporting fossil evidence to confirm or refute this theory. One objection is that the Edwards Plateau and its surrounding areas might had temperatures too cool to support warm-temperate Australes pine forests. Although temperatures were as much as six degrees C cooler than present during the summer months, this too is subject to debate because winters were not colder and seasonality was at a minimum (Toomey et al. 1993).

86

5.2.2

5 What Geological Records Add

The Brazos River

The Brazos River is defined by the steep precipitation gradient which splits into the river’s course into two parts: its semiarid western part and its subhumid eastern basin. The river’s basin is hypersensitive to the high-frequency climatic oscillations which took place between the late Pleistocene and Holocene periods (Sylvia and Galloway 2006). The Brazos River has a drainage area is similar in size to that of the Colorado River, roughly 110,850 km2 and its headwaters fan out into the vulnerable Southern High Plains of Texas, extending into eastern New Mexico (Sylvia and Galloway 2006). Typical of this river basin are vertisol soils which develop from calcareous marls and limestones and these consist of montmorillonite clays which are slick and impermeable to water. As an example, the Brazos River Basin has Houston Black Clay, an alkaline vertisol which is the dominant soil series for this area (Sorensen et al. 1976). Vertisols such as Houston black clay are typical of the prairie and oak savanna eco-regions around the Lost Pines area. They are typical of the prairiesavanna gap which separates the Lost Pines forest from east Texas. These too were Pleistocene events. Between 45,000 and 30,000 years BP, the Brazos River excavated a valley, possibly scouring out older paleosoils (Sylvia and Galloway 2006). Later, after the Last Glacial Maximum and well into the Holocene, the river’s flow rates slowed such that the river’s slow-moving flow layered large amounts of depositional fill into its basin. These layers of depositional fill started around 38,000–43,000 years BP then concentrated at 29,000, again at 20,000 and yet again at 15,000 years BP but there are also upper valley fill with dates around 3,000–8,000 years BP (Sylvia and Galloway 2006). The Brazos River’s depositional fill began in late Pleistocene well before the Last Glacial Maximum.

5.3

Geological Events

Geological records show that Pinus taeda has a restricted area, or narrow realized niche, at this time. This restricted area corresponds to the sedimentary geology of the Colorado River only. The river has its upper reaches where erosion begins, or gathers. The eroded materials are moved in a conveyor-like belt motion down the river’s course, through its transport reaches, by intense and highly variable precipitation. Some of these eroded materials are deposited here but most reach the lower alluvial-deltaic plain before deposition (Blum and Valastro 1994). Present-day Pinus taeda forests grow only in the transport reach of the Colorado River on the oldest Pleistocene terraces, not on younger fluvial deposits from the Holocene. Note that the presence of pine forests on these terraces cannot be taken as proof positive that these forests are Pleistocene in origin. Pinus taeda, as a prolific species, is notoriously migratory and so its range spreads and contracts rapidly. This means that the forested areas rapidly change over the course of decades or centuries even without human activity. Pine forests are not a constant landscape feature. Rather, pines

5.4 Wilcox-Carrizo Aquifer

87

spread during cooler climates and pines contract during hot-dry intervals (i.e. Grimm et al. 1983). These trend mitigates against the possibility that pine forests have been continuously here for more than 100,000 y BP or more, or as long as these Pleistocene terraces have been present along the Colorado River. Rather, one can only say that present-day pine forests correspond to soils typical of the Wilcox Group terraces along the Colorado River’s transport reaches. No fossil evidence ties Pinus taeda to this location on a geological time scale. These particular soils tends to have aquifer-fed springs and seeps: Bastrop County has more than 17 springs (Brune 2002). Even so, this description of the realized niche for Pinus taeda is incomplete. Agricultural clearing and settlement blur the picture of where pine forests might have grown as recently at 1850, the end of the Little Ice Age.

5.4

Wilcox-Carrizo Aquifer

The Wilcox Group is the source of natural gas, oil, lignitic coal and freshwater from the Lost Pines area. It dates back 65 to 55 million years (6.0 × 10−7) when the Wilcox Group was deposited as sediment during the Eocene-Paleocene epochs (Zachos et al. 2005). The Wilcox Group is extensive, starting swath-like at the Rio Grande River in south Texas then cutting across Texas into Arkansas and Louisiana (Fig. 5.2). The Wilcox Group, an ancient delta complex, consists of several formations of which three are Hooper, Calvert Bluffs and Simsboro Formations. Of these, the Simsboro Formation holds particular interest for Bastrop County’s subterranean water supply as it has the greatest water capacity. The Simsboro Formation, mostly sand, has a variable distance from the surface, or thickness. Its thickness is only 30 m in Bastrop County but deepens to 230 m to the northwesterly direction, in Milam County. The Carrizo formation was deposited later but it is hydrologically connected to the Wilcox Group (Dutton et al. 2003). The Carrizo Formation of the Claiborne Group overlays the Wilcox Group but it overlays the Wilcox Group in a narrow transect which runs through Bastrop, Burleson, Lee and Milam countries, dipping beneath the land surface towards the Gulf of Mexico (Zachos et al. 2005). Unlike the deltaic Wilcox Group, the Carrizo Formation is fluvial in origin. The Carrizo Sand, ranging in color from light to dark gray, is fine to coarse grained and loose. It forms a massive sheet of sand, ranging in thickness from only 33 m in Bastrop but deepening to a thickness of 125 m elsewhere. The Wilcox Group and the Carrizo Formation not only intersect in the Bastrop County area but it is here that they both are closer to the surface here than in other locations.

5.4.1

The Lost Pines Forest and the Wilcox-Carrizo Aquifer

Springs dot the Quaternary terrace sand and gravel of the Colorado River in Bastrop County. Brune (2002) writes: “The county’s springs issue chiefly from Quaternary terrace sand and gravel deposits along the Colorado River and from Tertiary Eocene

88

5 What Geological Records Add

Fig. 5.2 The Wilcox Group and the overlying Carrizo formation of the Claiborne Group form a hydrologically connected system known the Wilcox-Carrizo or Carrizo-Wilcox aquifer. It starts at the Rio Grande river in south Texas then cuts across Texas into Arkansas and Louisiana as a wide swath. It is the source of natural gas, oil, lignitic coal and freshwater from the Lost Pines area, dating back 65–55 million years (6.0 × 10−7) when the geological formation known as the Wilcox Group was deposited as sediment during the Eocene-Paleocene epochs (Map prepared by the State of Texas for public use)

sands such as the Wilcox, Carrizo, …” and he made a drawing showing how the geological formations are tied to the springs (Fig. 5.3). How fast does this aquifer recharge? Here is the crux of the matter for Pinus taeda forests and for the municipality of Bastrop. This aquifer recharges slowly at a rate of only 0.05–0.08 mm per year along the outcrops of sand-rich formations (Dutton et al. 2006; Nicot 2008). Aquifer usage could exceed recharge and, if so, then the aquifer will have been mined. Some of the pine forests have rich lignite deposits beneath them (Fig. 5.4; Davies 1981). This coal (Box 5.3) originates from the same Eocene deposits as the aquifer’s depths. To date, this formation has supplied 88 oil fields, 22 natural gas reservoirs and a large store of coal over the course of Bastrop’s twentieth century industrial history (Dutton et al. 2006).

5.5 Closing

89

Fig. 5.3 This figure shows the relationship between eocene geological formations of the WilcoxCarrizo with the present-day springs in the lost pines area. Groundwater is thought to move so slowly through the particles that the springs in the sand may flow for months or even years without any rainfall in the recharge area (Reprinted from Brune (2002). Copyright permission granted)

5.5

Closing

The tale of two rivers is this: the Colorado and Brazos River sedimentary geology respectively shape where pine forests can grow and cannot grow. The Lost Pines population also corresponds to local landscape heterogeneity which creates mottled pockets across its entirety where, as Sargent (1884) noted, a few pines germinate, thrive then succumb to extreme drought unless there is underground water. The geology for these two river basins has been well-studied and depositional fill has been assigned approximate dates. Geological records define the realized niche for the Lost Pines area as well as explain what defines the realized niche: sand-gravel terraces pocked with aquiferfed springs and seeps. These aquifer-fed springs and seeps fall outside the traditional measurement of the climate envelope. Measures of rainfall, potential evapotranspiration or aridity indices all provide incomplete description of what sustains Pinus taeda here at the westernmost edge of its range.

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Bastrop Country

290

Elgin Camp Swift

Bastrop

Smithville

71

N

State Parks Surface Minable Lignite Deep Basin Lignite Loblolly Pine Area: Coverage 30% or more

0

5 miles

Fig. 5.4 Lignite coal deposits are beneath some of the Pinus taeda forests in eastern Bastrop County (Reprinted from Davies (1981). Copyright permission granted). This material is reproduced with permission of John Wiley & Sons, Inc

References and Related Readings

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Box 5.3 Lignitic Coal Discovery Beneath the Lost Pines Beneath the surface of the Lost Pines area is a seam of lignitic coal and this was first described by geologist R.A.F. Penrose, Jr. in 1890.2 He describes how ancient forested swamps had decayed, forming coal. The present-day Lost Pines forest now grows over fossilized remains of extinct forest species. “The lignites of Eastern Texas …consist of the decayed vegetation which covered the region during the time that the lignites and their accompanying sandy and clayey strata were being deposited. In them are found the remains of trunks of trees, branches, and leaves, with impressions of reeds and other bog or swamp flora. In fact every lignite bed in the region represents the position occupied by an ancient swamp or coast lagoon. Probably most of the Texas lignites were formed in bayous and lagoons on the coast, and the vegetable matter was carried to them by rivers. Such places were probably heavily timbered, and year after year the trees dropped their leaves and dead branches on the moist ground.”…

References and Related Readings Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. in the late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Aten L (1983) Indians of the upper Texas coast. Academic, New York Blum M, Valastro S (1994) Late Quaternary sedimentation, lower Colorado river, Gulf coastal plain. Geol Soc Am Bull 106:1002–1016 Bousman CB (1998) Paleoenvironmental changes in central Texas: the palynological evidence. Plains Anthropol 43(164):201–219 Bray W (1904) Forest resources of Texas. USDA Bureau of Forestry, Government Printing Office, Washington, DC, 71 Brown A (1955) The lost pines. Gulf Coast Lumberman 42(August):28, 30 Brune G (2002) Springs of Texas. Texas A&M University Press, College Station Buckley SB (1866) A preliminary report of the geological and agricultural survey of Texas. Office of the State Gazette, Austin Burley J (2004) The restoration of research. For Ecol Manag 201:83–89 Davies C (1981) Policy implications of the banking of lignite leasing, Bastrop County Texas 1954–1979. Econ Geogr 57:238–256 Dutton A, Nicot J et al (2006) Hydrodynamic convergence of hydropressured and geopressured zones, Central Texas, Gulf of Mexico Basin, USA. Hydrogeol J 14:859–867 Dynesius M, Jansson R (2000) Evolutionary consequences in species geographic distribution driven by Milankovitch climatic oscillations. Proc Nat Acad Sci USA 97:9115–9120 Farjon A, Styles B (1997) Pinus (Pinaceae) Flora Neotropica. The New York Botanical Garden, New York Fehrenbach T (2000) Lone star: a history of Texas and the Texans. De Capo Press, Cambridge Fox T, Jokela E et al (2007) The development of pine plantations silviculture in the southern United States. J For 105:337–347 2 Excerpt comes from R.A.F. Penrose Jr. (1890) A preliminary report on the geology of the Gulf tertiary of Texas from Red River to the Rio Grande.

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Griffith GE, Bryce SA, Omernik JM, Comstock JA, Rogers AC, Harrison B, Hatch SL, Bezanson D (2004) Ecoregions of Texas. U.S. Geological Survey, Reston Hocker H (1956) Certain aspects of climate as related to the distribution of loblolly pine. Ecology 37:824–834 Jackson S, Williams J (2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu Rev Earth Planet Sci 32:495–537 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: Milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Kennedy W (1841) The rise, progress and prospects of the Republic of Texas. Molyneux Craftsmen Inc, Fort Worth (1925) Kesselus K (1999) History of Bastrop County, Texas before statehood. Jenkins Publishing, Austin Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 Little E (1971) Atlas of United States trees, vol 1, Conifers and important hardwoods. U.S. Dept. of Agriculture, Forest Service, Washington, DC Ludlum D (1963) Early American hurricanes 1492–1870. American Meterological Society, Boston Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Maxwell R, Martin J (1970) A short history of forest conservation in Texas 1880–1940. Stephen F. Austin State University School of Forestry, Nacogdoches, 61 McDougall A (2003) Did Native Americans influence the northward migration of plants during the Holocene? J Biogeogr 30:633–647 Meltzer D (1999) Human responses to middle Holocene (Altithermal) climate of the North American great plains. Quat Res 52:404–416 Meltzer D, Holliday V (2010) Would North American Paleoindians have noticed Younger Dryas climate change? J World Prehist 33:1–41 Miller C (2007) Ground work: conservation in American culture. Forest History Society, Durham Mirov N (1967) The genus pinus. Ronald Press, New York Moberg A et al (2005) Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 443:613–617 Nicot J-P (2008) Evaluation of large-scale CO2 storage on fresh-water sections of aquifers: an example from the Texas Gulf Coast Basin. Int J Greenh Gas Control 2:582–593 Oliver H, Mayhead G (1973) Wind measurements in a pine forest during a destructive gale. Forestry 47:185–194 Ostrom E, Janssen M et al (2007) Going beyond panaceas. Proc Nat Acad Sci USA 104:15176–15178 Parvin B (1982, January) Are the loblollies really lost? San Antonio Monthly pp 25–26, 56 Perry J (1991) The pines of Mexico and Central America. Timber Press, Portland Power M et al (1996) Challenges in the quest for keystones. Bioscience 46:609–620 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Russell D et al (2009) A warm thermal enclave in the late pleistocene of the South-eastern United States. Biol Rev Camb Philos Soc 84:173–202 Sargent C (1884) Report on the forests of North America. U.S. Department of Interior, Census Office, Washington DC Sen S, Magallanescedeno M et al (1994) In-vitro micropropagation of Afghan pine. Can J For Res 24:1248–1252 Sorensen CJ, Mandel RD et al (1976) Changes in bioclimate inferred from paleosols and paleohydrologic evidence in east-central Texas. J Biogeogr 3:141–149 Sylvia D, Galloway W (2006) Morphology and stratigraphy of the late Quaternary lower Brazos valley, discharge and sediment delivery. Sediment Geol 190:159–171 Thomas C et al (2002) Extinction risk from climate change. Nature 427:145–148 Thornbury W (1965) Regional geomorphology of the United States. Wiley, New York

References and Related Readings

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Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Vogel S (1984) Drag and flexibility in sessile organisms. Am Zool 24:37–44 Waters M et al (2011) The buttermilk creek complex and the origins of clovis at the Debra L. Friedkin site. Science 331:1599–1603 Zachos L, Garvie C et al (2005) Definitive locations of paleocene and eocene marine fossil localities, Colorado river, Bastrop County Texas. Texas J Sci 57:317–328 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from 1851 to 2000. Proc Nat Acad Sci USA 106:7888–7892 Zobel B, Talbert J (1984) Applied tree improvement. Wiley, New York, 505 p

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Part III

An Evolutionary Synthesis

David Quammen The Planet of the Weeds Harper’s Magazine October 1998 Still, evolution never rests. It’s happening right now, in weed patches all over the planet. I’m not presuming to alert you to the end of the world, the end of evolution, or the end of nature. What I’ve tried to describe here is not an absolute end but a very deep dip, a repeat point within a long, violent cycle. Species die, species arise. The relative pace of those two processes is what matters.

Pines are survivors of major climate change events. These climate change events, often cataclysmic, occurred on a scale of millions of years. These events coincided with the divergence and speciation of present-day taxa then Quaternary events subsequently shaped populations within each species. Migration has been a central tenet to evolutionary reconstructions for this taxon and this tenet shifts our emphasis away from the tree itself towards not only dispersal but the complex pine life cycle itself. Both its evolutionary past and its dispersal modes figures into the open question of whether pines are prolific, migratory generalists or prone to becoming locally adapted ecotypes. The Lost Pines population has a surprising amount of genetic diversity and this serves as its buffer against future climate change. Closely related to other Pinus taeda populations in east Texas, this disjunct population has long been thought to be more locally adapted than other populations. If so, then this disjunct population and its adaptive alleles are potentially valuable as a drought-adapted source of seeds for other parts of the Pinus taeda range. Taken together, short-term evolutionary processes and life cycle particulars inherent to the Lost Pines populations make for a dynamic climate change response. This system, expressed here as a set of verbal models, conveys a finely drawn guide for forest management practices.

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Chapter 6

Survivor of Past Climate Change Events

6.1

Introduction

Pines have a deeper evolutionary past than most seed plants and this past has coincided with many major climate upheavals over the course of 40 million years or more. With each new Tertiary upheaval, this taxon has shifted, merged, split, shrunk and expanded. New subsections and new species evolved. By contrast, the Quaternary climate change oscillations only shaped populations within a species. From the Tertiary to Quaternary til present-day conditions, Pinus spp, have survived climate change via its capacity for dispersal and migration.

6.2

Taxonomic Classification

The genus Pinus is the largest of the several genera which composes the family Pinaceae (Price et al. 1998; Gernandt et al. 2009). Where or when the genus Pinus evolved is not yet known (LePage 2003) but it has over 110+ species, of which more than half are indigenous to Mexico. Pinus taeda, as a warm-temperate eastern hard pine belongs to the North American subsection Australes within the hard pines subgenus. The subsection Australes includes not only Pinus taeda but also other species indigenous to the southeastern United States, Central American and several Caribbean islands (Little 1971; Adams and Jackson 1997). The focus here is a set of Australes species whose ranges overlap with Pinus taeda in the southeastern United States. Of particular interest to the Lost Pines narrative are the following Australes relatives: Pinus palustris, Pinus echinata, Pinus glabra, Pinus serotina and Pinus elliottii. Taxonomic classification belies the dynamics of its evolution. Within a forest tree species is an aggregate of populations. Any one of these populations acts as the unit of climate change response but it is not a solitary unit. Rather, a population is an integrated unit which is closely linked other higher-order taxonomic groups. The link is a shared evolutionary past which can be reconstructed using temporal C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_6, © Springer Science+Business Media B.V. 2012

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records. These links can be reconstructed using more temporal records: these can be fossil evidence, geological records, DNA-based records or some combination of these.

6.3

Evolutionary Events

The family Pinaceae and its genera are among the oldest living seed plant lineages tracing their origins to the Mesozoic era more than 140 million years ago (LePage 2003). This long evolutionary past coincides with major climate change events over the course of millions of years (Table 6.1). Scarce fossil evidence for Pinus spp. begins with Cretaceous fossil records in Asia, Europe and North America (Table 6.1) but its place of origin is not known. Any migration of Late Cretaceous pines from west to east in North America would have been impeded by seaways which extended the length of the continent. The Western Inland Sea covered the entirety of Texas during this time period.

6.3.1

Tertiary Period

The Late Cretaceous climate was warm and humid below latitudes of 45° because there was little seasonality. This changed with the Tertiary Era about 65 MY ago (Table 6.1) was marked by climate change. Temperatures and humidity begin to rise until they reached a maximum by the early Eocene ca. 52 MY. This change triggered a cascade of formative divergence and speciation events for Pinus spp. in the Northern Hemisphere: Europe, Asia, and North America. This warm, humid climate during the Tertiary period was already changing again by the time when the first fossil evidence is available the genus Pinus. New evidence places the divergence of Pinus into two subgenera by 45 MY. This divergence resulted in the soft pine subgenus Strobus and the hard pine subgenus Pinus (Table 6.1; Willyard et al. 2009). Contributing to the Tertiary climate change were major tectonic events. Among these were volcanism and mountain-building events which contributed to North America’s topography. They also brought rising atmospheric carbon dioxide concentrations and possibly greenhouse gas warming as well as changes in sea level and in ocean circulation (Millar 1998). Fossil evidence for Pinus spp. places the genus in western North America at early juncture (Axelrod 1986) but little can be said about Mexico or the U.S. Gulf Coast during this same time period. Still another Tertiary climate change event arrived by the late Eocene/early Oligocene. Temperatures were now regional temperatures and these dropped drastically, as much as 0–14°C over the course of a million years (Millar 1998). Regional climate patterns became increasingly complex as mountain-building in

Triassic

225 MY

Events center on North America and present-day Texas

Mesozoic

141 MY 195 MY

65 MY

Paleocene

Tertiary

Cretaceous Jurassic

38 MY 54 MY

Oligocene Eocene

Tertiary

45,000–30,000 118,000 y BP 130,000 y BP 1.7 MY 2.7 MY 7 MY

14,50 y BP 19,000 y BP 23,000–19,000

10,000–8,000 11,570–12,800

100–650 y BP 600–1,000 y BP 1,000–2,500 2,500–8,000

Millions years (MY) or years before present (y BP)

26 MY

Pliocene

Wisconsinan Sangamon Pleistocene

Last glacial maximum

Holocene Younger Dryas abruptly starts, ends Bølling-Allerød

Epoch

Miocene

Quaternary

Period

Mesozoic

Cenozoic

Era

Arid, savanna type climate

Stable, equable climate from poles to equator Humid, warmer climates

Subtropical climates prevail, rainfall is heavy, volcanism and mountain-building Wilcox Group deposited as sediment by Eocene-Paleocene boundary around 55 MY followed by deposits for Carrizo Group Warmer climate than present-day; subtropical climate

Climate transition prior to Altithermal’s local expression Abrupt rise in temperature begins and ends Valley incision for Colorado River Colorado River terraces start forming from alluvial deposition Abrupt period of warm, moist climate; mesic conditions onward with temperatures 2–3°C lower than present Abrupt rise in sea level due to glacial melting Last glacial sheets reach maximal extension Warm-temperate Pinus spp. in present-day Florida Valley incision for Brazos River Glacial interval begins Interglacial interval begins Polar ice caps form; glaciers form Onset of Northern Hemisphere glaciation Pinus spp. macro-fossils in Gulf Coast of Alabama Migration also proposed for Australes Late-Miocene migration proposed for Australes Continental uplifts

Little ice age (1300–1850 AD) Medieval climate anomaly (900–1350 AD) Warm-moist climate Local expression of the Altithermal Peak of the Altithermal 2,500–5,000 y BP

Climate

Table 6.1 Major climate change events coincided with divergence, migration and adaptation of Pinus spp. and its progenitors

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Mexico progressed. This marked the emergence of stable regional climates for the first time. This shift to regional climate change registered as a major upheaval for high-latitude angiosperm flora. These plant lineages died out, leaving great open expanses on the landscapes. The expanses were swiftly colonized by pines and so now pines occupied swiftly the middle latitudes of Europe, Asia and North America. This great pine diaspora gave rise to an abundance of new pine species which reached its zenith as these climate conditions deteriorated through the early Oligocene (Table 6.1). Next was a climate warming trend which arrived by the late Oligocene and this continued into the Miocene (Millar 1998). This trend coincided with the divergence of North American pine subsections and among these is the subsection Australes. The origins of the Australes subsection is also not known. Rarely is fossil evidence available but DNA-based phylogeny provides a supplement. Two major theories have been put forward, each drawing on different sources of DNA-based evidence from living or extant Australes members. The early progenitors of the Australes subsection are thought to have migrated from western North America to the Gulf of Mexico coast during the Oligocene and late Miocene, roughly 20–38 MY (Axelrod 1986; Krupkin et al. 1996; Millar 1993). This late-Miocene diaspora is thought to have split into a southeastern U.S. group of species and a group now found in Central America and some of the Caribbean islands (Adams and Jackson 1997). If so, then the divergence of the Australes subsection would date back to the Miocene, roughly ~8–15 MY (Krupkin et al. 1997; Gernandt et al. 2009). Equally plausible is a south-to-north migration route for the Australes subsection which would have started in present-day Mexico, ending along the Gulf of Mexico’s coast. This migration is estimated to have been more recent, occurring 5–10 MY ago (Dvorak et al. 2000). This theory gain support from a recent Pliocene soft pine macrofossil find along the northern end of the Gulf of Mexico coast (Stults et al. 2010). In either case, the Australes subsection is one of the youngest clade in North America.

6.3.2

Quaternary Period

Unlike the Tertiary speciation events, the Quaternary shaped populations within existing species. More climate change events arrived with the Quaternary but its climate oscillations cycled more rapidly and this might be one reason that Tertiary patterns of divergence were not altered or reshuffled (Millar 1998). This was the case for other seed plants; few if any new plant species emerged from the Quaternary (Comes and Kadereit 1998). A good example of how Quaternary climate events acted at the population level is presented in Box 2.2. where Pinus banksiana populations persiste, migrate and possibly extirpate (Chap. 2; Godbout et al. 2005). This species migrated back and forth across the middle latitudes between the formation of vast continent-sized glaciers.

6.3 Evolutionary Events

6.3.2.1

101

Pleistocene Epoch

With the arrival of the Quaternary’s Pleistocene epoch, the earth’s climate grew cooler and this led to a long series of major ice ages (Table 6.1). Both poles already had substantial amounts of ice by the end of the Tertiary period. The Arctic ice cap became the source of thick, continent-sized polar ice sheets, or glaciers. With each glaciation cycle, this ice sheet advanced and then receded across North America’s higher latitudes. When these North American ice sheets spread southward, they compressed temperature zones towards the equator (Table 6.1) but at no time did these ice sheets cover the southeastern part of North America. The formation of each new glacier began a climate swing between glacier formation, its melting and then its glacier-free or interglacial period. Each glaciation cycle thus had a cold interval and a warm interval; each cycle progressed on a time scale of thousands of years (Mannion 2006; Russell et al 2009). This strange periodicity corresponds the earth’s irregular and it is known as the Milankovitch cycles1 (i.e. Westfall and Millar 2004). Other planetary events accounted for other, shorter climatic swings which also took place during the late Pleistocene. Among these were the Younger Dryas (Table 6.1; Meltzer and Holliday 2010) and the Heinrich2 events.

Box 6.1 Orbital Range Dynamics Theory Pines and other forest trees are thought to have evolved a migratory response as a consequence of the orbital irregularities which brought glaciation cycles. Orbital range dynamics (ORD) theory provides an explanation for the transient generalism typical of Pinus banksiana and other high-latitude forest tree species during oscillating climate events at mid- to higher latitudes during the Quaternary period. Specifically, the theory proposes that past climate change at higher latitudes has selected for species with a) a high capacity for dispersal, b) little if any local adaptation and c) low divergence among populations within a species (Jansson and Dynesius 2000). This suggests too that boreal and temperate pines are colonizing generalists and thus not given to local adaptation.

1 The periodicity of these past climate change events have long suggested a controlling mechanism based on the Croll-Milankovitch theory. Here, the earth’s irregular orbit is proposed as the pacemaker of glacial cycles. Its largest orbital eccentricity has a 100,000-year cycle, the variation in the Earth’s axial tilt has a 41,000-year cycle and the precession due to the Earth’s axial wobble has a 19,000 to 23,000-year cycle (Westfall and Millar 2004). All modulate climate change by altering the amount of energy that the earth receives from the sun. These orbitally-induced climate change oscillations are now confounded with its human-induced rise in carbon dioxide and other greenhouse gases. 2 Heinrich events were massive, periodic advances of ice streams from the eastern margin of the Laurentide Ice Sheet. They occurred mostly on 7,000-year cycles: H6 at 60,000 y BP, H5 at 45,000 y BP, H4 at 38,000 y BP, H3 at 31,000 y BP, H2 at 24,000 y BP, H1 at 16,800 y BP.

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Glaciation was particularly harsh in North America when compared to Asia or Europe or to the Southern Hemisphere. At first, each glacier’s vast continental ice sheets lasted for 41,000 years then glaciation intervals began to lengthen to 100,000 years and longer (Hewitt 2000; Russell et al. 2009). The warmer period between glaciers, the interglacial periods, were brief. These lasted only 20,000 y BP. All told, North America had 27 oscillating cycles of glacial-interglacial intervals over the course of nearly two million years (Table 6.1; Russell et al. 2009). Here too, the migratory response of pines to climate change is clear (Box 2.2). Each time that North America’s glaciers sheared its forests, these same forest species migrated and then recolonized once again in their original range during the warmer interglacial intervals.

6.3.2.2

Pleistocene’s Last Glacial Maximum (LGM)

The last glacial cycle ended roughly 18,000 y BP and after this came a warming transition began. This warming transition is the Last Glacial Maximum (LGM) (Mannion 2006) and it is a series of mild climate oscillations which begin with cool, moist conditions which favored pine forest expansion, progress to increasingly hot, dry conditions and then end with present-day climate shifts which still continue. These mild oscillations during the LGM coincided with cool Heinrich cycles favored pine forest expansions in the southeastern quadrant of North America. Between the Heinrich cycles were drier, hotter episodes which coincide with pine forest contractions; these favored expansion of Quercus spp. and grasses instead (Grimm et al. 1983). The end of the Pleistocene and its last glacial melt ushered numerous shifts between open woodland, forest and grasslands in central Texas (Bryant 1977; Toomey et al. 1993; Bousman 1998). Pines, as migratory species, were transient during these increasingly dynamic from the LGM transition onward. These climate events played out across the Texas landscape. Western Texas experienced torrential rainfall while eastern Texas had a cool moist climate. Temperatures shifted upwards from the cooler full-glacial temperatures which had been 5–6° cooler than present-day temperatures (Toomey et al. 1993). Were Pinus taeda populations present in central Texas at this time? A lack of fossil evidence here too has led to numerous theories.

6.3.2.3

A Pleistocene Refugium in Florida

That warm-temperate pine species have occupied northern Florida since the Pleistocene reads clearly from the fossil record (Grimm et al. 1983; Jackson et al. 2000). Through the Pleistocene and Holocene epochs, pine populations waxed and waned here with the rise and fall of sea levels. Warm-temperate pine species persisted in northern Florida such an extent that this may have been their only refugial

Evolutionary Events

103

Arboreal Pollen %

min ea G ra

Pic ea

la Bet u

Pin us

0

Qu er

cu s

e

6.3

0

50

100 3700 ± 90 yrs BP 3850 ± 80 yrs BP

Depth (m)

1

2 9850 ± 160 yrs BP 10.010 ± 160 yrs BP

3

4 13.810 ± 210 yrs BP 14.410 ± 220 yrs BP

5

15.460 ± 250 yrs BP

0

50

100%

= 1% or less

Fig. 6.1 Fossil pine pollen profile from Boriack Bog in Lee County Texas is the only fossil evidence which might link Pinus taeda or perhaps other Australes taxa to this location at the Last Glacial Maximum (LGM) (Figure from Bryant (1977). Note that these data were not corroborated at Patsche’s Bog which is less than 5 km away (Camper 1991). Copyright permission granted)

location (Jackson et al. 2000). To be accurate, these were not the only taxa here. Northern Florida’s forests had an odd admixture of pine species from boreal, temperate and even subtropical latitudes by the LGM (Jackson et al. 2000). As the LGM gave way to warmer temperatures, pine forests expanded and this expansion coincides with a sharp rise in pine pollen in Marion County Florida around 6,000–4,000 y BP (Remington 1968). Another Pleistocene Refugium in Texas? Pinus taeda and other warm-temperate pines were likely to have another refugial location in Texas and/or Mexico (Wells et al. 1991; Millar 1998; Al-Rababah and Williams 2004). Only sparse fossil pollen data can tie this refugium to central Texas. Much of the Texas-based fossil pollen evidence comes from Boriack Bog in Lee County Texas, a location 30 km north-northeast of present-day Bastrop (Fig. 6.1; Bryant 1977). Here, far smaller amounts of warm-temperate pine pollen at Boriack

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Table 6.2 East-west differentiation among Pinus taeda populations has been reported using several methods Differentiation between western and eastern Pinus Data source taeda populations? References Molecular evidence from Yes isozymes, nuclear microsatellites, DNA sequence variation

Florence and Rink (1979) Schmidtling et al. (1999) Edwards and Hamrick (1995) Edwards-Burke et al. (1997) Al-Rababah and Williams (2002, 2004) Eckert et al. (2010)

Phenotypic data on growth, survival, fungal disease resistance and reproductive traits

Wells and Wakeley (1966) Wells et al. (1991) Zobel (1953)

Yes

DNA-based patterns of No Xu et al. (2008) variation using AFLP markers Some sources are coded as follows: (A) warm-temperate Pinus spp. fossil pollen, (B) patterns of present-day DNA variation and (C) phenotypic information and (D) DNA signatures using present-day populations

Bog peaked between 15,400 and 9,800 y BP before declining over the course of the Holocene (Bryant 1977). Similar patterns for fossil pine pollen are not reported from another nearby site, Patschke Bog, which also in Lee County (Camper 1991; Jackson et al. 1991). Note that fossil pine pollen concentrations are much lower here at Boriack Bog than those found in Florida (Grimm et al. 1983; Jackson et al. 2000). Fossil pollen at Boriack Bog introduces post-Pleistocene ambiguity. Its pollen sizes fit the Australes subsection and some other pine species yet fossil pine pollen cannot identified by species or even subsection (Cain 1940). One cannot be certain that this is Pinus taeda pollen. To this point, Bryant (1977) adds that Boriack Bog’s fossil pine pollen might belong to Pinus remota, a taxon in the Strobus subgenus. Hard pines are a more likely possibility than this soft pine because pollen morphology is so distinctly different between hard and soft pine subgenera. More compelling evidence of this second refugium has been inferred from genetic variation patterns (Table 6.2). Western and eastern parts of the Pinus taeda range are distinctly different ands such short amounts of time have lapsed that these differences must trace to their respective isolation during major climate change events. This line of thinking has led to the East-West Model (Fig. 6.2; Wells et al. 1991). The East-West Model (Fig. 6.3;Wells et al. 1991) was drawn from patterns of genetic variation which came from morphological, physiological and molecular data sources (Tables 6.2–6.3). Pinus taeda populations from the eastern part of the range are distinctively separate from those in the western part. Similarly, the eastern Pinus taeda populations typically have faster growth, longer needle length, larger cone

6.3

Evolutionary Events

Fig. 6.2 The East-West Model charts a hypothetical phylogeography for eastern and western parts of the Pinus taeda range since the Last Glacial Maximum (LGM) as described by Wells et al. (1991)

105

East-West Model (Wells et al. 1991) Eastern and western parts of the Pinus taeda range were already separate by LGM. The Lost Pines population was part of the large, continous western part of the range. DeSoto Canyon east of Mississippi River acted as a isolating barrier or the secondary contact point between western and eastern parts of the species range. Natural range of Pinus taeda extended west of the present-day Lost Pines area and farther south of its present-day location throughout eastern Mexico. Pinus taeda was a coastal species, extending along the Gulf Coast and along the Atlantic Seaboard.

Table 6.3 Eastern and western parts of the P. taeda range are mildly differentiated Population structure Area (km2) Sample size MNA Observed heterozygosity Eastern Range 228,023 52 10.0 ± 1.6 0.552 ± .053 Western Range 140,015 57 8.7 ± 1.3 0.493 ± .045 Total 368,038 109 10.8 ± 1.7 0.520 ± .046 Western part has lower levels of genetic diversity, possibly due to re-colonization of the western range from a bottlenecked Lost Pines refugial population. Geographic area, sample size, mean number of alleles per locus (unadjusted), mean observed heterozygosity (Ho) by the direct count method and mean expected heterozygosity (He) for P. taeda regions east and west of the Mississippi River Valley (Al-Rababah and Williams 2004, 2002)

and seed size and greater fusiform rust susceptibility (Wells and Wakeley 1966; Knauf and Bilan 1974). Populations from the western part of the Pinus taeda range typically have smaller cones, smaller needles and slower growth rates although all of these characters display unusually wide variation (Al-Rababah and Williams 2004; Table 6.3). These same molecular markers also affirm that the Lost Pines population is closely related to several western Pinus taeda populations, not only to other Texas populations (Al-Rababah 2003). The western part of the Pinus taeda range now extends through Mississippi, Louisiana, southwestern Arkansas, eastern Oklahoma, eastern Texas and as far west as central Texas (Table 6.3). The East-West Model spells out an interesting scenario: it proposes that the Lost Pines population was not the westernmost edge of the species range nor was it disjunct. Instead, the Lost Pines is thought to have been part of a historically large and

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continuous western part of the range which stretched westward into the Texas interior, southward into Mexico to then eastward to eastern Mississippi’s DeSoto Canyon. The East-West theory proposes that the two parts of the species range had already diverged by end of the LGM at 13,000 y BP (Fig. 6.2; Wells et al. 1991). The hypothetical scenario places Pinus taeda populations along Gulf of Mexico coastline as far inland as the present-day Lost Pines and as far south as Mexico, then around Florida to the Atlantic Seaboard as far as South Carolina. Note too that secondary contact between the eastern and western parts is placed at DeSoto Canyon which is >100 km east of the Mississippi River (Wells et al. 1991). Admixed east-west populations near the Mississippi River Valley now blur or overlook this subtle distinction (Al-Rababah and Williams 2002; Soltis et al. 2006).

6.3.2.4

The Holocene Epoch Brings Hot Dry Altithermal-Type Events

As the LGM came to a close, climate once again shifted from cool and moist to cool and dry then it moved into repeated episodes of increasingly hotter and drier climates which were pronounced in mid-continental North America, near the Southern High Plains (Fig. 6.2; Meltzer 1999; Meltzer and Holliday 2010). The drought-prone Edwards Plateau (Toomey et al. 1993) located west of the Lost Pines area has provided a detailed record of this Holocene climate shift. The account of Edwards Plateau area is based on temporal records which include vertebrate faunal remains in Hall’s Cave, fossil pollen and plant macrofossils from packrat middens and on geological records which come from river hydrology, cave formations, oxalate residue from lichens and radioisotope measurements (Musgrove et al. 2001). Taken together, all of these records support a Holocene epoch here in mid-continental North America. These had prolonged periods of drought and unusually high temperatures, higher than present-day. Some view these mid- to late Holocene episodes as the local expression of the Altithermal but the timing for the episodes are only approximate (Table 6.1): Toomey et al. (1993) estimates that Altithermal occurred between 7,000 and 5,000 years BP while others give this event a wider interval, roughly 8,000–2,500 y BP with a peak between 5,000 and 2,500 y BP (Deevey and Flint 1957; Wells 1970; Bryant 1977). How did pine forests fare under the harsh Holocene climatic conditions? Only indirect evidence is available and none of its anchors Pinus taeda or its relatives here to central Texas. In western North America, entire pine forests died; fallen remains can still be seen along the fossil timberline at high elevations in Nevada and other part of western North America (LaMarche and Mooney 1967; Betancourt et al. 1991; Cole et al. 2008; Cole 2009). No such remains are left in the flat, humid and subtropical expanses of central Texas. The only indicator here, again, is fossil pine pollen and the profiles at Boriack Bog are consistent with a decline after 8,000 y BP (Bryant 1977; Bryant and Holloway 1985; Toomey et al. 1993). Climate shifted yet again and the harsh Holocene conditions eased into a warmmoist climate from 2,500 to 1,000 y BP (Toomey et al. 1993). Only then did flora and fauna begin their migratory return to Edwards Plateau and other parts of Central

6.5

Closing

107

Texas. The constancy of climate change continued: mild oscillations have occurred even as recently as the last millennium.

6.4

From Holocene Onward

Two mild climate change oscillations have occurred within recorded history. The first was the Medieval Warming Anomaly which was a hot, dry period from 900 to 1350 AD (Table 6.1). The residue of this short yet harsh event is still apparent in western North American forests (Millar and Woolfenden 1999). The second was the Little Ice Age which lasted from 1300 to 1850 AD (Moberg et al. 2005; Rockman 2010). Its mark is also clearly apparent on North American forests (Westfall and Millar 2004) and this could well be the case for the Lost Pines forests. Pine forest expansion in central Texas would have been favored by the cool, moist climate conditions of the Little Ice Age and this lends credence to the presence of a pine archipelago. These effects were both too subtle to tease apart from human disturbance. This expansion from the Atlantic and Gulf coastal regions into the interior piedmont regions of the U.S. South occurred rapidly on the cusp of the early twentieth century. Piedmont pine forests are notably missing in North Carolina, South Carolina, Georgia, and Alabama when Sargent surveyed the U.S. South (Sargent 1884). This expansion was a product of natural regeneration in part. Pinus taeda readily colonized the red clay subsoils typical of eroded and abandoned agricultural fields in the U.S. South’s piedmont regions, earning the name of old field pine (Wahlenberg 1960). Another factor was the rise of planting programs and these were slow to contribute during this same time period. Planting did not become massive in scale until the mid-twentieth century (Fox et al. 2007). Natural regeneration, and to a lesser degree, tree planting programs shaped the present-day range for Pinus taeda. Its present-day range is an artifact of human disturbance and thus it is not realistic to assume that the current range of the species, as shown by Little 1971, is at equilibrium with its environment.

6.5

Closing

Pines are living fossils which have survived cataclysmic climate change events over the past 40 million years and their primary response has been migration. This Mesozoic fossil continued to evolve during the Tertiary during which massive migration, divergence and speciation of pine lineages coincided with floral extinctions, mountain-building and volcanism and the emergence of regional climates. Later, these same pine lineages remained stable through Quaternary climate events which oscillated more rapidly on the scale of millennia. Here too pine species responded to

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climate change with massive long-distance migrations. These migrations profoundly shaped population structure within high-latitude species. Glaciers did not extend as far south as the southeastern part of North America but here another outcome of climate change is likely to have shaped Pinus taeda populations: prolonged drought. Climate change during Quaternary’s Holocene included climate conditions which were hotter and drier than present-day ones. The real drawback here is the scarcity of fossil evidence and this means that no migration rates are available for many pines species including Pinus taeda. This organism’s propensity for migration points to the importance of dispersal for these sessile organisms.

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Lanner R (1966) Needed: a new approach to the study of pollen dispersion. Silvae Genetica 15:50–52 Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 LePage B (2003) The evolution, biogeography and paleoecology of the Pinaceae based on fossil and extant representatives. Acta Hortic 615:29–52 Levin DA (1990) The seed bank as a source of genetic novelty in plants. Am Nat 135:563–572 Lindgren D et al (1975) Can viable pollen carry Scots pine genes over long distances? Grana 34:64–69 Little E (1971) Atlas of United States trees, vol 1, Conifers and important hardwoods. USDA Forest Service, Washington DC Little S, Somes H (1959) Viability of loblolly pine seed stored on the forest floor. J For 57:848–849 Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Mason H (ed) (1949) Evidence of the genetic submergence of Pinus remorata Genetics, speciation and paleontology. Princeton University Press, Princeton Matos J, Schaal B (2000) Chloroplast evolution in the Pinus montezumae complex: a coalescent approach to hybridization. Evolution 54:1218–1233 McDonald J (1962) Collection and washout of airborne pollens and spores by raindrops. Science 135:435–437 McWilliam J (1959) Interspecific incompatibility in Pinus. Am J Bot 46:425–433 Mehra P (1976) Conifers of the Himalayas with particular reference to the Abies and Juniperus complexes. Nucleus 14:123–139 Meltzer D, Holliday V (2010) Would North American Paleoindians have noticed Younger Dryas climate change? J. World Prehistory 33:1–41 Mergen F, Stairs G et al (1963) Microsporogenesis in Pinus echinata and Pinus taeda. Silvae Genetics 12:127–129 Millar C (1993) Impact of the Eocene on the evolution of Pinus L. Ann Mo Bot Gard 80:471–498 Millar CI (ed) (1998) Early evolution of pines. In: Ecology and biogeography of Pinus. Cambridge University Press, Cambridge Millar C, Woolfenden W (1999) The role of climate change in interpreting historical variability. Ecological Applications 9:1207–1216 Mirov N (1967) The genus Pinus. Ronald Press, New York Moberg A, Sonechkin D et al (2005) Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 443:613–617 Musgrove M, Banner JL et al (2001) Geochronology of late Pleistocene to Holocene speleothems from central Texas for regional paleoclimate. Geol Soc Am Bull 113:1532–1543 Namkoong G, Bishir J (1987) Frequency of lethal alleles in forest tree populations. Evolution 415:1123–1127 Nathan R, Katul GG, Horn HS, Thomas SM, Oren R, Avissar R, Pacala SW, Levin SA (2002) Mechanisms of long-distance dispersal of seeds by wind. Nature 418:409–413 Nichols R, Hewitt G (1994) The genetic consequences of long-distance dispersal during colonization. Heredity 72:312–317 Nichols H, Kelly PM et al (1978) Holocene paleo-wind evidence from palynology in Baffin Island. Nature 273:140–141 Nielson R, Pitelka L et al (2005) Forecasting regional to global plant migration in response to climate change. BioScience 55:749–759 Niklas K (1984) The motion of windborne pollen grains around conifer ovulate cones - implications on wind pollination. Am J Bot 71:356–374 Niklas K (1985) The aerodynamics of wind pollination. Bot Rev 51:328–386 Niklas K, Paw U (1983) Conifer ovulate cone morphology: implications on pollen impaction patterns. Am J Bot 70:568–577 Parker S, Blush T (1996) Quantifying pollen production of loblolly pine (Pinus taeda L) seed orchard clones, Westvaco Forest Research Report 163. Forest Science Laboratory, Summerville

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Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspect Plant Ecol Evol Syst 11:157–189 Pease C, Lande R et al (1989) A model of population growth, dispersal and evolution in a changing environment. Ecology 70:1657–1664 Petit R, Hu F et al (2008) Forests of the past: a window on future changes. Science 320:1450–1451 Pielke R, Garstang M et al (1987) Use of a synoptic classification scheme to define seasons. Theor Appl Climatol 38:57–68 Plotnick R, Gardner R (2002) A general model for simulating the effects of landscape heterogeneity and disturbance on community patterns. Ecol Model 147:171–197 Price R, Liston A, Strauss S (1998) Phylogeny and systematics of Pinus. In: Ecology and biogeography of Pinus. Cambridge University Press, Cambridge Pyne SJ, Andrews PL et al (1996) Introduction to wildland fire, 2nd edn. Wiley, New York Quarterman E, Keever C (1962) Southern mixed hardwood forest: climax in the southeastern coastal plains U.S.A. Ecol Monogr 32(2):167–185 Rehfeldt G, Ying C et al (1999) Genetic response to climate in Pinus contorta: niche breadth, climate change and reforestation. Ecol Monogr 69:375–407 Remington CL (1968) Suture-zones of hybrid interaction between recently joined biotas. Evol Biol 2:321–428 Richardson D, Rundel P (1998) Ecology and biogeography of Pinus: an introduction. In: Richardson D (ed) Ecology and biogeography of Pinus. Cambridge University Press, Cambridge, pp 3–46 Richardson DM, Williams PA et al (1994) Pine invasions in the Southern Hemisphere: determinants of spread and invadability. J Biogeogr 21:511–527 Righter F, Duffield J (1951) Interspecies hybrids in pines: a summary of interspecific crosses in the genus Pinus made at the Institute of Forest Genetics. J Hered 42:75–80 Robledo-Arnuncio J (2011) Wind pollination over mesoscale distances: an investigation with Scots pine. New Phytol 190:222–233 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Rogers C, Levetin E (1998) Evidence of long-distance transport of mountain cedar pollen into Tulsa Oklahoma. Int J Biometeorol 42:65–72 Rousseau D-D, Schevin P et al (2006) New evidence of long distance pollen transport to southern Greenland in late spring. Rev Palaeobot Palynol 141:272–286 Rousseau D-D, Schevin P et al (2008) Long-distance pollen transport from North America to Greenland in the spring. J Geophys Res Biogeosci 113:1–10 Russ J, Lloyd DH et al (2000) A paleoclimate reconstruction for southwestern Texas using oxalate residue from lichen as a paleoclimate proxy. Quat Int 67:29–36 Russell D, Rich F et al (2009) A warm thermal enclave in the Late Pleistocene of the southeastern United States. Biol Rev Camb Philos Soc 84:173–202 Sargent C (1884) Report on the forests of North America. U.S. Department of Interior. Census Office Savolainen O et al (2004) Gene flow and local adaptation in forest trees. Annu Rev Ecol Evol Syst 38:595–619 Saylor L, Kang K (1973) A study of sympatric populations of Pinus taeda L and Pinus serotina Michx in North Carolina. J Elisha Mitchell Soc 89:101–110 Schafale MP, Harcombe PA (1983) Presettlement vegetation of Hardin-County Texas. Am Midl Nat 109(2):355–366 Schmidtling R (1994) Use of provenance tests to predict response to climate change: loblolly pine and Norway spruce. Tree Physiol 14:805–817 Schmidtling R et al (1999) Allozyme diversity of selected and natural loblolly pine populations. Silvae Genetica 48:35–45 Schuster W, Mitton B (2000) Paternity and gene flow dispersal in limber pine (Pinus flexilis James). Heredity 84:348–361 Slee M (1970) Crossability values within the slash-Caribbean Pinus species complex. Euphytica 19:184–189

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Smouse P, Saylor L (1973) Studies of the Pinus rigida-serotina complex. II. Natural hybrids among Pinus rigida-serotina complex, P. taeda, P. echinata. Ann Mo Bot Gard 60:192–203 Soltis D et al (2006) Comparative phylogeography of unglaciated North America. Mol Ecol 15:4261–4293 Streng DR, Harcombe PA (1982) Why don’t east Texas savannas grow up to forests? Am Midl Nat 108(2):278–294 Stults D, Axsmith B et al (2010) Evidence of white pine (Pinus subgenus Strobus) dominance from the Pliocene northeastern Gulf of Mexico coastal plain. Paleogeo Paleoclimatol Paleoecol 287:95–100 Thames JL (1963) Needle variation in loblolly pine from four geographic seed sources. Ecology 44(1):168–169 Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Global Planet Change 7:299–320 Tyldesley JB (1973) Long-range transmission of tree pollen to Shetland. I. Sampling and trajectories. New Phytol 72:175–181 van Buijtenen JP (1966) Testing loblolly pines for drought resistance. Texas A&M University, College Station Wade DD, Brock BL, et al (eds) (2000) Wildland fire in ecosystems: effects of fire on flora. General Technical Report RMRS-GTR-42. USDA Forest Service Rocky Mountain Research Station Wahlenberg W (1960) Loblolly pine: its uses, ecology, regeneration, growth and management. Duke School of Forestry & USDA Forest Service, Washington DC Wang X-R, Szmidt A et al (2001) Genetic composition and diploid speciation of a high mountain pine, Pinus densata, native to the Tibetan plateau. Genetics 159:337–346 Wells P (1970) Postglacial vegetational history of the great plains. Science 167:1574–1582 Wells O, Wakeley P (1966) Geographic variation in survival, growth and fusiform-rust infection of planted loblolly pine. Forest Science Monograph 11. Society of American Foresters, Washington DC, 40 p Wells OO, Switzer GL et al (1991) Geographic variation in Mississippi loblolly pine and sweetgum. Silvae Genetica 40:105–119 Westbrook J, Isard S (1999) Atmospheric scales of biotic dispersal. Agric For Meteorol 97:263–274 Westfall R, Millar C (2004) Genetic consequences of forest population dynamics influenced by historic climate variability in the western USA. For Ecol Manag 197:159–170 Williams G (1975) Sex and evolution. Princeton University Press, Princeton, 210 p Williams C (2008) Aerobiology of Pinus taeda pollen clouds. Can J For Res 38:2177–2188 Williams C (2009) Conifer reproductive biology. Springer, New York Williams C (2010) Long-distance pine pollen still germinates after meso-scale dispersal. Am J Bot 97:1–11 Willyard A, Cronn R et al (2009) Reticulate evolution and incomplete lineage sorting among the ponderosa pines. Mol Phylogenet Evol 52:498–511 Xu S, Tauer C et al (2008) Natural hybridization within seed sources of shortleaf pine (Pinus echinata Mill.) and loblolly pine (Pinus taeda L.). Tree Genet Genomes 4:849–858 Youngman AL (1965) An ecotypic differentiation approach to the study of isolated populations of Pinus taeda in south central Texas. University of Texas, Austin Zobel B (1953) Are there natural loblolly-shortleaf hybrids? J For 51:494–495 Zobel BJ, Goddard RE (1955) Preliminary results on tests of drought hardy strains of loblolly pine (Pinus taeda) L. Texas A&M University, College Station

sdfsdf

Chapter 7

The Pine Life Cycle

7.1

Introduction

Pines have had a long evolutionary record of surviving climate change and one means of survival has been migration. This migratory response to climate change events is conditioned on the organism’s capacity for dispersal but dispersal alone cannot account for migration. Dispersal is the culmination of the organism’s life cycle. How the entire life cycle responds to climate change is key to understanding on how forest tree populations will fare under climate change. Climate change response in one word: prolific. Pinus taeda and other prolific forest trees delightfully adhere to what G.C. Williams (1975) called the Elm-Oyster Model: “Elms and oysters and many other plants and animals have in common that they are large organisms that produce small propagules in such enormous numbers that many colonize a space in which only one could possibly survive to adulthood. They also have in common that they reproduce only sexually.” Prodigious reproduction is shared by elms and oysters but their life cycle could not be more different. The aim of this chapter is to make this distinction explicit.

7.2

The Two Phases of the Life Cycle

A pine is an unusually long-lived, exceptionally prolific organism with a two-phase life cycle which has already been well-characterized elsewhere (i.e. Wahlenberg 1960; Richardson and Rundel 1998; Williams 2009). The dominant phase is the diploid sporophyte. This is better known as the tree or seedling. The other is the gametophyte phase. Brief, small and transient, the male and female gametophyte phases develop annually in the crown of the adult sporophyte (Fig. 7.1).

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_7, © Springer Science+Business Media B.V. 2012

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Adult sporophyte Male spores (N)

Female spores (N)

Meiosis

Meiosis

Male Gametophytes (N)

Female Gametophytes (N)

Male gametes (N)

Female gametes (N) Syngamy Zygote (2N) Embryo (2N)

Fig. 7.1 Diplohaplontic life cycle for forest trees and other seed plants has two phases: the dominant sporophyte stage and the brief, transient gametophyte phase. This life cycle is framed around five characters: (1) heterospory or separate spore types for male and female reproduction, (2) multicellular male and female gametophytes, (3) retention of the female gametophyte within the adult sporophyte, (4) the siphonogamous pollen tube and (5) dispersal of mature embryos

7.2.1

The Diploid Sporophyte Phase

From its seedling development onward, Pinus taeda typically has a long interval before its reproductive onset begins around age 10–15 years. The young tree produces a few reproductive structures at first but more appear as its crown gets larger. The crown expands fully via its telescoping branching tips, or apical meristems. These meristems are where the gametophytes develop. Many apical meristems develop on the tree’s crown each spring but only a few are slated for reproduction. These few will develop female or male reproductive initials depending on where the meristem is located in the crown. Female strobili form from meristems in the upper Pinus taeda crown while male strobili form from those in the lower or middle crown. Female and male reproductive lineages are separate within a single tree and this can be traced to heterospory, a characteristic common to all seed plants. The gametophyte phase has two distinct parts from beginning to end: female or male. Within the larger Pinus taeda population, strobilus development (note that strobili are not flowers) is separate yet synchronous (Figs. 7.2–7.4) in these monecious (with only a rare case of hermaphrodism) and outcrossing plants. Self-pollination is possible but a number of deterrents block selfing at different stages in favor of outcrossing.

7.2

The Two Phases of the Life Cycle

117

Fig. 7.2 Germinating Pinus taeda pollen grains. The pollen tube emerges from an aperture located between the two sacci (Photograph taken by Floyd Bridgwater, USDA Forest Service. Copyright permission granted)

7.2.2

The Haploid Gametophyte Phase

Nested within each type of strobilus, are cells designated for meiosis. Meiosis within each of these designated cells cuts its chromosomal complement from diploid (2 N) to haploid (N). After pollination and then a lengthy post-pollination

Box 7.1 Long Generation Interval for Pinus taeda in Texas The generation interval for the western populations is effectively lengthened by major forest fires (Al-Rababah 2003). Texas pre-settlement history shows that wildfires occur on 35-year cycles (Wade et al. 2000) and such fires stretch the generation interval of fire-intolerant species (Pyne et al. 1996) such as Pinus taeda by destroying its even-aged cohort structure. If a seedling cohort is eradicated before reaching reproductive competence, then another cohort must take its place and this adds years to the population’s effective generation interval. An ecologically-lengthened generation interval matters because it slows a forest tree population’s response to climate change.

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Fig. 7.3 Female strobili emerge from Pinus taeda branch tips located in the tree’s upper crown. Each strobilus has scales and each scale has a pair of ovules at its base. These ovules have dangling micropylar arms which capture pollen grains upon deposition (Photograph taken by Floyd Bridgwater, USDA Forest Service. Copyright permission granted)

wait, fertilization occurs and this leads to the development of a seed. The seed contains the embryo and this is the young sporophyte. What separates the adult sporophyte from its next generation of young sporophytes is the tiny gametophyte phase.

7.3

Two Vehicles for Dispersal

Dispersal occurs at the sporophyte phase (seeds) and at the gametophyte phase (pollen). Pollen and seed dispersal together connect individuals and populations but only seed dispersal leads to colonization and colonization is the path to migration for these sessile organisms.

7.4

Pollen Dispersal

119

Fig. 7.4 Cross-section of female strobilus at the stage of maximum receptivity after it has been pollinated. At the base of each scale are pollen clustered around each pair of ovules (Photograph taken by Michael Greenwood, University of Maine. Copyright permission granted)

7.4

Pollen Dispersal

In simplest terms, pollen dispersal is release, passive transport and deposition of the male gametophyte enclosed within a spore wall. Pinus taeda pollen is large by comparison to other windborne biological particles; its diameter is roughly 50 mm and its size is similar to its warm-temperate relatives such as Pinus echinata (Jackson and Lyford 1999). More is known about the capacity for Pinus spp. pollen dispersal than its actual paternal success. Paternal success, when measured across generations, is defined as gene flow and this requirement for many generations makes for an unwieldy definition for those working with forest trees. It is difficult to estimate paternal success across generations given the longevity of forest trees and the sheer geographic distances that pollen can cover. The scale of dispersal for Pinus spp. far exceed its terrestrial boundaries, as shown next.

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Table 7.1 Micro-, meso- and macro-scale transport systems with associated meteorological and biological processes (Adapted from Gage et al. 1999) Scale Meteorological Systems Ecological System Biological Processes Macro-scale Tradewinds Evolution, flora and fauna Continents (107 km2) >103 km2 monsoons movement cyclones Domains 103–104 km2 Seasonal phenology Regions 102–103 km2 Life histories Meso-scale 1-103 km2

Hurricanes, jet-stream, sea breezes, thunderstorms

Sections (10 s to 102 km2) and Landscapes (1–10 km2)

Development within phenological stages; the rate of development is influenced by daily weather (i.e. heat sum)

Micro-scale < 1 km2

Thermal shells, eddies, turbulence

Habitats

Physiological processes of organisms; habitat strongly influences movement as well as horizontal and vertical gradients of atmospheric variables.

Table 7.2 Capacity for pollen dispersal across vertical distances Altitude (m) Method Location References 3000 Manned floating capsule Greenland Balter (2002), Rousseau et al. (2006) 600 Helicopter, ships North Carolina Williams (2010) 300 Finland Koski (1970) These were observed for passive wind transport of forest tree pollen from source

Some North American pine species move 2000 km from source (e.g. Campbell et al. 1999; Rousseau et al. 2006). Pollen is transported via low- and high-pressure systems, turbulent large-scale eddies or land-sea circulations. These are just some of the forces causing pollen grains to move through the atmosphere1 at meso- and macro-scale transport distances (Table 7.1). A few examples are presented here for a number of pines and other conifers (Table 7.2). Once released, pine pollen joins the rich aerial plankton above the earth’s surface. A few grains ascend as high as 3000 m above the earth’s surface (Rousseau et al. 2006) where it mixes with the rich aerial biota composed of other pollen (17–58 m), spores (1–30 m), bacteria (0.25–8 m), viruses (<0.3 m) as well as wingless insects, spiders and larvae (Gislén 1948; Gregory 1978; Westbrook and Isard 1999). Live or dead, pine pollen traveling at these phenomenal distances (Table 7.3) can have no lasting consequences for climate change response if it is not capable of germination at deposition (Fig. 7.2) or if it is deposited outside the range of receptive female strobili (Figs. 7.3–7.4).

1 This refers to the troposphere which is the layer of the atmosphere closest to the earth; it rises from sea level up to 12 km from the surface of the earth. This is distinct from the stratosphere which lies above the troposphere, extending upwards about 50 km.

7.4

Pollen Dispersal

121

Table 7.3 Capacity for pollen dispersal across horizontal distances. These have been observed for passive wind transport of conifer pollen from source. Asterisk (*) indicates that the pollen was live and capable of germination Nearest source Organism Location (km) References Pinus banksiana Repulse Bay, Canadian 2,000 Campbell et al. (1999) Arctic Picea glauca Pinus spp. Baffin Island, Canadian 1,200 Nichols et al. (1978) Arctic Picea spp. Pinus spp. North Atlantic Ocean 1,000 Erdtman (1937) Picea spp. Pinus spp. Greenland 600 to 1,000 Dyakowska (1948) [in DiGiovanni et al. (1996)] Betula spp. Pinus spp. Iowa USA 600 Bessey (1884) Juniperus spp. Oklahoma USA 500 Rogers and Levetin (1998) Pinus spp. Greenland 300 Rousseau et al. (2006, 2008) Pinus spp. Shetland Isles 250 Tyldesley (1973) Pinus sylvestris Iberian Peninsula Spain 100* Robledo-Arnuncio (2011) Pinus sylvestris Southern Sweden 72 Lanner (1966) Pinus spp. North Carolina USA 41* Williams (2010) Pinus spp. Gulf of Bothnia 30 Hesselman (1919) (in Koski 1970)

Box 7.2 The Synoptic Adaptation Theory Meteorological events and reproductive phenology during pollination influences forest tree population structure more than spatial distance (Lanner 1966). This theory is apt for the Pinus spp. life cycle. Consider that Pinus taeda pollen sheds on the cusp of the winter-spring transition, a time of maximum atmospheric turbulence. Spring turbulence speeds up the transport of pollen but equally important are the daily spring rains during Pinus taeda pollen shed (Blush 1986; Greenwood 1986). Raindrops rinse pollen from the atmosphere (McDonald 1962). To continue this thought experiment, consider that each year’s spring weather shapes the genetic composition of each year’s seeds. One year might have steady rainfall during pollen shed to such an extent that a few local trees are the only paternal parents to that year’s seed. The next year might have strong gusting winds coupled with dry conditions, drawing a larger number of distant paternal parents than the year before. Paternal contributions to seeds can thus vary widely from one seed cohort. With even-aged cohort structure then each cohort has a different effective population size than the next.

The current world’s record is the paternal success of Pinus sylvestris pollen alive at 100 km from source (Robledo-Arnuncio 2011). This exceptional finding numbers among other long-distance dispersal events (Table 7.1).

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7.5

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Seed Dispersal

Cones open each fall and winged pine seeds disperse when cones open each October in the Northern Hemisphere. A stand of mature Pinus taeda trees produces roughly 105 seeds per hectare (Cain and Shelton 2001). This prolific seed production is a feature also makes this species well-adapted to human-mediated disturbances. While Pinus taeda is clearly an early-succession species (Wahlenberg 1960), its seedling recruitment, can be quite dense after disturbance. Seedling recruitment is favored by open gaps created by disturbances such as fire (Quarterman and Keever 1962) or agricultural abandonment (Streng and Harcombe 1982; Schafale and Harcombe 1983). Most seeds fall near the source but here too, distances of up to 100 m are common for many pine species. Individual pine seeds travel from 8 to 25 km from source (Richardson et al. 1994; Nielson et al. 2005). Pinus taeda seedlings are shade intolerant and this contributes to the observation that only 6% of these seeds germinate or survive past the first year (Little and Somes 1959; DeSteven 1991). The prolific seed production of mature Pinus taeda adults contributes to its rapid resilience and recovery after a catastrophe or overlogging.

7.5.1

Colonization

Seed dispersal is the culmination of many steps and these steps link together as a pipeline. The synchronous development of female and male strobili is the first step in the pipeline. This leads to pollination which followed by fertilization. After fertilization, the young sporophyte inside the seed matures. The cone opens and the seed disperses. If it lands in a suitable habitat near or far from the home site of its parent then it germinates. Survival after germination eventually leads to its reproductive maturity. These are the steps leading the dispersal pipeline. Seed dispersal can be linked to colonization using the simple rules of percolation theory (Plotnick and Gardner 2002). Consider that the landscape is a gridded matrix and this matrix has cells within its grid. Some are favorable and others are unfavorable habitats for seed germination and subsequent colonization. Pine seeds spin across this matrix from their adult sporophyte. Each of these seeds must land inside a favorable cell before it can start a colony, i.e. migrate. If a seed disperses to an unfavorable grid cell then it dies. Viewed this way, dispersal and its colonization chances have a parallel to a lottery. Gusting winds cause millions of windborne Pinus taeda seeds to spin across the gridded landscape matrix, some landing near and other farther from source. If more of the grid’s cells are favorable than not then dispersal carries a high chance of successful colonization. In the case of the Lost Pines area, the matrix is more sieve-like especially because of the gap which separates its from the rest of the species range. Few cells have suitable cells so colonization and thus migration are more tenous. Migration is the outcome of this constant interplay between seed dispersal, colonization and the landscape matrix (Fig. 7.5). From the Lost Pines narrative, plenty

7.6

Evolutionary Consequences

123

Fig. 7.5 The concept map for how many Pinus taeda seed donors (or founders) colonize across the landscape of the Lost Pines area. This prolific species disperses its seeds across the gridded matrix of suitable and unsuitable sites. Only a few seeds germinate or thrive as seedlings (dark triangles). The rest fail (dark dots) because they land on pavement, buildings and agricultural areas. Seeds landing within full vegetation will also fail to thrive. These are present-day barriers to colonizing by this early-successional species; another class of barriers are geologically-influenced. These are grouped together under the wrong site category which refers geologically-influenced barriers imposed by mottled vertisols and cells lacking adequate water. These latter can and may be colonized by drought-tolerant Pinus echinata and its hybrids with Pinus taeda

of seeds from adult Pinus taeda trees will disperse into the river or the prairie. Others land in a parking lot or a sorghum field. None of these places will support new colony of pine seedlings.

7.6 7.6.1

Evolutionary Consequences Hybridization

The capacity for long-distance pollen dispersal can have some exceptional evolutionary consequences. Among these is hybridization. Pinus taeda pollen overlaps and occasionally hybridizes with its close relative, Pinus echinata (Table 7.4).

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Table 7.4 Examples of hybridization and introgression between Pinus taeda and Pinus echinata in eastern and western parts of their ranges. Present-day Pinus echinata has a larger overlap with Pinus taeda in the eastern part of the range (Xu et al. 2008) and both species show clear differentiation between eastern and western parts of their respective ranges (Wells et al. 1977). Oddly, the Pinus taeda (Pt) x Pinus echinata (Pech) hybrid yields more seeds than its reciprocal (Pech x Pt) even though its reciprocal appears more frequently Hybrids Reference Parents and hybrids have continuum in cone sizes in East Texas Zobel (1953) Pollen shed times for 1962, 1963 Mergen et al. (1963) Pinus taeda: Shed on Feb 27, March 13 Pinus echinata: April 2, April 5 Pinus taeda x Pinus echinata hybrid: March 12, March 18 4.6% west vs. 1.1% east

Edwards and Hamrick (1995)

Pinus taeda as female parent, Pinus echinata as male parent for Edwards-Burke et al. (1997) hybrids observed in Georgia Pinus echinata (female) x Pinus taeda (male) 16.3% (7/43) western part vs. 2.4% (2/50) eastern part of range

Xu et al. (2008)

Pinus taeda (female) x Pinus echinata (male) 4.5% (1/22) west Xu et al. (2008) vs. 3.3% (3/90) east Hybridization resulted in backcrossing; most occurred in the direction of Pinus taeda observed in Maryland

Smouse and Saylor (1973)

This can lead to transgressive segregation (Aitken et al. 2008) which is where hybrids descendants show trait values which fall outside the spectrum of trait values for either parental species. Such transgressive segregants open a novel and rapid evolutionary path towards new adaptive variation (Aitken et al. 2008). The timing of Pinus taeda pollen release affects not only which matings are more likely to occur within a particular population but also its chances of interspecific hybridization with nearby closely related species. This potential for hybridization is fluid from year to year and from location to location, as shown for a single year of overlapping pollen shed dates between Pinus taeda and Pinus echinata (Table 7.5). Partial barriers to such hybridization do exist (McWilliam 1959; Slee 1970) and this is reportedly the case for a few closely related species. Still, hybridization between closely related species can and does lead to mature seeds and later, fertile F1 adults capable of crossing to other hybrids, either parent or even a third species (Grant 981). This is particularly true if hybridization, and later introgression, follows the wake of human disturbance (Ledig 1992). Naturally occurring hybridization is not uncommon between Pinus taeda and its relatives (e.g. Smouse and Saylor 1973; Saylor and Kang 1973; Edwards and Hamrick 1995) and these relationships have been better defined using artificial crosses (Righter and Duffield 1951). Such open-ended hybridization, typical of many conifers worldwide (Table 7.5), has profound but poorly understood consequences when considering how forest trees adapt to climate change.

7.6

Evolutionary Consequences

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Table 7.5 Pollen shed shown as calendar days during 1954 for Pinus taeda versus Pinus echinata (Dorman and Barber 1956). Pollen shed timing between the two species varies widely Pinus taeda pollen Pinus echinata Minimum County & U.S. State Latitude shed dates pollen shed dates difference (in days) Hertford 36° 30’ 4–6 to 4–15 4–24 to 4–29 +9 North Carolina Union 34° 40 4–1 to 4–7 4–16 to 4–23 +9 South Carolina Jefferson 33° 35 3–20 to 4–5 4–1 to 4–15 −4 Alabama Ashley 33° 5 3–12 to 3–30 4–1 to 4–10 +2 Arkansas Angelina 31° 20 2–25 to 3–20 3–25 to 4–5 −5 Texas Rapides 31° 10 2–21 to 3–15 3–27 to 4–8 +12 Louisiana

7.6.2

Serial Colonization

Another oddity peculiar to forest trees is that new colonies tend to have large numbers of seed donors or founders (Austerlitz et al. 2000). This oddity can be traced to the long wait between germination and reproductive onset. A single seed might be transported at a long distance from its source into a favorable habitat where it starts a new colony. This seedling has a decade or longer before it reaches reproductive onset. Meanwhile, other seeds from the same or other populations arrive. These successive, or serial, dispersal events contribute more and more seed donors to the same new colony. With more donors come many new alleles and this colony is rich in alleles, or high in genetic diversity. Serial dispersal events year after year create a founding population with many seed donors.

7.6.3

Sweepstakes Dispersal

Another explanation for the oddity is sweepstakes dispersal (Darlington 1925; Gislén 1948; Petit et al. 2008). This refers to the wholesale transport of seeds by way of a catastrophic weather event. The case of Pinus glabra in Florida, as reported by Batista and Platt (2002) would qualify. Adult trees were destroyed by late-season Hurricane Kate but in its destructive wake came massive seedling recruitment. One would expect that these seedlings came from more than one seed donors. A new colony of forest trees originating from sweepstakes dispersal would typically has multiple founders and with multiple founders come high levels of genetic diversity. The telltale mark would be many seed donors along with a single even-aged seedling cohort.

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Abiotic Stress Alters Seed Production

One final point is that abiotic stress alters reproduction, not only the growth or survival of forest trees. Elevated CO2 levels triples Pinus taeda seed production and brings on earlier reproductive onset (LaDeau and Clark 2001). Pinus taeda also produces more male and female strobili when limited water is available in late summer (Greenwood 1980). These reproductive shifts are part of the phenotypic plasticity of the entire life cycle and they too must be factored into predictive climate change models too.

7.7

Closing

This chapter’s main message is that elms and oysters are not the same, that their reproduction could not be more different. Elms, pines and other seed plants have an extra phase in their complex life cycle when compared to oysters and other animals: that extra phase is the gametophyte phase. Male and female gametophytes separate adult tree and their young sporophytes developing inside seeds. The mobile male gametophyte is the genetic connector among populations and occasionally other species. The telling part of the elm-oyster dichotomy is that gametophyte and sporophyte phases alike respond to environmental stress. Is Lost Pines population is genetically connected to the larger Pinus taeda network in east Texas by way of either pollen or seeds? The answer is likely to be yes. Spatially separate, the Lost Pines population’s reproductive isolation cannot be taken as a given. Here is the gridded matrix of percolation theory useful for resolving that question using both experiments and theory. To extend this example, consider a hypothetical Pinus taeda tree on the banks of the Colorado River in 1691 which is still alive in 2011. By now, this tree has shed its pollen and seeds more about 300 times. Its living offspring now number in the thousands or perhaps millions because this monoecious tree is both maternal and paternal parent. Most of its offspring have perished but a few colonized nearby while others were transported farther by wind or vertebrates. Only a fraction reached reproduction but these now produce prodigious amounts of pollen and seeds. In short, climate change affects the entire life cycle of this prolific seed plant and its response takes in terrestrial, aerial and perhaps aquatic ecosystems. Little is known about the genetic exchange between the Lost Pines population and the rest of its range. Here is a timely research topic, rich with interesting questions.

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Hesselman H (1919) Iakttagelser över skogstradspollens spridningförmåga. Medd Skogsöfrsöksanst 16:27–60 [cited in Koski 1970] Hewitt G (2000) The genetic legacy of the Quanternary ice ages. Nature 405:907–913 Higgins SH, Richardson DM (1999) Predicting plant migration rates in a changing world: the role of long-distance dispersal. Am Nat 153:464–475 Ito M, Susama Y et al (2008) Airborne-pollen pool and mating pattern in a hybrid zone between Pinus pumila and P. parviflora var. pentaphylla. Mol Ecol 17:5092–5103 Jackson S, Lyford M (1999) Pollen dispersal models in Quaternary plant ecology: assumptions parameters and prescriptions. Bot Rev 65:39–75 Jackson ST, Webb RS et al (2000) Vegetation and environment in eastern North America during the last glacial maximum. Quat Sci Rev 19:489–508 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: Milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Knauf TA, Bilan MV (1974) Needle variation in loblolly pine from mesic and xeric sources. For Sci 20:88–90 Kormutak A, Manka P et al (2009) Seed quality in hybrid swarm populations of Pinus mugo Turra and P. sylvestris L. Plant Syst Evol 277:245–250 Koski V (1970) A study of pollen dispersal as a mechanism of gene flow in conifers. Commun Inst For Fenn 70(4):1–78 Krupkin AB, Liston A et al (1996) Phylogenetic analysis of the hard pines (Pinus Subgenus Pinus, Pinaceae) from chloroplast DNA restriction site analysis. Am J Bot 83:489–498 Kuparinen A, Savolainen O et al (2010) Increased mortality can promote evolutionary adaptation of forest tree to climate change. For Ecol Manag 259:1003–1008 LaDeau S, Clark J (2001) Rising CO2 levels and the fecundity of forest trees. Science 292:95–98 LaMarche V, Mooney H (1967) Altithermal timberline advance in western United States. Nature 213:980–982 Lanner R (1966) Needed: a new approach to the study of pollen dispersion. Silvae Genetica 15:50–52 Ledig F (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 87:87–108 LePage B (2003) The evolution, biogeography and paleoecology of the Pinaceae based on fossil and extant representatives. Acta Horticult 615:29–52 Levin DA (1990) The seed bank as a source of genetic novelty in plants. Am Nat 135:563–572 Lindgren D et al (1975) Can viable pollen carry Scots pine genes over long distances? Grana 34:64–69 Little E (1971) Atlas of United States trees, vol 1, Conifers and important hardwoods. USDA Forest Service, Washington DC Little S, Somes H (1959) Viability of loblolly pine seed stored on the forest floor. J For 57:848–849 Mannion A (2006) Carbon and its domestication. Springer, Dordrecht Mason H (ed) (1949) Evidence of the genetic submergence of Pinus remorata Genetics, speciation and paleontology. Princeton University Press, Princeton Matos J, Schaal B (2000) Chloroplast evolution in the Pinus montezumae complex: a coalescent approach to hybridization. Evolution 54:1218–1233 McDonald J (1962) Collection and washout of airborne pollens and spores by raindrops. Science 135:435–437 McWilliam J (1959) Interspecific incompatibility in Pinus. Am J Bot 46:425–433 Mehra P (1976) Conifers of the Himalayas with particular reference to the Abies and Juniperus complexes. Nucleus 14:123–139 Mergen F, Stairs G et al (1963) Microsporogenesis in Pinus echinata and Pinus taeda. Silvae Genetics 12:127–129 Millar C (1993) Impact of the Eocene on the evolution of Pinus L. Ann Mo Bot Gard 80:471–498 Millar CI (1998) Early evolution of pines. In: Millar CI (ed) Ecology and biogeography of Pinus. Cambridge University Press, Cambridge

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Mirov N (1967) The genus Pinus. Ronald Press, New York Moberg A, Sonechkin D et al (2005) Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 443:613–617 Musgrove M, Banner JL et al (2001) Geochronology of late Pleistocene to Holocene speleothems from central Texas for regional paleoclimate. Geol Soc Am Bull 113:1532–1543 Namkoong G, Bishir J (1987) Frequency of lethal alleles in forest tree populations. Evolution 415:1123–1127 Nathan R, Katul GG, Horn HS, Thomas SM, Oren R, Avissar R, Pacala SW, Levin SA (2002) Mechanisms of long-distance dispersal of seeds by wind. Nature 418:409–413 Nichols R, Hewitt G (1994) The genetic consequences of long-distance dispersal during colonization. Heredity 72:312–317 Nichols H, Kelly PM et al (1978) Holocene paleo-wind evidence from palynology in Baffin Island. Nature 273:140–141 Nielson R, Pitelka L et al (2005) Forecasting regional to global plant migration in response to climate change. BioScience 55:749–759 Niklas K (1984) The motion of windborne pollen grains around conifer ovulate cones - implications on wind pollination. Am J Bot 71:356–374 Niklas K (1985) The aerodynamics of wind pollination. Bot Rev 51:328–386 Niklas K, Paw U (1983) Conifer ovulate cone morphology: implications on pollen impaction patterns. Am J Bot 70:568–577 Parker S, Blush T (1996) Quantifying pollen production of loblolly pine (Pinus taeda L) seed orchard clones, Westvaco Forest Research Report 163. Forest Science Laboratory, Summerville Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspect Plant Ecol Evol Syst 11:157–189 Pease C, Lande R et al (1989) A model of population growth, dispersal and evolution in a changing environment. Ecology 70:1657–1664 Petit R, Hu F et al (2008) Forests of the past: a window on future changes. Science 320:1450–1451 Pielke R, Garstang M et al (1987) Use of a synoptic classification scheme to define seasons. Theor Appl Climat 38:57–68 Plotnick R, Gardner R (2002) A general model for simulating the effects of landscape heterogeneity and disturbance on community patterns. Ecol Model 147:171–197 Price R, Liston A, Strauss S (1998) Phylogeny and systematics of Pinus. In: Ecology and biogeography of Pinus. Cambridge University Press, Cambridge Pyne SJ, Andrews PL et al (1996) Introduction to Wildland Fire, 2nd edn. Wiley, Hoboken Quarterman E, Keever C (1962) Southern mixed hardwood forest: climax in the southeastern coastal plains U.S.A. Ecol Monogr 32(2):167–185 Rehfeldt G, Ying C et al (1999) Genetic response to climate in Pinus contorta: niche breadth, climate change and reforestation. Ecol Monogr 69:375–407 Remington CL (1968) Suture-zones of hybrid interaction between recently joined biotas. Evol Biology 2:321–428 Richardson D, Rundel P (1998) Ecology and biogeography of Pinus: an introduction. In: Richardson D (ed) Ecology and biogeography of Pinus. Cambridge University Press, Cambridge, pp 3–46 Richardson DM, Williams PA et al (1994) Pine invasions in the Southern Hemisphere: determinants of spread and invadability. J Biogeogr 21:511–527 Righter F, Duffield J (1951) Interspecies hybrids in pines: a summary of interspecific crosses in the genus Pinus made at the Institute of Forest Genetics. J Hered 42:75–80 Robledo-Arnuncio J (2011) Wind pollination over mesoscale distances: an investigation with Scots pine. New Phytol 190:222–233 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Rogers C, Levetin E (1998) Evidence of long-distance transport of mountain cedar pollen into Tulsa Oklahoma. Intl J Biometeorol 42:65–72 Rousseau D-D, Schevin P et al (2006) New evidence of long distance pollen transport to southern Greenland in late spring. Rev Palaeobot Palynol 141:272–286

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Rousseau D-D, Schevin P et al (2008) Long-distance pollen transport from North America to Greenland in the spring. J Geophys Res Biogeosci 113:1–10 Russ J, Lloyd DH et al (2000) A paleoclimate reconstruction for southwestern Texas using oxalate residue from lichen as a paleoclimate proxy. Quat Int 67:29–36 Russell D, Rich F et al (2009) A warm thermal enclave in the Late Pleistocene of the southeastern United States. Biol Rev Camb Philos Soc 84:173–202 Savolainen O et al (2004) Gene flow and local adaptation in forest trees. Annu Rev Ecol Evol Syst 38:595–619 Saylor L, Kang K (1973) A study of sympatric populations of Pinus taeda L and Pinus serotina Michx in North Carolina. J Elisha Mitchell Society 89:101–110 Schafale MP, Harcombe PA (1983) Presettlement vegetation of Hardin-County Texas. Am Midl Nat 109(2):355–366 Schmidtling R (1994) Use of provenance tests to predict response to climate change: loblolly pine and Norway spruce. Tree Physiolo 14:805–817 Schmidtling R et al (1999) Allozyme diversity of selected and natural loblolly pine populations. Silvae Genetica 48:35–45 Schuster W, Mitton B (2000) Paternity and gene flow dispersal in limber pine (Pinus flexilis James). Heredity 84:348–361 Slee M (1970) Crossability values within the slash-Caribbean Pinus species complex. Euphytica 19:184–189 Smouse P, Saylor L (1973) Studies of the Pinus rigida-serotina complex. II. Natural hybrids among Pinus rigida-serotina complex, P. taeda, P. echinata. Ann Mo Bot Gard 60:192–203 Soltis D et al (2006) Comparative phylogeography of unglaciated North America. Mol Ecol 15:4261–4293 Streng DR, Harcombe PA (1982) Why don’t east Texas savannas grow up to forests? Am Midl Nat 108(2):278–294 Stults D, Axsmith B et al (2010) Evidence of white pine (Pinus subgenus Strobus) dominance from the Pliocene northeastern Gulf of Mexico coastal plain. Paleogeogr Paleoclimatol Paleoecol 287:95–100 Thames JL (1963) Needle variation in loblolly pine from four geographic seed sources. Ecology 44(1):168–169 Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Tyldesley JB (1973) Long-range transmission of tree pollen to Shetland. I. sampling and trajectories. New Phytol 72:175–181 van Buijtenen JP (1966) Testing Loblolly Pines for drought resistance. Texas A&M University, College Station Wade DD, Brock BL et al (eds) (2000) Wildland fire in ecosystems: effects of fire on flora. General Technical Report RMRS-GTR-42, USDA Forest Service Rocky Mountain Research Station Wahlenberg W (1960) Loblolly pine: its uses, ecology, regeneration, growth and management. Duke School of Forestry & USDA Forest Service, Washington DC Wang X-R, Szmidt A et al (2001) Genetic composition and diploid speciation of a high mountain pine, Pinus densata, native to the Tibetan plateau. Genetics 159:337–346 Wells P (1970) Postglacial vegetational history of the Great Plains. Science 167:1574–1582 Wells O, Wakeley P (1966) Geographic variation in survival, growth and fusiform-rust infection of planted loblolly pine. Forest Science Monograph 11. Society of American Foresters, Washington DC, 40 p Wells OO, Switzer GL et al (1991) Geographic variation in Mississippi loblolly pine and sweetgum. Silvae Genetica 40:105–119 Westbrook J, Isard S (1999) Atmospheric scales of biotic dispersal. Agric For Meteorol 97: 263–274 Westfall R, Millar C (2004) Genetic consequences of forest population dynamics influenced by historic climate variability in the western USA. For Ecol Manag 197:159–170 Williams G (1975) Sex and evolution. Princeton University Press, Princeton, 210 p

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Chapter 8

Short-term Evolutionary Processes

8.1 Introduction Forest trees maintain exceptionally high levels of standing variation and this standing genetic variation is the raw material acted upon by selection, random drift and gene flow.1 Selection favors certain genotypic classes over others so that those selected contribute disproportionately more to the next generation. Random drift alters gene frequencies unpredictably, in a purely stochastic fashion, from one generation to the next. The third force, gene flow, homogenizes gene frequencies among all popu­ lations when pollen or seeds disperse from one population to another. The interplay of these forces, along with the plant’s own genetic mechanisms shape the population’s standing variation as its moves closer or farther from the phenotype optimal for its specific environment.

8.2 Genetic Variation Protects Take the example of an adult Pinus taeda sporophyte, a diploid individual (2 N). This individual tree has two sets of chromosomes. Assume that it has two different alleles at a single locus, one on each chromosome. Allele 1 is coded as A1 and Allele 2 is coded as A2 so the adult sporophyte’s genotype is thus a heterozygote or A1A2. Concept of heterozygosity. This adult sporophyte is restricted to outcrossing. It can contribute one of its two alleles to any of its gametophyte but not both alleles. Why? Meiosis reduces its diploidy to a state of haploidy and each of its gametophytes will receive either the A1 allele or the A2 allele. As haploids, none receive both alleles so its genotype does not pass intact to the next generation.

1 Mutation, or a change to the DNA code itself, is also a force but here it has been set aside because mutation rates for woody plants are low relative to annual plants (Smith and Donoghue 2008) and because the chance of a beneficial mutation is infinitesimally low.

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_8, © Springer Science+Business Media B.V. 2012

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Outcrossed mating. This same hypothetical tree now exchanges pollen with its unrelated neighbor. It disperses its pollen and it receives pollen grains with A1 and pollen grains with A2 alleles from the other tree. Fertilization unites alleles from each parent. Now, having completed a reproductive cycle, that hypothetical pine tree has maturing seeds. If we know the genotypes then we can sort these seeds into one of four classes. Two classes are homozygotes: either the A1A1 genotype or the A2A2 genotype. The other two classes are heterozygotes so these seeds have either A1A2 or A2A1 genotypes. This isolated population of two adults with the same two alleles have offspring which have one of four genotypes. This population is not well-buffered against allele loss. Large populations are buffered against allele loss. If more mates become available for this same tree then its offspring are better buffered against allele loss. Let us say that this larger population adds three more alleles coded as A3, A4 and A5 alleles to the allele pool for the population as a whole. With more alleles in the pool, a larger proportion of the offspring will be heterozygotes. As heterozygotes, their chances of drawing right adaptive allele for future environments increases. Thus larger populations of unrelated trees often have more standing variation than smaller populations. Gene flow redistributes good and bad alleles among populations. To this example, now add many more populations of similar size. These populations will exchange pollen. Now our original reference population donates alleles A1 to A5 elsewhere but now let us assume that it receives alleles A6, A7 and A9 from an pool of outside pollen. Its own allele A5 might confer an adaptive benefit for the original popu­lation’s home site but migrant allele A7 is poorly adapted to its present conditions. Even so, this larger allele pool is beneficial insurance because it confers alleles with a wide range of adaptive value. This rich pool of alleles acts as a form of protection against uncertain environmental conditions of the future. Allelic richness, or genetic diversity, is insurance against future environmental changes. Chances are better than one of these many alleles will be well-adapted one should the future environment suddenly change. To see this, let us assume a prolonged drought. Most of the original population dies without having contributed seeds to the next generation. Those that do survive are assumed to have one or more copies of the A5 or A7 alleles. Strong selection has favored these genotypic classes and these survivors seeds. Conditions get worse until only those few seeds that are transported to a distant location can successfully colonize. This new colony now has a higher frequency of A5 and A7 alleles than its parental generation. Compare this scenario with the original two-tree population with A1 and A2 alleles. Lacking either A5 or A7, its fate would have been extirpation, not migration.

8.3 Forest Tree Populations Harbor High Genetic Diversity Forest tree species as a whole have exceptionally large number of alleles; in fact they harbor more allelic richness than other plants (Hamrick and Godt 1989). Such allelic richness, defined as genetic diversity, buffers long-lived forests against rapid climate change. The greater the genetic variation, the more the population becomes adapted to new environmental conditions brought by climate change (i.e. Pease et al. 1989;

8.3  Forest Tree Populations Harbor High Genetic Diversity

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Table 8.1  Some of the genetic and life history mechanisms by which Pinus species conserve, protect and maintain exceptional amounts of genetic variation Mechanism Benefits Perennial meiosis Millions of chances each year to reshuffle alleles into new combinations Heterospory Meiotic exchange is sex-specific; i.e. male gametes have higher crossover rates than female gametes Homogamic hybridization Open-ended hybridization introduces new alleles or ­co-adapted gene complexes rapidly High degree of mobility for Gene flow distributes alleles among populations, whether pollen and seeds beneficial or maladapted Multiple donors (or founders) New colonies start with large amounts of genetic variation for a new colony Delayed reproductive onset Allows for serial dispersal events and multiple donors to a new colony Higher the crown, faster the wind speeds and farther diaspores Increased pollen and seed production with age disperse above the forest canopy Self-avoidance Outcrossing promotes heterozygous offspring Elimination of self-fertilized Promotes heterozygous offspring seeds Seed banks Genetic variation present even if parent dies Cone serotiny Genetic variation builds up until fire disperses seed cohort at once Animal-dispersed seed caches Genetic variation present even if parent dies Spring pollen shed Peak synoptic convergence ensures passive transport via strong regional atmospheric systems Autumn seed ripening Peak synoptic convergence ensures passive transport via strong regional atmosphere systems

Rehfeldt et al. 1999). This great reservoir of genetic variation translates into a larger proportion of well-adapted survivors (Westfall and Millar 2004). Pines and other forest trees maintain or conserve this innate allelic richness through numerous mechanisms (Table 8.1). How is this large amount of genetic diversity is distributed within and among populations is critical to the question of climate change response (Hamrick 2004). So far, most of the studies are based on whole-organism measurements or selectively neutral DNA markers: more definitive studies have yet to emerge for adaptive alleles. This paradigm for genetic diversity rests on the assumption that neutral genetic variation serves as an adequate proxy for adaptive variation. The largest amount of this genetic diversity resides within a population, not among populations. Genetic variation measured within the Lost Pines population is also shared among many other Pinus taeda populations (i.e. Al-Rababah and Williams 2002). Large amounts of genetic variation are maintained via a number of mechanisms and life history attributes (Hamrick 2004; Table 8.1). Another feature is that genetic differentiation among populations tends to be low. This is true for single traits measured at the whole-organism level or selectively neutral molecular data (Harmick 2004). Less is known about adaptive genetic ­variation although the experimental capacity is rapidly changing and with it are emerging profiles of adaptive variation at the DNA sequence level.

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8.3.1 Gene Flow Strong selection without gene flow favors local adaptation of a population to its home site (Savolainen et al. 2004). Put another way, when locally adapted populations come into contact with other populations, they interbreed and thereby tend to lose local adaptations. Instead, their offspring acquire less favorable alleles or even maladapted alleles and so the next generation is suboptimally adapted to its home site. Gene flow thus dilutes or even reverses locally adaptive variation. Gene flow is also beneficial because it spreads the same alleles among all populations. It spreads maladapted alleles and those which are rare and beneficial. Gene flow is a doubleedged evolutionary force.

8.3.2 Locally Adapted Populations Historically large population sizes, long generation intervals and prolific reproduction all work against a forest tree population’s accumulation of locally adaptive alleles. The prevailing view is that temperate and boreal forest tree populations are prone to migrate and that they are better described as demographically unstable (Slatkin 1987). This also means that forest tree populations are rarely in equilibrium with the environmental conditions of their home site (Namkoong 1979; Rehfeldt et al. 1999; Westfall and Millar 2004; Savolainen et al. 2004; Aitken et al. 2008). This suboptimal adaptation, or departure from environmental equilibrium, has numerous synonyms in the scientific literature: it is commonly defined as non-local optimality of a population (Namkoong 1979). These large stores of genetic variation inherent to forest tree populations predispose them towards suboptimal adaptation or evolutionary lag (Westfall and Millar 2004). Suboptimal adaptation is common for long-lived forest tree species but a few exceptions do occur. One example can be seen via the centerperiphery model and its variants.

8.3.3 The Center-Periphery Model Populations which are reproductively separated from the rest of the range are more prone to develop local adaptation because they receive less incoming gene flow. This can occur with the center-periphery model. The center-periphery model is based on the abundant center concept, which is described as follows: a species colonizes a new geographic area. Its numbers become more abundant in that part of the range which favors its survival and reproduction. This favored part becomes more populated until it becomes the abundant center for this species. The opposite is true at the margin or periphery of the range. This peripheral population is surviving at the less

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favorable edge. The peripheral population is thus predicted to be smaller and more reproductively isolated by comparison to the abundant center’s population (GarciaRamos and Kirkpatrick 1997). Without gene flow, this small population is also to more prone to become locally adapted. Whether the peripheral population becomes locally adapted depends on key predictions about (a) how genetic variation is distributed between the center and its peripheral population and (b) how much gene flow, if any, occurs between the two. First, a peripheral population is sometimes has less genetic diversity than the center. Second, a peripheral population soon becomes more genetically differentiated than the center population. Third, a peripheral population receives little if any gene flow from its center population. Without gene flow, genotypic distribution in this small peripheral population will gradually shift, i.e. its offspring will be less and less heterozygous with each new generation. Cut off from gene flow with its center, the periphery population is predicted to diverge from the rest of the species. The center population has conditions which do not favor its local adaptation; instead it is adheres to the generalist strategy on the continuum. The peripheral population, in theory, is going in the opposite direction: it is inching closer to becoming locally adapted on that same continuum. Eventually the peripheral population may become highly vulnerable to extreme events such as climate change but it is also more likely to be locally adapted than the center population. Do these verbal generalizations about the center-periphery model hold for forest trees? Center-periphery model predictions do hold for forest trees in some cases but not in others (i.e. Gapare and Aitken 2005; Pautasso 2009). A survey of 115 plants and animal species (22% of the plants were pine species) shows that about two-thirds of these cases adhere to center-periphery theory (Eckert et al. 2008). This discrepancy is not surprising given that a present-day population’s distribution is a culmination of past migration, its response to the last round of climate change events, its capacity for dispersal and its capacity to rapidly migrate across physical barriers. Statistical deviation also plays havoc with whether populations are measured correctly (Gregorius and Roberds 1986). Even so, various forms of the center-periphery theory still serve as foundation for predicting how forest populations responded to Quaternary climate change events (Hewitt 2000; Davis and Shaw 2001; Hampe and Petit 2005). Two of these predictive evolutionary models hold relevance for the Lost Pines population.

8.4 Evolutionary Models for Predicting Climate Change 8.4.1 Retreating Edge Model This generalized evolutionary dynamics model is an important variant of the centerperiphery model (Fig. 8.1). As such, it describes how the range of a species shifts forward under rapid climate change. A species’ range has a leading edge population and a retreating edge population with all other populations wedged between the two.

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Retreating Edge Model (Davis and Shaw 2001)

Stable Rear Edge (Hampe and Petit 2005)

Dispersal is random, but differential survival subsequently sieves out any genotypes maladapted to local conditions

Occurs in a region suitable for species to persist under cold and warm intervals

Strong selection against poorly adapted phenotypes

Occurs in a region with local landscape heterogeneity, i.e. small elevational gradients

Retreating edge receives no gene flow (i.e. no seed or pollen) from better adapted populations

Occur in islands of suitable habitat within a matrix of unsuitable habitat

Adaptation of the retreating edge depends on its own standing variation

Small isolated regional population dynamics cannot compensate for local extinction events

Center of the range has more standing variation than the retreating edge population. Evolutionary lags in adaptation also cause poor growth and high mortality Retreating edge has restricted adaptation due to its lack of gene flow; these population are often extirpated, causing the species’ range to shift towards the leading edge. These genetic constraints on adaptation are likely to reduce the rate of adaptation below the rapid pace of climate change: extirpation is the end result.

Demographic stochasticity has only a minor role (contrary to center-periphery model) Prolonged isolation has reduced its withinspecies variation while raising its genetic differentiation from other populations Not a source of post-glacial recolonizations Selected for local adaptation, not for vagility and not for generalism Reduced gene flow has already led to a distinct ecotype

Fig. 8.1  Two evolutionary dynamics models, the retreating edge model and the stable rear edge model, are compared here. These provides a useful framework for predicting for how a set of forest populations within a species might respond to future climate change. Both are variants of the center-periphery model

The leading edge expands the species’ range via seed dispersal and so it harbors far more genetic diversity than expected (Hewitt 2000; Davis and Shaw 2001). At the other end of the species’ range is the retreating edge population. This refers to a special case of a peripheral population which is contracting or shrinking while receiving no gene flow from other populations. With less genetic diversity, the retreating edge is progressively less buffered against rapid climate change. At the same time, its neighboring populations are becoming better adapted but they contribute no gene flow to the retreating edge. Most of its seeds now disperse into areas no longer suited as habitat. This peripheral population is fated for extirpation (Davis and Shaw 2001). The retreating edge now undergoes intense natural selection against its maladapted individuals and so, without the buffering afforded by high genetic diversity, no

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amount of seed production from the retreating population can hold off extirpation. Ultimately, the retreating edge dies out, registering as a latitudinal loss to the species’ range as a whole. The entire range of the species is now seen as migrating forward, towards the leading edge’s new colonies. The retreating edge’s response is based on several assumptions, two of which are given here: (1) selection acts against those trees, or phenotypes, which are poorly adapted to local conditions and (2) its own pollen and seeds migrate to neighboring populations which may be better adapted. The retreating edge ultimately dies out and this extirpation begins with a population contraction. A population contraction, if severe enough can leave a DNA signature of a bottleneck.

8.4.2 Stable Rear Edge Model Unlike the retreating edge model, this model is based on another type of locally persistent peripheral population (Fig.  8.1). This stable, relictual population can persist indefinitely in reproductive isolation from the rest of the species’ range (Hampe and Petit 2005). Its persistence is favored by habitat conditions which are suitable during both glacial and interglacial cycles, whether climate is getting colder or warmer. This stable rear edge population usually occurs within a heterogeneous topography, i.e. “usually restricted to particular habitat islands within a matrix of unsuitable habitats” (Hampe and Petit 2005). Rather, this population has been a relictual resident long enough at this location that it has become locally adapted and thus it can evolve into a distinct ecotype. This stable rear edge population is quite vulnerable because it is so small and so reproductively isolated that it is poorly buffered against a local extinction event. At the same time, its small size and reproductive isolation serve to widen the genetic differentiation between itself and other populations within the species. The stable rear edge population can have high adaptive value to the rest of the species’ range.

8.5 Evolutionary Dynamics Models: Experimental Findings 8.5.1 Lost Pines: Retreating Edge or Stable Rear Edge? Aligning these two models with the Lost Pines is a good opportunity to present information as testable hypotheses. These hypotheses have already been tested using a set of selectively neutral molecular markers and a sample of the Lost Pines Pinus taeda population (Al-Rababah 2003). These marker data were analyzed using an appropriate statistical test. In each case, the expected test statistic was compared against the observed test statistic derived from the marker data. If the two test statistics are the same then we accept the null hypothesis: the peripheral population is not different from its center. The results are surprising and paradoxical:

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 ypothesis (1) The Lost Pines population has the same amount of genetic H diversity as the rest of the populations in the western part of the species range. The answer? True, this null hypothesis can be accepted. A set of Lost Pines samples originally selected from the Bastrop State Park area has the same levels of genetic diversity found in the larger, more continuous East Texas Piney Woods (Al-Rababah and Williams 2002, 2004). Two caveats accompany this statement: the first is that the Lost Pines samples here represented only a small part of the entire Lost Pines spectrum and the second is that only selectively neutral variation was measured in these studies, not adaptive variation. This is a standard assay but it is not a complete one either with regard to samples or the part of the genome sampled. The genetic diversity of the Lost Pines is similar to east Texas and other parts of the western Pinus taeda range. The Lost Pines population is not more homo­ zygous despite its disjunct status at the periphery of the species range. Note that these conclusions are based on selectively neutral genetic variation, not on adaptive variation. The only clue about the adaptive variation comes from traits measured at the whole-organism levels. The Lost Pines population does have some novel adaptations to drought-tolerance and thus it has been long considered to be an ecotype. Its seedlings appear to be more drought resistant (Zobel and Goddard 1955; Thames 1963; Youngman 1965; van Buijtenen 1966; Knauf and Bilan 1974). The Lost Pines findings do not adhere to the center-periphery model but they do have some relevance to the two climate change models and this warrants closer examination.  ypothesis (2) The Lost Pines population has had no contractions or bottlenecks H and if so, this distinguishes it from a stable rear edge. The answer? This null hypothesis can be rejected. These Lost Pines samples2 have had one or more severe contractions or bottlenecks (Table  8.2). The bottleneck signature is present for present-day Lost Pines accessions and for other westernedge populations in southeast Oklahoma (Al-Rababah and Williams 2004). Bottleneck events for the Lost Pines population occurred between 30,000 and 3,000 year BP, an unusually wide range of dates spanning Pleistocene glaciation to the late Holocene (Al-Rababah and Williams 2004). Note too populations do not always lose their genetic diversity as a consequence of a bottleneck event (Betancourt et al. 1991).

The present-day Lost Pines is not only the consequence of local persistence or distant migration but also an admixture of late arrivals, splits and mergers. Its aggregate of progenitor populations have expanded, contracted, divided again or even vanished. All that remains are DNA signatures. Population expansion leaves one type of DNA signature while its contraction leaves another.

2

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Table 8.2  DNA-based signature for one or more bottleneck events is detected for the Lost Pines (LP) population yet notably absent in the northeastern Pinus taeda populations (NE includes North Carolina) region Popn Sign Test (TPM) SDT (TPM) 2-Tailed Model LP .01094 .00285 .00125 No OK .00672 .00620 .00304 Shift NE .36894 .23677 .07297 No As expected, the bottleneck test statistics are even more pronounced for Pinus taeda populations in eastern Oklahoma (OK) which are also at the westernmost edge of the species range (Al-Rababah and Williams 2004)

8.5.2 A Local Paleoclimate Model The Lost Pines population has some features common to both the retreating edge and the stable rear edge models yet a number of its features, as shown, are not consistent with either. This is presented as a localized model which can account for the less congruent features of Lost Pines population. These are as follows: (a) high levels of genetic diversity, (b) it is not strongly differentiated from other populations and (c) it has a high census population although it presents a history of bottleneck events. So far, this curious population has few indications of being reproductively isolated and, like the other Texas Pinus taeda populations, it has a history of introgression. As such, the Lost Pines population does not adhere to the earlier predictions for a true peripheral population. These findings have led to a paleo-climate synthesis specific to the Lost Pines population of central Texas (Table 8.3). Its major assumption is that Pinus taeda population has been locally persistent within its present area for at least 5,000 years or longer (Al’Rabaah 2003; Al-Rababah and Williams 2004). If so, then its local persistence might be explained by its history of introgression. Hybridization with Pinus echinata can provide an immediate source of adaptive alleles as well as add its reservoir of available genetic variation. As a consequence, the Lost Pines population could be more robust to climate change than either the retreating edge or stable rear edge would predict.

8.6 Closing Short-term evolutionary processes shape a population’s response to climate change. At the start is an anecdotal introduction conveying the value of allelic richness, or genetic diversity as a hedge against loss, a biological insurance policy, for the uncertainty of future climate change. These long-lived perennial plants have exceptionally large amounts of genetic diversity so the crux of the matter shifts to whether forest tree populations such as the Lost Pines are locally adapted or whether they are transient generalists; if the latter then they are more prone to a migratory response as a climate change response. A notable exception might be the center-periphery model and its two variants: the retreating edge model and the stable rear edge model.

Demographic contractions and expansions of the Lost Pines population Expansion of pine forests along Colorado River (paleosoils theory)

Cycles of mild wet and dry periods with dry periods of increasing duration

Cooler, more mesic than present

Early Holocene 11,000–5,000 year BP

Late Pleistocene and Pre-Holocene (11,000–21,000 year BP)

(Sorenson et al. 1976; Bryant and Holloway 1985; Toomey et al. 1993)

(Bryant and Holloway 1985; Toomey et al. 1993; Bousman 1998; Musgrove et al. 2001)

(Bryant and Holloway 1985; Toomey et al. 1993; Brown 1998; Goodfriend and Ellis 2000; Russ et al. 2000)

Sharp genetic bottleneck ameliorated by slow periods of population expansion

Local expression of Altithermal Prolonged dry period (drier than present conditions) with few short wet periods

Middle Holocene 5,000–2,500 year BP

(Toomey et al. 1993; Brown 1998; Goodfriend and Ellis 2000)

Lost Pines recolonized by locally persistent survivors

Warm and wetter than present

2,500–1,500 year BP

Table 8.3  A proposed model for the Lost Pines population of central Texas (altered from Al-Rababah and Williams 2004). The major assumption for this model is that this Pinus taeda population was locally persistent within its present area for at least 5,000 years or longer (Al’Rabaah 2003). As such, this population has some features of the retreating edge and the stable rear edge models yet it has features which are not predicted by either model: it has high levels of genetic diversity, it is not differentiated from other populations nor is it a true peripheral population. As shown for other Texas populations, the Lost Pines population has evidence of introgression with Pinus echinata (Modified from Al’Rababah and Williams 2004) Proposed Lost Pines population Time Paleoclimate in Central Texas response References Late Holocene 1,500 year BP Prolonged warm dry conditions with Demographic contractions and (Toomey et al. 1993; Brown 1998; few wet cycles expansions Russ et al. 2000)

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These ­provide a sturdy theoretical framework for testing our assumptions about the geographically isolated Lost Pines population. Testing adaptive variation for the Lost Pines population is a missing piece of this puzzle; selectively neutral DNA tested here offers an incomplete profile of its genetic variation. Throughout this chapter, human impact has been temporarily suspended. Evolutionary models, especially those which draw on past climate change, omit human impact so the next chapter incorporates human impact into short-term evolutionary processes on the question of what to plant. Reforestation programs must address the quality of the forest cover, not only its quantity. As humans, we now determine the genetic composition of the planted forest and evolutionary models must be applied towards planting more genetic diversity. What is planted from now forward in the Lost Pines area now will influence the genetic composition of forests under climate change. These future forests can stabilize climate change and they will come to maturity under decades of uncertainty. The best protection against their premature loss is genetic diversity and how much genetic diversity to plant is human-mediated. Whether or not a certain tree will be a parent to the next generation or now is determined by artificial selection. The technology for managing genetic diversity explicity is the best available yet.

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Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspect Plant Ecol Evol Syst 11:157–189 Pease C, Lande R et al (1989) A model of population growth, dispersal and evolution in a changing environment. Ecology 70:1657–1664 Petit R, Hu F et al (2008) Forests of the past: a window on future changes. Science 320:1450–1451 Pielke R, Garstang M et al (1987) Use of a synoptic classification scheme to define seasons. Theor Appl Climat 38:57–68 Plotnick R, Gardner R (2002) A general model for simulating the effects of landscape heterogeneity and disturbance on community patterns. Ecol Modell 147:171–197 Price R, Liston A, Strauss S (1998) Phylogeny and systematics of Pinus. In: Ecology and biogeography of pinus. Cambridge University Press, Cambridge Pyne SJ, Andrews PL et al (1996) Introduction to wildland fire, 2nd edn. John Wiley & Sons Inc, New York Quarterman E, Keever C (1962) Southern mixed hardwood forest: climax in the southeastern coastal plains U.S.A. Ecol Monogr 32(2):167–185 Rehfeldt G, Ying C et al (1999) Genetic response to climate in Pinus contorta: niche breadth, climate change and reforestation. Ecol Monogr 69:375–407 Remington CL (1968) Suture-zones of hybrid interaction between recently joined biotas. Evol Biol 2:321–428 Richardson D, Rundel P (1998) Ecology and biogeography of pinus: an introduction. In: Richardson D (ed) Ecology and biogeography of Pinus. Cambridge University Press, Cambridge, pp 3–46 Richardson DM, Williams PA et al (1994) Pine invasions in the Southern Hemisphere: determinants of spread and invadability. J Biogeogr 21:511–527 Righter F, Duffield J (1951) Interspecies hybrids in pines: A summary of interspecific crosses in the genus Pinus made at the institute of forest genetics. J Hered 42:75–80 Robledo-Arnuncio J (2011) Wind pollination over mesoscale distances: an investigation with scots pine. New Phytol 190:222–233 Rockman M (2010) New world with a new sky: climate variability, environmental expectations, and this historical period of eastern North America. Hist Archaeol 44:4–20 Rogers C, Levetin E (1998) Evidence of long-distance transport of mountain cedar pollen into Tulsa Oklahoma. Intl J Biometeorol 42:65–72 Rousseau D-D, Schevin P et al (2006) New evidence of long distance pollen transport to southern Greenland in late spring. Rev Palaeobot Palynol 141:272–286 Rousseau D-D, Schevin P et  al (2008) Long-distance pollen transport from North America to Greenland in the spring. J Geophysical Res Biogeosci 113:1–10 Russ J, Lloyd DH et al (2000) A paleoclimate reconstruction for southwestern Texas using oxalate residue from lichen as a paleoclimate proxy. Quat Int 67:29–36 Russell D, Rich F et al (2009) A warm thermal enclave in the Late Pleistocene of the southeastern United States. Biol Rev Camb Philos Soc 84:173–202 Savolainen O et al (2004) Gene flow and local adaptation in forest trees. Ann Rev Evol Evol Syst 38:595–619 Saylor L, Kang K (1973) A study of sympatric populations of Pinus taeda L and Pinus serotina Michx in North Carolina. J Elisha Mitchell Soc 89:101–110 Schafale MP, Harcombe PA (1983) Presettlement vegetation of Hardin-County Texas. Am Mid Nat 109(2):355–366 Schmidtling R (1994) Use of provenance tests to predict response to climate change: loblolly pine and Norway spruce. Tree Physiol 14:805–817 Schmidtling R et al (1999) Allozyme diversity of selected and natural loblolly pine populations. Silvae Genetica 48:35–45 Schuster W, Mitton B (2000) Paternity and gene flow dispersal in limber pine (Pinus flexilis James). Heredity 84:348–361 Slee M (1970) Crossability values within the slash-Caribbean Pinus species complex. Euphytica 19:184–189

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Smith S, Beaulieu J (2009) Life history influences rates of climatic niche evolution in flowering plants. Proc R Soc B Biol Sci 276:4345–4352 Smith S, Donoghue M (2008) Rates of molecular evolution are linked to life history in flowering plants. Science 322:86–89 Smouse P, Saylor L (1973) Studies of the Pinus rigida-serotina complex. II. Natural hybrids among Pinus rigida-serotina complex, P. taeda, P. echinata. Ann Mo Bot Gard 60:192–203 Soltis D et  al (2006) Comparative phylogeography of unglaciated North America. Mol Ecol 15:4261–4293 Streng DR, Harcombe PA (1982) Why don’t east Texas savannas grow up to forests? Am Midl Nat 108(2):278–294 Stults D, Axsmith B et al (2010) Evidence of white pine (Pinus subgenus Strobus) dominance from the Pliocene northeastern Gulf of Mexico coastal plain. Paleogeogr Paleoclimatol Paleoecol 287:95–100 Thames JL (1963) Needle variation in loblolly pine from four geographic seed sources. Ecology 44(1):168–169 Toomey RS et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Tyldesley JB (1973) Long-range transmission of tree pollen to Shetland. I. sampling and trajectories. New Phytol 72:175–181 van Buijtenen JP (1966) Testing loblolly pines for drought resistance. Texas A&M University, College Station Wade DD, Brock BL, et al (eds) (2000) Wildland fire in ecosystems: effects of fire on flora. General Technical Report RMRS-GTR-42, USDA Forest Service Rocky Mountain Research Station Wahlenberg W (1960) Loblolly pine: its uses, ecology, regeneration, growth and management. Duke School of Forestry & USDA Forest Service, Washington DC Wang X-R, Szmidt A et al (2001) Genetic composition and diploid speciation of a high mountain pine, Pinus densata, native to the Tibetan plateau. Genetics 159:337–346 Wells P (1970) Postglacial vegetational history of the Great Plains. Science 167:1574–1582 Wells O, Wakeley P (1966) Geographic variation in survival, growth and fusiform-rust infection of planted loblolly pine. For Sci Monogr 11:40 Wells OO, Switzer GL et al (1991) Geographic variation in Mississippi loblolly pine and sweetgum. Silvae Genetica 40:105–119 Westbrook J, Isard S (1999) Atmospheric scales of biotic dispersal. Agric For Meteorol 97: 263–274 Westfall R, Millar C (2004) Genetic consequences of forest population dynamics influenced by historic climate variability in the western USA. For Ecol Manag 197:159–170 Williams G (1975) Sex and evolution. Princeton University Press, Princeton, 210 p Williams C (2008) Aerobiology of Pinus taeda pollen clouds. Can J For Res 38:2177–2188 Williams C (2009) Conifer reproductive biology. Springer Publishers, Dordrecht Williams C (2010) Long-distance pine pollen still germinates after meso-scale dispersal. Am J Bot 97:1–11 Willyard A, Cronn R et al (2009) Reticulate evolution and incomplete lineage sorting among the ponderosa pines. Mol Phylogenet Evol 52:498–511 Xu S, Tauer C et al (2008) Natural hybridization within seed sources of shortleaf pine (Pinus echinata Mill.) and loblolly pine (Pinus taeda L.). Tree Genet Gen 4:849–858 Youngman AL (1965) An ecotypic differentiation approach to the study of isolated populations of Pinus taeda in south central Texas. University of Texas, Austin Zobel B (1953) Are there natural loblolly-shortleaf hybrids? J For 51:494–495 Zobel BJ, Goddard RE (1955) Preliminary results on tests of drought hardy strains of loblolly pine (Pinus taeda) L. Texas A&M University, College Station

Part IV

A First Approximation for the Future

Back to the Future (1985) Dr. Emmett Brown I remember when this was all farmland as far the eye could see. Old man Peabody owned all of this. He had this crazy idea about breeding pine trees.

Alfred Russel Wallace Island Life (1880) When, however, we consider the enormous quantity of seeds produced by plants; that the great numbers of these are more or less adapted to be carried by the wind; and that winds of great violence and long duration occur in most parts of the world, we are as sure that seeds must be carried to great distances as if we had seen them carried. Such storms carry leaves, hay, dust, and many small objects to a great height in the air, while many insects have been conveyed by them for hundreds of miles out to sea and far beyond what their unaided powers of flight could have effected.

The Lost Pines population is a proven drought-adapted resource for the rest of the Pinus taeda range and thus it could be an evolutionary jackpot for adaptive variation in the future. The genetic composition of its future forests should thus be managed as an insurance policy. This is feasible because, we humans now determine the genetic composition of the planted forests. It is our choice as to whether to manage in parallel to those evolutionary processes or short-circuit its reservoirs of adaptive genetic variation. Resource managers must be explicit on managing short-term evolutionary processes. Whether forest is planted or not, evolution is ultimately the architect of its response to climate change. This section brings us to the first approximation for gauging the Lost Pines forest will fare under human-induced climate change over the next century. The first half is the genetic composition of the planted forest and the other half is managing the standing forest. Together this first approximation lays a foundation for decades to comes, a placeholder for better information. The genetic composition of planted Pinus taeda forests is human-mediated. If forests planted now are to survive climate change then we must recognize, and act in accordance with the evolutionary dimensions of human-induced climate change.

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Managing the genetic diversity of the seedlings planted in the Lost Pines area is a hedge against large-scale loss and Pinus taeda breeding populations still have large reservoirs of genetic diversity to draw upon. Using scientific precision to maximize genetic diversity within the bounds of local adaptation is more akin to managed evolution than the path towards domestication. Much of the Lost Pines forest is well past harvest age and so its response to climate change must be conditioned on its unusual demography. Whether the Lost Pines forest will be locally persistent over the next few decades will hinge on the degree of its local adaptation as well as the degree of abiotic stress. Its environmental stress levels depends on (1) the manner in which climate change alters the drought-prone headwaters of the Colorado River and (2) whether the WilcoxCarrizo aquifer is mined or managed to the benefit of the springs and seeps which sustain this climate change anomaly, (3) wildfire management and (4) its losses under increased hurricane severity. These outcomes assume no outbreaks of pests and pathogens, new or old. Whether the Lost Pines forest will migrate is now less dependent on its inherent life cycle and on its surrounding land-use obstacle course. Its chief barrier for migration has been its narrow realized niche but now new land uses have created a highly fragmented landscape. Both present hit-or-miss challenges to its long-distance seed dispersal, a capacity which is as-yet to be determined. Instead, assisted colonization can guide its migratory route. Likewise, expanding local tree planting programs is another hedge against large-scale loss of the Lost Pines forest. All responses to climate change bring loss. Whether local persistence or migration, some losses to the Lost Pines forest are inevitable. Large trees are more vulnerable than younger ones to extreme weather events; both are susceptible to fire. Still, this is a colonizing species given to regenerating gaps and its losses could prove to be a transient state. Species such Pinus taeda originated under prolonged and severe disturbance and are thus likely to survive in an analogous situation of human-induced change. Pinus taeda is a synanthropic species and its loss is often followed by renewal. Forests are dynamic, not permanent fixtures on a landscape. Once global forecasts and scientific principles can be translated into ecologically realistic scenarios then new priorities will sharpen in focus while others, now thought to be vital, will shrink. Scale matters when it comes to climate change and forests alike.

Chapter 9

Genetic Composition of the Planted Forest

9.1

Introduction

A Pinus taeda seedling planted now, in 2011, will reach harvest age by 2046, which well into the timeframe for human-induced climate change. What should its genetic composition be in order to maximize its survival to harvest age or beyond? This question falls to the resource manager and the forest landowner but their seedling choices are narrowly dependent on other choice made along the seedling supply chain. The good news about this part of the first approximation is that maximizing genetic diversity of planted forests is still feasible and it can be scientifically precise. Forest tree species such as Pinus taeda are not fully domesticated (Fig. 9.1). Tree improvement programs1 in the U.S. South have recognized and conserved the large reservoir of genetic variation inherent to forest tree species. It took decades decipher the patterns of genetic variation and then even longer to match an adapted seed source to the right physiographic region. This was possible because profound adaptive differences do exist among populations within a species. But these efforts have taken decades, large land areas, highly educated personnel and long-term institutional stability. Such a steep investment has paid off handsomely for Pinus taeda and the Lost Pines population. So when it comes to weathering future climate change, the Lost Pines population may prove to be an evolutionary jackpot for the rest of the Pinus taeda range. Its genetic variation is still substantial, it has some measure of local adaptation and it can be managed to the benefit of planted forest here in central Texas and elsewhere. It may have drought-tolerant adaptive alleles yet to be identified which can be bred into other populations, if they are not present already. Even so, forestry is sharply divided as to where to go next.

1

Tree improvement has a goal is to improve the genetic value of the population while maintaining genetic diversity. As such, each tree improvement program must be designed to fit not only the life history and natural range of the species but also the organization’s planting schedule, annual budget and harvest goals.

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_9, © Springer Science+Business Media B.V. 2012

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Genetic Composition of the Planted Forest Complete Domestication

Stage 3) Intensive management Reverse and forward genomics methods High potential for genetic modification (GM)

Stage 2) Advanced generation seed or propagules Marker-assisted breeding & selection for varietals Mostly exotic species, few indigenous species Stage 1) Early-generation population improvement Mostly indigenous species, few exotics Longer timber rotations in temperate & boreal regions

• Relies on human intervention • Phenotypic differentiation • Modified to suit human needs

3) Semi-domestication

2) Early-stage Population improvement 1) Known, improved seed source

Indigenous or naturalized exotic species Both known & unknown seed or propagule sources Shelterbelts, windbreaks, agroforestry, multipurpose

Not domesticated

World’s planted forests

Fig. 9.1 State of domestication for forest tree species planted for timber (Modified from Williams 2010)

Some believe forestry should intensify forest trees as tools bent to human use and this means complete molecular domestication of a few choice genotypes for planting. Others want the same scientific precision to work towards managing genetic diversity so that forests survive climate change as resilient living bulwarks. There is no clear agreement at this time. This book weighs in the side of managing forests as living bulwarks, not as tools, and this option is still possible because Pinus taeda and other forest trees are largely undomesticated (Fig. 9.1). Tree improvement programs still have a wealth of genetic resources for this species because most manage for genetic diversity.

9.2

Forest Trees Are Largely Undomesticated

Domestication is commonly defined here as the case when a plant or animal is modified for human use to such an extent that it is dependent upon human intervention for its survival. Another comes from crop breeding: Allard (1960, p. 28) stated “Domestication as the bringing of a wild species under the management of humans.” Under either definition, even most intensively managed forest tree species are only

9.2 Forest Trees Are Largely Undomesticated

153

semi-domesticated (Fig. 9.1; Williams 2010) and Pinus taeda has programs at all of these stages. Note that tree improvement programs are largely undomesticated because they are different from agricultural crop breeding programs and this emphasis on population-level improvement and large population sizes can be traced to the genetic diversity imperative. Emphasis on genetic diversity has paid off. Tree improvement programs worldwide have enjoyed one of the longest investment runs in recorded forest history. Governments, private enterprise and universities still work in concert for enhancing breeding populations.

9.2.1

Stage 1 Improved Seed Source

This stage includes forest tree species which have stabilized at an early-stage tree improvement program.2 These meet planting needs for many low-cost agroforestry species, species with limited planting demand, species which are poorly adapted to plantation silviculture or programs dedicated solely to gene conservation. These are low-resource or low-demand programs which have a goal to supply a reliable seed source for planting.

9.2.2

Stage 2 Early Domestication

This type of planted forests provides industrial raw materials on a large planting scale. The single species used here for plantations may be indigenous or exotic but these planted forests are intensively managed. Advanced tree improvement, also known as recurrent tree breeding programs, is the norm at this stage. New choices are constantly available with each new breeding-testing-selecting cycle and now breeding and production populations are clearly separated. The breeding program might have high genetic diversity levels or large numbers of genotypes but this is now uncoupled from its downstream production population and the production is the actual source of planting stock. Planting stock tends to have far fewer genotypes than the breeding population so what is planted does not represent the full reservoir of available genetic diversity.

2 Many tree improvement programs halted at this early stage. In 1980, Gene Namkoong and his coauthors Richard Barnes and Jeff Burley wrote “Tree breeding is now an accepted activity in approximately half of the countries of the world…the breeding strategy has stopped at the first generation concepts of selection, progeny tests and clonal or seedling seed orchards.” Three decades later, this is still true.

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Box 9.1 How Tree Improvement Programs Use Genomics Public-domain DNA sequence data are available for Pinus taeda and these data allow identification of those parts of the Pinus taeda genome which are selectively neutral and those parts which confer an adaptive advantage during prolonged drought or some other abiotic stress. Managing sequence-based adaptive alleles (sensu Eckert et al. 2010) is also feasible so how many adaptive alleles segregating in a population can be determined and allele number for seedling sales can now be specified to the nearest nucleotide. This starts with genome scans using functional genes which influence drought stress (i.e. Eckert et al. 2010). This particular study looked at 1730 genes in 682 Pinus taeda genotypes across the species range. A number of these genes showed genetic differentiation; many function for drought stress and this is critical for population persistence in drought-prone areas such as the Lost Pines. Next, these findings can be incorporated into a tree improvement program (Fig. 9.2). In this case, forward genomics moves from the trait values measured at the whole-tree or phenotypic level to the tree’s DNA-based genotype. This is coupled with reverse genomics, or gene-based approaches.3 Both is used together to identify, verify and track specific segments of that same genotype which influence the trait of interest (Grattapaglia et al. 2008). This enhanced further by tracing which progenitor or founder transmitted certain chromosomal segments within a candidate’s genome (Williams and Reyes-Valdés 2007; Reyes-Valdés and Williams 2002).

9.2.3

Stage 3 Semi-domestication

This stage uses the most sophisticated forest biotechnology portfolio yet. The portfolio includes the recurrent tree breeding of Stage 2 but added here are wholegenome sequencing, backward and forward genomics and unlimited clonal replication of a single genotype. To this list, one can add genetic engineering (GE) or genetic modification (GM) which refers broadly to inserting DNA sequences from Pinus taeda, other forestry or non-forestry species. Recombinant DNA technology is the current method but this and other methods can be broadly defined as altering genomes via the insertion of genes. Another innovation can be added to this growing list: tracing desirable DNA segments, or haplotypes, through a pedigree or a hybrid cross. Of particular interest

3 Analyzing DNA sequence data has shifted to the elucidation of gene function and this is defined as functional genomics. Gene function is determined by using sequence alignment-based comparisons, by identifying homologs between and within organisms, by transcript profiling to determine gene expression patterns for small numbers of transcripts and by other methods suited to identifying metabolic pathways, gene networks and protein complexes.

9.3

Genetic Diversity as an Imperative

155

Forward genomics

Phenotypic Trait Values

Genomics

Reverse genomics Large-insert DNA portions (BACs) 500 to 1000 bp 10 cM

Gene expression Transcriptional Sequencing

<0.1 cM

Linkage Map Stress tolerance Allele numbers Introgressants

Gene Identity & Validation

Candidate genes Functional screening

Fine-Scale Whole-genome sequencing, Linkage assembly and Map annotation

Fig. 9.2 Example of a genomics-based selective breeding program suited to selecting for sequencebased adaptive alleles. Trait values are based on the phenotypic value of an individual tree. Forward genomics is trait-based while reverse genomics is gene-based. Reverse genomics refer to methods which identify, test and validate specific genes controlling the trait of interest. The most sophisticated forest biotechnology portfolios now use both forward and reverse approaches (Modified from Grattapaglia et al. 2008)

here is knowing which parents or perhaps which parental species contributed one or more adaptive alleles. Consider a hypothetical example where a particular DNA haplotype is traced from Pinus echinata parent into a Pinus taeda pedigree. The total chromosomal contribution of each grandparent can be traced through to its descendants. Doing so would make hybridization and introgression more explicit as immediate sources of adapted alleles.

9.3

Genetic Diversity as an Imperative

Conserving genetic diversity has long been high priority because forests are longlived, environmental conditions can shift over the course of their lifespan and they grow in less managed ecosystems (Namkoong et al. 1988). This thinking applies in the planted forests of U.S. South and other mid- to higher latitudes where harvest ages tend to be longer than those at equatorial latitudes. Early generations did an admirable job of conserving genetic diversity while making population-level improvements in commodity traits such as growth and disease resistance (i.e. Williams et al. 1994) but this same genetic diversity does not automatically translate into what is available for planting. This depends on the

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Box 9.2 Somatic Embryogenesis Seedling delivery systems have made massively changed over the past decade. Breeding and production programs are now separate and so the more sophisticated delivery systems now have the untapped potential to deliver an infinite number of same exact Pinus taeda genotype. This potential comes from somatic embryogenesis and this process refers to cloning a small group of vegetative cells which is stem-cell like. A few of these cells are induced on culture media to undergo tissue differentiation. Potential multiplication rates, particularly from cell suspension cultures, are extremely high. Rather than seedlings, these are known as emblings. Somatic embryogenesis can deliver unlimited copies of the same genotype on a commercial scale. This one of several technology changes for seedling delivery.

seedling producer and many low-cost shortcuts are now available (Box 9.2). Resource managers and private forest landowners have not shown high-precision scientific interest in the particulars of their planting stock. Their traditional focus has been on seedling survival and perhaps the best price. Educated consumers can shape markets and product availability. The trend now is towards sales of few genotypes or related genotypes in seedling markets and this will only change if consumers change.

9.4

Closing

Managing genetic diversity at the seedling sales end is not fully available yet for many Pinus taeda programs but the potential is there. This requires making the case for the managing forests using evolutionary principles and doing so calls for a sophisticated working knowledge of how adequate genetic variation can be detected in seedlings. This knowledge is the modern equivalent of the genetic diversity imperative. It can rely on the same scientific precision which has been dedicated to human health and food supplies. Genetic diversity is a form of insurance for forest landowners which can be measured. In scientific terms, a seedling buyer should be able to custom-order Pinus taeda seedlings well-suited to abiotic stress and combine this with a request for the maximum numbers of well-adapted alleles configured in optimal combinations. Whether this emerges as an market option for seedling buyers has yet to be seen. Managing genetic diversity in this way ideally is a hedge against some types of large-scale loss and if so then evolutionary dynamics models enter forest management as a form of insurance under climate change. Steering the evolutionary direction of the planted forests but this direction need not be adverse. In practice, genetic diversity can and should be kept high. Doing so matters more than ever. Such an endeavor is costly

References and Related Readings

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and it calls for more research, for more transparency behind seedling sales, better forest planting incentive programs and for better-educated seedling buyers. Consider that the Lost Pines population has the highest chances of being locally adapted to prolonged drought and here could be the preferred source of well-adapted seed and seedlings outside of its current region.

References and Related Readings Allard RW (1960) Principles of plant breeding. Wiley, New York, 485 p Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. In: The late quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Austerilitz F, Mariette S et al (2000) Effects of colonization processes on genetic diversity: differences between annual plants and tree species. Genetics 154:1309–1321 Bartlein PJ, Anderson KH et al (1998) Paleoclimate simulations for North America over the past 21,000 years: features of the simulated climate and comparisons with paleoenvironmental data. Quat Sci Rev 17(6–7):549–585 Batista W, Platt W (2003) Tree population responses to hurricane disturbance: syndromes in a southeastern USA old-growth forest. J Ecol 91:197–212 Blum M, Valastro S (1994) Late Quaternary sedimentation, lower Colorado River, Gulf Coastal Plain. Geol Soc Am Bull 106:1002–1016 Clark JS, Fastie C et al (1998) Reid’s paradox of rapid plant migration: dispersal theory and interpretation of paleoecological records. BioScience 48:13–24 Darlington P (1938) The origin of fauna of the Greater Antilles, with discussion of dispersal over animals over water and through the air. Q Rev Biol 131:274–300 Dutton A, Nicot J et al (2006) Hydrodynamic convergence of hydropressured and geopressured zones, Central Texas, Gulf of Mexico Basin, USA. Hydrogeol J 14:859–867 Dynesius M, Jansson R (2000) Evolutionary consequences in species geographic distribution driven by Milankovitch climatic oscillations. Proc Nat Acad Sci USA 97:9115–9120 Eckert A, Bower A et al (2010) Back to nature: ecological genomics of loblolly pine (Pinus taeda L.). Mol Ecol 19:3789–3805 Gislén T (1948) Aerial plankton and its conditions of life. Biol Rev Camb Philos Soc 23:109–126 Grattapaglia D et al (2008) Genomics of growth traits in forest trees. Curr Opin Plant Biol 12:148–156 Grimm E, Jacobson G Jr et al (1993) A 50,000-year record of climate oscillations from Florida and its temporal correlation with Heinrich events. Science 261:198–200 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: Milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Katul G, Poporato A et al (2005) Mechanistic analytical models for long-distance seed dispersal by wind. Am Nat 166:368–381 LePage B (2003) The evolution, biogeography and paleoecology of the Pinaceae based on fossil and extant representatives. Acta Horticult 615:29–52 Magsig M, Snow J (1998) Long-distance debris transport by tornadic thunderstorms. Part 1: The 7 May 1995 supercell thunderstorm. Mon Weather Rev 126:1430–1449 Marris E (2009) Planting the forest of the future. Nature 459:906–908 McKenney D, Pedlar J et al (2007) Potential impacts of climate change on the distribution of North American trees. BioScience 57:939–948 Namkoong G, Barnes RD et al (1980) A philosophy of breeding strategy for tropical forest trees. University of Oxford, Department of Forestry, Commonwealth Forestry Institute, Oxford, UK Namkoong G et al (1988) Tree breeding: principles and strategies. Springer, New York, 180 p

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Rehfeldt G, Tchebakova N et al (2002) Intraspecific responses to climate in Pinus sylvestris. Glob Change Biol 8:912–929 Reyes-Valdés MH, Williams CG (2002) A haplotypic approach to founder-origin probabilities and outbred QTL analysis. Genet Res 80:231–236 Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Visher S (1925) Tropical cycles from an ecological viewpoint. Ecology 6:117–122 Wallace A (1880) Island life. Prometheus Books, New York (1998) Westfall R, Millar C (2004) Genetic consequences of forest population dynamics influenced by historic climate variability in the western USA. For Ecol Manag 197:159–170 White P, Pickett S (eds) (1985) Natural disturbance and patch dynamics. The ecology of natural disturbance. Academic, San Diego Williams C (2008) Aerobiology of Pinus taeda pollen clouds. Can J For Res 38:2177–2188 Williams C (2009) Conifer reproductive biology. Springer, Dordrecht Williams C (2010) Of forests and time in the culture of possession. Int For Rev 12:407–417 Williams CG, Reyés-Valdes MH (2007) Estimating a founder’s genomic proportion for each descendant in an outbred pedigree. Genome 50:289–296 Williams CG, Hamrick JL, Lewis PO (1994) Genetic diversity levels in a multiple population breeding strategy: a case study using Pinus taeda L. Theor Appl Genet 90:384–394 Williams CG, LaDeau SL, Oren RA, Katul GG (2006) Modeling seed dispersal distances: implications for transgenic Pinus taeda. Ecol Appl 16(1):117–124 Willis K et al (2007) How can knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies. Philos Trans R Soc Lond 362:175–186 Xi W et al (2008) Tree damage and risk factors associated with large infrequent wind disturbances of Carolina forests. Forestry 81:317–334 Zeng H, Chambers J et al (2009) Impacts of tropical cycles on U.S. forest tree mortality and carbon flux from, 1851 to 2000. Proc Nat Acad Sci USA 106:7888–7892

Chapter 10

Managing the Existing Forest

10.1

Introduction

Most of the standing forest, now burned, is presented in the present tense. Its younger stands, many of which are now 60 years old, will reach 100 by 2050. The older trees in Bastrop State Park are those which were seedlings when Sargent came through in 1880 and these will be 180 years in the year 2050 but these advanced ages are not even halfway through the lifespan of 300 to 400 years. How will this standing forest fare under human-induced climate change? This is the next part of what is defined here as the concept of evolutionary forest management (Fig. 10.1). Evolutionary forest management provides some guidance on the question of how will this part of the Lost Pines forest respond to human-induced climate change? To address this next part of the first approximation, the Lost Pines ecosystem is aligned with progressive losses starting with local persistence then either migration or extirpation. Losses occur throughout but they can also be transient. The prevailing assumption here is keeping the Lost Pines forest alive and in place remains a priority in the future even under severe water, wildfire, hurricanes and/or energy scarcity.

10.2

A First Approximation

Progressive loss is cohesive constant for how forest tree populations actually respond to climate change in general. Early losses begin when the population is stressed to its physiological limits at its home site and individuals within this population have no more adaptive alleles within the reservoir of genetic variation. Local persistence comes to an end when these adult survivors die and leave no offspring. Migration, the next stage, is the next option if this population had already reached reproductive onset before it expired and if some of its seeds dispersed and colonized elsewhere. This population was now well into its winnowing process, i.e. natural selection, and such winnowing might favor retention of adaptive alleles; C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1_10, © Springer Science+Business Media B.V. 2012

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Evolutionary Forest Management Under Climate Change Predicted Range Shift

+

Bioclimate Envelope (BCE) Predicts Futue Species Range Coupled with Current Range + Its Climatic Variables Global Circulation Models (GCM) or Earth Systems Models

Evolutionary Dynamics Models Evolutionary Dynamics Models Inform Regional Decisions on Genetic Composition & Stand Vulnerability Forest Ecosystem as Anchor + Its Temporal Records Alignment Past Evolutionary Response + Life Cycle, Genetic Mechanisms, Common Garden Studies and Other Populations Survey

Fig. 10.1 Evolutionary forest management is a concept which emerges from anchoring evolutionary dynamics models to the particulars of a given forest ecosystem. The evolutionary past of the species, its life cycle and population surveys shape how that ecosystem will fare under climate change. This requires moving across spatial scales, from planetary to local, and across time scales from present-day to millions of years (MY)

if so disproportionate numbers of these alleles too will be carried elsewhere by those migrating seeds. Alternatively, if none of its offspring colonized elsewhere then the last survivors has come to its end and this is extirpation. Progressive loss is only a generalization. Short-term evolutionary processes shape each population within its ecological context and such is the case for the Lost Pines population.

10.2.1

A Scenario for Local Persistence

Managing for local persistence is the best option for the Lost Pines community although it is difficult as a practical solution. Some prescriptives include planting more seedlings from locally adapted sources and managing genetic diversity of those seedlings explicitly. Planting in urban areas, windbreaks, urban areas and any other places where its limited suitably habitat would increase its probability of survival and raise its resilience. This species is synanthropic, or well-adapted to human disturbances, so it thrives near and around the built environment, in pastures and in agricultural clearings. Research too has a role here in refine taxonomic identification of Pinus echinata: this is a putative occupant of the Lost Pines area and a quick scan of its pollen shed phenology would be a logical starting place. This is no trivial task: the Lost Pines population has a wide range of cones and seed sizes so separating one species from its close relative before measuring pollen shed requires sophisticated methods. Monitoring phenology through a citizen science program can also provide a baseline of change; the National Phenology Program has a protocol for

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monitoring pollen phenology. Doing so requires hourly weather records at a nearby weather station so this can be coordinated with the state’s climate office, state forester and the Bastrop State Park. Likewise, monitor for pest and pathogen attack. Aging pine forests under severe environmental stress can show a fading resilience to bark beetles, pathogens and point-source pollutants. A third step is to manage the aquifer’s water table and to monitor those springs and seeps which are vital to the Lost Pines forested areas. A focus on the interface between human activity and the necessities of forest survival will bring benefit to the Lost Pines community and its stakeholders, not only to the pine forests. Stabilizing climate change is the goal, not forest conservation as end unto itself. The good news is that the Lost Pines population still has large reserves of genetic variation to draw upon although little is known about its adaptive variation (Chap. 8). Based on this, pines are predicted to show a rapid evolutionary response to climate change which in turn leads to an adaptive response within a few generations (Rehfeldt et al. 2001). The strongest factor in favor of local persistence is that Texas Pinus taeda populations have hybridized with Pinus echinata (Tables 7.3 and 7.4; Chap. 7). Hybridization is the wild card in the climate change gamble. So far, the role of hybridization for conifers has not been made explicit for climate change response although hybridization is thought to have great evolutionary importance in how forest trees respond to rapid large-scale disturbances such as climate change (Whitham et al. 1991; Aitken et al. 2008). The scientific methods are already available; genomics-based research can provide useful answers as to the chances of local persistence.

10.2.2

A Scenario for Migration

In practice, the Lost Pines population of Pinus taeda has no clear migratory route to the rest of its range yet this belongs to a class of highly migratory taxa. Pinus taeda is a woody plant and woody plants are more adapted to migration rather to local persistence (Jansson and Dynesius 2002; Smith and Beaulieu 2009). Similarly, North American forest trees have a long history of migrating rather than adapt in place (i.e. Westfall and Millar 2004; Chap. 8), Likewise, bioclimate envelope models for eastern North America point to a future of Pinus taeda range expansion or net migration. A migratory outcome is also consistent with historical records where Pinus taeda rapidly shifted its range in central Texas and then expanded its twentieth century range. All of these findings are consistent with migration as an evolutionary constant for this taxon for millions of years. Pine forests migrate in response to environmental change. Stymied by geological barriers, the Lost Pines population has had a shrinking realized niche for centuries and now it competes poorly with agricultural and urbanization. Here human impacts can be positive and if so, then its loss of a migratory route is not a grave concern. The first reason is that local persistence can be managed. The other reason is that even with its dwindling niche, its migration is still feasible. Pinus taeda, like many other forest species, does have a capacity for long-distance

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Box 10.1 Assisted Colonization The concept of assisted migration, now known as assisted colonization (Aitken et al. 2008; Ledig et al. 2010) refers to the practice of matching seed source to location assuming a different climate in the future. Future migrations are first approximated using climate envelopes and then the right seed sources are then matched to these future climatic conditions for tree planting programs (Marra 2009).

seed dispersal but its limits are not well-established. Can its seeds move distances of 80 to 100 km eastward? This is improbable but no experimental findings can rule this out completely. The probability of its seeds landing in an open gap with suitable habitat and adequate water on the other side of the Brazos River basin does seem improbable but not unlikely (Chap. 7). Migration requires more than long-distance dispersal: it requires a suitable habitat with this complex landscape matrix. The other option is human-mediated or assisted colonization (Box 10.1). With this practice, the Lost Pines population can be planted outside its immediate area and this serves as migration, or assisted colonization.

10.2.3

A Scenario for Extirpation

This is the third stage in the progressive losses which are inherent to future climate change. Large-scale losses may be inevitable despite efforts to stabilize the population’s survival at the earlier stages of local persistence and with migration. This outcome was mentioned in the bioclimate envelope predictions in Chap. 2 where McKenney et al. (2007) predicted that Gulf Coast regions, presumed inclusive of the more interior Lost Pines area, could become populated with no-analog forest tree species which are not currently indigenous. If so, then large-scale losses could eliminate Pinus taeda along the Gulf Coast opening this area to colonization by other forest tree species. However, this is a theory which cannot be resolved with coarse-grained climate change forecasts for the Gulf of Mexico area. Losses to the Lost Pines population could be large but also likely to be incomplete. Losses which stop short of extirpation open the way to a migratory return if conditions improve; this scenario implies a progressive loss which is followed by a return or a renewal. The concept of a loss-and-renewal cycle for temperate pines gains some credence from both historical and paleo-climate patterns. How might this look? Consider the local site heterogeneity shown in the 1929 Bastrop map (Fig. 4.3 in Chap. 4) where its the mildly undulating topography has low-lying areas. These will collect more water than others and thus provide a refuge for scattered individuals or surviving stands of Pinus taeda. Refugial Pinus taeda spreads rapidly if water sources are adequate (Al-Rababah 2003).

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Scarcity of water will be one cause of large-scale losses to the Lost Pines forest. The Colorado River can run dry if its highly vulnerable headwaters in the Southern Great Plains receive no rainfall (Blum and Valastro 1994; Chap. 5). Similarly, the Wilcox-Carrizo aquifer is slow to recharge (Chap. 5) and so this aquifer could be mined if this area’s rising human population draws down its water too fast (Dutton et al. 2006). The real danger: that humans and forests will continue to compete for water from all of these sources. If so, then Pinus taeda forests will lose out. Another cause of large-scale loss is increased severity of hurricanes from the Gulf of Mexico. Bastrop’s strike frequency is less than one per century for hurricanes but the vulnerability of its pine forests to storm aftermath is disproportionately high. More than 67% of its trees are older than age 40 years (Chap. 3) and older Pinus taeda do not withstand hurricane-force winds to the same degree as younger trees; trees blow over in Cat 1 or Cat 2 hurricanes (Chap. 2). Storm-damaged forests attract an aftermath of wildfire, pests and pathogens and if so, secondary losses to this area’s pine forests will be heavy too. Here, too, renewal can follow storm losses if its water sources are still adequate: huge hurricane losses to adult trees are occasionally followed by massive seedling recruitment (Batista and Platt 2003). Loss may be permanent or transitional but, at the same time, renewal cannot be written off completely. This concept of loss-and-renewal rather than simply loss follows the Quaternary pattern for warm-temperate pines (Chap. 6). Fossil pollen profiles show pine-to-oak cyclic oscillations as early as 50,000 years BP at Lake Tulane, Florida USA. These pollen oscillations correspond to climate-cooling Heinrich events (Grimm et al. 1993). Pine pollen peaked during the moist climate regimes then dipped during the warm, dry ones. These pine pollen dips coincide with pollen peaks for Quercus (oak) and grasslands (Grimm et al. 1993). Large-scale losses to pine forests during hot dry climates might favor oak savanna but then pine forests re-colonized these same areas when conditions change yet again. Whether this oscillating pattern holds for the Lost Pines area is debatable. Boriack Bog is the only source of data (Chap. 6) and here the pine pollen concentrations are too low to trace peaks and dips. Even so, a few persistent pine stands in low-lying areas might provide enough seeds for re-colonization.

10.2.4

Summarizing Scenarios

A particular forest is neither old1 or ancient. A forest and its trees are renewed over the course of an hour, a day or a year. No forest is static and no forest stays put. Forests are transient, with pronounced migratory tendency. This tendency might be imperceptible to the human purview but the Lost Pines case study shows that a forest’s migration rate can be hastened or slowed by human impact, positive and negative. Even without human intervention, a species can expand its range in a matter of decades or centuries. The historical records for the Lost Pines forest attest to its migratory tendency.

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As transient, the Lost Pines forest as a forgotten Pleistocene landscape is largely illusory. This author, for one, is disappointed not to find stronger evidence in favor of its identity as a Pleistocene relic. Its only fossils on site are pollen-based and this evidence cannot make a compelling case for a long-standing relictual pine forest here. This pine forest has a shaky Quaternary reconstruction and this is borne out climate reconstructions for central Texas. None can make a strong case for the Lost Pines forest as a Pleistocene relic. More likely, this forest tree population has had a repeated loss-and-renewal cycle. This fits with its ecology: Pinus taeda is prolific early-successional species and thus prone to colonize open gaps caused by fire and ice, by storms and other catastrophic disturbances and by major climate upheavals such as a depositional fill along river terraces. To this list one must add human impact, early and widespread in central Texas. Such a rambunctious history for the Lost Pines population as a series of loss-andrenewal episodes has also required an adjustment to the view of the New World forests as pristine prior to the arrival of Europeans or even prior to the arrival of Native American tribes. Foraging humans have travelled through central Texas for more than 15,000 years, since the end of the last glacier. They probably raised the incidence of fire during severe climate change (Meltzer and Holliday 2010). Humans and forest in this narrative are closely intertwined. This forest stabilizes the harsh climate of central Texas and so its local persistence calls for a deliberate and positive impact on forests planted now. It also calls for protecting standing forests using the best available knowledge. Not an agricultural crop, Pinus taeda is a long-lived organism is planted on private land for benefits which supersede its dwindled timber harvest and if lost then these losses will be borne by the individual, not to governments. One way to hedge risk is to managing genetic diversity of planted forests. Doing so matters to those who shoulder the risks – and to those who do not.

10.3

Closing

This book began with a driving question: how might forests fare under climate change over the next century? The more apt question soon became whether a forested rigion population could migrate rapidly enough to outpace human-induced climate change. Part I. Human-induced climate change is complex and regional but uncertain in the absence of regional forecasts. Likewise, how temperate forests will respond is another source of uncertainty. The best measure under such uncertainty is to protect forests locally as living bulwarks. Predictions from economic and ecological models are overly optimistic and they rest on a simplified view of future climate change. Evolutionary dynamics models provide a needed complement which can guide forest management practices and eventually inform regional forecasts. Shaped by short-term evolutionary processes and by reconstructing the Quaternary past of forests, these models shows that progressive loss must be expected but that forests can be protected.

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Closing

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In particular, evolutionary dynamics borrows on how forest tree populations responded to North American glaciation over millennia. Glaciers here were vast and continuous during the Quaternary and their mark on forested landscapes was harsh and enduring. Local persistence did occur but most forest tree populations responded by migration or by large-scale loss. Part II. The value of evolutionary dynamics models comes through using a narrative of the Lost Pines area in central Texas. This small forest is highly vulnerable to the modern threat of human-induced climate change. Slated to face harsh effects of climate change sooner than most, the Lost Pines forest has a buffering value disproportional to its size and so managing for its local persistence should benefit its rising human populations, not only the forest ecosystem. A visit to central Texas in August will convince any reader of the need for forest canopy. The historical record for the Lost Pines area shows present-day assumptions about this forest must be revised and that our own activities change rapidly within the lifespan of a single tree. Early on, this and other forests were murky, fearful places. This view gave way to forests as obstacles to farm clearing and then to the profitable recognition of forests as timber suited to local and national markets. Then this forest became a source of sustained cash flow, to be managed for sustained yields. Timber markets ebbed in the U.S. South and here in central Texas so now the role of the Lost Pines forest has been fitted to a role as a keystone species for refugial ecosystems. This view is one step away from the concept of forests as living bulwarks against climate change. The value of short-term evolutionary processes for long-lived forests can be made explicit within a coupled human-forest system such as the Lost Pines one. Such systems must be built from available records using spatial imaging, molecular data from extant forest taxa, historical documents and geological records. As such, the Lost Pines ecosystem emerges not a setting or a platform but rather as a socio-ecological system as dynamic as evolution itself. Its geological records show that past climate change has altered the course of its rivers and adjusted the seasonality of its hurricanes. These events carve out where pine forests can spread and where they cannot thrive. None of these climate change effects is measured by using present-day climate variables. Part III. The Lost Pines ecosystem provides the right ecological context for showing how pines have responded to past climate change and this starts with generalizations about its evolutionary past and its life cycle. Most of the evidence weighs in favor of migration as the favored outcome. Pines are generalized as transient generalists, prone to migration rather than local adaptation. Transient generalists do not reside long enough to become locally adapted. Genetic variation is the raw materials for a forest population’s climate change response. Forest trees have exceptional amounts of genetic variation and how this reservoir is shaped depends on mutation migration (or gene flow), genetic drift and selection. Any one population has been shaped in unique ways by these forces but the models which best fit the Lost Pines case are the center-periphery models and its climate change variants. These provide sturdy theory for hypothesis construction

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and for experiments. The evolutionary dynamics models of the Lost Pines population are still incomplete; they have been partially reconstructed from DNA-based data: more will follow as we are enter the cusp of genomics-driven applications. The Lost Pines population is not really small: it does have a census count ranging in the millions. This large census population, if historical and closely keyed to its effective population, could be the primary reason that it does align fully with climate change models. These models do not completely account for its substantial genetic diversity or its close relationship to east Texas populations and the rest of the western part of the range. The reproductive isolation of the Lost Pines population is not well-established and thus cannot be assumed despite its spatial separation from the rest of its range. Other options must be considered given that Pinus taeda has demonstrated capacity for rapid migration. Here is an able colonizer and a prolific seed producer especially when situated under mild stress. This organism has a lifespan of three or four centuries and its pollen and seed reproduction increase with advanced age. We need to revise our climate change models to fit the particulars of this unusual life cycle and its genetic variation reservoir. For example, long-distance dispersal events for Pinus taeda do not always occur as singular and rare. Rather, seed dispersal for pines, conifers and many other forest trees can also occur as a series of repeated events or even wholesale seed dispersal via catastrophic events, so-called sweepstakes dispersal. This model of seed dispersal works in favor of rapid migration and rapid colonization if suitable habitat is open. Typical of Pinus taeda, a synanthropic species, its capacity long-distance dispersal seems to come at no cost to its exceptionally high levels of genetic variation. Seed dispersal models need revision here too. Part IV. Short-term evolutionary processes are neither gradual nor slow. They have practical and direct application to predicting how this forest might respond to climate change and they provide guidance on what to plant now. Thus the first approximation has two parts and both apply equally to the Lost Pines case study and to the larger Pinus taeda range in the U.S. South because forests of all ages now must survive rising uncertainty for climate change. That the Lost Pines area of central Texas is now a human-dominated biome there can be no doubt. This comes as no surprise but human impact can be made explicitly and it can be positive. Examples of both can be found in the Lost Pines narrative for Pinus taeda, a species which is clearly synanthropic. The first half of the first approximation is what to plant. A positive human impact would be to manage genetic diversity of planted forests. This is still feasible because Pinus taeda and other forest trees are largely undomesticated. With enough genetic diversity then these long-lived photosynthesizing organisms might survive in spite the sharp rise of human-induced climate change over the next century or so. Tree improvement programs were originally designed to maintain existing, or standing, variation as the means of meeting human need, not to bend the long-lived to a point of dependency on human intervention. Conversely, narrowing the genetic base down to a few choice genotypes across the U.S. South sold to all private landowners would be a negligent practice. Even so, the seedling market is free to sell any kind of seedling stock. This situation suggests a need for more consumer information for private U.S. landowners.

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The second half of the first approximation applies to standing forests. Local persistence of the Lost Pines forest is the preferred outcome. This might be sustained gradually if the Colorado River does not run dry and if the aquifer’s levels do not drop; this raises the question of whether the aquifer itself will be directly affected by climate change itself. That the Lost Pines population has a migratory tendency is apparent from historical records where its natural regeneration and its colonization were rapid for centuries. At the end of the nineteenth century, Pinus range had already begun to expand into agricultural clearings without benefit of large-scale planting programs. By the mid-twentieth century, it had expanded into its present-day continuous range where it is now composed of overlapping populations which aggregate more or less into latitudinal networks connected by gene flow via pollen and seed. This swing between local adaptation and transient generalist for any Pinus taeda population serves as a pivot for evolutionary dynamics models but it also omits a vital point: that the Lost Pines population might have had a more immediate source of local adaptation via repeated hybridization and introgression with its droughthardy relative, Pinus echinata. Repeated hybridization followed by strong natural selection for drought tolerance would have tilted the population in the direction of local adaptation. Human intervention assists the colonization of the Lost Pines population elsewhere and this could include a role for introgression. Progressive losses are to be expected for the first scenario, local persistence and the second one, migration. Whether these give way to large-scale losses leads to the third scenario. The only note of optimism here is that evidence from past records suggest that these losses may be transient. Forest ecosystems are transient. An entire ecosystem will not respond to climate change as a discreet entity. Its assemblage will dissemble, with each component species responding in its own way. As a local example, the Houston toad no longer resides in Houston. The toad has migrated, with assistance from the Houston Zoo, to the perimeter of its former range, the Lost Pines. More migration can be expected, assisted or not, and these losses can be slowed by managing for local persistence. Local persistence will endure longer with more genetic diversity, not less. More genetic diversity will insure long-term benefits to those private landowners in the U.S. South who now have little reason to retain forest cover. And, managing genetic diversity matters when it comes to assuring the larger societal benefits which come with stabilizing climate change. A proactive step towards climate change adaptation, managing genetic diversity of standing forests and newly planted forests alike constitutes a form of insurance for forests.

References and Related Readings Allard RW (1960) Principles of plant breeding. Wiley, New York, 485 p Al-Rababah M (2003) Evolutionary dynamics of Pinus taeda L. In: The late Quaternary: an interdisciplinary approach. Texas A&M University, College Station, 264 p Austerilitz F, Mariette S et al (2000) Effects of colonization processes on genetic diversity: differences between annual plants and tree species. Genetics 154:1309–1321

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Bartlein PJ, Anderson KH et al (1998) Paleoclimate simulations for North America over the past 21,000 years: features of the simulated climate and comparisons with paleoenvironmental data. Quat Sci Rev 17(6–7):549–585 Batista W, Platt W (2003) Tree population responses to hurricane disturbance: syndromes in a southeastern USA old-growth forest. J Ecol 91:197–212 Blum M, Valastro S (1994) Late Quaternary sedimentation, lower Colorado River, Gulf Coastal Plain. Geol Soc Am Bull 106:1002–1016 Clark JS, Fastie C et al (1998) Reid’s paradox of rapid plant migration: dispersal theory and interpretation of paleoecological records. BioScience 48:13–24 Darlington P (1938) The origin of fauna of the Greater Antilles, with discussion of dispersal over animals over water and through the air. Q Rev Biol 131:274–300 Dutton A, Nicot J et al (2006) Hydrodynamic convergence of hydropressured and geopressured zones, Central Texas, Gulf of Mexico Basin, USA. Hydrogeol J 14:859–867 Dynesius M, Jansson R (2000) Evolutionary consequences in species geographic distribution driven by Milankovitch climatic oscillations. Proc Natl Acad Sci USA 97:9115–9120 Eckert A, Bower A et al (2010) Back to nature: ecological genomics of loblolly pine (Pinus taeda L.). Mol Ecol 19:3789–3805 Gislén T (1948) Aerial plankton and its conditions of life. Biol Rev Camb Philos Soc 23:109–126 Grattapaglia D et al (2008) Genomics of growth traits in forest trees. Curr Opin Plant Biol 12:148–156 Grimm E, Jacobson G Jr et al (1993) A 50,000-year record of climate oscillations from Florida and its temporal correlation with Heinrich events. Science 261:198–200 Jansson R, Dynesius M (2000) The fate of clades in a world of recurrent climate change: milankovitch oscillations and evolution. Annu Rev Ecol Evol Syst 33:741–777 Katul G, Poporato A et al (2005) Mechanistic analytical models for long-distance seed dispersal by wind. Am Nat 166:368–381 LePage B (2003) The evolution, biogeography and paleoecology of the Pinaceae based on fossil and extant representatives. Acta Horticult 615:29–52 Magsig M, Snow J (1998) Long-distance debris transport by tornadic thunderstorms. Part 1: the 7, May 1995 supercell thunderstorm. Mon Weather Rev 126:1430–1449 Marris E (2009) Planting the forest of the future. Nature 459:906–908 McKenney D, Pedlar J et al (2007) Potential impacts of climate change on the distribution of North American trees. BioScience 57:939–948 Namkoong G, Barnes RD et al (1980) A philosophy of breeding strategy for tropical forest trees. Department of Forestry, Commonwealth Forestry Institute, University of Oxford, Oxford UK Namkoong G et al (1988) Tree breeding: principles and strategies. Springer, New York, 180 p Rehfeldt G, Tchebakova N et al (2002) Intraspecific responses to climate in Pinus sylvestris. Glob Chang Biol 8:912–929 Reyes-Valdés MH, Williams CG (2002) A haplotypic approach to founder-origin probabilities and outbred QTL analysis. Genet Res 80:231–236 Toomey RS, Blum MD et al (1993) Late Quaternary climate and environments of the Edwards Plateau, Texas. Glob Planet Change 7:299–320 Visher S (1925) Tropical cycles from an ecological viewpoint. Ecology 6:117–122 Wallace A (1880) Island life. Prometheus Books, New York (1998) Westfall R, Millar C (2004) Genetic consequences of forest population dynamics influenced by historic climate variability in the western USA. For Ecol Manag 197:159–170 White P, Pickett S (eds) (1985) Natural disturbance and patch dynamics. The ecology of natural disturbance. Academic, San Diego Williams C (2008) Aerobiology of Pinus taeda pollen clouds. Can J For Res 38:2177–2188 Williams C (2009) Conifer reproductive biology. Springer, Dordrecht Williams C (2010) Of forests and time in the culture of possession. Int For Rev 12:407–417 Williams CG, Reyés-Valdes MH (2007) Estimating a founder’s genomic proportion for each descendant in an outbred pedigree. Genome 50:289–296

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Williams CG, Hamrick JL, Lewis PO (1994) Genetic diversity levels in a multiple population breeding strategy: a case study using Pinus taeda L. Theor Appl Genet 90:384–394 Williams CG, LaDeau SL, Oren RA, Katul GG (2006) Modeling seed dispersal distances: implications for transgenic Pinus taeda. Ecol Appl 16(1):117–124 Willis K et al (2007) How can knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies. Philos Trans R Soc Lond 362:175–186 Xi W et al (2008) Tree damage and risk factors associated with large, infrequent wind disturbances of Carolina forests. Forestry 81:317–334

sdfsdf

Lexicon

AFLP amplified fragment length polymorphisms Anonymous DNA fragments assumed to be selectively neutral, dominant markers (band present, band absent). Adaptive management A systematic process for continually adjusting policies and practices by evaluating and learning from the outcomes of prior policies and practices. Additionality Measurements must clear this hurdle for a forest offset by showing lowered emissions would not have occurred without the policy. Aerosols Airborne particles that come from both natural (volcanic eruptions, dust storms, fires, biological particles) and manmade sources. Allele A particular form of a gene, presumably reflecting a certain DNA sequence. Allopatric Refers to the geographic separation of different populations. Allozyme An enzyme that is the product of a particular allelic form of a gene. Apical meristem Undifferentiated vegetative branch tip. Apomixis Embryo develops occurs without fertilization. Archegonium, archegonia (pl.) The multicellular covering around each egg cell within the female gametophyte. Black carbon Incomplete combustion of organic matter. Bottleneck A temporary reduction in population size from which future generations are derived. Breeding cycle Selective breeding followed by testing. Breeding population A group of individuals selectively bred, tested and culled in order to increase their mean genetic value for desired traits. C-value Genome size for an individual or taxon, measured in picograms. Catastrophe An extreme environmental fluctuation. Chiasma, chiasmata (pl.) A process inherent to meiotic recombination where two homologous chromatids exchange reciprocal DNA, i.e. a crossover. Chloroplast DNA (cpDNA) Circular DNA molecules found in chloroplasts transmitted intact, without recombination, from one parent to the next generation (uniparental inheritance). See plastid. Chromosome A chromosome consists of a long strand of DNA.

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1, © Springer Science+Business Media B.V. 2012

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Clade A sub-group of organisms from among a larger group sharing a common ancestry, not shared by the other organisms in the larger group. Cline Change in the frequency of an allele (or genotype) over space. Coancestry Kinship as measured by the probability that two alleles, one from each individual, are identical by descent. Common ancestor An individual which is an ancestor to both individuals in question. Cone A female strobilus after pollination and after fertilization. Conelet A female strobilus after pollination and prior to fertilization. Demographic stochasticity Fluctuations in birth and death rates and sex-ratio due to chance alone. Density-dependent selection Selection in which the relative fitness values are a function of the population density. Dichogamy Asynchronous male and female strobilus development which minimized probability of selfing. Dioecy Separate male and female strobili on different plants. Directional selection Selection in which individuals with the most extreme trait values are chosen as parents of the next generation. DNA fingerprint A unique genotypic combinations for distinguishing one individual from another. Ecological restoration Assist recovery of ecosystems which have been damaged, degraded or destroyed; forest practices intended to re-establish those which existed prior to a disturbance. Ecosystem services Essential functions supplied free of charge by living organisms such as oxygen production from forest trees and other green plants. Effective population size (Ne) The number of individuals that would result in the same inbreeding, or genetic drift, if their mating patterns adhered to that of an idealized population. Endangered A species or population with a high probability of extinction. Embryo lethal system Self-pollinated embryos die during embryo development; this enigmatic phenomenon has been collectively defined as the embryo lethal system. Equilibrium A state at which there is no change in the genetic constitution of the population. Evolution A shift in the genetic composition of a population. Expected heterozygosity (He) The heterozygosity expected for a random mating population with the given allele frequencies according to the Hardy-Weinberg equilibrium. Fitness The relative capacity of a genotypic class to transmit its gametes to future generations. Fundamental theorem of natural selection The concept stating that the rate of increase in fitness is equal to the additive genetic variance in fitness. Gametic disequilibrium The nonrandom association of alleles at different loci in gametes. Geitonogamy Self-pollination between separate male and female reproductive structures on the same plant (not autogamy).

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Gene Refers to a region of DNA on a chromosome which codes for biological information. Gene flow Movement of gametophytes (or gametes), individuals or groups of individuals from one home site to another. Gene pool The total amount of alleles segregating within a population. Genetic distance A measure of the genetic difference between allele frequencies in two populations. Genetic diversity The extent of genetic variation in a population, or species, or across a group of species e.g. a general term referring to heterozygosity, allelic diversity or a reservoir for future genetic response to environmental change. Genetic drift Allele change from random sampling of a small population. Genetic testing Replicated tests of offspring, sibs or other related individuals in which their trait values are measured. Common garden tests are a type of genetic testing. Genotype The genetic constitution of an individual. Genotype x environment interaction Differential performance of genotypes across diverse environments. Haploidy One-half of the chromosomal complement. Haplotype Allelic composition for several different loci on a linear or circular chromosome, e.g. A1B5C3. Haplotype network A diagram showing how different haplotypes are joined by lines; typically each haplotype has a different DNA sequence. Heritability The proportion of phenotypic variance that is genetic (heritability in the broad sense) or the additive genetic component (heritability in the narrow sense). Heterospory Condition of separate male (microspores) and female spores (megaspores). Heterozygosity The state of having two different alleles or DNA polymorphism at a single locus. Heterozygote An individual with two different alleles at a locus, e.g. A1A2. Heterozygote advantage A two-allele case in which the heterozygote has a higher fitness than either homozygote. Homogamic hybrid complex A type of hybridity which results in fertile hybrids which in turn mate with other hybrids or parental species. Homozygosity A genotype which has two of the same alleles at a single locus. Homozygote An individual with two copies of the same allele at a locus e.g. A1A1. Idealized population A random mating population with equal numbers of monecious individuals breeding in each generation. Identical by descent (IBD) An allele which is an identical copies of an allele present in a common ancestor. In situ conservation Conserving a species or population within its natural range. Inbreeding Mating between two related individuals. Inbreeding coefficient (F) The probability that two alleles at a locus in an individual are identical by descent. Inbreeding depression Phenotypic decline associated with inbreeding i.e. a reduction in reproduction, survival, or growth.

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Lexicon

Infinite-allele model A model where each mutation is a new, unique allele which has not occurred before. Iteroparity, iteroparous Capable of producing successive cohorts of offspring. Introgression Introduction of genetic material from another species or sub-species into another via hybridization. IUCN Acronym originally stood for the International Union for Conservation of Nature. Karyotype The chromosomal complement of the individual. Landscape genetics Field of study where specific landscape features and microevolutionary processes such as gene flow, genetic drift, and selection interact to shape the amount and spatial distribution of genetic variation Leptoma The opening or aperture for the germination tube. Lethal Inconsistent with survival, as in a recessive lethal allele that results in death when homozygous. Locus Where a gene is located on a chromosome; or, sometimes, the gene and its alleles. Mating design Intercrossing male and female parents in a systematic pattern. Examples include diallels, factorials, polymix or nested mating designs. Meiosis Process by which chromosomal number is halved. Megagametophyte Haploid, multicellular female gametophyte which usually forms from a single megaspore. Megasporangium Integumented ovule. Megaspore mother cell Sporogenous cell which undergoes female meiosis, yielding four megaspores. Megaspore wall Covering for the female gametophyte inside the ovule; derived from diploid tissue of the adult sporophyte. Megasporogenesis The process by which the megaspore mother cell undergoes female meiosis. Metapopulation Populations of the same species that undergo local extinction and recolonizations. Micropyle, micropylar An opening in the ovule through which pollen enters; an opening formed by the integument covering the ovule. Microsatellite A codominant, selectively neutral marker which has a short series of repeated DNA sequence. Microsatellites typically show variable numbers of repeats thus they are highly informative genetic markers for nuclear and organellar DNA. Microsporangia Pollen sacs borne on the abaxial side of a microsporophyll of the male strobilus. Microspore First cell of the male gametophyte which later becomes multicellular. The microspore divides into the central cell and a prothallial cell. Microsporogenesis Developmental process which produces four haploid microspores from a diploid microsporocyte via meiosis. Microspore mother cell Sporogenous cell which undergoes male meiosis yielding four haploid microspores. Microsporophyll Modified leaves on a male strobilus to which male sporangial sacs attach on the underside.

Lexicon

175

Migration Movement of gametophytes or seeds from one population to another. Minimum variable population size (MVP) The minimum size of population that will be viable in the long term, indicative of a probability of extinction. Mitochondria Organelle critical to cell metabolism. Has multiple copies of a circular DNA molecule. Mitochondrial DNA (mtDNA) Occurs as a circular DNA molecule within mitochondria. Mostly transmitted intact from one parent or the other so their haplotypes or variants can be used as a genetic markers to track dispersal. Molecular clock A hypothesis which states that replacement of molecular variants occurs via a steady state. Monecy, monecious Separate male and female structures both of which occur on the same plant. Monophyletic A group of species (or DNA sequences) which derive from a common ancestral origin. Monozygotic Originating from one fertilized embryo; see polyembryony, cleavage. Neutral model A genetic model where selective effects can be ignored. Norm of reaction A way of graphically showing the effect of the genotype, environment, and the genotype x environment interaction on the phenotype. Offsets Reduce or displace carbon emissions through a change in activity in another place, thus compensating emissions activity by the buyer. Outbreeding Opposite of inbreeding. i.e. mating with non-relatives. overdominance Heterozygote advantage. Ovule Integumented ovule; a structure attached to the female strobilus which includes the integument, the nucellus and the megaspore mother cell (which develops into the female gametophyte and its egg cells). Upon fertilization, the ovule becomes a developing seed. Ozone A gas that occurs both in the earth’s upper atmosphere and on the earth’s surface. In the upper atmosphere, the ozone layer protects the earth from the sun’s harmful rays but on the earth’s surface, ozone is a pollutant. Paleobotany The study of fossil plants. Partial dominance The condition where heterozygote Aa has a phenotype closer to one homozygote (aa) than the other (AA) i.e. not fully dominant, additive, or completely recessive. Paternity exclusion An algorithm which estimates probability of an individual’s paternal contribution to a given individual. Pedigree A diagram showing descent and relationship of individuals. Percentage of polymorphic loci(P) A measure of genetic diversity within a population. Permanence In defining a carbon offsets, this term refers to the fact that forests live and die and thus biological sequestration does not last indefinitely. Phenotype Molecular, morphological, behavioral, or other attributes of an organism. Phylogenetic tree A diagram which formalizes relationship between species or populations.

176

Lexicon

Phylogeography A field of geographical genetics concerned with the geographical distribution of genealogical lineages, especially within species. Typically these are shown as DNA sequence trees which correspond to geographic origins. Plastid A pigment-rich organelle in seed plants characterized by many copies of a circular DNA genome in a cell. Pollen Male gametophyte enclosed in a pollen wall; microspores with a germination tube emerging from the distal face. Pollen wall This secreted enclosure surrounds the multicellular male gametophyte to form a pollen grain. Secreted by tapetal cells surrounding each pollen mother cell inside the microsporangial sac, the porous wall is composed of sporopollenin and other substances. Pollen tube Arises from the inner layer of the pollen wall or the intine then emerges from aperture or leptoma on distal face of pollen grain before growing between nucellar cells inside the ovule. Pollination drop Aqueous, protein-rich substance secreted at the micropyle of the ovule during pollination which then retracts upon pollen capture. Polyembryony, simple Fertilization of multiple egg cells within a single female gametophyte, results in polyzygotic embryos. Polyembryony, cleavage Fertilization of a single egg cell which later splits into multiple embryos; results in monozygotic embryos. Polymorphic The presence of more than one allele at a locus. Polymorphism Existence of two or more allelic forms. Polyphyletic A group of species (or DNA sequences) which derives from multiple ancestral species (or DNA sequence). Polyzygotic Originating from multiple zygotes; see polyembryony, simple. Population A group of individuals capable of interbreeding. Population viability analysis (PVA) The process of predicting the fate of a population (including risk of extinction) due to the combined effects of stochastic and deterministic threats to that population. Positive selection Selection which favors increased frequency of a beneficial mutation. Propagule A vegetatively propagated individual. Provenance Refers to a place of geographic origin. Quantitative genetic variation Genetic variation affecting a quantitative character, such as growth or disease resistance. Quantitative trait locus (QTL) A locus affecting a quantitative trait. Radiative forcing The shift in the energy balance of the earth from preindustrial times to present. Random genetic drift See genetic drift. Random mating A pattern of intermating where the chances of two genotypes, or phenotypes breeding is roughly equal to their frequencies in the population. Recombination, meiotic Collective term for the processes of DNA exchange, such as unequal (gene conversion) and reciprocal (crossing over). Relative fitness The relative ability of different genotypes to pass on their alleles to future generations.

Lexicon

177

Resilience Capacity of ecosystems to absorb impact of disturbances and still stay in same state with essentially same structure, function and feedback mechanisms. Scion A branch tip, usually grafted onto rootstock. Seed orchard A production population managed for seed production. Seed source Refers to seed collected from trees within a region. Selection (artificial) Choosing a phenotype on the basis of one or more traits. Selection coefficient (s) The difference in relative fitness between genotypic classes. Selection differential (S) Measures the intensity of selection on a quantitative trait, i.e. the difference between the mean value of the selected parents and the mean of the total population from which they drawn. Selectively neutral An allele whose fate is determined by chance. Selfing Self-pollinating or perhaps self-fertilization. Speciation The process or processes by which populations diverge and become reproductively isolated so that they differentiate into separate species. Spermatophytes Seed plants which exhibit heterospory. Sporogenesis Reproducing via spore or spore cells. Sporophyte The diploid stage in the diplohaplontic life cycle. Standing variation Allelic variation which currently segregating within a population; does not include alleles which arise via new mutational events. Stratosphere Occurs above the trophosphere layer, extending upward about 50 km. Strobilus, strobili (pl.) Male or female reproductive structures; composed of a central axis with attached megasporophylls (female) or microsporophylls (male) to which sporangia are attached. Surface albedo Refers to the degree of reflectivity of the earth’s surface. Lighter surfaces, such as snow, reflects more solar radiation than a darker surface. Sympatric Populations or species are distributed in the same geographic area. Syngamy A female gamete and a male gamete unite. Terminal velocity One of the aerodynamic properties of a particle. Refers to the rate at which a particle descends in still air due to gravity. Transient polymorphism When a gene locus is temporarily polymorphic; this might occur within a population when a favorable mutation approaches fixation, or when neutral alleles drift. Troposphere A layer of the atmosphere which is close to the earth, rising from sea level to roughly 12 km (>7 miles). Vulnerable Refers to a species or population which has a risk of extinction within a moderate timeframe, i.e. as defined by the IUCN this refers to a 10% probability within 100 years. Wildlings Naturally occurring seedlings; not planted.

sdfsdf

Index

A Adaptation. See Persistence Adaptive alleles, 95, 135, 136, 141, 151, 154, 155, 159 Allele loss, 134 Alleles, 95, 105, 125, 133–136, 141, 151, 154–156, 159 Anthropocene, 107–108 Apical meristems, 116 Aquifers, 9, 53, 54 Austin, 33, 35, 39, 41, 50–52, 61–65, 72, 76, 83, 84

B Bastrop, 17, 35–41, 44, 45, 47, 48, 51, 53, 57, 59–69, 72, 74–77, 82–84, 86–90, 103, 140, 159, 160, 161 Bastrop County, 36, 37, 39–41, 44, 47, 53, 62, 65, 67, 82, 87, 90 Bastrop State Park, 36–40, 47, 48, 57, 63, 74, 76, 140 Bioclimate envelope (BCE), 17, 19–22, 161, 162 Bog’s, 91, 99, 103, 104, 106, 163 Breeding-testing-selection cycles, 153 Buescher State Park, 36, 38, 39, 44

Climate envelope. See Bioclimate envelope (BCE) Coahuila, 39, 51, 64 Coal, 4, 5, 53, 68, 76, 78, 87–91 Colonization, 25, 105, 118, 122–126, 138, 150, 161–163, 166, 167 Colorado River of Texas, 35, 50, 51, 81

D Dispersal pollen, 119–121 seed, 21, 25, 118 Domestication, 150, 152–155

E Ecosystems, 5, 6, 21, 42, 44, 126, 155, 165, 167 Empresario, 62, 64 Endangered Species Act, 42, 44 Eocene, 88–90, 98, 99 Evolutionary lag, 138 Extinction, 22, 26, 107, 138, 139 Extirpation, 24, 26, 134, 138, 159, 160, 162–164

F Fitzroya cupressoides, 25 C Climate, 1, 3–13, 17–27, 33, 35, 42–47, 50, 52, 57, 74, 78, 81, 82, 84, 89, 91, 95, 97–108, 115, 117, 120, 124, 126, 134, 135, 137–143, 149–151, 156, 159–167 Climate change human-induced, 3–13, 17, 20, 22, 27, 35, 57, 149–151, 159, 164, 166 orbital, 101

G Gametophyte, 26, 115–119, 126, 133 Gene flow, 119, 133–138, 165, 166 General circulation models, 19 Genetic diversity, 95, 105, 125, 134, 135, 137, 138, 140–143, 150–153, 155–156, 160, 164–167

C.G. Williams, Evolutionary Dynamics of Forests under Climate Change, DOI 10.1007/978-94-007-1936-1, © Springer Science+Business Media B.V. 2012

179

180 Genetic variation, 23, 24, 104, 133–137, 140, 141, 143, 149, 151, 156, 159, 161, 165, 166 Genomics, 152, 154, 155, 161, 165 Greenhouse effect, 6–10 Greenhouse gases, 6–10, 54, 98, 101 Gulf of Mexico, 10, 18, 33, 45, 47, 51, 52, 58, 62, 65, 83, 84, 87, 100, 106, 162

Index Molecular markers, 24, 105, 139 Monoecious, 126

N Nuevo Leon, 51

O Outcrossing, 116, 133–135 H Haploid, 117–118, 133, 134 Heterozygosity, 105, 133 Holocene, 84–87, 99, 102, 104, 106–108, 140, 142 Houston, 33, 35, 39, 41, 44, 52, 71, 75, 86, 167 Houston toad, 33, 41, 44, 167 Hurricanes, 3, 10, 22, 45–47, 65, 78, 120, 159, 162, 165 Hybridization, 25, 123–125, 135, 141, 150, 161,167

J Juniperus ashei, 50

K Keystone species, 44, 53, 165

L LaGrange, 51, 60, 83, 87 Last Glacial Maximum (LGM), 84–86, 99, 102, 103, 105 Lignite, 88–91 Little Ice Age, 77, 78, 99, 107 Lost Pines, 18–20, 22, 28, 33–54, 57–78, 81–91, 97, 105–107, 122, 123, 126, 135, 137, 139–143, 151, 154, 157, 159–167

M Managed evolution, 150 Matagorda, 39, 51, 58, 65, 84 Meiosis, 117, 133, 135 Mexico, 10, 21, 22, 33, 39, 45–47, 51, 52, 57–60, 62–65, 76, 77, 83, 84, 86, 87, 97, 98, 100, 103, 105, 106, 162 Microsatellites, 104 Migration, 19, 21, 23–27, 34, 44, 64, 95, 97–100, 107, 108, 115, 118, 122, 134, 137, 139–141, 150, 159, 161–167

P Paleoclimate, 141, 142, 162 Percolation theory, 122, 126 Persistence, 20, 22, 24–27, 48, 139–141, 150, 154, 159–164, 166, 167 Phenology, 120, 121, 160 Pinus banksiana, 25, 100, 101, 121 Pinus contorta, 27 Pinus echinata, 34, 57, 66, 67, 70, 74, 75, 78, 97, 119, 123–125, 141, 142, 155, 160, 167 Pinus edulis, 27 Pinus eldarica, 43, 50 Pinus elliottii, 50, 74, 97 Pinus glabra, 97, 125 Pinus mitis, 66, 67 Pinus palustris, 70, 74, 97 Pinus remota, 104 Pinus strobus, 98, 104 Pinus sylvestris, 121 Pinus taeda, 17–22, 35, 36, 38, 40, 41, 43, 44, 48–50, 52, 53, 57, 58, 66–68, 70–72, 74, 77, 78, 82–84, 88, 90, 97, 102–108, 115–119, 121–126, 133, 135, 139–142, 151–156, 160–164, 166 Pleistocene, 27, 81, 82, 85–87, 99, 101–104, 140, 142, 161, 163 Pollen, 20, 99, 103, 104, 106, 116–121, 123–126, 133–135, 138, 139, 160, 163, 164, 166 Population, 8, 11, 22–27, 35, 40, 43, 44, 51, 52, 65, 67, 78, 82, 87, 89, 95, 97, 100, 105, 108, 116, 117, 121, 124, 126, 133–143, 151–155, 159–167 Population genetics, 24 Prairie, 35–54, 57–59, 68, 69, 84–86, 123

Q Quaternary, 27, 81, 83, 84, 87, 97, 99–108, 137, 162–164

Index R Railroads, 67, 68 Recombinant DNA, 154 Retreating edge, 137–139, 141, 142

S San Antonio, 35, 48, 49, 51, 58, 61, 82 Savanna, 34, 48–50, 86, 99, 163 Seeds, 24, 26, 48, 75, 85, 95, 118, 121–126, 133–135, 138, 159, 161, 163 Selfing, 116 Sequencing, 154 Smithville, 39, 44, 51, 58, 59 Somatic embryogenesis, 156 Species, 17, 19–23, 25–27, 40, 42–45, 51, 53, 57, 66, 67, 69–71, 73, 78, 81, 82, 84, 91, 97, 100–108, 117, 120, 122–126, 134–141, 151–155, 160–163, 165–167

181 Species diversity, 51, 97, 134, 138, 152 Sporophyte, 26, 115, 116, 118, 122, 126, 133 Springs, 47–48, 59, 65, 77, 81, 88, 89, 135, 150, 161 Stable rear edge, 138–142 Strobili, 116, 118, 120, 122, 126 Strobilus, 116–119 Sweepstakes dispersal, 125, 166 Synanthropic, 43, 150, 160, 166 Synoptic, 3, 121, 135

T Transgressive segregration, 124 Tree improvement, 57, 73, 74, 76, 151–154, 166

V Vertisols, 49, 72, 86, 87, 123