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Understanding the mechanisms driving biological diversity remains a central problem in ecology and evolutionary biology. Traditional explanations assume that differences in selection pressures lead to different adaptations in geographically separated locations. This book takes a different approach and explores adaptive diversification—diversification rooted in ecological interactions and frequency-dependent selection. In any ecosystem, birth and death rates of individuals are affected by interactions with other individuals. What is an advantageous phenotype therefore depends on the phenotype of other individuals, and it may often be best to be ecologically different from the majority phenotype. Such rare-type advantage is a hallmark of frequency-dependent selection and opens the scope for processes of diversification that require ecological contact rather than geographical isolation. This book investigates adaptive diversification using the mathematical framework of adaptive dynamics. Evolutionary branching is a paradigmatic feature of adaptive dynamics that serves as a basic metaphor for adaptive diversification, and the book explores the scope of evolutionary branching in many different ecological scenarios, including models of coevolution, cooperation, and cultural evolution. It also uses alternative modeling approaches. Stochastic, individual-based models are particularly useful for studying adaptive speciation in sexual populations, and partial differential equation models confirm the pervasiveness of adaptive diversification. Showing that frequency-dependent interactions are an important driver of biological diversity, the book provides a comprehensive theoretical treatment of adaptive diversification.

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This book provides a comprehensive and accessible introduction to the latest Bayesian methods. It emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach, and is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. The book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This book enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.

This book provides an accessible introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. It begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes. It then describes in detail the control and dynamical systems tools used to analyze these models. These include tools for analyzing stability of equilibria, limit cycles, robustness, and parameter uncertainty. Modeling and analysis techniques are then applied to design examples from both natural systems and synthetic biomolecular circuits. In addition, the book addresses the problem of modular composition of synthetic circuits, the tools for analyzing the extent of modularity, and the design techniques for ensuring modular behavior. It also looks at design trade-offs, focusing on perturbations due to noise and competition for shared cellular resources. Featuring numerous exercises and illustrations throughout, the book is the ideal textbook for advanced undergraduates and graduate students. For researchers, it can also serve as a self-contained reference on the feedback control techniques that can be applied to biomolecular systems.

This textbook provides a unique and thorough look at the application of chemical biomarkers to aquatic ecosystems. Defining a chemical biomarker as a compound that can be linked to particular sources of organic matter identified in the sediment record, the book indicates that the application of these biomarkers for an understanding of aquatic ecosystems consists of a biogeochemical approach that has been quite successful but underused. This book offers a wide-ranging guide to the broad diversity of these chemical biomarkers, is the first to be structured around the compounds themselves, and examines them in a connected and comprehensive way. This book is appropriate for advanced undergraduate and graduate students seeking training in this area; researchers in biochemistry, organic geochemistry, and biogeochemistry; researchers working on aspects of organic cycling in aquatic ecosystems; and paleoceanographers, petroleum geologists, and ecologists.

After World War II, the question of how to define a universal human nature took on new urgency. This book charts the rise and precipitous fall in Cold War America of a theory that attributed man's evolutionary success to his unique capacity for murder. The book reveals how the scientists who advanced this “killer ape” theory capitalized on an expanding postwar market in intellectual paperbacks and widespread faith in the power of science to solve humanity's problems, even to answer the most fundamental questions of human identity. The killer ape theory spread quickly from colloquial science publications to late-night television, classrooms, political debates, and Hollywood films. Behind the scenes, however, scientists were sharply divided, their disagreements centering squarely on questions of race and gender. Then, in the 1970s, the theory unraveled altogether when primatologists discovered that chimpanzees also kill members of their own species. While the discovery brought an end to definitions of human exceptionalism delineated by violence, the book shows how some evolutionists began to argue for a shared chimpanzee–human history of aggression even as other scientists discredited such theories as sloppy popularizations. A wide-ranging account of a compelling episode in American science, the book argues that the legacy of the killer ape persists today in the conviction that science can resolve the essential dilemmas of human nature.

Humans possess an extraordinary capacity for cultural production, from the arts and language to science and technology. How did the human mind—and the uniquely human ability to devise and transmit culture—evolve from its roots in animal behavior? This book presents a new theory of human cognitive evolution. It reveals how culture is not just the magnificent end product of an evolutionary process that produced a species unlike all others—it is also the key driving force behind that process. The book shows how the learned and socially transmitted activities of our ancestors shaped our intellects through accelerating cycles of evolutionary feedback. The truly unique characteristics of our species—such as our intelligence, language, teaching, and cooperation—are not adaptive responses to predators, disease, or other external conditions. Rather, humans are creatures of their own making. The book explains how animals imitate, innovate, and have remarkable traditions of their own. It traces our rise from scavenger apes in prehistory to modern humans able to design iPhones, dance the tango, and send astronauts into space. This book tells the story of the painstaking fieldwork, the key experiments, the false leads, and the stunning scientific breakthroughs that led to this new understanding of how culture transformed human evolution. It is the story of how Darwin's intellectual descendants picked up where he left off and took up the challenge of providing a scientific account of the evolution of the human mind.

As human populations grow and resources are depleted, agriculture will need to use land, water, and other resources more efficiently and without sacrificing long-term sustainability. This book presents an entirely new approach to these challenges, one that draws on the principles of evolution and natural selection. It shows how both biotechnology and traditional plant breeding can use Darwinian insights to identify promising routes for crop genetic improvement and avoid costly dead ends. It explains why plant traits that have been genetically optimized by individual selection—such as photosynthesis and drought tolerance—are bad candidates for genetic improvement. Traits like plant height and leaf angle, which determine the collective performance of plant communities, offer more room for improvement. Agriculturalists can also benefit from more sophisticated comparisons among natural communities and from the study of wild species in the landscapes where they evolved. The book reveals why it is sometimes better to slow or even reverse evolutionary trends when they are inconsistent with our present goals, and how we can glean new ideas from natural selection's marvelous innovations in wild species.

Human beings have evolved to become the most dominant species on Earth. This astonishing transformation is usually explained in terms of cognitive ability—people are just smarter than all the rest. But this book argues that culture—our ability to learn from each other—has been the essential ingredient of our remarkable success. The book shows how a unique combination of cultural adaptation and large-scale cooperation has transformed our species and assured our survival—making us the different kind of animal we are today. The book is based on the Tanner Lectures delivered at Princeton University, featuring challenging responses across the chapters.

In recent years, scientists have realized that evolution can occur on timescales much shorter than the “long lapse of ages” emphasized by Darwin—in fact, evolutionary change is occurring all around us all the time. This book provides an authoritative and accessible introduction to eco-evolutionary dynamics, a cutting-edge new field that seeks to unify evolution and ecology into a common conceptual framework focusing on rapid and dynamic environmental and evolutionary change. The book covers key aspects of evolution, ecology, and their interactions. Topics range from natural selection, adaptive divergence, ecological speciation, and gene flow to population and community dynamics, ecosystem function, plasticity, and genomics. The book evaluates conceptual and methodological approaches, and draws on empirical data from natural populations—including those in human-disturbed environments—to tackle a number of classic and emerging research questions. It also discusses exciting new directions for future research at the intersection of ecology and evolution. The book reveals how evolution and ecology interact strongly on short timescales to shape the world we see around us.

This book provides a first synthetic view of an emerging area of ecology and biogeography, linking individual- and population-level processes to geographic distributions and biodiversity patterns. Problems in evolutionary ecology, macroecology, and biogeography are illuminated by this integrative view. The book focuses on correlative approaches known as ecological niche modeling, species distribution modeling, or habitat suitability modeling, which use associations between known occurrences of species and environmental variables to identify environmental conditions under which populations can be maintained. The spatial distribution of environments suitable for the species can then be estimated: a potential distribution for the species. This approach has broad applicability to ecology, evolution, biogeography, and conservation biology, as well as to understanding the geographic potential of invasive species and infectious diseases, and the biological implications of climate change. The book lays out conceptual foundations and general principles for understanding and interpreting species distributions with respect to geography and environment. Focus is on development of niche models. While serving as a guide for students and researchers, the book also provides a theoretical framework to support future progress in the field.

Rising temperatures are affecting organisms in all of Earth's biomes, but the complexity of ecological responses to climate change has hampered the development of a conceptually unified treatment of them. In a remarkably comprehensive synthesis, this book presents past, ongoing, and future ecological responses to climate change in the context of two simplifying hypotheses, facilitation and interference, arguing that biotic interactions may be the primary driver of ecological responses to climate change across all levels of biological organization. The author's synthesis and analyses of ecological consequences of climate change extend from the Late Pleistocene to the present, and through the next century of projected warming. The book's investigation is grounded in classic themes of enduring interest in ecology, but developed around novel conceptual and mathematical models of observed and predicted dynamics. Using stability theory as a recurring theme, the book argues that the magnitude of climatic variability may be just as important as the magnitude and direction of change in determining whether populations, communities, and species persist. It urges a more refined consideration of species interactions, emphasizing important distinctions between lateral and vertical interactions and their disparate roles in shaping responses of populations, communities, and ecosystems to climate change.

This book develops a unified framework for understanding the structure of ecological community and the dynamics of natural selection that shape the evolution of the species inhabiting them. All species engage in interactions with many other species, and these interactions regulate their abundance, define their trajectories of natural selection, and shape their movement decisions. This book synthesizes the ecological and evolutionary dynamics generated by species interactions that structure local biological communities and regional metacommunities. The book explores the ecological performance characteristics needed for invasibility and coexistence of species in complex networks of species interactions. This species interaction framework is then extended to examine the ecological dynamics of natural selection that drive coevolution of interacting species in these complex interaction networks. The models of natural selection resulting from species interactions are used to evaluate the ecological conditions that foster diversification at multiple trophic levels. Analyses show that diversification depends on the ecological context in which species interactions occur and the types of traits that define the mechanisms of those species interactions. Lastly, looking at the mechanisms of speciation that affect species richness and diversity at various spatial scales and the consequences of past climate change over the Quaternary period, the book considers how metacommunity structure is shaped at regional and biogeographic scales. Integrating evolutionary theory into the study of community ecology, the book provides a new framework for predicting how communities are organized and how they may change over time.

Fish are one of the most important global food sources, supplying a significant share of the world's protein consumption. From stocks of wild Alaskan salmon and North Sea cod to entire fish communities with myriad species, fisheries require careful management to ensure that stocks remain productive, and mathematical models are essential tools for doing so. This book is an introduction to the modern size- and trait-based approach to fish populations and communities. It covers the theoretical foundations, mathematical formulations, and real-world applications of this powerful new modeling method, which is grounded in the latest ecological theory and population biology. It begins with fundamental assumptions on the level of individuals and goes on to cover population demography and fisheries impact assessments. The book shows how size- and trait-based models shed new light on familiar fisheries concepts such as maximum sustainable yield and fisheries selectivity—insights that classic age-based theory can't provide—and develops novel evolutionary impacts of fishing. It extends the theory to entire fish communities and uses it to support the ecosystem approach to fisheries management, and forges critical links between trait-based methods and evolutionary ecology. The book unifies the thinking in ecology and fisheries science and is an indispensable reference for anyone seeking to apply size- and trait-based models to fish demography, fisheries impact assessments, and fish evolutionary ecology.

Human impacts are dramatically altering our natural ecosystems but the exact repercussions on ecological sustainability and function remain unclear. As a result, food web theory has experienced a proliferation of research seeking to address these critical areas. Arguing that the various recent and classical food web theories can be looked at collectively and in a highly consistent and testable way, this book synthesizes and reconciles modern and classical perspectives into a general unified theory. The book brings together outcomes from population-, community-, and ecosystem-level approaches under the common currency of energy or material fluxes. It shows that these approaches—often studied in isolation—all have the same general implications in terms of stability of the population dynamics. Specifically, increased fluxes of energy or material tend to destabilize populations, communities, and whole ecosystems. With this understanding, stabilizing structures at different levels of the ecological hierarchy can be identified and any population-, community-, or ecosystem-level structures that mute energy or material flow also stabilize systems dynamics. The book uses this powerful general framework to discuss the effects of human impact on ecological stability and sustainability, and it demonstrates that there is clear empirical evidence that the structures supporting ecological systems have been dangerously eroded. Uniting the latest research on food webs with classical theories, this book will be a standard source in the understanding of natural food web functions.

Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The book identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. The book is tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management.

Homology—a similar trait shared by different species and derived from common ancestry, such as a seal's fin and a bird's wing—is one of the most fundamental yet challenging concepts in evolutionary biology. This book provides the first mechanistically based theory of what homology is and how it arises in evolution. The book argues that homology, or character identity, can be explained through the historical continuity of character identity networks—that is, the gene regulatory networks that enable differential gene expression. It shows how character identity is independent of the form and function of the character itself because the same network can activate different effector genes and thus control the development of different shapes, sizes, and qualities of the character. Demonstrating how this theoretical model can provide a foundation for understanding the evolutionary origin of novel characters, the book applies it to the origin and evolution of specific systems, such as cell types; skin, hair, and feathers; limbs and digits; and flowers. The first major synthesis of homology to be published in decades, this book reveals how a mechanistically based theory can serve as a unifying concept for any branch of science concerned with the structure and development of organisms, and how it can help explain major transitions in evolution and broad patterns of biological diversity.

This book brings together startling evidence from neuroscience, psychology, and psychiatry to present revolutionary new insights into how our brains enable us to experience the range of sensations and mental states known as feelings. Drawing on own cutting-edge research, the author has identified an area deep inside the mammalian brain—the insular cortex—as the place where interoception, or the processing of bodily stimuli, generates feelings. The book shows how this crucial pathway for interoceptive awareness gives rise in humans to the feeling of being alive, vivid perceptual feelings, and a subjective image of the sentient self across time. The book explains how feelings represent activity patterns in our brains that signify emotions, intentions, and thoughts, and how integration of these patterns is driven by the unique energy needs of the hominid brain. It describes the essential role of feelings and the insular cortex in such diverse realms as music, fluid intelligence, and bivalent emotions, and relates these ideas to the philosophy of William James and even to feelings in dogs. The book is also a compelling insider's account of scientific discovery, one that takes readers behind the scenes as the astonishing answer to this neurological puzzle is pursued and pieced together from seemingly unrelated fields of scientific inquiry. This book will fundamentally alter the way that neuroscientists and psychologists categorize sensations and understand the origins and significance of human feelings.

Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods. The book fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided. The book covers the latest research in mathematical modeling of infectious disease epidemiology; it integrates deterministic and stochastic approaches; and teaches skills in model construction, analysis, inference, and interpretation.

Ecologists now recognize that the dynamics of populations, communities, and ecosystems are strongly affected by adaptive individual behaviors. Yet until now, we have lacked effective and flexible methods for modeling such dynamics. Traditional ecological models become impractical with the inclusion of behavior, and the optimization approaches of behavioral ecology cannot be used when future conditions are unpredictable due to feedbacks from the behavior of other individuals. This book provides a comprehensive introduction to state- and prediction-based theory, or SPT, a powerful new approach to modeling trade-off behaviors in contexts such as individual-based population models where feedbacks and variability make optimization impossible. This book features a wealth of examples that range from highly simplified behavior models to complex population models in which individuals make adaptive trade-off decisions about habitat and activity selection in highly heterogeneous environments. The book explains how SPT builds on key concepts from the state-based dynamic modeling theory of behavioral ecology, and how it combines explicit predictions of future conditions with approximations of a fitness measure to represent how individuals make good—not optimal—decisions that they revise as conditions change. The resulting models are realistic, testable, adaptable, and invaluable for answering fundamental questions in ecology and forecasting ecological outcomes of real-world scenarios.

Mutualistic interactions among plants and animals have played a paramount role in shaping biodiversity. Yet the majority of studies on mutualistic interactions have involved only a few species, as opposed to broader mutual connections between communities of organisms. This is the first book to comprehensively explore this burgeoning field. Integrating different approaches, from the statistical description of network structures to the development of new analytical frameworks, the book describes the architecture of these mutualistic networks and shows their importance for the robustness of biodiversity and the coevolutionary process. Making a case for why we should care about mutualisms and their complex networks, this book offers a new perspective on the study and synthesis of this growing area for ecologists and evolutionary biologists. It will serve as the standard reference for all future work on mutualistic interactions in biological communities.