This book describes a powerful and flexible technique for the modeling of behavior, based on evolutionary principles. The technique employs stochastic dynamic programming and permits the analysis of behavioral adaptations wherein organisms respond to changes in their environment and in their own current physiological state. Models can be constructed to reflect sequential decisions concerned simultaneously with foraging, reproduction, predator avoidance, and other activities. The authors show how to construct and use dynamic behavioral models. Part I covers the mathematical background and computer programming, and then uses a paradigm of foraging under risk of predation to exemplify the general modeling technique. Part II consists of five "applied" chapters illustrating the scope of the dynamic modeling approach. They treat hunting behavior in lions, reproduction in insects, migrations of aquatic organisms, clutch size and parental care in birds, and movement of spiders and raptors. Advanced topics, including the study of dynamic evolutionarily stable strategies, are discussed in Part III.

Ecologists are aware of the importance of natural dynamics in ecosystems. Historically, the focus has been on the development in succession of equilibrium communities, which has generated an understanding of the composition and functioning of ecosystems. Recently, many have focused on the processes of disturbances and the evolutionary significance of such events. This shifted emphasis has inspired studies in diverse systems. The phrase "patch dynamics" (Thompson, 1978) describes their common focus. The Ecology of Natural Disturbance and Patch Dynamics brings together the findings and ideas of those studying varied systems, presenting a synthesis of diverse individual contributions.

A plethora of different theories, models, and concepts make up the field of community ecology. Amid this vast body of work, is it possible to build one general theory of ecological communities? What other scientific areas might serve as a guiding framework? As it turns out, the core focus of community ecology—understanding patterns of diversity and composition of biological variants across space and time—is shared by evolutionary biology and its very coherent conceptual framework, population genetics theory. The Theory of Ecological Communities takes this as a starting point to pull together community ecology's various perspectives into a more unified whole. Mark Vellend builds a theory of ecological communities based on four overarching processes: selection among species, drift, dispersal, and speciation. These are analogues of the four central processes in population genetics theory—selection within species, drift, gene flow, and mutation—and together they subsume almost all of the many dozens of more specific models built to describe the dynamics of communities of interacting species. The result is a theory that allows the effects of many low-level processes, such as competition, facilitation, predation, disturbance, stress, succession, colonization, and local extinction to be understood as the underpinnings of high-level processes with widely applicable consequences for ecological communities. Reframing the numerous existing ideas in community ecology, The Theory of Ecological Communities provides a new way for thinking about biological composition and diversity.

From climate change to species extinction, humanity is confronted with an increasing array of societal and environmental challenges that defy simple quantifiable solutions. Complexity-based ecology provides a new paradigm for ecologists and conservationists keen to embrace the uncertainty that is pressed upon us. This book presents key research papers chosen by some sixty scholars from various continents, across a diverse span of sub-disciplines. The papers are set alongside first person commentary from many of the seminal voices involved, offering unprecedented access to experts' viewpoints. The works assembled also shed light on the process of science in general, showing how the shifting of wider perspectives allows for new ideas to take hold. Ideal for undergraduate and advanced students of ecology and conservation, their educators and those working across allied fields, this is the first book of its kind to focus on complexity-based approaches and provides a benchmark for future collected volumes.

“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.

Model development is of vital importance for understanding and management of ecological processes. Identifying the complex relationships between ecological patterns and processes is a crucial task. Ecological modelling—both qualitatively and quantitatively—plays a vital role in analysing ecological phenomena and for ecological theory. This textbook provides a unique overview of modelling approaches. Representing the state-of-the-art in modern ecology, it shows how to construct and work with various different model types. It introduces the background of each approach and its application in ecology. Differential equations, matrix approaches, individual-based models and many other relevant modelling techniques are explained and demonstrated with their use. The authors provide links to software tools and course materials. With chapters written by leading specialists, “Modelling Complex Ecological Dynamics” is an essential contribution to expand the qualification of students, teachers and scientists alike.

Dynamic Food Webs challenges us to rethink what factors may determine ecological and evolutionary pathways of food web development. It touches upon the intriguing idea that trophic interactions drive patterns and dynamics at different levels of biological organization: dynamics in species composition, dynamics in population life-history parameters and abundances, and dynamics in individual growth, size and behavior. These dynamics are shown to be strongly interrelated governing food web structure and stability and the role of populations and communities play in ecosystem functioning. Dynamic Food Webs not only offers over 100 illustrations, but also contains 8 riveting sections devoted to an understanding of how to manage the effects of environmental change, the protection of biological diversity and the sustainable use of natural resources. Dynamic Food Webs is a volume in the Theoretical Ecology series. Relates dynamics on different levels of biological organization: individuals, populations, and communities Deals with empirical and theoretical approaches Discusses the role of community food webs in ecosystem functioning Proposes methods to assess the effects of environmental change on the structure of biological communities and ecosystem functioning Offers an analyses of the relationship between complexity and stability in food webs