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Dynamic State Variable Models in Ecology

Author: Colin W. Clark

Publisher: Oxford University Press

Published: 2000-02-10

Total Pages: 302

ISBN-13: 0198028628

This book introduces readers to a set of powerful and extremely flexible modeling techniques, starting at "square one" and continuing with carefully chosen applications. Some of these applications of methodology include insect oviposition behavior, overwinter survival of birds and fish, avian migration, resource management, conservation biology, agroecology, and human behavior. This book also explains how to construct, test, and use dynamic state variable models in a wide range of contexts in evolutionary ecology, and its complete and up-to-date coverage allows readers to immediately begin using the described techniques. Dynamic State Variable Models in Ecology is designed for self-instruction or for use in upper division undergraduate or graduate courses. It is ideal for students and scientists interested in behavior, ecology, anthropology, conservation biology, and related fields.

Dynamic State Variable Models in Ecology

Author: Colin Whitcomb Clark

Publisher: Oxford University Press on Demand

Published: 2000

Total Pages: 289

ISBN-13: 9780195122671

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Dynamic Modeling in Behavioral Ecology

Author: Marc Mangel

Publisher: Princeton University Press

Published: 2019-12-31

Total Pages:

ISBN-13: 0691206961

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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.

Dynamic Modeling in Behavioral Ecology

Author: Marc Mangel

Publisher: Princeton University Press

Published: 1988

Total Pages: 328

ISBN-13: 9780691085067

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Dynamic Models in Biology

Author: Stephen P. Ellner

Publisher: Princeton University Press

Published: 2011-09-19

Total Pages: 352

ISBN-13: 1400840961

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From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.

A Practical Guide to Ecological Modelling

Author: Karline Soetaert

Publisher: Springer Science & Business Media

Published: 2008-10-14

Total Pages: 376

ISBN-13: 1402086245

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Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way. The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.

Encyclopedia of Theoretical Ecology

Author: Alan Hastings

Publisher: Univ of California Press

Published: 2012-05-31

Total Pages: 848

ISBN-13: 0520269659

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"A bold and successful attempt to illustrate the theoretical foundations of all of the subdisciplines of ecology, including basic and applied, and extending through biophysical, population, community, and ecosystem ecology. Encyclopedia of Theoretical Ecology is a compendium of clear and concise essays by the intellectual leaders across this vast breadth of knowledge."--Harold Mooney, Stanford University "A remarkable and indispensable reference work that also is flexible enough to provide essential readings for a wide variety of courses. A masterful collection of authoritative papers that convey the rich and fundamental nature of modern theoretical ecology."--Simon A. Levin, Princeton University "Theoretical ecologists exercise their imaginations to make sense of the astounding complexity of both real and possible ecosystems. Imagining a real or possible topic left out of the Encyclopedia of Theoretical Ecology has proven just as challenging. This comprehensive compendium demonstrates that theoretical ecology has become a mature science, and the volume will serve as the foundation for future creativity in this area."--Fred Adler, University of Utah "The editors have assembled an outstanding group of contributors who are a great match for their topics. Sometimes the author is a key, authoritative figure in a field; and at other times, the author has enough distance to convey all sides of a subject. The next time you need to introduce ecology students to a theoretical topic, you'll be glad to have this encyclopedia on your bookshelf."--Stephen Ellner, Cornell University “Everything you wanted to know about theoretical ecology, and much that you didn’t know you needed to know but will now! Alan Hastings and Louis Gross have done us a great service by bringing together in very accessible form a huge amount of information about a broad, complicated, and expanding field.”--Daniel Simberloff, University of Tennessee, Knoxville

Behavioral Ecology of Insect Parasitoids

Author: Eric Wajnberg

Publisher: John Wiley & Sons

Published: 2008-04-30

Total Pages: 464

ISBN-13: 0470695455

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Written by a team of leading international specialists, Behavioral Ecology of Insect Parasitoids examines the optimal behaviors that parasitoids exhibit in order to maximize long term offspring production. It is an essential reference for research scientists and students studying these fascinating insects or for anyone involved in using parasitoids in biological control programs. Reviews topical issues, including cutting edge research on parasitoid decision making and the implications for biological control Explores applications in other fields, provides information on the latest research methods, and includes helpful case studies and statistical tools Creates a deeper understanding of the link between behavioural strategies and host mortality, resulting in more efficient selective pest management programs “Overall, this is a fascinating volume that provides a significant contribution to the literature on parasitoid insects. It goes a long way toward providing insights into numerous aspects of parasitoid behavior and will stimulate a diversity of future projects, something that should be the goal of any such text. I highly recommend Wajnberg et al. for all of those working on the biology or evolution of parasitoids.” Palaios 2009

Individual-based Modeling and Ecology

Author: Volker Grimm

Publisher: Princeton University Press

Published: 2013-11-28

Total Pages: 445

ISBN-13: 1400850622

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Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is "theory"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.

Introduction to Hierarchical Bayesian Modeling for Ecological Data

Author: Eric Parent

Publisher: CRC Press

Published: 2012-08-21

Total Pages: 429

ISBN-13: 1584889195

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Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts and techniques of the Bayesian paradigm from a practical point of view using real case studies. They emphasize how hierarchical Bayesian modeling supports multidimensional models involving complex interactions between parameters and latent variables. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website. This book shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. It also illustrates how conditional reasoning can dismantle a complex reality into more understandable pieces. As conditional reasoning is intimately linked with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling, estimation, and prediction.