Dynamic Modeling in Behavioral Ecology
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Dynamic Modeling in Behavioral Ecology by Marc Mangel
Book DescriptionThis 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.
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Book DetailsISBN: 9780691085067
(229mm x 152mm x 18mm)
Imprint: Princeton University Press
Publisher: Princeton University Press
Publish Date: 1-Jan-1989
Country of Publication: United States
Books By Author Marc Mangel
Theoretical Biologist's Toolbox, Paperback (July 2006)
This textbook provides a no-nonsense introduction to the principles of theoretical and mathematical biology.
Dynamic State Variable Models in Ecology, Paperback (March 2000)
This is an introduction to a set of powerful and extremely flexible modelling techniques, starting at "square one" and continuing with chosen applications. The text also explains how to construct, test, and use dynamic state variable models in a wide range of contexts in evolutionary ecology.
Ecological Detective, Paperback (February 1997)» View all books by Marc Mangel
How do we make the field and laboratory coherent? How do we use statistics to help experimentation? How do we integrate modeling and statistics? This book answers these questions. It makes liberal use of computer programming for the generation of hypotheses, exploration of data, and the comparison of different models.
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