Modeling Populations of Adaptive Individuals:
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...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Princeton, NJ
Princeton University Press
[2020]
|
| Series: | Monographs in Population Biology
63 |
| Subjects: | |
| Links: | https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377?locatt=mode:legacy https://doi.org/10.1515/9780691195377 https://www.degruyter.com/isbn/9780691195377 |
| Summary: | 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.Modeling Populations of Adaptive Individuals 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. Steven Railsback and Bret Harvey explain 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 |
| Item Description: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020) |
| Physical Description: | 1 online resource (216 pages) 34 b/w illus |
| ISBN: | 9780691195377 |
| DOI: | 10.1515/9780691195377 |
Staff View
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| 520 | |a 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.Modeling Populations of Adaptive Individuals 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. Steven Railsback and Bret Harvey explain 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 | ||
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| spelling | Railsback, Steven F. 1957- Verfasser (DE-588)1015200079 aut Modeling Populations of Adaptive Individuals Steven F. Railsback, Bret C. Harvey Princeton, NJ Princeton University Press [2020] © 2020 1 online resource (216 pages) 34 b/w illus txt rdacontent c rdamedia cr rdacarrier Monographs in Population Biology 63 Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020) 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.Modeling Populations of Adaptive Individuals 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. Steven Railsback and Bret Harvey explain 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 In English Alasdair I. Houston Colin W. Clark Dynamic Modeling in Behavioral Ecology Dynamic State Variable Models in Ecology John M. NcNamara Marc Mangel Models of Adaptive Behaviour activity selection adaptive behavior behavioral ecology competition decision algorithm dynamic state variable modeling facultative anadromy fitness measures forager patch selection foraging growth and size habitat selection modeling prediction population ecology population simulations predicting offspring reproductive success time horizons vertical migration SCIENCE / Life Sciences / Ecology bisacsh Adaptation (Biology) Ecology Population biology Mathematical models Harvey, Bret C. 1958- (DE-588)1214842097 aut https://doi.org/10.1515/9780691195377 Verlag URL des Erstveröffentlichers Volltext https://www.degruyter.com/isbn/9780691195377 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Railsback, Steven F. 1957- Harvey, Bret C. 1958- Modeling Populations of Adaptive Individuals Alasdair I. Houston Colin W. Clark Dynamic Modeling in Behavioral Ecology Dynamic State Variable Models in Ecology John M. NcNamara Marc Mangel Models of Adaptive Behaviour activity selection adaptive behavior behavioral ecology competition decision algorithm dynamic state variable modeling facultative anadromy fitness measures forager patch selection foraging growth and size habitat selection modeling prediction population ecology population simulations predicting offspring reproductive success time horizons vertical migration SCIENCE / Life Sciences / Ecology bisacsh Adaptation (Biology) Ecology Population biology Mathematical models |
| title | Modeling Populations of Adaptive Individuals |
| title_auth | Modeling Populations of Adaptive Individuals |
| title_exact_search | Modeling Populations of Adaptive Individuals |
| title_full | Modeling Populations of Adaptive Individuals Steven F. Railsback, Bret C. Harvey |
| title_fullStr | Modeling Populations of Adaptive Individuals Steven F. Railsback, Bret C. Harvey |
| title_full_unstemmed | Modeling Populations of Adaptive Individuals Steven F. Railsback, Bret C. Harvey |
| title_short | Modeling Populations of Adaptive Individuals |
| title_sort | modeling populations of adaptive individuals |
| topic | Alasdair I. Houston Colin W. Clark Dynamic Modeling in Behavioral Ecology Dynamic State Variable Models in Ecology John M. NcNamara Marc Mangel Models of Adaptive Behaviour activity selection adaptive behavior behavioral ecology competition decision algorithm dynamic state variable modeling facultative anadromy fitness measures forager patch selection foraging growth and size habitat selection modeling prediction population ecology population simulations predicting offspring reproductive success time horizons vertical migration SCIENCE / Life Sciences / Ecology bisacsh Adaptation (Biology) Ecology Population biology Mathematical models |
| topic_facet | Alasdair I. Houston Colin W. Clark Dynamic Modeling in Behavioral Ecology Dynamic State Variable Models in Ecology John M. NcNamara Marc Mangel Models of Adaptive Behaviour activity selection adaptive behavior behavioral ecology competition decision algorithm dynamic state variable modeling facultative anadromy fitness measures forager patch selection foraging growth and size habitat selection modeling prediction population ecology population simulations predicting offspring reproductive success time horizons vertical migration SCIENCE / Life Sciences / Ecology Adaptation (Biology) Ecology Population biology Mathematical models |
| url | https://doi.org/10.1515/9780691195377 https://www.degruyter.com/isbn/9780691195377 |
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