A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics
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Dr Royle is a Senior Scientist and Research Statistician at the U.S. Geological Survey's Patuxent Wildlife Research Center. His research is focused on the application of probability and statistics to ecological problems, especially those related to animal sampling and demographic modeling. Much of his research over the last 10 years has been devoted to the development of methods illustrated in our new book. He has authored or coauthored more than 100 journal articles, and co-authored the books Spatial Capture Recapture, Hierarchical Modeling and Inference in Ecology and Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, all published by Academic Press.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including \* occurrence or occupancy models for estimating species distribution\* abundance models based on many sampling protocols, including distance sampling\* capture-recapture models with individual effects\* spatial capture-recapture models based on camera trapping and related methods\* population and metapopulation dynamic models\* models of biodiversity, community structure and dynamics 464 pp. Englisch. Nº de ref. del artículo: 9780123740977
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Hardcover. Condición: new. Hardcover. A Hierarchical Modeling Approach to Inference in Population, Metapopulation, and Community Ecology A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. It describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780123740977
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including \* occurrence or occupancy models for estimating species distribution\* abundance models based on many sampling protocols, including distance sampling\* capture-recapture models with individual effects\* spatial capture-recapture models based on camera trapping and related methods\* population and metapopulation dynamic models\* models of biodiversity, community structure and dynamics. Nº de ref. del artículo: 9780123740977
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Gebunden. Condición: New. Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis Detailed explanations describi. Nº de ref. del artículo: 594356977
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