Applied Hierarchical Modeling in Ecology. Analysis of distribution, abundance and species richness in R and BUGS: Volume 1: Prelude and Static Models

__Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness__ offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. __Applied Hierarchical Modeling in Ecology,____Volume 1__ serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. * Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection * Presents models and methods for identifying unmarked individuals and species * Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses * Includes companion website containing data sets, code, solutions to exercises, and further information

Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management.

This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields.

• Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection
• Presents models and methods for identifying unmarked individuals and species
• Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses
• Includes companion website containing data sets, code, solutions to exercises, and further information

Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection Presents models and methods for identifying unmarked individuals and species Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses Includes companion website containing data sets, code, solutions to exercises, and further information Content: Front Matter,Copyright,Dedication,Foreword,Preface,AcknowledgmentsEntitled to full textPart 1: PreludeChapter 1 - Distribution, Abundance, and Species Richness in Ecology, Pages 3-18 Chapter 2 - What Are Hierarchical Models and How Do We Analyze Them?, Pages 19-78 Chapter 3 - Linear Models, Generalized Linear Models (GLMs), and Random Effects Models: The Components of Hierarchical Models, Pages 79-122 Chapter 4 - Introduction to Data Simulation, Pages 123-143 Chapter 5 - Fitting Models Using the Bayesian Modeling Software BUGS and JAGS, Pages 145-215 Chapter 6 - Modeling Abundance with Counts of Unmarked Individuals in Closed Populations: Binomial N-mixture Models, Pages 219-312 Chapter 7 - Modeling Abundance Using Multinomial N-Mixture Models, Pages 313-392 Chapter 8 - Modeling Abundance Using Hierarchical Distance Sampling, Pages 393-461 Chapter 9 - Advanced Hierarchical Distance Sampling, Pages 463-550 Chapter 10 - Modeling Static Occurrence and Species Distributions Using Site-occupancy Models, Pages 551-629 Chapter 11 - Hierarchical Models for Communities, Pages 631-728 Summary and Conclusion, Pages 729-735 References, Pages 737-760 Author Index, Pages 761-770 Subject Index, Pages 771-783