Description

Spatial Capture-Recapture provides a comprehensive how-to manual with detailed examples of spatial capture-recapture models based on current technology and knowledge. Spatial Capture-Recapture provides you with an extensive step-by-step analysis of many data sets using different software implementations. The authors' approach is practical – it embraces Bayesian and classical inference strategies to give the reader different options to get the job done. In addition, Spatial Capture-Recapture provides data sets, sample code and computing scripts in an R package.

Key Features

  • Comprehensive reference on revolutionary new methods in ecology makes this the first and only book on the topic
  • Every methodological element has a detailed worked example with a code template, allowing you to learn by example
  • Includes an R package that contains all computer code and data sets on companion website

Readership

Ecologists and biologists

Table of Contents

Foreword

Preface

Themes of this book

Computing

Organization of this book

Acknowledgments

Part I: Background and Concepts

Chapter 1. Introduction

Abstract

1.1 The study of populations by capture-recapture

1.2 Lions and tigers and bears, oh my: genesis of spatial capture-recapture data

1.3 Capture-recapture for modeling encounter probability

1.4 Historical context: a brief synopsis

1.5 Extension of closed population models

1.6 Ecological focus of SCR models

1.7 Summary and outlook

Chapter 2. Statistical Models and SCR

Abstract

2.1 Random variables and probability distributions

2.2 Common probability distributions

2.3 Statistical inference and parameter estimation

2.4 Joint, marginal, and conditional distributions

2.5 Hierarchical models and inference

2.6 Characterization of SCR models

2.7 Summary and outlook

Chapter 3. GLMs and Bayesian Analysis

Abstract

3.1 GLMs and GLMMs

3.2 Bayesian analysis

3.3 Characterizing posterior distributions by MCMC simulation

3.4 Bayesian analysis using the BUGS language

3.5 Practical Bayesian analysis and MCMC

3.6 Poisson GLMs

3.7 Poisson GLM with random effects

3.8 Binomial GLMs

3.9 Bayesian model checking and selection

3.10 Summary and outlook

Chapter 4. Closed Population Models

Abstract

4.1 The simplest closed population model: model

4.2 Data augmentation

4.3 Temporally varying and behavioral effects

4.4 Models with individual heterogeneity

4.5 Individual covariate models: toward spatial capture-recapture

4.6 Distance sampling: a primitive SCR model

4.7 Summary and outlook

Part II: Basic SCR Models

Chapter 5. Fully Spatial Capture-Recapture Models

A

Details

No. of pages:
612
Language:
English
Copyright:
© 2014
Published:
Imprint:
Academic Press
Print ISBN:
9780124059399
Electronic ISBN:
9780124071520

About the authors

J. Royle

Dr Royle is currently a 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.

Reviews

"...a book for the DIY quantitative ecologist who wants to understand their data...I enjoyed it tremendously and it already had a strong influence on how I think about some of my current research projects."--Basic and Applied Ecology, Spatial Capture-Recapture

"...a timely and informative contribution that summarizes the history and motivation behind SCR models,...will be a vital addition to wildlife ecologist’s book shelves for many years to come."--The Journal of Wildlife Management, Sep 14