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.
Table of Contents
Preface Acknowledgments I. Background and Concepts 1. Introduction 2. Statistical Models and SCR 3. GLMs and Bayesian Analysis 4. Closed Population Models II. Basic SCR Models 5. Fully Spatial Capture-Recapture Models 6. Likelihood Analysis of Spatial Capture-Recapture Models 7. Modeling Variation In Encounter Probability 8. Model Selection and Assessment 9. Alternative Observation Models 10. Sampling Design III. Advanced SCR Models 11. Modeling Spatial Variation in Density 12. Modeling Landscape Connectivity 13. Integrating Resource Selection with Spatial Capture-Recapture Models 14. Stratified Populations: Multi-session and Multi-site Data 15. Models for Search-Encounter Data 16. Open Population Models IV. Super-Advanced SCR Models 17. Developing Markov Chain Monte Carlo Samplers 18. Unmarked Populations 19. Spatial Mark-Resight Models for partially identifiable populations 20. 2012: A Spatial Capture-Recapture Odyssey V. Appendices WinBUGS OpenBUGS JAGS R Bibliography
