Spatial Capture-Recapture

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.

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

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