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 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 Content: Spatial Capture-Recapture , Page i Spatial Capture-Recapture , Page iii Copyright , Page iv Foreword , Pages xvii-xxi Preface , Pages xxiii-xxviii Acknowledgments , Page xxix Chapter 1 - Introduction , Pages 3-19 Chapter 2 - Statistical Models and SCR , Pages 21-46 Chapter 3 - GLMs and Bayesian Analysis , Pages 47-85 Chapter 4 - Closed Population Models , Pages 87-121 Chapter 5 - Fully Spatial Capture-Recapture Models , Pages 125-170 Chapter 6 - Likelihood Analysis of Spatial Capture-Recapture Models , Pages 171-196 Chapter 7 - Modeling Variation in Encounter Probability , Pages 197-218 Chapter 8 - Model Selection and Assessment , Pages 219-243 Chapter 9 - Alternative Observation Models , Pages 245-275 Chapter 10 - Sampling Design , Pages 277-303 Chapter 11 - Modeling Spatial Variation in Density , Pages 307-327 Chapter 12 - Modeling Landscape Connectivity , Pages 329-347 Chapter 13 - Integrating Resource Selection with Spatial Capture-Recapture Models , Pages 349-363 Chapter 14 - Stratified Populations: Multi-Session and Multi-Site Data , Pages 365-379 Chapter 15 - Models for Search-Encounter Data , Pages 381-399 Chapter 16 - Open Population Models , Pages 401-430 Chapter 17 - Developing Markov Chain Monte Carlo Samplers , Pages 433-471 Chapter 18 - Unmarked Populations , Pages 473-495 Chapter 19 - Spatial Mark-Resight Models , Pages 497-526 Chapter 20 - 2012: A Spatial Capture-Recapture Odyssey , Pages 527-535 Appendix - I—Useful Software and R Packages , Pages 539-544 Bibliography , Pages 545-568 Index , Pages 569-577

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 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

"Space plays a vital role in virtually all ecological processes (Tilman and Kareiva, 1997; Hanski, 1999; Clobert et al., 2001). The spatial arrangement of habitat can influence movement patterns during dispersal, habitat selection, and survival. The distance between an organism and its competitors and prey can influence activity patterns and foraging behavior. Further, understanding distribution and spatial variation in abundance is necessary in the conservation and management of populations"-- Provided by publisher "Space plays a vital role in virtually all ecological processes (Tilman and Kareiva, 1997; Hanski, 1999; Clobert et al., 2001). The spatial arrangement of habitat can influence movement patterns during dispersal, habitat selection, and survival. The distance between an organism and its competitors and prey can influence activity patterns and foraging behavior. Further, understanding distribution and spatial variation in abundance is necessary in the conservation and management of populations"--Résumé de l'éditeur