The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world. Several chapters are devoted to introducing models that utilize detection/non-detection data, count data, combined count and capture-recapture data, and spatial capture-recapture data, respectively. The book provides R code of Metropolis-Hastings algorithms that allow efficient computing of these complex models. The book is aimed at graduate students and researchers who are interested in using and further developing these models.

Synthesizes a vast and diverse set of advanced statistical tools for modeling spatially structured population dynamics Provides sufficiently detailed R code for applying and further developing these models Illustrates the presentation of modeling results with elegant graphs

Autorentext

****Qing Zhao is a quantitative ecologist with strong interests in developing and applying statistical models to understand and predict how animal populations, communities and movement respond to our changing world. He has worked closely with conservation agencies for more than 10 years to broaden the impacts of his research on biodiversity conservation at local, regional, and international scales.

Inhalt

Chapter 1: Background.- Chapter 2: Occupancy Models.- Chapter 3: N-mixture models.- Chapter 4: Integrated population models (IPMs).- Chapter 5: Spatial capture-recapture (SCR) models.- Chapter 6: Summary and outlook.