Hierarchical Modeling and Inference in Ecology

This book offers researchers a new and emerging population analysis tool, allowing for more flexible strategy in sampling data. Leading ecologists provide insight into combining two complex models and using a simplified unified model (referred to as a hierarchical or state-space model). This new approach yields surprisingly simple solutions to some very complex problems. Examples include: (1) Hierarchical models of simple counts (2) Modelling individual heterogeneity in capture-recapture models (3) Estimating community structure by modelling occurrence of species

Introduction; Site-occupancy models; Closed population models; Modelling individual effects in closed populations; Abundance as a state variable; Abundance as a state variable; Dynamic site occupancy models; Cormack-Jolly-Seber models; Jolly-Seber models; Animal community models; Occupancy models with spatial dynamics; Open models for animal communities; Temporaly dynamic models for abundance; Other potential topics; Statistical concepts and philosophy; Appendices (online or in text) Appendix1: R-tutorial, Sample R-functions for implementing several methods Appendix2: WinBUGS tutorial and R2WinBUGS package Appendix3:Sample WinBUGS and R-scripts for examples used in book