Hierarchical Modeling and Inference in Ecology
The Analysis of Data from Populations, Metapopulations and Communities

A guide to data collection and modelling and inference strategies for biological survey data

J. Andrew Royle (Author), Robert M. Dorazio (Author)

9780123740977

Hardback, published 15 October 2008

464 pages
23.4 x 19 x 2.9 cm, 1.08 kg

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution* abundance models based on many sampling protocols, including distance sampling* capture-recapture models with individual effects* spatial capture-recapture models based on camera trapping and related methods* population and metapopulation dynamic models* models of biodiversity, community structure and dynamics

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

Subject Areas: Natural history [WN], Applied ecology [RNC], The environment [RN], Ecological science, the Biosphere [PSAF], Biology, life sciences [PS]