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Hierarchical Modeling and Inference in Ecology
The Analysis of Data from Populations, Metapopulations and Communities
1st Edition - July 3, 2008
Authors: J. Andrew Royle, Robert M. Dorazio
Hardback ISBN:
9 7 8 - 0 - 1 2 - 3 7 4 0 9 7 - 7
eBook ISBN:
9 7 8 - 0 - 0 8 - 0 5 5 9 2 5 - 4
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… Read more
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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
- Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants)
- Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis
- Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS
- Computing support in technical appendices in an online companion web site
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
- No. of pages: 464
- Language: English
- Published: July 3, 2008
- Imprint: Academic Press
- Hardback ISBN: 9780123740977
- eBook ISBN: 9780080559254
JR
J. Andrew Royle
Dr Royle is a Senior Scientist and Research Statistician at the U.S. Geological Survey's Patuxent Wildlife Research Center. His research is focused on the application of probability and statistics to ecological problems, especially those related to animal sampling and demographic modeling. Much of his research over the last 10 years has been devoted to the development of methods illustrated in our new book. He has authored or coauthored more than 100 journal articles, and co-authored the books Spatial Capture Recapture, Hierarchical Modeling and Inference in Ecology and Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, all published by Academic Press.
Affiliations and expertise
Research Statistician, U.S. Geological Survey, Patuxent Wildlife Research Center, Laurel, MD, USARD
Robert M. Dorazio
Affiliations and expertise
USGS Florida Integrated Science Center and Department of Statistics, University of Florida, Gainesville, FL , USA