By
J. Royle, USGS Patuxent Wildlife Research Center, Laurel, MD, USA
Robert Dorazio, USGS Florida Integrated Science Center and Department of Statistics, University of Florida, Gainesville, FL , USA
Description
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
Audience:
Post-graduate research biologists in ecology and population dynamics and field surveys - engaged in field data collection and modelling
for all practical and theoretical applications; Biostatisticians
