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BAYESIAN INFERENCE AND DECISION THEORY—A FRAMEWORK FOR DECISION MAKING IN NATURAL RESOURCE MANAGEMENT
Author(s) -
Dorazio Robert M.,
Johnson Fred A.
Publication year - 2003
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1890/1051-0761(2003)013[0556:biadta]2.0.co;2
Subject(s) - inference , bayesian inference , decision theory , bayesian probability , natural resource management , natural resource , influence diagram , ecology , natural (archaeology) , computer science , management science , decision analysis , decision rule , artificial intelligence , mathematics , biology , decision tree , economics , statistics , paleontology
Bayesian inference and decision theory may be used in the solution of relatively complex problems of natural resource management, owing to recent advances in statistical theory and computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models of adequate complexity and for evaluating the expected consequences of alternative management actions. We illustrate these features using an example based on management of waterfowl habitat. Corresponding Editor: D. B. Lindenmayer.