IMIST


Hierarchical modeling and inference in ecology (notice n° 8823)

000 -LEADER
fixed length control field 02573nam a2200241 u 4500
001 - CONTROL NUMBER
control field UNI0000357
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20161123114313.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131125s2008 XX eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0123740975 (hardcover)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780123740977 (hardcover)
040 ## - CATALOGING SOURCE
Original cataloging agency DCLC
040 ## - CATALOGING SOURCE
Modifying agency IMIST
Description conventions AFNOR
041 1# - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 577.015 118
Edition number 22
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Royle, J. Andrew
245 #0 - TITLE STATEMENT
Title Hierarchical modeling and inference in ecology
Remainder of title the analysis of data from populations, metapopulations and communities
Statement of responsibility, etc J. Andrew Royle, Robert M. Dorazio
250 ## - EDITION STATEMENT
Edition statement 1st ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Amsterdam
-- Burlington
Name of publisher, distributor, etc Academic Press
Date of publication, distribution, etc 2008
300 ## - PHYSICAL DESCRIPTION
Extent xviii, 444 p.
Other physical details ill. (some col.)
Dimensions 24 cm.
500 ## - GENERAL NOTE
General note 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Spatial ecology--Mathematical models
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dorazio, Robert M.
Exemplaires
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        La bibliothèque des Sciences Exactes et Naturelles La bibliothèque des Sciences Exactes et Naturelles   D13543   577.015 118 ROY 0000000019949 11/23/2016 11/23/2016 Livre
        La bibliothèque des Sciences Exactes et Naturelles La bibliothèque des Sciences Exactes et Naturelles   D13542   577.015 118 ROY 0000000021080 11/23/2016 11/23/2016 Livre
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