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Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence

Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence

Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species
Stock photo: cover may vary

Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence Hardback - 2006 - 1st Edition

by Mackenzie, Darryl I

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  • Hardback

Description

Academic Press, 2006. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9780120887668
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Details

  • Title Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence
  • Author Mackenzie, Darryl I
  • Binding Hardback
  • Edition number 1st
  • Edition 1
  • Pages 344
  • Volumes 1
  • Language ENG
  • Publisher Academic Press, St Louis, Missouri, U.S.A.
  • Publication date 2006
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Table of Contents
  • Bookseller's Inventory # 8690681
  • ISBN 9780120887668 / 0120887665
  • Weight 1.49 lbs (0.68 kg)
  • Dimensions 8.24 x 6.18 x 0.95 in (20.93 x 15.70 x 2.41 cm)
  • Themes
    • Topical: Ecology
  • Category Animals
  • Library of Congress subjects Animal populations - Estimates, Animal populations - Mathematical models
  • Library of Congress Catalogue Number 2005051372
  • Dewey Decimal Code 591.788

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Reader reviews for Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence

From the publisher

Occupancy Estimation and Modeling is the first book to examine the latest methods in analyzing presence/absence data surveys. Using four classes of models (single-species, single-season; single-species, multiple season; multiple-species, single-season; and multiple-species, multiple-season), the authors discuss the practical sampling situation, present a likelihood-based model enabling direct estimation of the occupancy-related parameters while allowing for imperfect detectability, and make recommendations for designing studies using these models.
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