Darryl I. Mackenzie, James D. Nichols, J. Andrew Royle, Kenneth H. Pollock, Larissa Bailey, James E. Hines

Occupancy Estimation and Modeling (eBook, PDF)

Inferring Patterns and Dynamics of Species Occurrence

• Format: PDF

Produktbeschreibung

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.

• Provides authoritative insights into the latest in estimation modeling
• Discusses multiple models which lay the groundwork for future study designs
• Addresses critical issues of imperfect detectibility and its effects on estimation
• Explores the role of probability in estimating in detail

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 344
• Erscheinungstermin: 17. November 2005
• Englisch
• ISBN-13: 9780080455044
• Artikelnr.: 38115775

Autorenporträt

Dr. MacKenzie is biometrician for Proteus Wildlife Research Consultants in New Zealand. His main area of expertise is in using occupancy models for monitoring and research. He started working in this area while on a year long stint at Patuxent Wildlife Research Center with Drs William L. Kendall and James D. Nichols during 2000/01. He has acted as a statistical consultant to the Department of Conservation, Ministry of Fisheries and the U.S. Geological Survey. In 2002 Darryl was awarded a prestigious Fast-Start Marsden Grant from the Royal Society of New Zealand for research into optimal study designs for estimating the proportion of area occupied by a target species.James Nichols received a B.S. in Biology from Wake Forest Univ., M.S. in Wildlife Management from Louisiana State Univ., and Ph.D. in Wildlife Ecology from Michigan State Univ. He has spent his entire research career at Patuxent Wildlife Research Center working for the U.S. Fish and Wildlife Service, the National Biological Service, and now the U.S. Geological Survey. He is currently a Senior Scientist at Patuxent. His research interests focus on the dynamics and management of animal populations and on methods for estimating population parameters.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.

Inhaltsangabe

Part I: BACKGROUND AND CONCEPTS1. Introduction2. Occupancy Applications3. Fundamental Principals of Statistical Inference

Part II: SINGLE SPECIES, SINGLE SEASON OCCUPANCY MODELS4. Basic Presence/absence Situation5. Beyond Two Occupancy States6. Extensions to Basic Approaches7. Modeling Hetergeneous Detection Probabilities

Part III: SINGLE SPECIES, MULTIPLE SEASON OCCUPANCY MODELS8. Basic Presence/absence Situation9. More than Two Occupancy States10. Further Topics

Part IV: STUDY DESIGN11. Design of Single-season Occupancy Studies12. Multiple Season Study Design

Part V: ADVANCED TOPICS13. Integrated Modeling of Habitat and Occupancy Dynamics14. Species Co-occurrence15. Occupancy in Community-level Studies16. Final Comments

Rezensionen

"MacKenzie et al, writes clearly and make sensible points that are illustrated with excellent case studies and figures..." --Erica Fleishman, Stanford University, Department of Biological Sciences, for Ecology