This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 138
Type: Contributed
Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #308459
Title: An Evaluation of the N-Mixture Model for Pseudo-Replicated Count Data in Animal Abundance Estimation
Author(s): Sherwin G. Toribio*+ and Brian R. Gray
Companies: University of Wisconsin-La Crosse and U.S. Geological Survey
Address: 1725 State St., La Crosse, WI, 54601,
Keywords: N-mixture model ; Abundance estimation ; Bayesian method ; MCMC ; Hierarchical models

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this presentation, I will talk about the robustness of the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability in the N-mixture model are biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

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