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Activity Number: 646
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract #316533
Title: A Comparison of Models for Analyzing Occupancy Data Collect with Multiple Detectors
Author(s): Derek Sonderegger*
Companies: Northern Arizona University
Keywords: Occupancy ; camera trap ; Bayesian ; San Fransico
Abstract:

Traditional occupancy models using presence/absence data require multiple observation periods for detection and presence probabilities to be estimable. When camera trap data is used, this requirement typically results in the creation of artificial time periods that may or may not make biological sense. We propose a sampling scheme a single long sampling period (2 weeks of daily recordings) but utilizes multiple cameras in a single plot. When one or more cameras in a plot capture an animal, the detection probability can simply be estimated from the number of cameras that capture the individual and can avoid the traditional confounding of the presence and detection probabilities. We implement this model using a hierarchical Bayesian model and investigate the effect of particular modeling choices (e.g. random effects versus additional hierarchy levels) and conclude with a analysis of a multi-year camera trap study in the San Francisco Bay eco-region.


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