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Activity Number: 201
Type: Contributed
Date/Time: Monday, August 7, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract - #307256
Title: Bayesian Spatio-Temporal Models for Radio-Telemetry Contacts
Author(s): Albert N. Hendrix*+ and Rip Shively and Barbara Adams
Companies: R2 Resource Consultants, Inc. and U.S. Geological Survey and U.S. Geological Survey
Address: 15250 NE 95th Street, Redmond, WA, 98052,
Keywords: MCMC ; WinBUGS ; spatio-temporal ; fish
Abstract:

Radio-tagged animals are contacted in different spatial locations over time to evaluate their spatial distribution. If the study area is divided into spatial cells, the number of contacts within a cell may be modeled as a Poisson random variable. The mean of the Poisson process can be modeled as a function of environmental covariates, a temporal component, and a spatial component. The spatial component can be specified as a conditional autoregressive process, and the temporal component can be modeled in several forms: fixed time effects, time varying coefficients, or an autoregressive process. These models were evaluated in a Bayesian framework using Markov chain Monte Carlo implemented in winBUGS with simulated data. Subsequently, these models will be applied to the contacts of radio-tagged endangered suckers (fish) in Upper Klamath Lake, Oregon.

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