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1 January 2005 MODELING REGIONAL WATERFOWL HARVEST RATES USING MARKOV CHAIN MONTE CARLO
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Abstract

We developed models for simultaneous inference on movement and harvest rates, and of factors influencing harvest rates, using band-recovery data and Markov chain Monte Carlo (MCMC) modeling. We modeled variation in harvest rates for American black ducks (Anas rubripes) during 1971–1994 using recoveries of ducks banded in 3 breeding regions and recovered in 6 harvest regions in Canada and the United States. Models based on season length or bag limit together with season length, and incorporating a random year- and area-specific effect, were superior to other models as gauged by information criteria, fit statistics, and cross-validation. We used these models to generate posterior predictive distributions for harvest rates as a function of harvest regulations, for application to adaptive harvest management.

MICHAEL J. CONROY, CHRISTOPHER J. FONNESBECK, and NATHAN L. ZIMPFER "MODELING REGIONAL WATERFOWL HARVEST RATES USING MARKOV CHAIN MONTE CARLO," Journal of Wildlife Management 69(1), 77-90, (1 January 2005). https://doi.org/10.2193/0022-541X(2005)069<0077:MRWHRU>2.0.CO;2
Published: 1 January 2005
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