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Activity Number: 311 - Statistical Models in Ecology
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract #329059 Presentation
Title: Estimating Behavioral Transition Probabilities of Greater White-Fronted Geese Using Non-Homogenous Markov Models
Author(s): Toryn Schafer* and Christopher K. Wikle and Mitchell Weegman
Companies: University of Missouri and University of Missouri and University of Missouri
Keywords: Bayesian; ecology; Markov models

The North American mid-continent Greater White-fronted goose (Anser albifrons) annually migrates long distances from breeding grounds in the Arctic circle to various staging grounds including Canadian prairies and wintering grounds in Southern United States. Novel wildlife devices allow for remote collection of behavioral and spatial data throughout the year. We equipped geese with accelerometers that recorded movement every 6 minutes. Acceleration values were classified into discrete behaviors such as flying, stationary and walking, for comparisons of strategies among individuals with implications for understanding mechanisms for population dynamics. We used non-homogeneous Markov transition models to estimate transition probabilities between behavior categories. We implemented models in a Bayesian hierarchical framework that allowed for covariates to inform individual transitions. We explored a suite of covariates including habitat, weather, and behavior of neighboring individuals.

Authors who are presenting talks have a * after their name.

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