Activity Number:
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207
- Ecology and Animal Movement
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #313529
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Title:
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Two-Stage Bayesian Approach for Fitting Animal Movement Models
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Author(s):
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Hanna M McCaslin* and Abigail M Feuka and Mevin Hooten
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Companies:
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Colorado State University and Colorado State University and Colorado State University
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Keywords:
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Ecology;
Potential function;
Recursive;
Spatial ;
Spatio-temporal;
Stochastic differential equation
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Abstract:
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Telemetry data and animal movement models allow ecologists to study how animals interact with their environments as they move through them. For example, as birds move through the aerial environment, atmospheric processes such as wind induced by pressure change can impact movement passively through drift and actively by affecting decision-making. We developed a continuous-time movement model based on a mixture of stochastic differential equations to examine how the dynamics of wind influence avian movement and used a hierarchical framework to scale inference to the population level. We fit our model using a two-stage recursive Bayesian approach and demonstrate that using a transformation between the modeling stages can ease computation and interpretation of parameters. We applied our methods to model seasonal movements of migratory species and understand how environmental features influenced migratory route and stopover decisions at multiple scales.
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Authors who are presenting talks have a * after their name.