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Activity Number:
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196
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Type:
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Invited
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Date/Time:
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Monday, August 3, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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WNAR
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| Abstract - #303147 |
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Title:
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Accounting for Animal Movement in Estimation of Resource Selection Functions: Sampling and Data Analysis
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Author(s):
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James D. Forester and Hae Kyung Im and Paul J. Rathouz*+
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Companies:
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Harvard University and The University of Chicago and The University of Chicago
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Address:
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5841 S. Maryland, MC 2007, Chicago, IL, 60637,
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Keywords:
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animal movement ; telemetry ; conditional logistic regression ; case-control ; resource selection function ; relocation kernel
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Abstract:
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Resource selection by animal populations is typically studied by tracking individuals via telemetry, mapping observed locations to available resources at those points, and comparing observed locations to a sample of control points via conditional logistic regression. We study this design through a model for animal step selection functions (SSF) composed of a resource-independent movement kernel and a resource selection function (RSF). We examine three control point sampling schemes and study the bias in selection estimates associated with ignoring each scheme. We also propose a simple method for correcting the sampling bias involving the addition of a movement distance function to the regression model. The method can be implemented with standard software. We present a case-study using location and resource data collected from elk in Yellowstone National Park.
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