Using multilevel models to quantify heterogeneity in resource selection

Authors

  • Tyler Wagner,

    1. United States Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, PA 16802, USA
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  • Duane R. Diefenbach,

    Corresponding author
    1. United States Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, 404 Forest Resources Bldg., University Park, PA 16802, USA
    • United States Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, 404 Forest Resources Bldg., University Park, PA 16802, USA.
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  • Sonja A. Christensen,

    1. Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, PA 16802, USA
    Current affiliation:
    1. Massachusetts Division of Fisheries and Wildlife, 1 Rabbit Hill Rd., Westborough, MA 01581, USA.
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  • Andrew S. Norton

    1. Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, PA 16802, USA
    Current affiliation:
    1. Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI 53706, USA.
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  • Associate Editor: Terry L. Shaffer.

Abstract

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection. © 2011 The Wildlife Society.

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