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Temporal variation and scale in movement-based resource selection functions

Statistical Methodology

By:
, , ,
DOI: 10.1016/j.stamet.2012.12.001

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Abstract

A common population characteristic of interest in animal ecology studies pertains to the selection of resources. That is, given the resources available to animals, what do they ultimately choose to use? A variety of statistical approaches have been employed to examine this question and each has advantages and disadvantages with respect to the form of available data and the properties of estimators given model assumptions. A wealth of high resolution telemetry data are now being collected to study animal population movement and space use and these data present both challenges and opportunities for statistical inference. We summarize traditional methods for resource selection and then describe several extensions to deal with measurement uncertainty and an explicit movement process that exists in studies involving high-resolution telemetry data. Our approach uses a correlated random walk movement model to obtain temporally varying use and availability distributions that are employed in a weighted distribution context to estimate selection coefficients. The temporally varying coefficients are then weighted by their contribution to selection and combined to provide inference at the population level. The result is an intuitive and accessible statistical procedure that uses readily available software and is computationally feasible for large datasets. These methods are demonstrated using data collected as part of a large-scale mountain lion monitoring study in Colorado, USA.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Temporal variation and scale in movement-based resource selection functions
Series title:
Statistical Methodology
DOI:
10.1016/j.stamet.2012.12.001
Volume
17
Year Published:
2013
Language:
English
Publisher:
Elsevier
Contributing office(s):
Colorado Cooperative Fish and Wildlife Research Unit
Description:
17 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Statistical Methodology
First page:
82
Last page:
98