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Exploring Habitat Selection by Wildlife with adehabitat

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  • Calenge, Clément

Abstract

Knowledge of the environmental features affecting habitat selection by animals is important for designing wildlife management and conservation policies. The package adehabitat for the R software is designed to provide a computing environment for the analysis and modelling of such relationships. This paper focuses on the preliminary steps of data exploration and analysis, performed prior to a more formal modelling of habitat selection. In this context, I illustrate the use of a factorial analysis, the K-select analysis. This method is a factorial decomposition of marginality, one measure of habitat selection. This method was chosen to present the package because it illustrates clearly many of its features (home range estimation, spatial analyses, graphical possibilities, etc.). I strongly stress the powerful capabilities of factorial methods for data analysis, using as an example the analysis of habitat selection by the wild boar (Sus scrofa L.) in a Mediterranean environment.

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  • Calenge, Clément, 2007. "Exploring Habitat Selection by Wildlife with adehabitat," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i06).
  • Handle: RePEc:jss:jstsof:v:022:i06
    DOI: http://hdl.handle.net/10.18637/jss.v022.i06
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    References listed on IDEAS

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    1. Dray, Stéphane & Dufour, Anne-Béatrice, 2007. "The ade4 Package: Implementing the Duality Diagram for Ecologists," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i04).
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    1. Hengl, Tomislav & Sierdsema, Henk & Radović, Andreja & Dilo, Arta, 2009. "Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging," Ecological Modelling, Elsevier, vol. 220(24), pages 3499-3511.
    2. repec:jss:jstsof:22:i01 is not listed on IDEAS
    3. Kneib, Thomas & Petzoldt, Thomas, 2007. "Introduction to the Special Volume on "Ecology and Ecological Modeling in R"," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i01).

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