IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v022i06.html
   My bibliography  Save this article

Exploring Habitat Selection by Wildlife with adehabitat

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v022i06/v22i06.pdf
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v022i06/adehabitat_1.6-1.tar.gz
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v022i06/v22i06.R.zip
    Download Restriction: no

    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v022.i06?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:v:022:i06. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.