IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0105132.html
   My bibliography  Save this article

A Generalized Approach to the Modeling of the Species-Area Relationship

Author

Listed:
  • Katiane Silva Conceição
  • Werner Ulrich
  • Carlos Alberto Ribeiro Diniz
  • Francisco Aparecido Rodrigues
  • Marinho Gomes de Andrade

Abstract

This paper proposes a statistical generalized species-area model (GSAM) to represent various patterns of species-area relationship (SAR), which is one of the fundamental patterns in ecology. The approach enables the generalization of many preliminary models, as power-curve model, which is commonly used to mathematically describe the SAR. The GSAM is applied to simulated data set of species diversity in areas of different sizes and a real-world data of insects of Hymenoptera order has been modeled. We show that the GSAM enables the identification of the best statistical model and estimates the number of species according to the area.

Suggested Citation

  • Katiane Silva Conceição & Werner Ulrich & Carlos Alberto Ribeiro Diniz & Francisco Aparecido Rodrigues & Marinho Gomes de Andrade, 2014. "A Generalized Approach to the Modeling of the Species-Area Relationship," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-9, August.
    • Handle: RePEc:plo:pone00:0105132
    DOI: 10.1371/journal.pone.0105132
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105132
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0105132&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0105132?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
    ---><---

    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:plo:pone00:0105132. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.