Testing the performance of beta diversity measures based on incidence data: the robustness to undersampling

Authors

  • Pedro Cardoso,

    Corresponding author
    1. CITA-A (Azorean Biodiversity Group), Dep. Ciências Agrárias, Universidade dos Açores, Angra do Heroísmo, Portugal
    2. Natural History Museum of Denmark, Zoological Museum and Centre for Macroecology, University of Copenhagen, Copenhagen, Denmark
    3. Smithsonian Institution, National Museum of Natural History, Washington, DC, USA
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  • Paulo A. V. Borges,

    1. CITA-A (Azorean Biodiversity Group), Dep. Ciências Agrárias, Universidade dos Açores, Angra do Heroísmo, Portugal
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  • Joseph A. Veech

    1. Department of Biology, Texas State University, San Marcos, TX, USA
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*Pedro Cardoso, Smithsonian Institution, National Museum of Natural History, PO Box 37012, MRC 105, Room E-509, Washington, DC 20013-7012, USA.
E-mail: pcardoso@ennor.org

Abstract

Aim  Researchers measuring beta diversity have rarely concerned themselves with the problems of how complete the species lists of studied communities are, and of how the varying degrees of completeness can actually change estimates of beta diversity. No comprehensive assessment has been made regarding the behaviour of most beta diversity indices when applied to incomplete samples, a situation which is more common than usually recognized. Our objective was to assess the behaviour and robustness of a number of beta diversity measures for incidence data from undersampled communities.

Location  Mainland Portugal and the Azorean archipelago (North Atlantic).

Methods  Data from intensive sampling of spiders in mainland Portugal and arthropods in Azores were collected. We examined the properties of 15 beta diversity measures developed for incidence data. We simulated varying degrees of completeness, whereas computing beta diversity for selected pairs of samples. The robustness of these beta diversity accumulation curves was assessed for the purpose of finding the best measures for undersampled communities.

Results  The Harrison et al.β-2 and the Williams β-3 are particularly robust to undersampling. These measures are also insensitive to differences of alpha diversity (species richness) between communities, and therefore to nestedness. Colwell & Coddington βcc and the related Jaccard βj and Gaston et al.βg performed best of the measures sensitive to alpha diversity. They performed poorly, however, when compared communities exhibited very low values of beta diversity. In such cases, the Routledge βr performed the best.

Main conclusions  No index was found to perform without bias in all circumstances. Overall, β-2, β-3 and βcc (or related measures βj and βg) are recommended as they seem to be the most robust to undersampling.

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