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Prediction of bird community composition based on point-occurrence data and inferential algorithms: a valuable tool in biodiversity assessments

Authors

  • T. Patricia Feria A.,

    Corresponding author
    1. Facultad de Ciencias, Universidad Nacional Autónoma de México, Apartado Postal 70–399, México, DF 04510, México; and Natural History Museum, University of Kansas, Lawrence, Kansas 66045, U.S.A.
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  • A. Townsend Peterson 

    1. Facultad de Ciencias, Universidad Nacional Autónoma de México, Apartado Postal 70–399, México, DF 04510, México; and Natural History Museum, University of Kansas, Lawrence, Kansas 66045, U.S.A.
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 Present address: Department of Biology, University of Missouri, St. Louis, 8001 Natural Bridge Road, St. Louis, Missouri 63121-4499, U.S.A. E-mail: tpfz89@admiral.umsl.edu

Abstract.

Local biological communities are made up of species, each of which has its own particular relationship with the environment. To the extent that these autecological niches limit species’ distributions, and by extension community composition, models of species’ ecological niches can predict species composition at particular sites, or at least provide a null hypothesis of potential species composition in the absence of effects of species interactions. We developed distributional predictions (ecological niche models) for 89 species occurring in dry tropical forest in the Balsas Basin of south-western Mexico using an interpolation technique, and predicted the species likely to occur at 8 sites across the region. Onsite field inventory data were then used to test the community predictions, all of which were statistically significant. These results suggest that inventory efforts can be made more efficient by development beforehand of hypotheses that focus onsite collecting and inventory.

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