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Biodiversity and species interactions: extending Lotka–Volterra community theory

Authors

  • W. G. Wilson,

    Corresponding author
    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
    2. Dept of Biology, Duke University, Durham, NC 27708, USA
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  • P. Lundberg,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
    2. Dept of Theoretical Ecology, Lund University, SE-22362 Lund, Sweden
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  • D. P. Vázquez,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
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  • J. B. Shurin,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
    2. Dept of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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  • M. D. Smith,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
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  • W. Langford,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
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  • K. L. Gross,

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
    2. Kellogg Biological Station, Michigan State University, Hickory Corners, MI 49060, USA
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  • G. G. Mittelbach

    1. National Center for Ecological Analysis and Synthesis, University of California, 735 State Street, Suite 300, Santa Barbara, CA 93101-5504, USA
    2. Kellogg Biological Station, Michigan State University, Hickory Corners, MI 49060, USA
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* E-mail: wgw@duke.edu

Abstract

A new analysis of the nearly century-old Lotka–Volterra theory allows us to link species interactions to biodiversity patterns, including: species abundance distributions, estimates of total community size, patterns of community invasibility, and predicted responses to disturbance. Based on a few restrictive assumptions about species interactions, our calculations require only that the community is sufficiently large to allow a mean-field approximation. We develop this analysis to show how an initial assemblage of species with varying interaction strengths is predicted to sort out into the final community based on the species’ predicted target densities. The sorting process yields predictions of covarying patterns of species abundance, community size, and species interaction strengths. These predictions can be tested using enrichment experiments, examination of latitudinal and productivity gradients, and features of community assembly.

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