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Publications [#168038] of Stuart L. Pimm

Papers Published

  1. Sugihara, G and Bersier, LF and Southwood, TRE and Pimm, SL and May, RM, Predicted correspondence between species abundances and dendrograms of niche similarities, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 100 no. 9 (2003), pp. 5246-5251, ISSN 0027-8424
    (last updated on 2009/12/26)

    We examine a hypothesized relationship between two descriptions of community structure: the niche-overlap dendrogram that describes the ecological similarities of species and the pattern of relative abundances. Specifically, we examine the way in. which this relationship follows from the niche hierarchy model, whose fundamental assumption is a direct connection between abundances and underlying hierarchical community organization. We test three important, although correlated, predictions of the niche hierarchy model and show that they are upheld in a set of 11 communities (encompassing fishes, amphibians, lizards, and birds) where both abundances and dendrograms were reported. First, species that are highly nested in the dendrogram are on average less abundant than species from branches less subdivided. Second, and more significantly, more equitable community abundances are associated with more evenly branched dendrogram structures, whereas less equitable abundances are associated with less even dendrograms. This relationship shows that abundance patterns can give insight into less visible aspects of community organization. Third, one can recover the distribution of proportional abundances seen in assemblages containing two species by treating each branch point in the dendrogram as a two-species case. This reconstruction cannot be achieved if abundances and the dendrogram are unrelated and suggests a method for hierarchically decomposing systems. To our knowledge, this is the first test of a species abundance model based on nontrivial predictions as to the origins and causes of abundance patterns, and not simply on the goodness-of-fit of distributions.

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