Tilman's predicted productivity–diversity relationship shown by desert rodents View Full Text


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Article Info

DATE

1984-05

AUTHORS

Z. Abramsky, M. L. Rosenzweig

ABSTRACT

Tilman1 has developed a model to predict the number of plant species that can coexist competitively on a limited resource base. Species diversity first increases over low resource supplies, then declines as the environment becomes richer. Although Tilman's model was developed to describe interspecific interactions between plant species, it may also apply to animal species. Tilman1 questions whether animals specialize on particular proportions of nutrients. However, we believe animals probably specialize on relatively subtle microhabitat differences, especially in a multispecies competitive regime2. Thus, microhabitats may act like nutrients. We hypothesize that animal species, too, show a peaked curve of diversity over productivity. The present data provide a confirmation of the hypothesis using rodent species. We have investigated the number of rodent species along a geographical gradient of increasing rainfall. The gradient extends from extremely poor desert habitats to those with annual rainfall over 300 mm. Because of the aridity, precipitation reflects productivity. The diversity pattern in desert rodents agrees with that predicted by Tilman for plants. It even possesses similar asymmetry, rising steeply then falling slowly. The pattern is duplicated in rocky and sandy habitats, each of which has a distinct and almost non-overlapping assemblage of species. As mean precipitation is closely correlated with the variability of precipitation, the diversity pattern might also be caused by a decline in the frequency of disturbances, models for which have been proposed by several investigators. More... »

PAGES

150-151

References to SciGraph publications

  • 1978-01. Small mammal community ecology in OECOLOGIA
  • Identifiers

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    http://scigraph.springernature.com/pub.10.1038/309150a0

    DOI

    http://dx.doi.org/10.1038/309150a0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1048399134

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/6717592


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