• Medientyp: E-Artikel
  • Titel: Healthy wrinkles for population dynamics: unevenly spread resources can support more users
  • Beteiligte: C. Patrick, Doncaster
  • Erschienen: Wiley, 2001
  • Erschienen in: Journal of Animal Ecology, 70 (2001) 1, Seite 91-100
  • Sprache: Englisch
  • DOI: 10.1111/j.1365-2656.2001.00474.x
  • ISSN: 1365-2656; 0021-8790
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  • Beschreibung: AbstractResource users have a curvilinear relation of abundance to the richness of their limiting resource, with richness defined by the carrying capacity of renewing resource in the absence of exploitation. The non‐linearity means that local unevenness in the distribution of resources can directly influence the overall abundance of users. This effect is entirely independent of overall resource abundance.Outcomes are demonstrated for a classical model of consumer aggregations under conditions of ideal and free exploitation. Consumers that make little impact on the stock of their limiting resource can benefit directly from environmental heterogeneity. They can sustain higher abundance in an environment with unevenly spread resources than in one of equivalent richness with an even spread. Positive effects of heterogeneity are reduced by density dependence in the exploitation rate, for example caused by mutual interference between users. Heterogeneity may have a negative impact on abundance for consumers with a more efficient exploitation of resources.Similar outcomes are predicted for classical models of consumer breeding populations as for consumer aggregations. At still larger scales, unevenness in the distribution of resource patches in metapopulations, and of niches in communities, can increase the abundances of populations and species. Species or communities most likely to benefit from unevenness in their resource carpet are those most vulnerable to local extinction from loss or degradation of their habitat.These effects illustrate applications of non‐spatial models to spatial contexts. They show how steady‐state predictions are likely to be biased by ignoring any underlying heterogeneity in the environment.
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