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Niche Overlap as a Function of Environmental Variability

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May, Robert M., Arthur, Robert H. Mac·1972·Proceedings of the National Academy of Sciences

Abstract

The relationship between environmental variability and niche overlap is studied for a class of model biological communities in which several species compete on a one-dimensional continuum of resources, e.g., food size. In a strictly unvarying (deterministic) environment, there is in general no limit to the degree of overlap, short of complete congruence. However, in a fluctuating (stochastic) environment, the average food sizes for species adjacent on the resource spectrum must differ by an amount roughly equal to the standard deviation in the food size taken by either individual species. This mathematical result emerges in a nonobvious yet robust way for environmental fluctuations whose variance relative to their mean ranges from around 0.01% to around 30%. In short, there is an effective limit to niche overlap in the real world, and this limit is insensitive to the degree of environmental fluctuation, unless it be very severe. Recent field work, particularly on bird guilds, seems in harmony with the model's conclusion.

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Metadata

Authors
May, R. M., & Arthur, R. H. M.
Venue
Proceedings of the National Academy of Sciences
Published
1972-05
Volume
69
Issue
5
Pages
1109-1113
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2067813367
Cited by
708
References
0
FWCI
30.14
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Niche Overlap as a Function of Environmental Variability. https://app.cochat.ai/papers/10.1073/pnas.69.5.1109
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May, R. M., & Arthur, R. H. M. (1972). Niche Overlap as a Function of Environmental Variability. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.69.5.1109

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.