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Reconciling niche and neutrality: the continuum hypothesis

Gravel, Dominique, Canham, Charles D., Beaudet, Marilou, Messier, Christian·2006·Ecology Letters

Abstract

In this study, we ask if instead of being fundamentally opposed, niche and neutral theories could simply be located at the extremes of a continuum. First, we present a model of recruitment probabilities that combines both niche and neutral processes. From this model, we predict and test whether the relative importance of niche vs. neutral processes in controlling community dynamics will vary depending on community species richness, niche overlap and dispersal capabilities of species (both local and long distance). Results demonstrate that niche and neutrality form ends of a continuum from competitive to stochastic exclusion. In the absence of immigration, competitive exclusion tends to create a regular spacing of niches. However, immigration prevents the establishment of a limiting similarity. The equilibrium community consists of a set of complementary and redundant species, with their abundance determined, respectively, by the distribution of environmental conditions and the amount of immigration.

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Crossref · 10.1111/j.1461-0248.2006.00884.x

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Metadata

Authors
Gravel, D., Canham, C. D., Beaudet, M., & Messier, C.
Venue
Ecology Letters
Publisher
Wiley
Published
2006-02-16
Volume
9
Issue
4
Pages
399-409
ISSN
  • 1461-023X (ISSN-L)
  • 1461-0248
OpenAlex
W2106890697
Cited by
828
References
1
FWCI
20.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Reconciling niche and neutrality: the continuum hypothesis. https://app.cochat.ai/papers/10.1111/j.1461-0248.2006.00884.x
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Gravel, D., Canham, C. D., Beaudet, M., & Messier, C. (2006). Reconciling niche and neutrality: the continuum hypothesis. Ecology Letters. https://doi.org/10.1111/j.1461-0248.2006.00884.x

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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.