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Are communities saturated? On the relationship between α, β and γ diversity
Abstract
A popular way to suggest a regional influence on local species diversity has been to plot local versus regional diversity. The form of these curves has been interpreted as evidence for or against “community saturation” due to species interactions. This interpretation, however, is unwarranted. Using the concepts of α, β and γ diversity, I show that local–regional richness curves are determined by the way total diversity is partitioned between its α and β components, which itself is a matter of scale. Changing the scale of the local community amounts to changing the scale at which the heterogeneity of the interactions between organisms and their environment manifests itself, and hence the balance between α and β diversity. Community saturation may occur because of physical limitations, but there are no theoretical grounds for the belief that species interactions set an absolute upper limit to diversity at any scale. A distinction between different meanings of the concept of “saturation” is proposed to clarify this issue. I argue that the challenge now is to understand the relationship between α and β diversity at multiple scales, and the processes that determine it.
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Cites
Species Diversity in Space and Time
Rosenzweig, M. L. (1995) · doi:10.1017/cbo9780511623387 · Cited by 3,690
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Metadata
- Authors
- Loreau, M.
- Venue
- Ecology Letters
- Publisher
- Wiley
- Published
- 2000-03
- Volume
- 3
- Issue
- 2
- Pages
- 73-76
- ISSN
- 1461-023X (ISSN-L)
- 1461-0248
- OpenAlex
- W1863193264
- Cited by
- 470
- References
- 1
- FWCI
- 18.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Loreau, M. (2000). Are communities saturated? On the relationship between α, β and γ diversity. Ecology Letters. https://doi.org/10.1046/j.1461-0248.2000.00127.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.