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Immigration, Local Dispersal Limitation, and the Repeatability of Community Composition under Neutral and Niche Dynamics

Overview of attention for article published in PLOS ONE, September 2012
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Title
Immigration, Local Dispersal Limitation, and the Repeatability of Community Composition under Neutral and Niche Dynamics
Published in
PLOS ONE, September 2012
DOI 10.1371/journal.pone.0046164
Pubmed ID
Authors

Dexiecuo Ai, Philippe Desjardins-Proulx, Chengjin Chu, Gang Wang

Abstract

Repeatability of community composition has been a critical aspect for community structure, which is closely associated with community stability, predictability, conservation biology and ecological restoration. It has been shown that both immigration and local dispersal limitation can affect the community composition in both neutral and niche model. Hence, we use a spatially explicit individual-based model to investigate the potential influence of immigration rate and strength of local dispersal limitation on repeatability in both neutral and niche models. Similarity measures are used to quantify repeatability. We examine the repeatability of community composition among replicate communities (which means the same community repeats many times), and between niche and neutral replicate communities. We find the correlation between repeatability and immigration rate is positive in the neutral model and an inverted unimodal in the niche model. The correlation between repeatability and local dispersal distance is positive in the niche model and negative in the neutral model. High repeatability between niche communities and neutral communities is observed with high immigration rates or when high local dispersal distance appears in the niche model or low local dispersal distance in the neutral model. Our results show that repeatability of community composition is not only dependent on the types of community models (niche vs. neutrality) but also strongly determined by immigration rates and local dispersal limitation.

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Geographical breakdown

Country Count As %
France 2 2%
Brazil 2 2%
Réunion 1 1%
Israel 1 1%
Mexico 1 1%
Argentina 1 1%
United States 1 1%
Unknown 73 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 27%
Student > Ph. D. Student 19 23%
Professor > Associate Professor 9 11%
Student > Master 7 9%
Professor 5 6%
Other 14 17%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 54%
Environmental Science 21 26%
Social Sciences 2 2%
Mathematics 1 1%
Unspecified 1 1%
Other 4 5%
Unknown 9 11%