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Emergence of Structural Patterns in Neutral Trophic Networks

Overview of attention for article published in PLOS ONE, August 2012
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Title
Emergence of Structural Patterns in Neutral Trophic Networks
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0038295
Pubmed ID
Authors

Elsa Canard, Nicolas Mouquet, Lucile Marescot, Kevin J. Gaston, Dominique Gravel, David Mouillot

Abstract

Interaction networks are central elements of ecological systems and have very complex structures. Historically, much effort has focused on niche-mediated processes to explain these structures, while an emerging consensus posits that both niche and neutral mechanisms simultaneously shape many features of ecological communities. However, the study of interaction networks still lacks a comprehensive neutral theory. Here we present a neutral model of predator-prey interactions and analyze the structural characteristics of the simulated networks. We find that connectance values (complexity) and complexity-diversity relationships of neutral networks are close to those observed in empirical bipartite networks. High nestedness and low modularity values observed in neutral networks fall in the range of those from empirical antagonist bipartite networks. Our results suggest that, as an alternative to niche-mediated processes that induce incompatibility between species ("niche forbidden links"), neutral processes create "neutral forbidden links" due to uneven species abundance distributions and the low probability of interaction between rare species. Neutral trophic networks must be seen as the missing endpoint of a continuum from niche to purely stochastic approaches of community organization.

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The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 6 4%
Brazil 5 3%
Japan 3 2%
Mexico 2 1%
Israel 2 1%
Réunion 1 <1%
Italy 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Other 5 3%
Unknown 143 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 22%
Researcher 31 18%
Student > Master 29 17%
Student > Bachelor 17 10%
Student > Doctoral Student 8 5%
Other 25 15%
Unknown 23 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 90 53%
Environmental Science 31 18%
Earth and Planetary Sciences 3 2%
Immunology and Microbiology 2 1%
Physics and Astronomy 2 1%
Other 11 6%
Unknown 31 18%