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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-61814

Beckerman, A P; Petchey, O L; Warren, P H (2006). Foraging biology predicts food web complexity. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 103(37):13745-13749.

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Abstract

Food webs, the networks of feeding links between species, are central to our understanding of ecosystem structure, stability, and function. One of the key aspects of food web structure is complexity, or connectance, the number of links expressed as a proportion of the total possible number of links. Connectance (complexity) is linked to the stability of webs and is a key parameter in recent models of other aspects of web structure. However, there is still no fundamental biological explanation for connectance in food webs. Here, we propose that constraints on diet breadth, driven by optimal foraging, provide such an explanation. We show that a simple diet breadth model predicts highly constrained values of connectance as an emergent consequence of individual foraging behavior. When combined with features of real food web data, such as taxonomic and trophic aggregation and cumulative sampling of diets, the model predicts well the levels of connectance and scaling of connectance with species richness, seen in real food webs. This result is a previously undescribed synthesis of foraging theory and food web theory, in which network properties emerge from the behavior of individuals and, as such, provides a mechanistic explanation of connectance currently lacking in food web models.

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
DDC:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:2006
Deposited On:10 Jul 2012 16:01
Last Modified:30 Nov 2013 22:12
Publisher:National Academy of Sciences
ISSN:0027-8424
Publisher DOI:10.1073/pnas.0603039103
Other Identification Number:Accession Number: WOS:000240648300036
Citations:Web of Science®. Times Cited: 102
Google Scholar™
Scopus®. Citation Count: 94

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