Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability.
Author
Valdovinos, Fernanda SBrosi, Berry J
Briggs, Heather M
Moisset de Espanés, Pablo
Ramos-Jiliberto, Rodrigo
Martinez, Neo D
Affiliation
Univ Arizona, Dept Ecol & Evolut BiolIssue Date
2016-10Keywords
Adaptive behaviourcommunity stability
consumer-resource interactions
mechanistic models
mutualistic networks
population dynamics
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WILEY-BLACKWELLCitation
Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability. 2016, 19 (10):1277-86 Ecol. Lett.Journal
Ecology lettersRights
© 2016 John Wiley & Sons Ltd/CNRS.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Much research debates whether properties of ecological networks such as nestedness and connectance stabilise biological communities while ignoring key behavioural aspects of organisms within these networks. Here, we computationally assess how adaptive foraging (AF) behaviour interacts with network architecture to determine the stability of plant-pollinator networks. We find that AF reverses negative effects of nestedness and positive effects of connectance on the stability of the networks by partitioning the niches among species within guilds. This behaviour enables generalist pollinators to preferentially forage on the most specialised of their plant partners which increases the pollination services to specialist plants and cedes the resources of generalist plants to specialist pollinators. We corroborate these behavioural preferences with intensive field observations of bee foraging. Our results show that incorporating key organismal behaviours with well-known biological mechanisms such as consumer-resource interactions into the analysis of ecological networks may greatly improve our understanding of complex ecosystems.Note
Version of Record online: 6 SEP 2016. 12 Month EmbargoISSN
1461-0248PubMed ID
27600659Version
Final accepted manuscriptSponsors
University of Arizona; US NSF [ICER-131383, DEB-1241253, DEB-1120572, OIA-0963529, DBI 0821369, DBI 1219635, DBI 1034780, DBI 0420910, DBI 1262713]; Rocky Mountain Biological Laboratory; Emory University; University of California, Santa Cruz; FONDECYT [1150348]; Chilean CONICYT doctoral fellowshipAdditional Links
http://onlinelibrary.wiley.com/doi/10.1111/ele.12664/abstractae974a485f413a2113503eed53cd6c53
10.1111/ele.12664
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