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   . 2008 Mar;11(3):208-16.
   doi: 10.1111/j.1461-0248.2007.01137.x. Epub 2007 Dec 7.

Network structural properties mediate the stability of mutualistic communities

   [39]Toshinori Okuyama^ [40] 1 , [41]J Nathaniel Holland
   Affiliations (BUTTON) Expand

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     * ^1 Department of Ecology and Evolutionary Biology, Rice University, Houston,
       TX 77005, USA.

     * PMID: 18070101
     * DOI: [42]10.1111/j.1461-0248.2007.01137.x

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Network structural properties mediate the stability of mutualistic communities

   Toshinori Okuyama et al. Ecol Lett. 2008 Mar.
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   . 2008 Mar;11(3):208-16.
   doi: 10.1111/j.1461-0248.2007.01137.x. Epub 2007 Dec 7.

Authors

   [46]Toshinori Okuyama^ [47] 1 , [48]J Nathaniel Holland

Affiliation

     * ^1 Department of Ecology and Evolutionary Biology, Rice University, Houston,
       TX 77005, USA.

     * PMID: 18070101
     * DOI: [49]10.1111/j.1461-0248.2007.01137.x

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   Key advances are being made on the structures of predator-prey food webs and
   competitive communities that enhance their stability, but little attention has
   been given to such complexity-stability relationships for mutualistic
   communities. We show, by way of theoretical analyses with empirically informed
   parameters, that structural properties can alter the stability of mutualistic
   communities characterized by nonlinear functional responses among the interacting
   species. Specifically, community resilience is enhanced by increasing community
   size (species diversity) and the number of species interactions (connectivity),
   and through strong, symmetric interaction strengths of highly nested networks. As
   a result, mutualistic communities show largely positive complexity-stability
   relationships, in opposition to the standard paradox. Thus, contrary to the
   commonly-held belief that mutualism's positive feedback destabilizes food webs,
   our results suggest that interplay between the structure and function of
   ecological networks in general, and consideration of mutualistic interactions in
   particular, may be key to understanding complexity-stability relationships of
   biological communities as a whole.

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