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Disentangling nestedness from models of ecological complexity

Nature volume 487, pages 227–230 (2012)Cite this article

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Abstract

Complex networks of interactions are ubiquitous1 and are particularly important in ecological communities, in which large numbers of species exhibit negative (for example, competition or predation) and positive (for example, mutualism) interactions with one another. Nestedness in mutualistic ecological networks is the tendency for ecological specialists to interact with a subset of species that also interact with more generalist species2. Recent mathematical and computational analysis has suggested that such nestedness increases species richness3,4. By examining previous results and applying computational approaches to 59 empirical data sets representing mutualistic plant–pollinator networks, we show that this statement is incorrect. A simpler metric—the number of mutualistic partners a species has—is a much better predictor of individual species survival and hence, community persistence. Nestedness is, at best, a secondary covariate rather than a causative factor for biodiversity in mutualistic communities. Analysis of complex networks should be accompanied by analysis of simpler, underpinning mechanisms that drive multiple higher-order network properties.

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Figure 1: Real networks exhibit a wide range of nestedness and connectance.
Figure 2: Adding mutualistic interactions to models of real networks decreases persistence and this decrease is not related to nestedness.
Figure 3: The number of mutualistic partners is a robust and consistent metric of species viability in mutualistic networks.

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Acknowledgements

We thank D. Franks, D. Kelly, R. Law, D. Stouffer, C. Thomas and J. Tylianakis for discussions and constructive criticisms, and J.Williams for independent verification of numerical results. M.J.P., A.J. and J.W.P. were supported by the Royal Society of New Zealand Marsden Fund, grant number 08-UOC-034. J.W.P. acknowledges the support of the University of Canterbury Erskine Programme.

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Authors and Affiliations

  1. Biomathematics Research Centre, University of Canterbury, Private Bag 4800, Christchurch 8040, New Zealand ,

    Alex James & Michael J. Plank

  2. and Departments of Biology and Mathematics, York Centre for Complex Systems Analysis, University of York, Heslington, York YO10 5DD, United Kingdom,

    Jonathan W. Pitchford

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  1. Alex James
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All authors contributed equally to this work.

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Correspondence to Alex James.

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The authors declare no competing financial interests.

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James, A., Pitchford, J. & Plank, M. Disentangling nestedness from models of ecological complexity. Nature 487, 227–230 (2012). https://doi.org/10.1038/nature11214

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