Self-regulation and the stability of large ecological networks

György Barabás, Matthew J. Michalska-Smith, Stefano Allesina

Research output: Contribution to journalArticlepeer-review

78 Scopus citations


The stability of complex ecological networks depends both on the interactions between species and the direct effects of the species on themselves. These self-effects are known as 'self-regulation' when an increase in a species' abundance decreases its per-capita growth rate. Sources of self-regulation include intraspecific interference, cannibalism, time-scale separation between consumers and their resources, spatial heterogeneity and nonlinear functional responses coupling predators with their prey. The influence of self-regulation on network stability is understudied and in addition, the empirical estimation of self-effects poses a formidable challenge. Here, we show that empirical food web structures cannot be stabilized unless the majority of species exhibit substantially strong self-regulation. We also derive an analytical formula predicting the effect of self-regulation on network stability with high accuracy and show that even for random networks, as well as networks with a cascade structure, stability requires negative self-effects for a large proportion of species. These results suggest that the aforementioned potential mechanisms of self-regulation are probably more important in contributing to the stability of observed ecological networks than was previously thought.

Original languageEnglish (US)
Pages (from-to)1870-1875
Number of pages6
JournalNature Ecology and Evolution
Issue number12
StatePublished - Dec 1 2017
Externally publishedYes

Bibliographical note

Funding Information:
We thank A. Celani, J. Grilli, M. Marsili, T. Rogers and E. Sander for discussions, as well as D. Gravel and C. Guill for their valuable input and thorough reading of earlier versions of the paper. This work was supported by the National Science Foundation (#1148867) and United States Department of Education grant P200A150101.

Publisher Copyright:
© 2017 The Author(s).

Copyright 2017 Elsevier B.V., All rights reserved.


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