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Effects of network modularity on the spread of perturbation impact in experimental metapopulations

Luis J. Gilarranz, Bronwyn Rayfield, Gustavo Liñán-Cembrano, Jordi Bascompte, Andrew Gonzalez



Modularity limits disturbance effects. The networks that form natural, social, and technological systems are vulnerable to the spreading impacts of perturbations. Theory predicts that networks with a clustered or modular structure—where nodes within a module interact more frequently than they do with nodes in other modules—might contain a perturbation, preventing it from spreading to the entire network. Gilarranz et al. conducted experiments with networked populations of springtail (Folsomia candida) microarthropods to show that modularity limits the impact of a local extinction on neighboring nodes (see the Perspective by Sales-Pardo). In networks with high modularity, the perturbation was contained within the targeted module, and its impact did not spread to nodes beyond it. However, simulations revealed that modularity is beneficial to the network only when perturbations are present; otherwise, it hinders population growth.

Abstract. Networks with a modular structure are expected to have a lower risk of global failure. However, this theoretical result has remained untested until now. We used an experimental microarthropod metapopulation to test the effect of modularity on the response to perturbation. We perturbed one local population and measured the spread of the impact of this perturbation, both within and between modules. Our results show the buffering capacity of modular networks. To assess the generality of our findings, we then analyzed a dynamical model of our system. We show that in the absence of perturbations, modularity is negatively correlated with metapopulation size. However, even when a small local perturbation occurs, this negative effect is offset by a buffering effect that protects the majority of the nodes from the perturbation.


Science, Vol. 357, No. 6347. (14 July 2017), pp. 199-201, https://doi.org/10.1126/science.aal4122 
Key: INRMM:14392758

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