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  5. Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks

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Article
en
2020

Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks

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en
2020
Vol 10 (1)
Vol. 10
DOI: 10.1038/s41598-020-66131-5

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Carlos M. Duarte
Carlos M. Duarte

King Abdullah University of Science and Technology

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Somaye Sheykhali
Juan Fernández-Gracia
Anna Traveset
+4 more

Abstract

Understanding the response of ecological networks to perturbations and disruptive events is needed to anticipate the biodiversity loss and extinction cascades. Here, we study how network plasticity reshapes the topology of mutualistic networks in response to species loss. We analyze more than one hundred empirical mutualistic networks and considered random and targeted removal as mechanisms of species extinction. Network plasticity is modeled as either random rewiring, as the most parsimonious approach, or resource affinity-driven rewiring, as a proxy for encoding the phylogenetic similarity and functional redundancy among species. This redundancy should be positively correlated with the robustness of an ecosystem, as functions can be taken by other species once one of them is extinct. We show that effective modularity, i.e. the ability of an ecosystem to adapt or restructure, increases with increasing numbers of extinctions, and with decreasing the replacement probability. Importantly, modularity is mostly affected by the extinction rather than by rewiring mechanisms. These changes in community structure are reflected in the robustness and stability due to their positive correlation with modularity. Resource affinity-driven rewiring offers an increase of modularity, robustness, and stability which could be an evolutionary favored mechanism to prevent a cascade of co-extinctions.

How to cite this publication

Somaye Sheykhali, Juan Fernández-Gracia, Anna Traveset, Maren Ziegler, Christian R. Voolstra, Carlos M. Duarte, Victor M. Eguı́luz (2020). Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks. , 10(1), DOI: https://doi.org/10.1038/s41598-020-66131-5.

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Publication Details

Type

Article

Year

2020

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1038/s41598-020-66131-5

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