Coevolution increases robustness to extinctions in mutualistic but not exploitative communities

IF 4.4 2区 环境科学与生态学 Q1 ECOLOGY
Ecology Pub Date : 2025-03-03 DOI:10.1002/ecy.70044
Fernando Pedraza, Klementyna A. Gawecka, Jordi Bascompte
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Abstract

Coextinctions may exacerbate the current biodiversity crisis. Yet, we do not understand all the factors that shape the robustness of communities to the loss of species. Here we analyze how coevolution influences the robustness to secondary extinctions of mutualistic and exploitative communities. We find that coevolution increases robustness in mutualism but reduces it under exploitative interactions. These differences are due to coevolution altering the density of interactions in communities. Coevolution leads to densely connected mutualistic communities and sparsely connected exploitative communities. We find the magnitude of these effects depends on the strength of coevolution and the size of the community. The largest changes to the density of interactions and robustness of communities occur when coevolutionary selection is strong. Moreover, the changes to network robustness are greater for small mutualistic communities and large exploitative communities. Our results broaden our understanding of the suite of mechanisms affecting the resilience of ecological communities. These insights may inform efforts to reduce the risk of species loss in the face of global change.

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来源期刊
Ecology
Ecology 环境科学-生态学
CiteScore
8.30
自引率
2.10%
发文量
332
审稿时长
3 months
期刊介绍: Ecology publishes articles that report on the basic elements of ecological research. Emphasis is placed on concise, clear articles documenting important ecological phenomena. The journal publishes a broad array of research that includes a rapidly expanding envelope of subject matter, techniques, approaches, and concepts: paleoecology through present-day phenomena; evolutionary, population, physiological, community, and ecosystem ecology, as well as biogeochemistry; inclusive of descriptive, comparative, experimental, mathematical, statistical, and interdisciplinary approaches.
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