Raimundo RLG, Guimarães PR Jr, Evans DM. Adaptive Networks for Restoration Ecology.
Trends Ecol Evol 2018;
33:664-75. [PMID:
30005837 DOI:
10.1016/j.tree.2018.06.002]
[Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 06/06/2018] [Accepted: 06/12/2018] [Indexed: 11/22/2022]
Abstract
The urgent need to restore biodiversity and ecosystem functioning challenges ecology as a predictive science. Restoration ecology would benefit from evolutionary principles embedded within a framework that combines adaptive network models and the phylogenetic structure of ecological interactions. Adaptive network models capture feedbacks between trait evolution, species abundances, and interactions to explain resilience and functional diversity within communities. Phylogenetically-structured network data, increasingly available via next-generation sequencing, inform constraints affecting interaction rewiring. Combined, these approaches can predict eco-evolutionary changes triggered by community manipulation practices, such as translocations and eradications of invasive species. We discuss theoretical and methodological opportunities to bridge network models and data from restoration projects and propose how this can be applied to the functional restoration of ecological interactions.
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