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Adaptive Networks for Restoration Ecology

Lookup NU author(s): Dr Rafael Raimundo, Professor Darren Evans



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


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.

Publication metadata

Author(s): Raimundo RLG, GuimarĂ£es PR, Evans DM

Publication type: Article

Publication status: Published

Journal: Trends in Ecology and Evolution

Year: 2018

Volume: 33

Issue: 9

Pages: 664-675

Print publication date: 01/09/2018

Online publication date: 11/07/2018

Acceptance date: 12/06/2018

Date deposited: 20/06/2018

ISSN (print): 0169-5347

ISSN (electronic): 1872-8383

Publisher: Elsevier


DOI: 10.1016/j.tree.2018.06.002


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