Adaptive Networks for Restoration Ecology

Autor(es)

Raimundo, Rafael L. G. ^{[1, 2]} ; Guimaraes, Jr., Paulo R. ^[1] ; Evans, Darren M. ^[3]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Biociencias, Dept Ecol, Sao Paulo, SP - Brazil

^[2] Univ Fed Paraiba, Ctr Ciencias Aplicadas & Educ, Dept Engn & Meio Ambiente, Campus 4, Rio Tinto, PB - Brazil

^[3] Newcastle Univ, Sch Nat & Environm Sci, Newcastle Upon Tyne, Tyne & Wear - England

• Tipo de documento: Artigo de Revisão
• Fonte: TRENDS IN ECOLOGY & EVOLUTION; v. 33, n. 9, p. 664-675, SEP 2018.
• Citações Web of Science: 14

Resumo

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. (AU)

• Processo FAPESP: 14/21106-4 - Divergência fenotípica e especiação ecológica em mutualismos: efeitos da estrutura espacial e intimidade de interação
• Beneficiário: Rafael Luís Galdini Raimundo
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 17/08406-7 - Como a perda e adição de espécies e interações influencia a dinâmica coevolutiva em redes mutualistas?
• Beneficiário: Paulo Roberto Guimarães Junior
• Modalidade de apoio: Auxílio à Pesquisa - Regular