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Individual-based eco-evolutionary models for understanding adaptation in changing seas.
Xuereb, Amanda; Rougemont, Quentin; Tiffin, Peter; Xue, Huijie; Phifer-Rixey, Megan.
Afiliación
  • Xuereb A; Institut de Biologie Intégrative et des Systèmes, Département de Biologie, Université Laval, 3050 Avenue de la Médecine, Québec, Quebec, Canada G1 V 0A6.
  • Rougemont Q; CEFE, Centre d'Ecologie Fonctionnelle et Evolutive UMR 5175, CNRS, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France.
  • Tiffin P; Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Avenue, Saint Paul, MN 55108, USA.
  • Xue H; School of Marine Sciences, University of Maine, 5706 Aubert Hall, Orono, ME 04469-5706, USA.
  • Phifer-Rixey M; Department of Biology, Monmouth University, 400 Cedar Avenue, West Long Branch, NJ, USA.
Proc Biol Sci ; 288(1962): 20212006, 2021 11 10.
Article en En | MEDLINE | ID: mdl-34753353
ABSTRACT
As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Adaptación Fisiológica / Evolución Biológica Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Adaptación Fisiológica / Evolución Biológica Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2021 Tipo del documento: Article