Individual-based eco-evolutionary models for understanding adaptation in changing seas

Amanda Xuereb, Quentin Rougemont, Peter Tiffin, Huijie Xue, Megan Phifer-Rixey

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Article number20212006
JournalProceedings of the Royal Society B: Biological Sciences
Issue number1962
StatePublished - 2021

Bibliographical note

Funding Information:
A.X. received support from Louis Bernatchez and the Canada Research Chair in Genomics and Conservation of Aquatic Resources to attend the workshop. M.P.-R. is supported by a Faculty Fellowship from Monmouth University and the Urban Coast Institute. H.X. is supported by OCE-14-58239 from the National Science Foundation to the University of Maine. P.T. received support from National Science Foundation award IOS-1856744. Acknowledgements

Publisher Copyright:
© 2021 The Author(s).


  • SLiM
  • climate change
  • eco-evolutionary model
  • individual-based model
  • marine


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