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Predicting the future of our oceans—Evaluating genomic forecasting approaches in marine species

  • K. K.S. Layton
  • , M. S.O. Brieuc
  • , R. Castilho
  • , N. Diaz-Arce
  • , D. Estévez-Barcia
  • , V. G. Fonseca
  • , A. P. Fuentes-Pardo
  • , N. W. Jeffery
  • , B. Jiménez-Mena
  • , C. Junge
  • , J. Kaufmann
  • , T. Leinonen
  • , S. M. Maes
  • , P. McGinnity
  • , T. E. Reed
  • , C. M.O. Reisser
  • , G. Silva
  • , A. Vasemägi
  • , I. R. Bradbury
  • University of Toronto
  • University of Aberdeen
  • Institute of Marine Research
  • University of Algarve
  • Pattern Institute
  • Basque Research and Technology Alliance (BRTA)
  • Greenland Institute of Natural Resources
  • Centre for the Environment Fisheries and Aquaculture Science
  • Uppsala University
  • Fisheries and Oceans Canada
  • Technical University of Denmark
  • Marine Institute
  • Luke Natural Resources Institute Finland
  • Research Institute for Agriculture and Fisheries
  • Université de Montpellier
  • Institute of Applied Psychology
  • Swedish University of Agricultural Sciences
  • Estonian University of Life Sciences

Research output: Contribution to journalArticlepeer-review

Abstract

Climate change is restructuring biodiversity on multiple scales and there is a pressing need to understand the downstream ecological and genomic consequences of this change. Recent advancements in the field of eco-evolutionary genomics have sought to include evolutionary processes in forecasting species' responses to climate change (e.g., genomic offset), but to date, much of this work has focused on terrestrial species. Coastal and offshore species, and the fisheries they support, may be even more vulnerable to climate change than their terrestrial counterparts, warranting a critical appraisal of these approaches in marine systems. First, we synthesize knowledge about the genomic basis of adaptation in marine species, and then we discuss the few examples where genomic forecasting has been applied in marine systems. Next, we identify the key challenges in validating genomic offset estimates in marine species, and we advocate for the inclusion of historical sampling data and hindcasting in the validation phase. Lastly, we describe a workflow to guide marine managers in incorporating these predictions into the decision-making process.

Original languageEnglish
Article numbere17236
JournalGlobal Change Biology
Volume30
Issue number3
DOIs
Publication statusPublished - Mar 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • adaptation
  • climate change
  • genomic offset
  • marine species
  • validation

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