Climate change is a threat to biodiversity. One way that this threat manifests is through pronounced shifts in the geographical range of species over time. To predict these shifts, researchers have primarily used species distribution models. However, these models are based on assumptions of niche conservatism and do not consider evolutionary processes, potentially limiting their accuracy and value. To incorporate evolution into the prediction of species’ responses to climate change, researchers have turned to landscape genomic data and examined information about local genetic adaptation using climate models. Although this is an important advancement, this approach currently does not include other evolutionary processes—such as gene flow, population dispersal and genomic load—that are critical for predicting the fate of species across the landscape. Here, we briefly review the current practices for the use of species distribution models and for incorporating local adaptation. We next discuss the rationale and theory for considering additional processes, reviewing how they can be incorporated into studies of species’ responses to climate change. We summarize with a conceptual framework of how manifold layers of information can be combined to predict the potential response of specific populations to climate change. We illustrate all of the topics using an exemplar dataset and provide the source code as potential tutorials. This Perspective is intended to be a step towards a more comprehensive integration of population genomics with climate change science.
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Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia
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The exemplar mexicana data used in all analyses are available at Zenodo (https://doi.org/10.5281/zenodo.4746517).
The Markdown file is available as Supplementary Information. All R code is also available at Zenodo (https://doi.org/10.5281/zenodo.4746517).
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The study was supported by a UC-Mexus postdoctoral fellowship to J.A.A.-L., National Science Foundation grant no. 1741627 to B.S.G. and CONACyT Ciencia de Frontera 2019 grant no. 263962 to S.R.-B.
The authors declare no competing interests.
Peer review information Nature Ecology & Evolution thanks Matthew Fitzpatrick, Ann-Marie Waldvogel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Aguirre-Liguori, J.A., Ramírez-Barahona, S. & Gaut, B.S. The evolutionary genomics of species’ responses to climate change. Nat Ecol Evol 5, 1350–1360 (2021). https://doi.org/10.1038/s41559-021-01526-9