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The evolutionary genomics of species’ responses to climate change


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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Fig. 1: Genetic structure and species distribution models.
Fig. 2: Turnover functions and genetic offsets.
Fig. 3: Gene flow into focal populations.
Fig. 4: Predicting potential areas of future dispersal.
Fig. 5: The FOLDS integrated framework.

Data availability

The exemplar mexicana data used in all analyses are available at Zenodo (

Code availability

The Markdown file is available as Supplementary Information. All R code is also available at Zenodo (


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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.

Author information




J.A.A.-L., S.R.-B. and B.S.G shaped ideas and content, discussed the results and wrote the manuscript. J.A.A.-L. wrote the code, and S.R.-B. and J.A.A.-L. constructed the Markdown file.

Corresponding author

Correspondence to Brandon S. Gaut.

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The authors declare no competing interests.

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Supplementary protocols, containing the description and code used to perform all of the analyses in the manuscript, and Supplementary Figs. 1–15.

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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 (2021).

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