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Dryad

Data from: Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

Cite this dataset

Fournier-Level, Alexandre et al. (2017). Data from: Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana [Dataset]. Dryad. https://doi.org/10.5061/dryad.jn4qq

Abstract

Anticipating the effect of climate change on plants requires understanding its evolutionary consequence on traits and genes in complex realistic environments. How seasonal variation has an impact on the dynamics of adaptation in natural populations remains unclear. We simulated adaptation to different climate change scenarios, grounding our analysis in experimental data and explicitly exploring seasonal variation. Seasonal variation dramatically affected the dynamics of adaptation: Marked seasonality led to genetic differentiation within the population to different seasonal periods, whereas low seasonality led to a single population with fast-evolving fitness. Our results suggest the prevalence of phenotypic plasticity across environmental conditions in determining how climate change will shift selection on traits and loci. In this unpredictable context, maintaining broad genomic diversity is critical.

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