Theoretical perspective highlights detection biases overlooking small-effect alleles in local adaptation, suggesting integrated genomic and phenotypic approaches are vital.
How will species adapt to changing environments? To what extent does adaptation to previous conditions maintain the variation needed to adapt to future conditions? To answer these kinds of questions, we need to identify locally adaptive alleles and quantify their effects. Theory shows that the architecture of adaptation can depend upon the nature of mutation and on how ecology shapes the processes of migration and selection. Depending on this interplay, adaptation can be driven by few alleles of large effect or many alleles of small effect, but little is known about the relative prevalence of such architectures in nature. Unfortunately, our statistical methods are also biased: it is much easier to identify loci of large effect that contribute repeatedly across populations or species, while alleles of small effect are all but invisible to genomic analysis. There is, therefore, a gap between the total amount of locally adaptive variation and that which is explained by genomic studies. To quantify this missing local adaptation, future studies require a deep integration of genomic and phenotypic analyses.
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Booker et al. (2026) studied this question.
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