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Updated: Jul 1, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Nucleotide diversity is a poor predictor of short-term adaptive potential
Katie L Abson1, Lillith Zijmers2, Elizabeth A Mittell1
1Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, United Kingdom.
None:
The capacity to adapt is essential for a population to avoid extinction in a changing world and is recognized as a global conservation priority. Adaptation requires additive (heritable) genetic variation for traits that influence survival and fecundity, but measuring this variation is difficult, particularly in species of conservation concern. Instead, molecular genetic diversity is often used to infer adaptive potential. However, previous research has cast doubt on the suitability of traditional molecular markers (allozymes and microsatellites) for this purpose given their weak relationship with heritability-a common measure of additive genetic variance. Advances in sequencing technology have since shifted focus toward nucleotide diversity and variation in functional regions, but their practicality for predicting adaptive potential remains debated. Furthermore, heritability itself is a poor proxy for adaptive potential because it depends on environmental variance. We collated 2,113 published estimates of evolvability-a measure of additive genetic variance that avoids environmental confounding-across 193 eukaryotic species, and evaluated how well evolvability is predicted by molecular diversity. We find that microsatellite and nucleotide diversity are not significantly correlated to each other, and neither predict evolvability. Nucleotide diversity explains 1.1% of interspecific differences in evolvability and doubling nucleotide diversity only corresponds to a 11.7% increase in evolvability. With theoretical work, we show that such weak associations are expected. Together, our results suggest that simple molecular measures of genetic variation are insufficient for predicting adaptive potential and reliance on these metrics risks misinforming conservation management.
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