Common garden experiments to study local adaptation need to account for population structure

• Published in: The Journal of ecology Vol. 110; no. 5; pp. 1005 - 1009
• Main Authors: Villemereuil, Pierre, Gaggiotti, Oscar E., Goudet, Jérôme
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.05.2022; Wiley
• Subjects: Adaptation; Biodiversity; common garden; Divergence; Gardens & gardening; Genetics; Life Sciences; local adaptation; Noise generation; phenotypic divergence; Phenotypic plasticity; Population genetics; Population structure; Populations and Evolution; QST − FST comparison; quantitative genetics; common garden; population genetics; quantitative genetics; Q ST − F ST comparison; population structure; Local adaptation; phenotypic divergence
• ISSN: 0022-0477; 1365-2745
• DOI: 10.1111/1365-2745.13528

Common garden experiments are precious to study adaptive phenomenon and adaptive potential, in that they allow to study local adaptation without the confounding effect of phenotypic plasticity. The QST − FST comparison framework, comparing genetic differentiation at the phenotypic and molecular level, is the usual way to test and measure whether local adaptation influences phenotypic divergence between populations. Here, we highlight that the assumptions behind the expected equality QST = FST under neutrality correspond to a very simple model of population genetics. While the equality might, on average, be robust to violation of such assumptions, more complex population structure can generate strong evolutionary noise. Synthesis. We highlight recent methodological developments aimed at overcoming this issue and at providing a more general framework to detect local adaptation, using less restrictive assumptions. We invite empiricists to look into these methods and theorists to continue developing even more general methods. We highlight recent methodological developments aimed at overcoming this issue and at providing a more general framework to detect local adaptation, using less restrictive assumptions. We invite empiricists to look into these methods and theorists to continue developing even more general methods.