title: Are molecular markers useful predictors of adaptive potential?
abstract: Estimates of molecular genetic variation are often used as a cheap and simple surrogate for a population's adaptive potential, yet empirical evidence suggests they are unlikely to be a valid proxy. However, this evidence is based on molecular genetic variation poorly predicting estimates of adaptive potential rather than how well it predicts true values. As a consequence, the relationship has been systematically underestimated and the precision with which it could be measured severely overstated. By collating a large database, and using suitable statistical methods, we obtain a 95% upper bound of 0.26 for the proportion of variance in quantitative genetic variation explained by molecular diversity. The relationship is probably too weak to be useful, but this conclusion must be taken as provisional: less noisy estimates of quantitative genetic variation are required. In contrast, and perhaps surprisingly, current sampling strategies appear sufficient for characterising a population's molecular genetic variation at comparable markers.
authors.affiliation: Institute of Biodiversity, Animal Health and Comparative Medicine, Graham Kerr Building, University of Glasgow, Glasgow, G12 8QQ, UK.|Institute of Evolutionary Biology, University of Edinburgh, The King's Buildings, Charlotte Auerbach Road, EH9 3FL, UK.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Mittell
authors.affiliation: Evolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia.|Department of Zoology, University of Otago, Great King Street, Dunedin, 9016, New Zealand.
authors.forename: Shinichi
authors.identifier: http://orcid.org/0000-0002-7765-5182
authors.initials: S
authors.lastname: Nakagawa
authors.affiliation: Institute of Evolutionary Biology, University of Edinburgh, The King's Buildings, Charlotte Auerbach Road, EH9 3FL, UK.
authors.forename: Jarrod D
authors.initials: JD
authors.lastname: Hadfield
mesh_terms: D000220:Adaptation, Biological; D030541:Databases, Genetic; D005819:Genetic Markers; D014644:Genetic Variation; D005828:Genetics, Population; D016014:Linear Models; D018895:Microsatellite Repeats; D008957:Models, Genetic
chemical_list: D005819:Genetic Markers
keywords: Adaptive potential; conservation genetics; heritability; microsatellite diversity & heterozygosity; nucleotide diversity; quantitative genetics