Aim: A central question in landscape genetics is how local adaptation among heterogeneous environments leads to genetic variation in natural populations. This article has two aims: (1) to examine associations between non-neutral genetic diversity of stream insect populations and environmental heterogeneity simulated by a hydrothermal model; and (2) to establish a novel framework for simulating the spatial distribution of adaptive genetic variation at catchment scale. Location: Natori River basin, north-eastern Japan. Methods: A distributed hydrothermal model was used to simulate current velocity, water depth and water temperature throughout the basin. We used empirical genetic data from 6-21 non-neutral amplified fragment length polymorphism (AFLP) loci in four target stream insect species found at 45 sampling sites. We constructed multiple regression models using allele frequencies at the non-neutral loci as objective variables and the hydrothermal and geographical parameters as candidate explanatory variables. Results: Of the four species, one caddisfly species provided strong evidence of local adaptation to the annual maximum water temperature. Assuming a priori that the regression models were applicable throughout the study area, we visualized the geographical distributions of genetically similar groups - UPGMA (unweighted pair group method with arithmetic mean) clusters based on genetic distance - and local genetic diversity along the simulated hydrothermal gradients. The UPGMA clusters of two caddisfly species (Hydropsyche orientalis and Stenopsyche marmorata) showed clear spatial turnover along an elevational gradient. Local genetic diversities of these species showed lower genetic diversity in lowland areas. Main conclusions: The predicted spatial patterns along an elevational gradient could be explained by a hypothetical mechanism whereby lowland habitats only accommodate genotypes adapted to severe thermal conditions. Our approach of combining a hydrothermal simulation with genome-wide scans of non-neutral loci is promising for the identification of evolutionary associations of adaptive loci to the temporal regime of hydrothermal conditions, such as maxima and temporal variability.
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