Data from: Local topography shapes fine-scale spatial genetic structure in the Arkansas Valley evening primrose, Oenothera harringtonii (Onagraceae)
Rhodes, Matthew K.
Fant, Jeremie B.
Skogen, Krissa A.
Published Jul 14, 2014 on Dryad.
Cite this dataset
Rhodes, Matthew K.; Fant, Jeremie B.; Skogen, Krissa A. (2014). Data from: Local topography shapes fine-scale spatial genetic structure in the Arkansas Valley evening primrose, Oenothera harringtonii (Onagraceae) [Dataset]. Dryad. https://doi.org/10.5061/dryad.h0f07
Identifying factors that shape the spatial distribution of genetic variation is crucial to understanding many population- and landscape-level processes. In this study, we explore fine-scale spatial genetic structure in Oenothera harringtonii (Onagraceae), an insect-pollinated, gravity-dispersed herb endemic to the grasslands of south-central and southeastern Colorado, USA. We genotyped 315 individuals with 11 microsatellite markers and utilized a combination of spatial autocorrelation analyses and landscape genetic models to relate life history traits and landscape features to dispersal processes. Spatial genetic structure was consistent with theoretical expectations of isolation by distance, but this pattern was weak (Sp = 0.00374). Anisotropic analyses indicated that spatial genetic structure was markedly directional, in this case consistent with increased dispersal along prominent slopes. Landscape genetic models subsequently confirmed that spatial genetic variation was significantly influenced by local topographic heterogeneity, specifically that geographic distance, elevation and aspect were important predictors of spatial genetic structure. Among these variables, geographic distance was ~68% more important than elevation in describing spatial genetic variation, and elevation was ~42% more important than aspect after removing the effect of geographic distance. From these results, we infer a mechanism of hydrochorous seed dispersal along major drainages aided by seasonal monsoon rains. Our findings suggest that landscape features may shape microevolutionary processes at much finer spatial scales than typically considered, and stress the importance of considering how particular dispersal vectors are influenced by their environmental context.
This file contains multilocus microsatellite genotypes for all individuals included in the study. Matt Rhodes collected these data in 2012 and 2013.
Rhodes et al. 2014 - genotypes.xlsx
This file contains SPAGeDi input for the population-wide SGS analysis (n=315) and the subsetted landscape genetic analysis (n=192), including UTM coordinates for all individuals included in the study.
Rhodes et al. 2014 - SPAGeDi input.xlsx
This file contains raster values for elevation, slope and aspect for the subset of individuals (n=192) included in the landscape genetic analysis. Matt Rhodes and Jeremie Fant collected these data in 2013.