Data from: Plant dispersal in the sub-Antarctic inferred from anisotropic genetic structure

Climatic conditions and landscape features often strongly affect species’
local distribution patterns, dispersal, reproduction and survival, and may
therefore have considerable impacts on species' fine-scale spatial
genetic structure (SGS). In this paper we demonstrate the efficacy of
combining fine-scale SGS analyses with isotropic and anisotropic spatial
autocorrelation techniques to infer the impact of wind patterns on plant
dispersal processes. We genotyped 1304 Azorella selago (Apiaceae)
specimens, a wind-pollinated and wind-dispersed plant, from four
populations distributed across sub-Antarctic Marion Island. SGS was
variable with Sp values ranging from 0.001 to 0.014, suggesting notable
variability in dispersal distance and wind velocities between sites.
Nonetheless, the data supported previous hypotheses of a strong NW – SE
gradient in wind strength across the island. Anisotropic autocorrelation
analyses further suggested that dispersal is strongly directional, but
varying between sites depending on the local prevailing winds. Despite the
high frequency of gale-force winds on Marion Island, gene dispersal
distance estimates (σ) were surprisingly low (< 10 m), most likely
because of a low pollen dispersal efficiency. An SGS approach in
association with isotropic and anisotropic analyses provides a powerful
means to assess the relative influence of abiotic factors on dispersal,
and allow inferences that would not be possible without this combined
approach.