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...
| Main Authors: | , , , , |
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| Format: | Dataset |
| Language: | English |
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Dryad
2011
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.4f1r5vg8 https://datadryad.org/stash/dataset/doi:10.5061/dryad.4f1r5vg8 |
| Summary: | 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 ... : MEC-11-0847 Born CThis file is an excel spreadsheet giving details about individuals' locations (in decimal degree) and genotypes (6 microsatellites markers) for the four study sites presented in the study. ... |
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