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.气候条件与景观特征往往会显著影响物种的局部分布格局、扩散过程、繁殖能力与存活状况，进而对物种的精细尺度空间遗传结构（spatial genetic structure，SGS）产生重要影响。本研究验证了将精细尺度空间遗传结构分析与各向同性、各向异性空间自相关技术相结合，以推断风场模式对植物扩散过程影响的有效性。我们对分布于亚南极马里恩岛的四个种群的1304株Azorella selago（伞形科Apiaceae）样本进行了基因分型，该物种为风媒传粉且以风力进行扩散的植物。该物种的空间遗传结构存在显著差异，Sp统计量取值范围为0.001至0.014，表明不同样地间的扩散距离与风速存在明显波动。尽管如此，研究数据支持了此前提出的‘全岛风速存在显著西北-东南向梯度’的假说。各向异性自相关分析进一步表明，植物扩散具有强烈的方向性，但不同样地的扩散方向会随局地盛行风发生变化。尽管马里恩岛频发暴风级大风，基因扩散距离估计值（σ）却低得出奇（<10米），这大概率源于花粉扩散效率较低。将空间遗传结构分析方法与各向同性、各向异性分析相结合，为评估非生物因子对物种扩散的相对影响提供了强有力的手段，且能够得出单一方法无法实现的推断结论。