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

Authors

  • CÉLINE BORN,

    1. Evolutionary Genomics Group, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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  • PETER C. Le ROUX,

    1. Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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    • Current address: Department of Geosciences and Geography, University of Helsinki, PO Box 64, FI-00014, Finland

  • COLIN SPOHR,

    1. Evolutionary Genomics Group, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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  • MELODIE A. McGEOCH,

    1. Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
    2. Cape Research Centre, South African National Parks, PO Box 216, Steenberg 7947, South Africa
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  • BETTINE JANSEN Van VUUREN

    1. Evolutionary Genomics Group, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
    2. Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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    • Department of Zoology, University of Johannesburg, PO Box 524, Auckland Park, 2006, South Africa


Céline Born, Fax: +27 21 808 2405; E-mail: celineborn@hotmail.com; celineborn@gmail.com

Abstract

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 study, 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 probably 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.

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