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Relating geographical variation in pollination types to environmental and spatial factors using novel statistical methods

Authors

  • Ingolf Kühn,

    1. UFZ – Centre for Environmental Research Leipzig-Halle, Department of Community Ecology (BZF), Theodor-Lieser-Strasse 4, D–06120 Halle, Germany;
    2. Virtual Institute Macroecology, Theodor-Lieser-Strasse 4, D–06120 Halle, Germany;
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  • Stijn Martinus Bierman,

    1. BioSS – Biomathematics and Statistics Scotland, James Clerk Maxwell Building, The King's Building, Edinburgh EH9 3JZ, UK
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  • Walter Durka,

    1. UFZ – Centre for Environmental Research Leipzig-Halle, Department of Community Ecology (BZF), Theodor-Lieser-Strasse 4, D–06120 Halle, Germany;
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  • Stefan Klotz

    1. UFZ – Centre for Environmental Research Leipzig-Halle, Department of Community Ecology (BZF), Theodor-Lieser-Strasse 4, D–06120 Halle, Germany;
    2. Virtual Institute Macroecology, Theodor-Lieser-Strasse 4, D–06120 Halle, Germany;
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Author for correspondence:
Ingolf Kühn Tel: +49 345 5585311 Fax: +49 345 5585329 Email: ingolf.kuehn@ufz.de

Summary

  • • The relative frequencies of functional traits of plant species show notable spatial variation, which is often related to environmental factors. Pollination type (insect-, wind- or self-pollination) is a critical trait for plant reproduction and provision of ecosystem services.
  • • Here, we mapped the distribution of pollination types across Germany by combining databases on plant distribution and plant pollination types. Applying a new method, we modelled the composition of pollination types using a set of 12 environmental variables as predictors within a Bayesian framework which allows for the analysis of compositional data in the presence of spatial autocorrelation.
  • • A clear biogeographical pattern in the distribution of pollination types was revealed which was adequately captured by our model. The most striking relationship was a relative increase in insect-pollination and a corresponding decrease of selfing with increasing altitude. Further important factors were wind speed, geology and land use.
  • • We present a powerful tool to analyse the distribution patterns of plant functional types such as pollination types and their relationship with environmental parameters in a spatially explicit framework.

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