A fine-scaled predictive model for changes in species distribution patterns of high mountain plants induced by climate warming

Authors

  • Michael Gottfried,

    1. Department of Vegetation Ecology and Conservation Biology, Institute of Plant Physiology, University of Vienna, Althanstr. 14, PO Box 285, A–1091 Wien, Austria.
    2. E-mail: gottf@pflaphy.pph.univie.ac.at
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  • Harald Pauli,

    1. Department of Vegetation Ecology and Conservation Biology, Institute of Plant Physiology, University of Vienna, Althanstr. 14, PO Box 285, A–1091 Wien, Austria.
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  • Karl Reiter,

    1. Department of Vegetation Ecology and Conservation Biology, Institute of Plant Physiology, University of Vienna, Althanstr. 14, PO Box 285, A–1091 Wien, Austria.
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  • Georg Grabherr

    1. Department of Vegetation Ecology and Conservation Biology, Institute of Plant Physiology, University of Vienna, Althanstr. 14, PO Box 285, A–1091 Wien, Austria.
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Summary

Induced by global warming, mountain plant species are migrating upwards. Species inhabiting the nival zone of today are threatened by competitors which move from the alpine zone towards the summits. The manner in which species move depends on their abilities to cope with microtopographical situations. We present a spatially explicit predictive model which draws scenarios of future species distribution patterns at a typical high mountain of the European Alps. The altitudinal temperature gradient is examined. Based on the lapse rate and on definitions of topographical niches of species, a +1 °C- and a +2 °C-warming scenario are modelled using a fine-scaled digital elevation model. Nival species will lose area and become restricted to specific topographical situations. Alpine and subnival grassland species are predicted to expand their area, mainly along stable surface situations. Whether the migration will take place as a filling or a moving process is specific to the particular species. Overall, biodiversity is apparently not threatened on the decadal scale. In special cases, however, genetic losses are likely both on a local and on a regional scale.

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