Assessing alpine plant vulnerability to climate change: a modeling perspective |
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Authors: | Antoine Guisan Jean-Paul Theurillat |
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Institution: | (1) Swiss Center for Faunal Cartography (CSCF), Terreaux 14, CH-2000 Neuchatel, Switzerland;(2) Fondation J.-M. Aubert, Centre Alpien de Phytogéographie (CAP), CH-1938 Champex, Switzerland;(3) Botanical Center, University of Geneva, CJB, CP60, CH-1292 Chambésy, Switzerland |
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Abstract: | The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified
early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed
in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface
area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g.,
slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating
upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their
habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution
modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence
of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology,
rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution
maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These
scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest
risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models
and scenarios are further discussed.
This revised version was published online in July 2006 with corrections to the Cover Date. |
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Keywords: | climate change ecological impact assessment alpine and subalpine belts plant distribution statistical modeling local scale GIS GLM Swiss Alps |
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