4.7 Article

Estimation of the extinction risk for high-montane species as a consequence of global warming and assessment of their suitability as cross-taxon indicators

Journal

ECOLOGICAL INDICATORS
Volume 10, Issue 2, Pages 341-352

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2009.06.014

Keywords

Climate change; Species distribution modeling; Generalized linear models; Species monitoring; Cross-taxon indicators; High-montane species

Funding

  1. Bayerisches Staatsministerium fur Umwelt, Gesundheit und Verbraucherschutz

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The evidence for climate change is increasing, and global warming could lead to the extinction of some species. Here we estimated the extinction risk of six high-montane species of different taxonomic groups (fern, vascular plant, wood-inhabiting fungus, mollusk, saproxylic beetle, and bird) by modeling their occurrence under two global warming scenarios. We also assessed the cross-taxon indicator suitability of the selected species for monitoring climate change in low-mountain-range forests in southeastern Germany (Bavarian Forest National Park). We tested the influence of temperature and other habitat variables by applying semi-parametric spatial generalized linear models with binomial error. The probability of occurrence for each species under the present conditions and under two conditions of global warming was calculated. To assess the cross-taxon suitability, we tested the predictability of the final generalized linear models for each species using the measured occurrence of the other selected species and a discrimination technique. We identified temperature as the main driver for all selected high-montane species. Our statistical models predict a considerable risk of extinction of these species within the Bavarian Forest National Park as a result of global warming. Our discrimination model indicates that these species have essentially similar relationships with the environment and that five of the six species are suitable as indicators of early signs of global warming. The choice of which indicators to use should involve a consideration of the type of monitoring systems already in place. (C) 2009 Elsevier Ltd. All rights reserved.

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