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Climate change and plant distribution: local models predict high‐elevation persistence
Author(s) -
RANDIN CHRISTOPHE F.,
ENGLER ROBIN,
NORMAND SIGNE,
ZAPPA MASSIMILIANO,
ZIMMERMANN NIKLAUS E.,
PEARMAN PETER B.,
VITTOZ PASCAL,
THUILLER WILFRIED,
GUISAN ANTOINE
Publication year - 2009
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2008.01766.x
Subject(s) - climate change , habitat , range (aeronautics) , elevation (ballistics) , environmental science , species distribution , extinction (optical mineralogy) , biodiversity , physical geography , ecology , spatial ecology , occupancy , ecosystem , scale (ratio) , geography , geology , biology , cartography , paleontology , materials science , geometry , mathematics , composite material
Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across‐scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change‐induced habitat losses predicted at the European scale (10 × 10′ grid cells) are also predicted from local‐scale data and modeling (25 m × 25 m grid cells) in two regions of the Swiss Alps. We show that local‐scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European‐scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine‐grain elevation range within 10 × 10′ cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local‐scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.