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Proc Natl Acad Sci U S A.
2006 Aug 29;103(35):13116-20. Epub 2006 Aug 21.
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A climate-change risk analysis for world ecosystems.
Scholze M
,
Knorr W
,
Arnell NW
,
Prentice IC
.
Quantifying and Understanding the Earth System, Department of Earth Sciences, University of Bristol, Wills Memorial Building, Queen's Road, Bristol BS8 1RJ, United Kingdom. marko.scholze@bristol.ac.uk
We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenarios or weights to models. Instead, we consider distribution of outcomes within three sets of model runs grouped by the amount of global warming they simulate: <2 degrees C (including simulations in which atmospheric composition is held constant, i.e., in which the only climate change is due to greenhouse gases already emitted), 2-3 degrees C, and >3 degrees C. High risk of forest loss is shown for Eurasia, eastern China, Canada, Central America, and Amazonia, with forest extensions into the Arctic and semiarid savannas; more frequent wildfire in Amazonia, the far north, and many semiarid regions; more runoff north of 50 degrees N and in tropical Africa and northwestern South America; and less runoff in West Africa, Central America, southern Europe, and the eastern U.S. Substantially larger areas are affected for global warming >3 degrees C than for <2 degrees C; some features appear only at higher warming levels. A land carbon sink of approximately 1 Pg of C per yr is simulated for the late 20th century, but for >3 degrees C this sink converts to a carbon source during the 21st century (implying a positive climate feedback) in 44% of cases. The risks continue increasing over the following 200 years, even with atmospheric composition held constant.
Publication Types:
Research Support, U.S. Gov't, Non-P.H.S.
PMID: 16924112 [PubMed - indexed for MEDLINE]
PMCID: PMC1559762
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