Prof. YUE Tian-Xiang, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, and his colleagues including Ze-Meng Fan, Chuan-Fa Chen, Xiao-Fang Sun and Bai-Lian Li, recently simulated global terrestrial ecosystems under three climate change scenarios by means of a high accuracy and speed method of surface modeling (HASM), as reported in the latest issue of Ecological Modelling 2011 (222).

Since early 1980s, surface modelling of terrestrial ecosystems has received a great interest and achieved various results. Understanding past, present and future of ecosystem distribution depends strongly on accuracy of digital elevation model (DEM) because ecological patterns and terrain are closely related.

HASM is developed to find a solution for error problem and to improve computation speed. A digital elevation model (DEM) is established on spatial resolution of . Regression formulations among temperature, elevation and latitude are simulated in terms of data from 2766 weather observation stations scattered over the world by using the  DEM as auxiliary data. Three climate scenarios of HadCM3 are refined from spatial resolution of to  in terms of the regression formulations. HASM is employed to simulate surfaces of mean annual bio-temperature, mean annual precipitation and potential evapotranspiration ratio during the periods from 1961 to 1990 (T₁), from 2010 to 2039 (T₂), from 2040 to 2069 (T₃), and from 2070 to 2099 (T₄) on spatial resolution of .

Three scenarios of terrestrial ecosystems on global level are finally developed on the basis of the simulated climate surfaces. The scenarios show that all polar/nival, subpolar/alpine and cold ecosystem types would continuously shrink and all tropical types, except tropical rain forest in scenario A1Fi, would expand because of the climate warming. Especially at least 80% of moist tundra and 22% of nival area might disappear in period T₄ comparing with the ones in the period T₁. Tropical thorn woodland might increase by more than 97%. Subpolar/alpine moist tundra would be the most sensitive ecosystem type because its area would have the rapidest decreasing rate and its mean center would shift the longest distance towards west. Subpolar/alpine moist tundra might be able to serve as an indicator of climatic change. In general, climate change would lead to a continuous reduction of ecological diversity.

Howerver, Deserts in Australia and in Chile could not be completely found from the simulated results even in the period from 1960 to 1990. This phenomenon means that HadCM3 climate scenarios in southern hemisphere might have a very serious error problem.