资源环境科技发展态势分析平台

In order to map potential shifts of rubber (Hevea brasiliensis) cultivation as a consequence of the ongoing climate change in the Greater Mekong Subregion (GMS), we applied rule-based classifications to a selection of nine gridded climatic data projections (precipitation and temperature, and global circulation models (GCMs)). These projections were used to form an ensemble model set covering the representative concentration pathways (RCPs) 4.5 and 8.5 of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change at three future time sections: 2030, 2050 and 2070. We used a post classification ensemble formation technique based on a majority outcome of the classification to not only provide an ensemble projection but also to spatially track and weight the disagreements between the classified GCMs. A similar approach was used to form an ensemble model aggregating the involved climatic factors. The level of agreement between the ensemble projections and GCM products was assessed for each climatic factor separately, and also at the aggregate level. Shifting zones with high confidence were clustered based on their land use composition, physiographic attributes and proximity. Following the same ensemble formation technique and by setting a 28 degrees C threshold for annual mean temperature, we mapped areas prone to exposure to potentially excessive heat levels. Almost the entire shift projected with high certainty was in the form of expansion, associated with temperature components of climate and temporally limited to the 2030 time window where the total area conducive to rubber cultivation in the GMS is projected to exceed 50% by 2030 (from 44.3% at the turn of the century). The largest detected cluster (41% of the total shifting area), which also is the most ecologically degraded, corresponds to Northern Vietnam and Guangxi Autonomous Region of China. The area exposed to potentially excessive heat is projected to undergo a 25-fold increase under RCP4.5 by 2030 from 14568 km(2) at the baseline.