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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• 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.

Land use and climate change exert pressure on ecosystems and threaten the sustainable supply of ecosystem services (ESS). In Southeast-Asia, the shift from swidden farming to permanent cash crop systems has led to a wide range of impacts on ESS. Our study area, the Nabanhe Reserve in Yunnan province (PR China), saw the loss of extensive forest areas and the expansion of rubber (Hevea brasiliensis Müll. Arg.) plantations. In this study, we model water yield and sediment export for a rubber-dominated watershed under multiple scenarios of land use and climate change in order to assess how both drivers influence the supply of these ESS. For this we use three stakeholder-validated land use scenarios, varying in their degree of rubber expansion and land management rules. As projected climate change varies remarkably between different climate models, we combined the land use scenarios with datasets of temperature and precipitation changes, derived from nine General Circulation Models (GCMs) of the Fifth Assessment Report of the IPCC (Intergovernmental Panel on Climate Change) in order to model water yield and sediment export with InVEST (Integrated Valuation of Ecosystem Services and Trade-offs). Simulation results show that the effect of land use and land management decisions on water yield in Nabanhe Reserve are relatively minor (4% difference in water yield between land use scenarios), when compared to the effects that future climate change will exert on water yield (up to 15% increase or 13% decrease in water yield compared to the baseline climate). Changes in sediment export were more sensitive to land use change (15% increase or 64% decrease) in comparison to the effects of climate change (up to 10% increase). We conclude that in the future, particularly dry years may have a more pronounced effect on the water balance as the higher potential evapotranspiration increases the probability for periods of water scarcity, especially in the dry season. The method we applied can easily be transferred to regions facing comparable land use situations, as InVEST and the IPCC data are freely available.

South American leaf blight (SALB) of Para rubber trees (Hevea brasiliensis Muell. Arg.) is a serious fungal disease that hinders rubber production in the Americas and raises concerns over the future of rubber cultivation in Asia and Africa. The existing evidence of the influence of weather conditions on SALB outbreaks in Brazil has motivated a number of assessment studies seeking to produce risk maps that illustrate this relationship. Subjects with dynamic and cyclical spatiotemporal features need to embody sufficiently fine spatial resolution and temporal granulation for both input data and outputs in order to be able to reveal the desired patterns. Here, we apply emerging hot spot analysis to three decades of gridded daily precipitation and surface relative humidity data to depict their temporal and geographical patterns in relation to the occurrence of weather conditions that may lead to the emergence of SALB. Inferential improvements through improved handling of the uncertainties and fine-scaled temporal breakdown of the analysis have been achieved in this study. We have overlaid maps of the potential distribution of rubber plantations with the resulting dynamic and static maps of the SALB hot spot analysis to highlight regions of distinctly high and low climatic susceptibility for the emergence of SALB. Our findings highlight the extent of low-risk areas that exist within the rubber growing areas outside of the 10° equatorial belt.