The rapid process of urbanization, accompanied by the sharp increase of urban population and expansion of artificial surface, has resulted in the loss of natural ecosystems and the degradation of ecosystem services. Identifying and protecting key places that have high importance for ecological sustainability are great challenges. Ecological security patterns are such an integrated approach to protecting regional ecological sustainability. In this study, taking Yunnan Province, China as a case study area, ecological sources were identified through ecosystem services, and circuit theory was used to model ecosystem processes in heterogeneous landscapes via calculating the 'resistance' or 'current', and thus to identify ecological corridors and key ecological nodes. The results showed that, ecological security patterns included 66 ecological sources, 186 ecological corridors, 24 pinch-points and 10 barriers. In details, the ecological sources were mainly distributed in the southwest and northwest of Yunnan Province, with the ecological corridors locating along the high mountains, and both ecological sources and corridors were mostly covered with forest land. Pinch-points covered by forest land and cultivated land, were distributed in the middle of Yunnan Province along the rivers. Approximately 75.9% nature reserves were located in the identified ecological sources, and the remainings were mainly distributed in eastern Yunnan Province with small area, showing the effectiveness in identifying ecological security patterns. Among 81 projects of low-slope hill development carried out in Yunnan Province, 46.9% showed potential human stress on regional ecological security. Based on ecosystem services and circuit theory, this study provides a new approach to identifying the spatial range of ecological corridors and the specific location of key nodes for effective ecological conservation and restoration.

Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Changes in soil organic carbon (SOC) stocks are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOC stocks is a priority. The French soil monitoring network has been established on a 16 km × 16 km grid and the first sampling campaign has recently been completed, providing around 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory. We calibrated a boosted regression tree model on the observed stocks, modelling SOC stocks as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOC stocks for mainland France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on SOC for such soils. The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOC stocks and pedo-climatic variables (plus their interactions) over the French territory. These relationships strongly depended on the land use, and more specifically, differed between forest soils and cultivated soil. The total estimate of SOC stocks in France was 3.260 ± 0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOC stock distributions of France, and consequently that the previously published approach at the European level greatly overestimates SOC stocks.