[Spatial and Temporal Evolution of Ecosystem Service Supply and Demand and Analysis of Driving Factors in Chongqing...

Exploring the spatial and temporal differentiation patterns and driving factors of ecosystem service supply and demand in complex mountainous and hilly subsoil is of great significance for optimizing the regional ecological security pattern and sustainable development. Taking Chongqing as the research object, the spatial and temporal evolution characteristics of ecosystem service supply and demand in Chongqing from 2000 to 2020 and their driving factors were systematically revealed by using the InVEST model, the spatial autocorrelation analysis method, and the XGBoost-SHAP model. The results show that: ① The urban clusters of the Three Gorges Reservoir area in northeast Chongqing and the Wuling Mountain Area in southeast Chongqing exhibited a "high supply-low demand" pattern, while the main city metropolitan area exhibited a "low supply-high demand" pattern. From 2000 to 2020, carbon sequestration, habitat quality, and recreational supply declined, while water production and soil conservation supply first declined and then increased. Demand for carbon sequestration, water production, habitat quality, and recreation increased, while demand for soil conservation first declined and then increased. ② The supply and demand of ecosystem services in Chongqing maintained a dynamic balance in general, but the supply and demand deficits continued to expand in the main city metropolitan area, while the surpluses in the southeast and northeast areas of Chongqing remained stable. ③ The I of the ratio of ecosystem services supply to demand in 2000, 2010, and 2020 were 0.674, 0.666, and 0.679, respectively, with significant positive correlation in the space. The distribution characteristics were dominated by high-high aggregation and low-low aggregation, with high-high aggregation concentrated in the ecological barrier areas such as Chengkou County and Nanchuan District and low-low aggregation concentrated in the urbanization core areas such as Yuzhong District and Shapingba District. ④The XGBoost-SHAP model indicated that precipitation, urbanization rate, industrial output value, and the proportion of agricultural output value were the key driving factors influencing the relationship between supply and demand. The results can provide scientific references for regional ecological protection, ecological zoning control, and sustainable development.