Land Use Zoning Management to Coordinate the Supply–Demand Imbalance of Ecosystem Services: A Case Study in the City Belt Along the Yellow River in Ningxia, China

The imbalance between the supply and demand of ecosystem services (ESs) is one of the main reasons for ecological degradation, which significantly impacts human well-being and ecological safety. Spatial heterogeneity of ES supply–demand, ES tradeoffs, and the socioecological environment calls for zoning management, while few studies have combined the above three aspects in dividing management zones and proposed strategies. Using the City Belt along the Yellow River in Ningxia in northwestern China as a case study, this study quantified the supply and demand for five key ESs (crop production, carbon sequestration, nutrient retention, sand fixation, and recreational opportunity), analyzed ES tradeoffs/synergies and bundles through correlation analysis and the self-organizing map (SOM) method, and investigated their socioecological driving mechanisms through a random forest model and the SOM method. Management zones were proposed and differentiated suggestions were provided through overlaying ES bundles and driver clusters. The results suggested that crop production, carbon sequestration, and nutrient retention mostly correlated to the same intrinsic ecological process, resulting in consistent synergies among these three ESs at both supply and demand sides. On the contrary, the variance in interactions between the two ESs of sand fixation and recreational opportunity and the other three ESs is due to the low similarity of their intrinsic ecological processes and external driving mechanisms. Fourteen socioecological factors could effectively explain the spatial heterogeneity of ES supply, demand, and match degree. Fourteen management zones with similar ecological problems and socioecological environments were delineated, and differentiated suggestions were provided for each zone. Adopting both ES characteristics and the socioecological environment into zoning management could effectively detect ecological problems and help to promote management suggestions in different socioecological contexts. This framework could offer new insights for integrating ESs into actual decision-making and ecosystem management.