Dynamic Spatio-Temporal Simulation of Land Use and Ecosystem Service Value Assessment in Agro-Pastoral Ecotone, China

In the past, during development processes, major ecological and environmental problems have occurred in the agro-pastoral ecotone of China, which have had a strong impact on regional sustainable development. As such, analyzing the evolution of the regional ecosystem service value (ESV) and predicting the futural spatio-temporal evolution under different development scenarios will provide a scientific basis for further sustainable development. This research analyzed the regional land use and land cover change (LUCC) from 2000 to 2020, adopted the Mark-PLUS model to construct different scenarios (prioritizing grassland development, PDG; prioritizing cropland development, PCD; business as usual, BAU), and simulated the future LUCC. The driving factors influencing each land use type were revealed using the PLUS model. Based on the LUCC data, the spatio-temporal distribution of the regional ESV was calculated via the ESV equivalent factor method, including four primary services (supply service, adjustment service, support service, and cultural service) and eleven secondary services (water resource supply, maintaining nutrient circulation, raw material production, aesthetic landscape, food production, environmental purification, soil conservation, maintaining biodiversity, gas regulation, climate regulation, and hydrologic regulation). The results showed that the total ESV increased first and then declined from 2000 to 2020, reaching the highest value of CNY 8207.99 million in 2005. In the different future scenarios, the ESV shows a trend of PGD (CNY 8338.79 million) > BAU (CNY 8194.82 million) > PCD (CNY 8131.10 million). The global Moran index also follows this distribution. Additionally, precipitation (18%), NDVI (16%), and DEM (16%) are the most important factors in the regional LUCC. The spatial agglomeration characteristics of ESV were revealed using the global Moran’s index and local indicators of spatial auto-correlation, which show a high coordination degree between the high–high cluster areas and water areas. These results point out the key points in the next step of ecological restoration projects and help with achieving the sustainable development goals more effectively.