摘要：Assessing and predicting the impact of land use/cover changes on ecosystem service supply and demand are crucial to formulating effective sustainable land use policies. In this study, we use the ecosystem service (ES) score matrix, ES supply rate, and ES supply/demand ratio to analyze the supply/demand pattern of ecosystem services based on land use/cover changes in the Beijing-Tianjin-Hebei region from 1990 to 2020. The Conversion of Land Use and Its Effects-Simulation (CLUE-S) model is used to simulate the spatiotemporal patterns of land use change in three scenarios of natural development, ecological priority development, and economic priority development and to predict and simulate the evolution of the ES supply and demand patterns in these different scenarios from 2030 to 2050. It was found that the main land use types are farmland and woodland in the Beijing-Tianjin-Hebei region, accounting for more than 67% from 1990 to 2020, the proportion of farmland decreased from 51.79% to 46.11%, and the proportion of woodland increased from 20.99% to 21.34%; the land use transformation was mainly from farmland to construction land from 1990 to 2020. The supply of ES in the Beijing-Tianjin-Hebei region was at a high level, the supply rate of ES increased from 0.78 to 0.81, the supply/demand ratio of ES decreased from 0.33 to 0.16 from 1990 to 2020, and the supply and demand of ES in the northern and western parts of the Beijing-Tianjin-Hebei region were in surplus. In the natural development scenario, the ES in the Beijing-Tianjin-Hebei region would remain in a high supply state from 2030 to 2050, but the pressure would be greater than before. The deficit, centered on urban construction, would widen, and the ecological situation would deteriorate. In the ecological priority development scenario, the pressure on the ES would be relieved, and the rate of deficit expansion would be reduced. In the economic development priority scenario, the pressure on the ES would increase sharply, and the deficit area would expand rapidly.
