Ecosystem services (ES), defined as benefits provided by the ecosystem to society, are essential to human well-being. However, it remains unclear how they will be affected by land-use changes due to lack of knowledge and data gaps. Therefore, understanding the response mechanism of ecosystem services to land-use change is critical for developing systematic and sound land planning. In this study, we aimed to explore the impacts of land-use change on the three ecosystem services, carbon storage (CS), flood regulation (FR), and soil conservation (SC), in the ecological conservation area of Beijing, China. We first projected land-use changes from 2015 to 2030, under three scenarios, i.e., Business as Usual (BAU), Ecological Land Protection (ELP), and Rapid Economic Development (RED), by interactively integrating the Markov model (Quantitative simulation) with the GeoSOS-FLUS model (Spatial arrangement), and then quantified the three ecosystem services by using a spatially explicit InVEST model. The results showed that built-up land would have the most remarkable growth during 2015–2030 under the RED scenario (2.52% increase) at the expense of cultivated and water body, while forest land is predicted to increase by 152.38 km2 (1.36% increase) under the ELP scenario. The ELP scenario would have the highest amount of carbon storage, flood regulation, and soil conservation, due to the strict protection policy on ecological land. The RED scenario, in which a certain amount of cultivated land, water body, and forest land is converted to built-up land, promotes soil conservation but triggers greater loss of carbon storage and flood regulation capacity. The conversion between land-use types will affect trade-offs and synergies among ecosystem services, in which carbon storage would show significant positive correlation with soil conservation through the period of 2015 to 2030, under all scenarios. Together, our results provide a quantitative scientific report that policymakers and land managers can use to identify and prioritize the best practices to sustain ecosystem services, by balancing the trade-offs among services.
PREDICTION OF POLLUTANT RUNOFF LOAD FROM BASINS OF ISAHAYA FLOOD REGULATION POND UNDER THE RAIN CONDITION
