Understanding the key factors and future trends of ecosystem service value to support the decision management in the cluster cities around the Yellow River floodplain area

Abstract

The ecosystem services value (ESV) is an important basis for measuring ecological environment quality and efficient management of ecosystems. Although there have been many studies devoted to the measurement of ESV, the research on the key influencing factors of ESV and the prediction of future development scenarios is still limited. This study coupled the Deep Forest model and Patch-generating Land Use Simulation (PLUS) model to identify the key factors of ESV, and simulated the change trend of ESV under the Shared Socioeconomic Pathways (SSPs). Taking the cluster cities around the Yellow River floodplain area as the research object, this study quantitatively analyzed the spatiotemporal evolution characteristics of its ESV from 2000 to 2020, and identified the key factors affecting ESV using the Deep Forest model. The results showed that: (1) The ESV showed an overall upward trend from 2000 to 2020, with strong spatial heterogeneity; (2) The key factors affecting ESV were construction land ratio, distance to railway, SHDI, etc.; (3) The best development pathway of ESV in 2025, 2030 and 2035 would be SSPs5, SSPs2 and SSPs4 respectively. This study can provide theoretical support for the management of maximizing the overall benefits of ecosystem services in the study area.

Keywords

• Ecosystem service value
• Deep Forest model
• PLUS model
• Scenario Simulation
• Shared Socioeconomic Pathways