Analysis of Factors Influencing the Ecosystem Service Value in Yuzhong County and Multi-Scenario Predictions

Jixuan Yan (), Gengxin Zhang, Wenning Wang, Zichen Guo, Jie Li, Xiangdong Yao, Pengcheng Gao, Qiang Li, Meihua Zhang and Miao Song
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Jixuan Yan: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Gengxin Zhang: Yaojie Coal Power Group Tianzhu Coal Industry Company, Wuwei 733211, China
Wenning Wang: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Zichen Guo: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Jie Li: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Xiangdong Yao: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Pengcheng Gao: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Qiang Li: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Meihua Zhang: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
Miao Song: College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China

Land, 2025, vol. 14, issue 4, 1-17

Abstract: The value of ecosystem services (ESV) serves as a crucial metric for assessing the cost-effectiveness of ecosystems and evaluating their economic worth. Predicting the evolution of ESV across various land uses under different scenarios is essential for maintaining ecological stability and fostering sustainable developm0ent. Utilizing land use change data combined with the PLUS predictive model and ecosystem service value equivalence techniques, this study analyzes the spatiotemporal patterns and underlying drivers of ESV in Yuzhong County, China. The results indicate that the overall ESV distribution exhibits a “fragmented northeast, clustered southwest” pattern, dominated by high-high and low-low clustering. Among the driving factors, elevation exerts the greatest influence on ESV, followed by precipitation and population density, while slope contributes least. Under natural development scenarios, the ESV remains relatively stable compared to the base year of 2020. In contrast, the farmland protection scenario effectively preserves the ESV associated with cultivated land. However, the economic development scenario leads to a significant decline in the overall ESV, with a retraction of high-value areas and an expansion of low-value regions. These insights provide a fresh perspective for analyzing the factors influencing ESV and for conducting multi-scenario predictions, thereby aiding in the development of ecological resource conservation and landscape ecological risk prevention strategies in the study region.

Keywords: ecological service value; influencing factors; multi-scenario prediction; Yuzhong County; spatiotemporal evolution (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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