Spatiotemporal Distribution Characteristics and Their Driving Forces of Ecological Service Value in Transitional Geospace: A Case Study in the Upper Reaches of the Minjiang River, China

Abstract

Ecosystem service value (ESV) is a key indicator for evaluating ecosystem services. Thus, a unique quantitative assessment instrument that comprehensively and objectively evaluates ESV is of great significance for protecting regional ecosystems and achieving sustainable development. Based on data for meteorology, hydrology, soil use, and land use, this paper comprehensively employs the InVEST model, spatial autocorrelation, and geographic detectors to study the spatiotemporal characteristics and driving forces of spatial variations in ESV in the upper reaches of the Minjiang River. The results indicate the following: (1) The ecosystem service capacity of the study area has continuously improved, with the ecosystem service value (ESV) increasing by USD 4.078 billion over 20 years. Soil conservation has made the most significant contribution to the growth of ESV, accounting for over 85%. (2) The distribution of ESV exhibits a “lower in the northwest, higher in the southeast” trend. The Moran’s I value for each year exceeds 0.7, indicating characteristics of High–High and Low–Low aggregation. (3) Slope plays a dominant role in causing the spatial differentiation of ESV, contributing 30.9%. Slope is followed by HAI at 19.7% and the urbanization rate at 16.8%. Rainfall has the least impact at 4%. (4) The results from the multi-factorial interactions reveal that all factors experience synergistic enhancement effects when interacting. The spatiotemporal differentiation of ESV is the result of multiple factors acting in conjunction, underscoring the importance of coordinated efforts in ecological restoration and comprehensive environmental management in the upper reaches of the Minjiang River. The methodology of this research could be applied to assess the impact of natural changes and human activities on ESV. The findings offer theoretical support for regional resource and environmental management, as well as ecological compensation decision making.