Multi-scale trade-off and synergy relationship and influencing factors of ecosystem services in the Yangtze River Basin.

内容摘要

The rapid urbanization has posed a serious threat to the ecological security of river basins. Exploring the trade-offs, synergies, driving factors, and ecological management zoning of regional ecosystem services is of great significance for achieving the sustainable utilization of ecosystems in the Yangtze River Basin. We employed the InVEST model to quantitatively assess the spatial patterns of five major ecosystem services (soil conservation, water yield, habitat quality, and carbon sequestration and food supply) from 2000 to 2023, and used the Spearman correlation coefficient to examine the trade-off and synergy relationships among different ecosystem services and their scale effects. We then applied the Geodetector model and random forest method to identify the dominant driving factors, interactive effects and nonlinear response characteristics, while used the K-means clustering method to identify ecosystem service bundles. Based on these analyses, we proposed ecological management zones and their optimization pathways for the Yangtze River Basin. The results showed that carbon sequestration, habitat quality, and soil conservation exhibited a slight declining trend from 2000 to 2023 by 0.5%, 2.0%, and 10.2%, respectively, whereas water yield and food supply increased by 1.0% and 14.6%. The trade-offs and synergies among ecosystem services displayed significant scale effects. As the spatial scale expanded from grid to county and city levels, the weak synergistic relationships gradually strengthened and became dominant, while the trade-off intensity weakened and the spatial distribution became more clustered. The key driving factors of the five ecosystem services varied significantly. There was also a distinct nonlinear response and a threshold effect: vegetation coverage (explanatory power q=0.45) dominated carbon sequestration, population density (q=0.71) mainly affected habitat quality, precipitation determined (q=0.93) water yield, and slope (q=0.60) affected soil conservation, population density (q=0.56) affected food supply. Based on the clustering of ecosystem services, we classified the study area into three ecological management zones, namely ecological protection zones, ecological conservation zones, and provisioning service zones. We proposed differentiated optimization strategies for each zone. 快速的城镇化进程对流域的生态安全造成威胁,探索区域生态系统服务的权衡协同关系、驱动因素及生态管理分区,对实现长江流域生态系统的可持续利用具有重要意义。本研究通过InVEST模型对2000—2023年间长江流域的土壤保持、产水量、生境质量、固碳量和粮食供给这5种主要生态系统服务进行空间定量化测算,运用Spearman相关系数探究不同生态系统服务之间的权衡协同关系及其尺度效应,并采用地理探测器和随机森林方法探究其主要影响因素、交互作用与非线性响应特征,进而结合K-Means聚类分析法识别生态系统服务簇,探索长江流域的生态管理分区及其优化路径。结果表明:2000—2023年间,长江流域的固碳量、生境质量、土壤保持均小幅下降,分别下降了0.5%、2.0%、10.2%,产水量和粮食供给分别上升了1.0%和14.6%。长江流域生态系统服务的权衡协同关系具有显著的尺度效应,并随着空间尺度从栅格扩大到县域和市域,其弱协同关系逐渐加强成为主导,而权衡强度减弱且空间分布更加集中。长江流域各生态系统服务的关键驱动因子存在显著差异,且存在明显的非线性响应和阈值效应。其中,植被覆盖率(解释力q=0.45)主导固碳量,人口密度(q=0.71)主要影响生境质量,降水(q=0.93)决定产水量,坡度(q=0.6)决定土壤保持,人口密度(q=0.56)决定粮食供给。基于生态系统服务簇,将研究区划分为3个生态管理分区,分别为生态防护区、生态保育区及供给服务区,并提出了差异化的分区优化路径。.