Study on Priority Conservation Areas in the Yangtze River Delta Based on Multi-Scenario Trade-offs of Ecosystem Services

Objective The study on the spatiotemporal evolution characteristics of ecosystem services and priority conservation areas in the Yangtze River Delta region is of great significance for mitigating conflicts between regional economic development and ecological protection and achieving sustainable development. Methods Six key ecosystem services—food supply (FP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), and landscape aesthetics (LA)—were measured using the NDVI matching method, InVEST model, and landscape indicators. The trade-off/synergy relationships among these services were assessed using Spearman correlation analysis, and an ecosystem service synergistic benefit index (ESSB) was introduced to reveal their spatial heterogeneity. Seven scenarios were established based on the ordered weighted average method (OWA), and the optimal scenario was determined by comparing conservation efficiencies and trade-off values across different scenarios. The optimal parameter geodetector model was employed to analyze the main influencing factors affecting the distribution of priority protected areas. Results (1) The spatial distribution of ecosystem services in the YRD region is uneven, with FP values highest in the northern plains and the remaining five services peaking in the southwestern mountainous hills. From 2000 to 2020, FP and WY showed continuous growth, while SC and LA experienced a decline followed by recovery, and CS and HQ exhibited a continuous downward trend. (2) FP exhibits a trade-off relationship with other ecosystem services, whereas WY, CS, SC, HQ, and LA display synergistic relationships among themselves. (3) Scenario 4 presents the highest combined conservation efficiency, with respective efficiencies of 0.32 (FP), 1.37 (WY), 1.87 (CS), 1.84 (SC), 1.84 (HQ), and 1.37 (LA). (4) The primary factors influencing the distribution of priority conservation areas are natural endowment factors, including slope, mean annual temperature, mean annual precipitation, and DEM, which show significantly higher explanatory power than socioeconomic factors. Conclusion The findings of this study can provide decision-making support for the optimal regulation of ecosystem services and the scientific delineation of priority conservation areas in the YRD region.