Exploring the evolution of coupled natural-cultural ecosystem services and their geographically scaled driven modeling in a coastal city of Southeast China.

Rapid urban expansion and economic development challenges to the sustainability of ecosystem services (ESs), a solid understanding of the mechanisms that drive ESs helps policymakers to respond. However, few existing studies on ES-driven mechanisms emphasize the integration of natural and cultural services, with most neglecting spatial non-stationarity at the geographic scale. Here, we improved the ROS model to quantify cultural ecosystem services (CES) and developed a comprehensive ecosystem services index (CESI) by coupling CES with 6 typical natural ESs (carbon storage (CS), water yield (WY), nitrogen export (NE), soil conservation (SC), habitat quality (HQ), food supply (FS)), subsequently, Spearman's correlation and MGWR were employed to reveal the CESI-driven mechanism considering geographic scales. The results showed that: (1) From 2000 to 2020, CS, WY, SC, and HQ exhibited decline, which contrasts with the significant increase in CES. (2) The CESI showed a decreasing trend (3.28-3.70) while the coefficient of variation was increasing over time (0.11-0.15). The overall spatial distribution of CESI shows higher northwest than southeast, with strong spatial autocorrelation. (3) The CESI exhibits synergistic associations with CS, SC, HQ, and CES (0.54-0.83), and forms trade-offs with WY, NE, and FS. (4) Climate, vegetation, landscape, human, and topography have significant effects on CES and CESI with a significantly geographic scale differences, especially areas closer to the sea exhibit heightened sensitivity. Besides, the combined effects of multiple factors are stronger than any individual driver. The results emphasize the necessity of introducing ecological land in coastal cities and establishing natural reserves in high CESI areas to maintain diversity. The study improves the CES assessment methodology and proposes an integrated analytical framework that combines natural and cultural ESs with geographic-scale drivers, providing a new perspective on the analysis of ESs mechanisms.