Assessing the Scale Effects of Dynamics and Socio-Ecological Drivers of Ecosystem Service Interactions in the Lishui River Basin, China

Grasping how scale influences the interactions among ecosystem services (ESs) is vital for the sustainable management of multiple ESs at the regional level. However, it is currently unclear whether the actual ES interactions and their driving mechanisms are consistent across different spatial and temporal scales. Therefore, using the Lishui River Basin of China as a case study, we analyzed the spatial and temporal distribution of five key ESs across three scales (grid, sub-watershed, and county) from 2010 to 2020. We also innovatively used Pearson correlation analysis, Self-organizing Mapping (SOM), and random forest analysis to assess the dynamic trends of trade-offs/synergies among ESs, ecosystem service bundles (ESBs), and their main socio-ecological drivers across different spatiotemporal scales. The findings showed that (1) the spatial distribution of ESs varied with land use types, with high-value areas mainly in the western and northern mountainous regions and lower values in the eastern part. Temporally, significant improvements were observed in soil conservation (SC, 3028.23–5023.75 t/hm2) and water yield (WY, 558.79–969.56 mm), while carbon sequestration (CS) and habitat quality (HQ) declined from 2010 to 2020. (2) The trade-offs and synergies among ESs exhibited enhanced at larger scales, with synergies being the predominant relationship. These relationships remained relatively stable over time, with trade-offs mainly observed in ES pairs related to nitrogen export (NE). (3) ESBs and their socio-ecological drivers varied with scales. At the grid scale, frequent ESB flows and transformations were observed, with land use/land cover (LULC) being the main drivers. At other scales, climate (especially temperature) and topography were dominant. Ecosystem management focused on city bundles or downstream city bundles in the east of the basin, aligning with urban expansion trends. These insights will offer valuable guidance for decision-making regarding hierarchical management strategies and resource allocation for regional ESs.