Understanding scale effects and differentiation mechanisms of ecosystem services tradeoffs and synergies relationship: A case study of the Lishui River Basin, China

•Three pairs of ESs showed significant spatial heterogeneity.•Characteristics and relationships of multi-ES were analyzed from multi-scales.•Interactions of ESs gradually intensifying as the scale increased.•Precipitation was the most important driver of the interrelations between ESs. Understanding the scale effect of relationships among ecosystem services (ESs) and the factors influencing these relationships, is vital for sustainable management of ESs. Previous research has focused less on multiple scale units, and the driving mechanisms behind ESs interactions remain unclear. Therefore, in this study, we assessed the spatial distribution of water yield (WY), water purification (WP), and soil conservation (SC) across four spatial scales (3 km × 3 km grid, 5 km × 5 km grid, sub-watershed, and county scales) in the Lishui River Basin of China during 2020. Using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, geographical weighted regression, and Pearson correlation analysis, we examined tradeoffs and synergies among these ESs at various scales. Additionally, we employed a geographic detector to analyze the reactions and scale effects among these tradeoffs/synergies and social-ecological factors. Our findings revealed the following: (1) Significant spatial heterogeneity in ESs was observed in the basin. The WY decreased from west (2511.65 mm) to east (890.06 mm), with high WP values concentrated in the eastern part, and high SC values (8.30 × 105 t/hm2) found in densely forested and grassland areas surrounding water bodies. Forested and cultivated lands were key contributors to ESs in the basin. (2) Across the four investigated scales, tradeoffs or synergies between the same ESs becoming more pronounced as the scale increased. Notably, most ES relationships displayed their strongest synergies at the county scale, with certain spatial areas demonstrating change in interaction directions. (3) The explanatory power of single- or double-factor interactions increased with scale. ESs interactions were found to be closely linked to climatic factors, as well as topographic features (including slope gradient and elevation), with precipitation exhibiting relatively high explanatory power. The interaction of natural and social factors significantly outweighed the combined interaction of dual social factors. This indicated that socio-ecological factors, especially climate and topography, jointly influenced the intensity and direction of ES