Multiscale characteristics of ecosystem service value trade-offs/synergies and their response to landscape pattern evolution in a typical karst basin in southern China

The study of ecosystem service value (ESV) response to landscape pattern evolution has become a research hotspot in the fields of geography and ecology, however, the multi-scale response mechanism of ESV to landscape pattern change in Karst region is still unclear, which to some extent restricts the precise regulation of regional ecosystems and multi-level human-land coupling coordination. This research focuses on the Nanming River Basin (NMRB) in Guizhou Province, a representative karst basin in southern China. Using various methods such as an equivalent factor, an landscape pattern index, and an optimal parameter geo-detector(OPGD), we calculated the ESVs, explored the spatial and temporal evolution of the landscape pattern from 2000 to 2020, and scientifically analyzed the multi-scale response mechanism of the ESVs to the change of the landscape pattern at the sub-watershed scale (27 and 124 sub-watersheds) and at the grid scale (2.4 km × 2.4 km and 1.2 km × 1.2 km grids), respectively. The results revealed that synergies have been the dominant relationship between the ESVs in the NMRB since the beginning of the 21st century. At the 124 sub-basin scale, the landscape shape index (LSI) (21–43%) and coefficient of variation of the shape index (SHAPE_CV) (20–35%) were the main drivers of the geographical differentiation of the trade-offs/synergies among the ESVs, with a few attenuation effect types that weakened the geographic differentiation. However, the two-factor enhancement and nonlinear enhancement were the exception. At the 1.2 km × 1.2 km grid scale, the patch cohesion index (COHESION) (4–49%) and contiguity index (CONTIG_MN) (15–39%) were the main drivers of the spatial divergence of the ESV trade-offs/synergies, and the factor interactions weakened the geographic divergence. At the 2.4 km × 2.4 km grid scale, the COHESION (3%–21%) and LSI (4%–13%) became the primary influences on the spatial divergence, with no independence or attenuation of the type of two-factor interactions. The results are crucial for optimising ecosystem services and formulating appropriate strategies for coordinating ecological-economic development in the karst regions in southern China and around the world.