A comprehensive understanding of the complex interactions of ecosystem services and socio-ecological driving factors can help promote the effectiveness of ecological management decisions. Previous studies have mostly focused on the interactions of ecosystem services at a single scale, neglecting the characteristics of trade-offs and synergies at multiple scales. Spatiotemporal and cross-scale analysis helps reveal the spatial differentiation rules of ecosystem services, which is key to enhancing the value of ecological services in large lake basins. Taking the Dongting Lake Basin as an example, this study quantified 5 key ecosystem services from 2000, 2010, and 2020 based on the InVEST model, using a 1 km grid and sub-basin scale to analyze the trade-off relationships and their scale characteristics of ecosystem services. The SOM algorithm was used to extract ecosystem service cluster information, combined with the optimal parameter geographic detector to analyze driving factors. The results show that: 1) there is a significant trade-off relationship between food supply and other ecosystem services at both grid and sub-basin scales. Compared to the grid scale, the trade-off between water retention and food supply at the sub-basin scale weakens, while the trade-off effect between other ecosystem services strengthens. 2) Five ecosystem service clusters were identified at both scales, with the spatial distribution at the sub-basin scale being more uniform and the cluster concentration higher. 3) Terrain and climate are the main influencing factors, and their impact at the sub-basin scale is more significant than at the grid scale. This study explores the spatiotemporal characteristics and driving mechanisms of the interactions of ecosystem services from the perspectives of grid and sub-basin, providing decision-making support for the formulation and adjustment of ecological management strategies in the Dongting Lake Basin.