Based on the InVEST and RUSLE models, and using 5 km × 5 km and 10 km × 10 km grid cells as well as counties as analysis units, this study assessed grain production, water yield, soil conservation, and carbon sequestration services in the middle reaches of the Yellow River (MRYR) in 2000, 2010, and 2020, and analyzed their spatiotemporal changes and trade-off/synergy relationships from both static and dynamic perspectives. From 2000 to 2020, grain production, water yield and soil conservation in the MRYR increased overall with distinct spatial differentiation, while carbon storage remained basically stable with a slight decline. Significant static trade-offs/synergies existed among ecosystem service (ES) bundles with temporal evolution characteristics, and their interaction intensity presented clear scale dependence with typical threshold effects. Dynamically, positive synergies dominated all ES pairs during 2000–2010, whereas trade-offs/negative synergies expanded significantly during 2010–2020, especially at the county scale. This study further reveals the hierarchical driving mechanism of ES trade-off/synergy spatial pattern: fine-scale fragmentation is driven by micro-topographic and local management factors, meso-scale integration by regional ecological and agricultural configuration, and county-level differentiation by macro-policy and socio-economic drivers. Beyond the traditional correlation-based analysis framework, we propose a multi-scale coupling analysis framework of ES trade-off/synergy that integrates static correlation, dynamic difference and hierarchical driving mechanism, and clarify the emergent system behavior of ES interactions (non-linear change of interaction intensity with scale expansion). This framework breaks the single-scale and pure statistical analysis paradigm of existing studies, enriches the scale effect theory of ES, and provides a new theoretical perspective and methodological reference for the coordinated regulation of ES in ecologically fragile areas with intense human-environment conflicts worldwide.
Zhang et al. (2026) studied this question.