Layering for governance: Ecosystem service supply–demand trade-offs and social-ecological system network topologies from a cluster perspective

A key challenge in ensuring the coordinated development of ecological conservation and economic growth is to gain a solid understanding of the interactions between supply–demand of ecosystem services (ES). However, empirical research on spatial imbalance among ESs and its interrelationships remain scarce, especially regarding its bidirectional network topology with ecological-social elements. Here, ecosystem service supply–demand rate (ES-SDR) was assessed in the Mulan River basin, one of the birthplaces of China’s modern ecological civilization ideology, and four bundles of supply–demand rate for ecosystem services (BSDRES) were constructed. The study hierarchically identified global and local ES-SDR trade-offs/synergies and identified core of ES-SDR connections by constructing the Hub-ES index. Finally, established a comprehensive ecological-social coupling network and hierarchically identified the dominant factors of ES-SDR trade-offs/synergies using redundancy analysis. Results reveal that nearly all ES-SDRs exhibit a gradient transition from surplus (northwest) to deficit (southeast), forming four BSDRES Ⅰ–Ⅳ, highlighting diverse imbalances. From global and local perspectives in different bundles, the spatial heterogeneity of trade-off/synergy relationships was identified, with carbon supply–demand relationships losing central role, while water supply–demand relationships becoming hub. Additionally, the network established between these relationships and ecological-social factors reveals that land use/cover change (LUCC) plays a critical hub function in coupled system, dominating multi-factor interaction and transmission. Trade-off/synergy of ES-SDR are mostly distributed around LUCC and become key transmission medium. Across different bundles, population density has the highest explanatory power for ES-SDR trade-off/synergy. Overall, our research provides novel insights into the emerging attributes and complexity of these supply–demand relationships.