A framework of composite factors for assessing ecosystem service supply drivers: A sustainable socio-ecological perspective

• Established a sustainable SES framework to analyze ESS driving factors comprehensively. • Revealed spatial heterogeneity: various environmental and social factors drive ESS variability. • Enhanced interaction between ecology and socio-economy since 2005, aiding SDGs. • GM-ANN predicts increased future spatial heterogeneity in ESS by 2035. Studying the coupled relationship between social-ecological systems (SES) provides a more comprehensive understanding of the impact of human activity on ecosystems, thereby facilitating the formulation of more rational environmental protection policies. A deeper understanding of this relationship can promote the sustainable utilization and management of the environment. With its abundant natural resources, Ganzhou City represents the most typical ecological location in the southern hilly region of China. In this study, we constructed a sustainable framework for composite factors to analyze their effects on the ecosystem services supply (ESS). This framework emphasizes the positive roles assessment indicators such as water, forests, lakes, grasslands, and governance have on ESS, which are directly linked to the objectives of Sustainable Development Goal (SDG) 15, which include forest conservation, biodiversity maintenance, and water resource management. The results indicate that: (1) From 2005 to 2020, the overall ESS index in the central and western regions of Ganzhou showed a trend of being lower in the north and higher in the south, with areas outside the central and western regions showing a yearly increase. (2) Water, forest, lake, grassland, and governance indicators have a positive impact on the total ESS, while indicators such as mountains, sand, society, and actors have a negative impact. (3) From 2005 to 2020, the coupling coordination relationship in the central-northern and southern regions of Ganzhou gradually strengthened, with most areas shifting from a dysfunctional state to a low coupling state. By 2030, the total ESS index in counties such as Ningdu, Yudu, Huichang, Chongyi, and Xunwu is expected to decline. Some northeastern and southern regions are projected to show an upward trend by 2035. This study will significantly contribute to the realization of SDG 15, as it integrates closely related composite factors into a sustainable SES framework, by further delving into the factors influencing ESS and providing practical guidance for achieving SDGs.