Exploring the impact of socio-ecological drivers on ecosystem services (ESs) is critical to ES conservation and restoration. Although a considerable amount of the literature has focused on this topic, few studies have investigated the non-linear impact thresholds of socio-ecological drivers on ESs from a global perspective. In this study, multisource geospatial data was integrated with ecological modeling to quantify six typical ESs in Wuhan, China. Dominant drivers were identified through random forests, and non-linear relationships and thresholds were analyzed by partial dependence analysis. The results revealed that elevator, distance from rivers, soil organic carbon content, aggregation index, and Shannon diversity index were the dominant drivers of most ESs. Moreover, three types of non-linear impact thresholds exist in the relationship between ESs and their socio-ecological drivers: “single threshold” effects; “monotonic impact” effects; and “complex curve” effects, including “S-shape”, “inverted U-shape” and “inverted S-shape” effects. Based on these findings, we proposed policy guidance to inform ecological protection and restoration aimed at enhancing ES provision and promoting sustainable development.

Understanding the mechanisms that drive ecosystem services (ESs) is critical to reversing the trend of ESs deterioration and allocating targeted restoration measures. However, previous studies have not utilized machine learning methods to explore the impacts and thresholds of social-ecological drivers on ESs from a global perspective. Therefore, in this study, we employed a random forest model to identify the dominant drivers of ESs. We then utilized partial dependence analysis to investigate the non-linear impacts and thresholds of these dominant drivers on ESs. The results revealed that elevator, distance from rivers, soil organic carbon content, aggregation index, and Shannon diversity index were the dominant drivers of most ESs. Moreover, three types of non-linear impacts existed in the relationship between ESs and their social and ecological drivers: the majority of drivers exhibited “single threshold” effects on ESs, the minority showed “monotonic change” effects, and the rest had “complex curve” effects in the forms of “S-shape”, “inverted U-shape” and “inverted S-shape” effects, etc. Based on these findings, we proposed policy guidance to inform ecological protection and restoration aimed at enhancing ESs provision and promoting sustainable development.

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is fundamental in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a “two-step refinement zoning method” to address this gap, first using a self-organizing feature mapping method to delineate EFZs at a township scale, and then applying a hotspot overlay analysis to refine the resulting EFZs by designating them with different grades at the village scale. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ES combinations and land use compositions. Furthermore, 5.23% of villages were identified as level I areas of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is a fundamental work in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a "two-step refinement zoning method" to address this gap, first using the self-organizing feature mapping method to delineate EFZs based on ESs at a township scale, and then applying hotspot overlay analysis to identify hotspots of dominant ESs within EFZs at a village scale. By overlaying the outcomes of these two steps, EFZs can be further graded by designating villages with hotspots of dominant ESs as level I and those without as level II. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ESs combinations and land use compositions. Furthermore, 5.23% of villages were identified as Level I of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.