Temporal–Spatial Evolution and Driving Mechanism for an Ecosystem Health Service Based on the GD-MGWR-XGBOOT-SEM Model: A Case Study in Guangxi Region

With the expansion of urbanization in China, ecological environments are becoming more and more prominent. Uncovering driving factors and ways of regulating ecosystem health has become a hot topic for regional sustainable development. This paper adopted the improved vigor–organization–resilience service (VORS) model to diagnose the regional ecosystem health status in Guangxi from 2000 to 2020 and verify the main factors affecting ecosystem health. Considering the influencing factors (including vegetation, terrain, climate and human activities), the mechanism of driving factors associated with regional ecosystem health was analyzed by using a geographic detector (GD), a multiscale geographically weighted regression model (MGWR), and the XGBOOTS-SHAP model. The results show that the spatial distribution of ecosystem health is characterized by low values in the central region and high values in the northern and eastern regions with higher elevations from 2000 to 2020. The spatial agglomeration evolution changes from agglomeration to dispersion, and the regional urbanization distribution and evolution are consistent. The interaction of driving factors for ecosystem health and vegetation is enhanced significantly, while the interaction of climate factors is relatively weak. And most of the impacts of human activities on the ecological environment are negative. The vegetation factor has a dominant positive effect on ecosystem health, while human activity elements have a weak negative effect on ecosystem health. Meanwhile, climate factors are complex and changeable, and their impacts on ecosystem health are changeable, leading to corresponding changes in other factors. This study provides scientific reference for the harmonious and sustainable development of humans and nature in southern China.