A framework for large-scale analyses of ecosystem health and its driving factors in complex underlying basins

• The study presented a novel framework to assess global ecosystem health. • It overcomes the spatial adaptability limitations of traditional indicator systems. • It reduces redundant data and calculations, handling large-scale data effectively. • It improves the objectivity and accuracy of the assessment. Global climate change and biodiversity loss has accelerated ecosystem degradation. Comprehensive assessing and monitoring global ecosystem health is the basis for ecosystem restoration and climate adaptation. However, the previous indicator systems are complex and subjective, making them difficult to be applied in large-scale complex subsurface basins, hinding effective assessment and monitoring on global ecosystems. To this end, this paper constructs a new ecosystem health evaluation framework based on landscape pattern indicators and Condition-Vitality-Organization-Resilience (CVOR) model, applicable to large-scale complex subsurface watersheds, based on which the key factors driving the spatial and temporal evolution of health status are identified. Coupling the landscape pattern with the CVOR model greatly reduced data requirement, and can effectively handle large-scale ecosystem issues. It overcomes the limitations of the traditional indicator system in terms of spatial adaptability and ensures the consistency of comparisons between different indicators and model results of high-resolution landscape distribution data. Using high-resolution landscape distribution data dramatically reduced the errors caused by subjective judgment and improve the objectivity and accuracy of the assessment. Application to the Yellow River water conservation area in China shows that the health status was in the state of warning from 1990 to 1994, and the health status was in the state of unhealthy from 1995 to 2021. The greatest influence on health status was landscape separation (DIVISION, Pearson correlation coefficient 0.91), followed by the patch shape indicators (LSI, −0.90). Grassland and cropland, which are the largest landscape types in the areas, are gradually decreasing, with overgrazing, reforestation and urbanization being the main reasons. The decline was more pronounced in the western plateau areas than in the eastern plains, while the southwestern part showed significant improvement. The connectivity between patches of various landscape types has been enhanced, and the water conservation capacity has been continuously improved. The methodology and results of this study can provide a scientific basis for ecological restoration in the Yellow River Basin. It can also provide reference and guidance for other regions across the world to cope with climate change and biodiversity loss indued problems.