A “Foundation-Function-Structure” Framework for Multiple Scenario Assessment of Land Change-Induced Dynamics in Regional Ecosystem Quality

Understanding the changes in ecosystem quality caused by land use changes is critical for sustainable urban development and environmental management. This study investigates the spatial-temporal evolution of ecosystem quality in Wuhan from 2000 to 2020 and forecasts future trends under multiple land use scenarios for 2030. Using a “foundation-function-structure” assessment framework, we integrate system dynamics (SD), the Patch-generating Land Use Simulation (PLUS) model, and a neural network-based ecosystem quality inversion model to analyze land use transitions and their ecological impacts. The results indicate that rapid urban expansion has significantly contributed to the decline of cropland and forest areas, while impervious surfaces have increased, leading to notable ecological degradation. Simulations for 2030 under three scenarios—ecological protection, natural development, and economic priority—demonstrate that the ecological protection scenario yields the highest ecosystem quality, preserving landscape connectivity and mitigating degradation risks. In contrast, the economic priority scenario results in extensive urban expansion, exacerbating ecological stress. Under the ecological protection scenario from 2020 to 2023, the decline in ecosystem quality was primarily due to the expansion of urban fringes and the erosion of forest and grassland areas. The increase in ecosystem quality was mainly attributed to the transformation of early urban edge conflict zones into stable urban edge interior areas and the integration of fragmented ecological land patches. These findings highlight the need for strategic land use planning to balance economic growth and environmental conservation. This study provides a robust methodological framework for assessing and predicting ecosystem quality changes, offering valuable insights for policymakers and urban planners striving for sustainable development.