A park landscape connectivity restoration model based on ecosystem service flows

With the acceleration of urbanization, the fragmentation problem of urban park landscapes has become increasingly prominent, resulting in the interruption of ecosystem service flow transmission and the decline of landscape connectivity, which seriously threatens the stability of urban ecosystems. To break through the limitations of traditional restoration methods in the collaborative optimization of service flows and connectivity, this paper proposes a park landscape connectivity restoration model based on ecosystem service flows. This model characterizes the coupling relationship between ecosystem service flows and landscape elements through topological modeling, and constructs a coupled topological structure covering the generation, transmission, loss, and node interaction of service flows; designs multi-objective restoration functions to coordinate the connectivity index, service flow transmission efficiency, and ecological loss cost; and proposes an adaptive weighted optimization algorithm to achieve dynamic iterative optimization of the restoration plan; finally, through scenario simulation and empirical verification, a closed-loop restoration framework is formed. Experimental results show that in three typical fragmentation scenarios (low, medium, and high), the model increases the landscape connectivity index by an average of 42.3%, reduces service flow transmission loss by 31.7%, and controls the unit area restoration cost within 186.5 ten thousand yuan per square kilometer, with significantly better comprehensive performance than traditional methods. In the case of sudden ecological disturbances, the model can still maintain 89.2% service flow stability, and the spatial adaptability of the restoration plan reaches 91.5%. This model provides a scientific and practical technical path for the construction of urban park ecological networks, and is applicable to landscape restoration, ecological corridor planning, and ecosystem optimization scenarios in different levels of urbanization and different urban contexts.