Abstract: The optimization of ecological networks based on the coupling of natural and human systems is of great significance for mitigating the fragmentation of ecological spaces and the disconnection of human landscape spaces in old industrial cities. Taking Shenyang City as a case, we identified ecological sources using morphological spatial pattern analysis and landscape connectivity analysis. We integrated historical landscapes and industrial heritage as human sources, applied the circuit theory to construct three types of spatial networks: ecological, historical landscape, and industrial heritage networks. We further employed topological structure analysis and the coupling coordination degree model to analyze the structural characteristics and spatial coupling relationships among these three networks and propose optimization strategies. The results showed that the ecological network structure of Shenyang City was relatively fragile, with network closure (α), connectivity (β), and connection rate (γ) indices being 0.30, 1.48, and 0.54, respectively. A total of 16 ecological sources were identified, with a corridor density of 0.07 km·km^-2. There were 38 ecological key points and 115 ecological interference points. The historical landscape network structure was intermediate, with the three indices being 0.35, 1.66, and 0.57, respectively, exhibiting a polycentric radial pattern spatially. The industrial heritage network structure was relatively stable, with the three indices being 0.38, 1.70, and 0.59, respectively, showing a high concentration of industrial heritage in Tiexi District. The coordination degree of the three networks decreased from the center to the periphery. Interaction hotspot areas were all located within the Third Ring Road of Shenyang City, where the ecological-historical landscape hotspot areas highly overlapped with the composite hotspot areas of the three networks. After optimization, the number of ecological sources increased to 33, and the area increased 144.31 km². Corridor density increased to 0.15 km·km^-2, while the α, β and γ indices improved by 37.7%, 19.1%, and 11.2%, respectively, compared to those of the pre-optimization ecological network. This study validated the feasibility of integrating historical landscape conservation and ecological restoration of industrial brownfields into ecological networks, which would provide a quantitative scientific basis for old industrial cities to implement “multi-plan integration” and achieve systematic governance and collaborative optimization of ecological, historical, and industrial spaces within territorial spatial planning.

Key words: ecological network optimization, human heritage, spatial coupling, circuit theory, old industrial city