Industrialization-driven restructuring of ecological networks: A resilience and topology-based assessment framework

Industrialization reshapes urban landscapes not only through land conversion but also by altering ecological connectivity, network organization, and systemic resilience. However, existing ecological network (EN) planning frameworks rarely integrate industrial spatial dynamics with topology- and resilience-based assessment, limiting their ability to diagnose systemic ecological vulnerability in industrial cities. This study develops a resilience-informed EN framework to examine how sustained industrial pressure restructures ENs and to identify opportunities for structural reinforcement under alternative development pathways. Using Zhuzhou, China, as a representative industrial city, industrial pollution intensity and proximity to production facilities were incorporated into ecological resistance modeling to reconstruct ENs from 2000 to 2020 and simulate their development to 2030 under natural development (ND), urban expansion (UE), and ecological priority (EP) scenarios. Graph theory and weighted complex-network analysis were used to evaluate topological restructuring and multidimensional resilience under random and targeted node removal. From 2000 to 2020, ecological source area declined and connectivity cost increased by 61%, accompanied by reduced diffusion capacity and increasing concentration of structural importance in a limited number of critical nodes and corridors. These changes indicate that industrialization not only intensified habitat fragmentation but also increased network dependence on key ecological components. The 2030 scenarios exhibited distinct trajectories, with UE tending to reinforce structural concentration and vulnerability, whereas EP promoted lower resistance and a more balanced network configuration. Resilience-informed optimization further improved network structure, increasing the α, β, and γ indices by approximately 67, 35, and 34%, respectively. The overall resilience curve under random disturbance increased by approximately 2.4%, with larger improvements under high-intensity node removal. These findings show that ecological-network degradation involves source-area contraction, fragmentation, altered potential connectivity, and increased structural dependence. Integrating network topology and resilience into industrial spatial planning can therefore provide a stronger basis for identifying structural vulnerabilities and supporting sustainable urban transition.