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Demonstrates enhanced ecological network resilience through corridor optimization in ecological barrier zones, suggesting effective conservation strategies.
Ecological barrier zones are increasingly threatened by habitat fragmentation, climate change, and human disturbance. Designing ecological networks that remain functional under disturbance requires the identification of ecological sources and corridors and the optimization of network topology and redundancy. Here, we developed a resilience-oriented ecological security framework for the Sichuan–Yunnan Ecological Barrier Zone by integrating morphological spatial pattern analysis, the minimum cumulative resistance model, circuit theory, and complex network analysis. Using data-driven thresholds, we identified 28 ecological sources totaling 50,919 km 2 , equivalent to 21.51% of the study area, and 93 baseline corridors. The baseline network exhibited dense southern connectivity, a central longitudinal axis, and relatively sparse northern links. Adding 35 cost-constrained corridors increased the number of edges from 93 to 128, equivalent to an edge-count increase of 37.6%. The optimized network reduced the Gini coefficient of composite node importance from 0.381 to 0.249 and maximum node importance from 1.609 to 1.243, while increasing global efficiency from 0.536 to 0.613. Under random node removal, mean relative largest-connected-component size and global efficiency increased by approximately 6.2% and 25.6%, respectively. Under targeted removal, the slope of relative global efficiency over the 0–30% node-removal interval changed from −1.25 to −0.27, and relative efficiency at 30% node loss increased from 60.7% to 90.7%. At 50% targeted node removal, the optimized network retained twice the relative largest-connected-component size of the baseline network, with values of 0.50 and 0.25, respectively. These results show that topology-based corridor optimization can enhance ecological network resilience by increasing alternative pathways and reducing composite hub dependence. The framework provides a quantitative basis for conservation prioritization and spatial planning in complex mountainous ecological barrier zones.
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Miao et al. (2026) studied this question.
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