Ecological networks (ENs) were vital maintaining regional ecological security and enhancing ecosystem services. This study introduces a collaborative optimization framework integrating mechanical and complex network analyses to enhance EN connectivity and robustness. By coupling stress identification with network structural reconfiguration, the framework enables targeted local risk mitigation while simultaneously enhancing global connectivity and robustness. This framework involved: (1) identifying the EN in a typical karst region; (2) introducing finite-element simulation to achieve risk assessment and optimization of the EN; (3) analyzing the EN from a topological perspective and validating the results optimized by finite-element simulation; (4) integrating topological features and stress conditions to propose strategies for ecological restoration. A typical karst region in Southwest China, characterized by severe rocky desertification, ecological fragility, and fragmented habitats under strong human disturbance, was selected as a case study to evaluate the framework's feasibility. Traditional EN studies often overlook corridor stability under external disturbances. To overcome this limitation and achieve a more physically grounded risk assessment, this study introduced finite-element simulation into EN research. The finite-element simulation from mechanical engineering was introduced to transform ecological corridors into threedimensional mechanical models. In addition, landscape pattern indices were mapped to material properties, and the normalized difference vegetation index (NDVI) and road network density defined dynamic loads, quantifying corridor stress distribution and identifying high-risk fracture zones. Furthermore, a weighted undirected topological network was constructed based on complex networks to analyze node centrality and clustering characteristics, revealing the spatial imbalance and connectivity vulnerability of the EN. Then, collaborative optimization was achieved by adding stepping stones, resulting in a maximum 14.5% reduction in corridor stress and an increase in natural connectivity from 0.340 to 0.368, indicating improved network robustness. This study offered precise decision-making support for enhancing landscape connectivity and construct ENs.