Finite-element simulation: A new method for risk assessment and pattern optimization towards ecological security pattern

Risk assessments of ecological security patterns (ESPs) are crucial for maintaining ecosystem connectivity and stability. Although numerous studies of the construction of ESPs have been conducted, novel perspectives and approaches are still needed for ESP risk analysis. The regional ESP is constructed using morphological spatial pattern analysis (MSPA) and circuit theory, forming the basis for subsequent risk assessment and optimization. This study introduces an innovative finite-element simulation framework to identify ecological corridors and assess their structural stability, providing a new approach for ESP optimization, addressing four key research objectives: (1) constructing a novel ESP analysis method, (2) simulating ecological corridors to evaluate their stability under environmental disturbances, (3) establishing multi-scenario comparative analyses, and (4) exploring the impact of stepping stones on corridor stability. The technical framework constructed on the basis of the ESP comprises five core components: corridor discretization, finite element-oriented corridor strength conversion, load transformation from external impacts on corridors, and constraint configurations for ecological sources and stepping stones. The framework is used to further optimize the ESP through finite-element simulations via multiple scenario analyses. Corridors with potential instability (e.g., high stress concentration and deformation) are identified through structural analysis, with corridor B exhibiting the maximum deformation (0.734 m) and significant stress concentration (200 MPa), indicating vulnerability to environmental disturbances. Multi-scenario simulations reveal that stepping stones enhance corridor resilience, but their placement may destabilize adjacent corridors, necessitating strategic spatial planning. Through an interdisciplinary methodology, the feasibility of implementing finite-element simulations in ESP risk assessment and optimization is verified, offering a novel perspective for ecological conservation research.