Integrating Multi-Criteria Decision Analysis and 3D Resistance Surfaces to Optimize Ecological Security Patterns in High-Density Urban Areas

Constructing ecological security patterns (ESPs) in high-density urban areas is challenged by severe habitat fragmentation and intense multi-objective conflicts. Traditional ESP optimization methods, typically designed for regional or municipal scales, struggle to effectively address the complex socio-ecological trade-offs in dense urban cores due to scale mismatch, oversimplified objectives, and insufficient representation of three-dimensional urban structures. To address this, this study develops an integrated framework combining multi-criteria analysis with 3D resistance surface modeling. Applied to Beijing’s core districts, the framework quantifies four key dimensions—species suitability, environmental vulnerability, ecological health, and implementation feasibility—using MARXAN spatial conservation planning software (an optimization model) to reveal dynamic trade-offs among conservation targets, benefits, and costs. The analysis delineates a hierarchical zoning system and generates two scenario-based governance plans: an Ecological Core Enhancement Plan for near-term, low-cost stabilization of the ecological foundation, and a Multi-criteria Collaborative Governance Plan for long-term, cross-sectoral conflict mitigation. The results show a strategic shift in governance logic, from site-specific protection to systematic enhancement, as priority area relationships evolve from “relative independence” to “convergent coverage” and, finally, “intensified differentiation” as targets increase. Thus, this framework provides an operable tool for dynamic ESP optimization, advancing urban ecological planning from static blueprinting toward adaptive governance.