How to Robustly Assess and Effectively Improve Ecological Health in Small-Sample Coastal Reclamation Areas? An Integrated Two-Step fsQCA Framework

Coastal reclamation ecological restoration is critical for mitigating nearshore ecosystem degradation; however, achieving robust ecological assessment and effectively improving ecological health remain challenging for governance and sustainable development. This research develops an integrated framework based on two-step fuzzy-set qualitative comparative analysis (two-step fsQCA) that combines ecological assessment with pathway identification to address this issue under small-sample conditions. The framework includes: (i) constructing a tailored ecological health indicator framework; (ii) determining weights via a combined model selected by the Weighted Average of Mutual Information Redundancy (WAMIR) index; (iii) measuring health status and introducing the Rank Sum Ratio (RSR) for objective grading; and (iv) employing two-step fsQCA to identify configurational pathways. The framework was validated using time-series data from Laizhou Bay (1980–2019) and cross-sectional data from 14 functional zones in Zhejiang Province, China. Results show that, compared to previous approaches, the proposed framework can provide a robust ecological health assessment under small-sample conditions and effectively capture the hierarchical combinatorial causality between conditions and outcomes, offering a practical reference for assessment and differentiated management in coastal reclamation areas.