Evaluating Community Resilience in Resettlement Contexts from a Social–Ecological Systems Perspective

Migrant resettlement communities in large-scale development regions face persistent pressures from environmental change, livelihood disruption, and social restructuring. Evaluating resilience in such communities requires a framework that captures both external stressors and internal adaptive capacity. This study asks whether differences in resilience between resettlement communities are driven more by differences in external pressure exposure or by differences in internal development conditions. To address this question it applies a Pressure–State–Response (PSR) framework to assess community resilience in the Three Gorges Reservoir Area (TGRA) of China. A four-level indicator system of 29 variables was developed across pressure, state, and response dimensions. Weights were determined by combining the Analytic Hierarchy Process with the entropy method; standardisation and entropy weights were computed across all 25 surveyed communities. Survey data statistical records, and remote sensing information were collected from 25 migrant resettlement communities. Three of these communities—CT, SQ, and GGB—were then selected by purposive maximum-variation sampling for detailed comparison. Results show that overall resilience ranked CT (0.646) > GGB (0.600) > SQ (0.483), with state resilience contributing the largest share to composite scores in all three communities. Obstacle-factor analysis revealed distinct constraint profiles: CT was primarily limited by ecological pressure, SQ by weak livelihood development, and GGB by limited industrial diversity and incomplete social integration. These findings indicate that resilience in resettlement communities depends more on internal development quality than on exposure levels alone; a Monte Carlo analysis confirmed that this ordering held in 99.9% of simulated draws. Differentiated governance strategies are needed rather than uniform approaches. The PSR-based framework and obstacle-factor diagnosis provide a practical tool for assessing and improving resilience in communities shaped by large-scale infrastructure development.