Shaping Risk Perception in Mountain Communities: From Community Resilience to Personal Tendency in Landslide‐ and Debris‐Flow‐Prone Regions of China

As climate‐related hazards intensify, understanding how collective resilience capacities shape individual psychological responses has become essential for advancing sustainable adaptation, yet this relationship remains insufficiently explored. This study investigates the associations between three dimensions of community resilience (i.e., absorptive capacity, self‐organization, and learning capacity) and individual risk perception, which serves as an important cognitive precursor to adaptive behavior. Drawing on survey data from 1052 households in landslide‐ and debris‐flow‐prone areas of China, we employ a boosted regression tree (BRT) model, an ensemble machine learning method that captures complex, nonlinear patterns and interaction effects. This approach accommodates high‐dimensional predictors without strong parametric assumptions, making it ideal for exploring resilience indicators whose relationships with outcomes may be nonlinear or threshold‐based. Model performance was validated using cross‐validation to ensure generalizability and robustness. The findings reveal that all three resilience dimensions are significantly associated with individual risk perception. Key predictors include proactive preparedness, recovery policy, and disaster risk reduction publicity (absorptive capacity); community self‐efficacy, mutual aid, and development planning (self‐organization); and peer influence and information exchange (learning capacity). Hazard‐specific differences are also observed: self‐organization has greater impact in landslide‐prone areas, whereas absorptive capacity is more prominent in debris‐flow contexts. By identifying the most impactful components of community resilience, this study provides policy‐relevant insights into how collective capacities can shape adaptive awareness. These findings support the development of context‐sensitive, community‐anchored strategies that align with Sustainable Development Goals 11 and 13, emphasizing the role of local governance in enhancing both social resilience and climate adaptation.