Assessment of resilience and key drivers of Tibetan villages in Western Sichuan

This study employs an integrated analytical framework combining the Social-Ecological System (SES) and Driver-Pressure-State-Impact-Response (DPSIR) models, supplemented by quantitative methodologies including the Entropy Weight Method (EWM), Generalized Additive Model (GAM), Lasso regression, and shallow neural networks, to conduct a systematic resilience assessment of six representative Tibetan villages in western Sichuan based on longitudinal data from 2015 to 2022. The analysis reveals significant differences in resilience levels among the villages, primarily influenced by multiple factors. Disposable income and employment are key positive drivers that enhance adaptive capacity and resilience. Conversely, excessive reliance on policy interventions may constrain local self-organization and adaptive governance. The study highlights the complexity of balancing ecological sustainability with economic growth, underscoring the need for flexible and inclusive policy frameworks. Furthermore, the findings indicate that integrating top-down policies with community-based governance can effectively mitigate external pressures. Key recommendations involve promoting economic diversification via agroecology and cultural tourism, enhancing local governance capacity, and adopting adaptive environmental policies. These strategies are crucial for reducing dependence on traditional agriculture and alleviating resource pressures. The insights gained from this study deepen the understanding of restoration mechanisms in ecologically fragile areas and contribute to the development of effective strategies for sustainable management.