Effects of Knowledge Transfer on Integrated Forest Management in China: A Social–Ecological System Framework Analysis

Against the backdrop of global biodiversity crises and climate change, integrated forest management (IFM) has emerged as a critical pathway for sustainable forest development. Grounded in the social–ecological system (SES) framework, we examine the mechanisms and pathways through which knowledge transfer influences IFM, with a focus on residents in China’s state-owned forest regions in the Northeast. By constructing an IFM-SES theoretical framework and utilizing survey data, we employ OLS regression and mediation effect models to empirically assess the driving effects of knowledge transfer on IFM and its heterogeneous impacts. We show that: (a) community-based knowledge transfer significantly enhances IFM; (b) knowledge transfer indirectly promotes IFM by fostering collective action efficacy, strengthening institutional rule compliance, and optimizing conflict resolution mechanisms; and (c) heterogeneity analysis indicates that the impact of knowledge transfer varies across governance models, with stronger effects observed among local residents compared to migrants. This study provides theoretical insights for integrating traditional ecological knowledge with modern scientific management and offers empirical support for global forest sustainability policy design.