Applying the Norm Activation Model to analyze climate change adaptation behaviors of forest-dwellers

Climate change poses a serious threat to economies that depend on agriculture and natural resources. Iran is especially at risk due to both its difficult environmental conditions and management challenges. Understanding how forest dwellers in western Iran adapt to climate change is key to developing effective strategies. This study investigates the adaptive behaviors of these communities using the Norm Activation Model. Data was collected through a questionnaire completed by 374 participants. The findings confirmed all the model's hypotheses, explaining 74.9 % of the variation in adaptive behavior. These results provide valuable guidance for policymakers to design targeted support measures. Specifically, adaptation behaviors were positively linked to household size, education level, income from forest resources, livestock ownership, use of the internet and social media for climate information, participation in training, and reliance on forests, surface water, and weather-dependent jobs. The government should strengthen public policies, promote a variety of adaptive behaviors, and support social networks that allow forest dwellers to share knowledge. Using big data and AI can further enhance these efforts by offering better tools and insights for climate adaptation.