Objective: The consequences of climate change in the agricultural and rural sectors have significantly destroyed and threatened the assets and livelihoods of rural farmers, and ultimately, have reduced the resilience and increased the vulnerability of the agricultural production system and even led to rural migration to the city. This study aimed to analyze the resilience of rural people to climate change with three resilience capacities of production systems, including robustness, adaptability, transformability, in the villages of Mazandaran province.
Methods:The statistical population consisted of 178,316 rural rice farmers in the western, central, and eastern regions of Mazandaran province, and the sample size was determined to be 204 people based on G-Power software. Sampling was carried out using multi-stage random sampling with proportional assignment. The face and content validity of the questionnaire was confirmed using expert opinion, and the discriminant validity was confirmed using AVE index. The reliability of the questionnaire was also assessed through Cronbach's alpha and composite reliability. Data analysis was performed using SPSS26 and Smart PLS3 software.
Results: The results indicate that the villagers in the region have a relatively high level of perception of climate change in the past ten years. Most of the villagers (about 58.8%) have demonstrated relatively high and high levels of resilience to climate change in the rice production system. The findings from the confirmatory factor analysis showed that "adaptability", "robustness" and "transformability" explain the largest amount of the total variance of rice farm resilience in dealing with climate change, with path coefficients of 0.752, 0.739 and 0.752, respectively.
Conclusions: These results indicate that the existence of strong and almost equal path coefficients between the three constructs, these dimensions complement each other in a balanced and synergistic manner, and no dimension alone is sufficient for the resilience of the production system to climate change.