The aim of this research is to investigate behavioral adaptation to climate change among livestock breeders in Iran by using an exploratory sequential mixed-methods approach. Considering the different effects of climate change in Varamin city, one of the most important livestock ecosystems in Iran, design of an adaptation pattern to climate change for livestock breeders in this region is necessary. Based on the axial coding paradigm model in qualitative research, adaptation strategies used by livestock breeders were found. The theoretical basis for the structural model in the quantitative investigation was Ajzen's theory of planned behavior. The awareness variable derived from the results of the qualitative section was added to the model. The results indicate that awareness on attitude is the greatest driver of livestock breeders' adaptive behavior in the region. Awareness, attitude, social norms, and perceived behavioral control can predict 68% of the changes in the livestock breeders' climate change-related adaptive behavior. Eventually, the information and results of this study can help authorities, financial supporters, staff, and executive experts understand the situation of livestock breeders, enabling them to develop future plans and to make a more detailed choice about regulation at the macro level. Mixed-methods research, such as that used in this study, can produce a clearer, more societally relevant understanding of how the climate is changing and the human livelihood adaptations to these changes.
Ahmadi, M; Najafabadi, MO; Motamedvaziri, B
Identifying drivers of adaptive behavior among livestock breeders in Varamin County, Iran: an exploratory sequential mixed-methods approach
Regional Environmental Change