The increasing severity of climate change has posed a great challenge to smallholders' livelihoods. In addition to smallholders' autonomous adaptations, policy-makers need to consider how to make sound government interventions to help smallholders effectively adapt to climate change. This study aims to explore how smallholders adapt to climate change under government interventions, and in turn provide recommendations for the government to better promote smallholder adaptation. To achieve this purpose, 1552 household survey data were collected in four agro-pastoral regions of the Tibetan Plateau (TP). A machine learning approach (boosted regression tree, BRT) was used to explore the factors influencing the adaption strategies of smallholders to climate change, especially the role of government interventions in this process. The results show that the smallholders mainly adopted four adaptation strategies (off-home activities, nature reclaiming farmland, raising more livestock, and crop management), while local governments helped them by providing subsidies, training, credit, insurance, and improved varieties; building roads and irrigation facilities; and organizing cooperatives. The results of the BRT model show that the natural capital indicators (elevation, farmland area) were still important factors influencing the smallholders' adoption of adaptation strategies, because natural capital reflects the livelihood basis of smallholders to some extent. The results also suggest that government interventions such as subsidies, cooperatives, and training played an important role in this process. Based on these results, we propose targeted policy recommendations to help local governments improve existing government interventions and to provide lessons for governments in other regions or countries to plan government interventions to promote smallholder adaptation.
He, XJ; Yan, JZ; Yang, LE; Wu, Y; Zhou, H
Climate change adaptation of smallholders on the Tibetan plateau under government interventions
Journal Of Cleaner Production