Land Inequality and Climate Change Adaptation: An Agent-Based Approach

Abstract

As an alternative to traditional agricultural practices, no-till farming can increase farmers' resilience to climate change by reducing their dependence on high-input techniques. However, the lack of a comprehensive support system for such practices in Türkiye hinders widespread adoption. The presence of farmers unconvinced of the benefits of no-till farming is also a barrier, as their influential position and views within the farming community can influence the decisions of other farmers. To understand the adoption and diffusion process of no-till farming, it is crucial to understand the complex interplay of factors that influence farmers' decision-making processes. This thesis explores the factors contributing to the diffusion of alternative production systems, such as no-till farming, considering social interaction mechanisms, market price dynamics, and farmers' perceptions of climate change. For this purpose, an agent-based model is used as a modeling technique. Agent-based models, which have a bottom-up modeling methodology by analyzing micro components to draw macro conclusions, have been widely used in modeling climate change in recent years. In our model, we simulated farmers' decision-making processes by developing an agent typology to analyze wheat farmers' decision processes based on data from various farmer reports on their experiences with no-tillage farming in Turkey. For this, we used NetLogo software. As the first study to model wheat farmers' adaptation to climate change in Türkiye using agent-based modeling, this thesis analyzes the potential contribution of farmers with previous direct cultivation experience to regional climate change adaptation. In line with the literature, the findings show that the number of conservation farmers in a region can influence the adoption and diffusion of conservation agriculture. However, it also emphasizes the importance of the average land size of these farmers in the diffusion of conservation agriculture. In conclusion, this thesis contributes to the growing knowledge of the complex diffusion dynamics of sustainable agricultural innovations, ultimately promoting farmers' adaptation to climate change.