Doctoral Dissertation Research: Computational Modeling of the Effects of Climate Change and Land Acquisition on Household Dynamics in Southern Ethiopia

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The current surge in large-scale land acquisition in developing countries is a complex socio-natural systems problem that also is emerging as a global policy issue. Significant tracts of land are being leased to agribusiness enterprises based in both poor and industrialized countries. The resulting expansion of large-scale land acquisition contributes to the rural economy by creating jobs, developing infrastructure, and transferring technologies. It also negatively affects rural households, however, because most large-scale land acquisition (combined with ongoing effects of climate change) affects the pastoralist livelihoods of rural people by limiting their access to resources, eventually leading them to dispossession and displacement. Although agent-based models previously have been used for modeling complexity in human-environmental systems, the influence of large actors and their interactions with local households have not been addressed and remain poorly understood. This doctoral dissertation research project will apply an agent-based modeling simulation approach that explicitly represents the main actors (enterprises, households, and institutions) to understand their interactions and dynamics with the environment in the South Omo region in southwestern Ethiopia. The doctoral student will integrate methods from spatial agent-based modeling and GIS along with social network analysis and quantitative analysis. The agent simulation model will use quantitative and qualitative socioeconomic data, with explicit spatial referencing based on geographic data, thereby enabling agents to interact in environments resembling the real world. He also will use a participatory modeling strategy that involves consultation before, during, and after each stage of modeling with local stakeholders, such as agribusiness enterprises, government officials, and local community households.The project will enhance understanding regarding dynamic interactions between rural households and enterprises; the consequences of different actions of actors on the land and reciprocal feedbacks; and the impact of climate change on ecosystems and local communities. By using a complex system approach, the project will contribute fundamental new understanding regarding the nonlinear dynamic interaction of human and environment components at multiple spatial and temporal scales. The project will enhance current scientific knowledge about human-environment systems by explicitly modeling the dynamics of heterogeneous actors, institutions, and their environments. The participatory modeling approach will expose a broad spectrum of constituencies to scientific research on complex socio-environmental systems. The project also will provide new, scientifically informed perspectives for the science-policy debate on this significant development issue. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.