GCR: Collaborative Research: Disentangling Environmental Change and Social Factors as Drivers of Migration
- Lead PI: Dr. Richard Seager , Dr. Michael Joseph Puma , Wolfram Schlenker , Alex DeSherbinin
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Unit Affiliation: Ocean and Climate Physics, Lamont-Doherty Earth Observatory (LDEO)
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Unit Affiliation: Center for International Earth Science Information Network (CIESIN)
- October 2019 - September 2023
- Inactive
- Global
- Project Type: Research
DESCRIPTION:
The objectives of this Growing Convergence Research project are to develop a comprehensive analysis of large-scale human migrations and improve our ability to predict them. The challenges that drive and are created by large-scale migrations motivate this research into how regional and international migrant flows will change in the future and how sensitive these flows are to changing social and environmental conditions. The analysis methods are intended to have universal application but the research focus is on West Africa. The research team aims to achieve convergence across geography, economics, political science, environmental science, and agricultural sciences to better understand the causes of migration and predict future migrations. Such understanding will allow society to better anticipate, adapt to, and manage such migrations to maximize human wellbeing in both source and destination countries.
In the proposed work, a team of researchers who are individually experts in the multiple subject areas relevant to migration will work together to transcend their disciplinary boundaries and develop a common language and methodology for understanding, analyzing, modeling and predicting migration within social, economic, and environmental contexts and how they influence food production, security, and household livelihoods. The team will engage in intentional convergence activities where all team members together with stakeholders will work with social, economic and environmental data and models to analyze the complexity of migration decision making and flows. This analysis will be translated into predictive models that will be calibrated and verified against historical data. The modeling effort will couple climate, crop, and global food trade models with models of household livelihoods. These will drive agent-based models of migration decisions that account for perceptions of opportunity and risk, migrant and family networks, resources, and standard economic utility maximizing models. The integrated modeling will be developed and modified as needed with input from the stakeholder community.