GCR: Collaborative Research: Disentangling Environmental Change and Social Factors as Drivers of Migration

  • Seager, Richard (PI)
  • de Sherbinin, Alex (CoPI)
  • Schlenker, Wolfram (CoPI)
  • Puma, Michael (CoPI)

Projet

Détails sur le projet

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 research team aims to achieve convergence across geography, economics, political science, environmental science, and crop sciences to better understand the causes of migration and predict future mass-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 their impacts on 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 the migration issues. 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.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

StatutActif
Date de début/de fin réelle10/1/199/30/24

Financement

  • National Science Foundation: 1 179 841,00 $ US

Keywords

  • Ciencias ambientales (todo)
  • Psicobiología
  • Neurociencia cognitiva

Empreinte numérique

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