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Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment.

Gonzalo Suarez1, Rachata Muneepeerakul1

  • 1Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States of America.

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Migration dynamics are complex, influenced by changing mindsets, social ties, and environment. These factors interact non-linearly, impacting city survival and population diversity in migration models.

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Area of Science:

  • Sociology
  • Environmental Science
  • Computational Modeling

Background:

  • Migration is a key adaptation strategy to adverse conditions.
  • Socio-economic and environmental factors significantly influence migration patterns.
  • Existing migration models often underrepresent crucial drivers.

Purpose of the Study:

  • To investigate the interplay of underrepresented drivers on migration dynamics.
  • To analyze how changing mindsets, agglomeration, social ties, and the environment (CHASE) affect migration outcomes.
  • To develop a mechanistic model capturing these complex interactions.

Main Methods:

  • Development of a parsimonious Markov chain model.
  • Analysis of transient dynamics and long-term outcomes of migration.
  • Systematic study of the interplay between CHASE drivers.

Main Results:

  • Drivers interact in nonlinear and complex ways, exhibiting legacy effects.
  • Increased population size counter-intuitively reduces surviving cities, mediated by mindset change speed and social tie strength.
  • Strong social ties decrease population diversity, influenced by the number of remaining cities.

Conclusions:

  • The interplay of CHASE drivers is crucial for understanding migration.
  • Mechanistic migration models must incorporate these complex interactions.
  • Findings highlight the need for applying such models to real-world migration scenarios.