Abstract for: Climate migration system causal loop diagramming using the mental models of experts
Migration relating to climate change is a complex phenomenon coalescing from many interrelating decision-making factors (Black et al., 2011; Parrish et al., 2020). While early approaches to estimating climate migration have directly linked hazard exposure to migration (Myers, 2002), many scholars now agree that migration is driven by a complex array of factors. Our approach for understanding the interactions between these factors builds off of a systematic literature review that identified 21 factors which influence migration decision-making, and their interactions. Using eigenvector centrality values, we ranked the factors into a top ten list. These ten factors and interactions were then validated and more deeply explored through a survey of experts, who gave their perceptions on the interactions between the identified factors. The resulting interaction data will be analyzed using causal loop diagramming. By using causal loop diagramming to analyze the interaction data from the survey, we are able to show important feedback loops and leverage points in the system which can inform policy priorities for governments and nongovernment decision-makers.