Global migration and mobility dynamics are expected to shift in the coming decades as a result of climate change. However, the extent to which migration is caused by climate hazards, in contrast or addition to other intervening factors, is a point of debate in literature. In this study, we conducted a systematic literature review to identify and consolidate factors which directly and indirectly influence climate change migration. In our review of the literature, we found a total of 21 economic, environmental, demographic, political, social, and personal intervening decision‐making factors which affect climate migration. Causal interactions between these factors were identified using an axial qualitative coding technique called purposive text analysis. By combining causal links, a semi‐quantitative causal loop diagram was created that represented factor interaction and feedback within the “climate migration system.” Using this model, we highlight influential feedback loops and point to how intervention strategies may cause downstream effects. This research helps to address calls for a better understanding of the complex decision‐making dynamics in climate migration. In particular, results from our causal feedback loops show that intervention strategies targeted toward economic factors such as financial capital and livelihoods, as well as food security, would have the greatest impact in assisting climate‐affected communities. These results help inform climate migration policy and aid planners in the future to better understand the interconnected system of factors that lead to the emergent outcome of climate migration. This article is categorized under: Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies The Social Status of Climate Change Knowledge > Climate Science and Decision Making
As the impacts of climate change increase, the Intergovernmental Panel on Climate Change advises that global migration will also increase. A deeper understanding of the factors and interactions that influence the migration decision-making of climate-affected populations is needed to more accurately predict migration estimates and adequately inform and prepare future receiving cities. In this study, we survey thirty-two experts in the field of climate migration to explore how demographic, economic, environmental, political, and social factors interact to lead to climate (im)mobility and how these interactions change within sea level rise, drought, flooding, and erosion contexts. We use system mapping and network analysis to determine which factors should be targeted as leverage points for policy makers and their resulting effects within each hazard context. Our findings identify physical infrastructure, social services, social capital, and political stability as places to intervene to increase resiliency in drought, flooding, and erosion climate migration systems. Using hazard context and community consultation, we recommend selecting target factors with direct relationships to other highly influential factors (livelihoods, food security, and financial capital) to elicit the most positive cascading effects through the whole system, leading to changes in migration. We also highlight the sea level rise climate migration system as highly complex in comparison to the other contexts examined and the need for multi-factored interventions in this context to create more resilient migration systems. Our findings contribute to the growing body of work which seeks to better understand the interactions between factors influencing climate migration.
Consequences of climate inaction are already felt by many vulnerable populations, and adapting to these impacts is an increasingly important necessity for affected communities. This study assessed adaptation priority differences in the Philippines to determine if traditional climate change decision makers accurately represent the marginalized communities they serve. Specifically, this study gathered baseline data of climate change knowledge, compared resiliency priorities and proposed strategies between local government workers and village residents, and analyzed factors that contribute to identify differences. The study's target group (residents of small villages) has historically been marginalized in municipal environmental decision making. Data collected through focus group discussions and interviews demonstrated there was a statistical difference between local government officials who were more likely to propose abstract, systemic adaptation strategies to build social capacity (69% of government officials' proposed strategies), while village residents focused on physical infrastructure (59% of village residents' proposed strategies). A second study outcome was the identification of contributing factors in how Filipinos might propose climate change adaptation strategies: for example, education levels, social or economic class, accessibility to resources, sources of information, and past experience with hazards. The significance of this research is the evidence of climate change adaptation prioritization differences between the country's traditional decision-making group, the municipal government unit, and marginalized members of local villages. The differences show that local municipal government units in the Philippines may not be the most effective base group for bottom-up adaptation and support the need for effective collaboration and community engagement in future climate change planning.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.