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Climate migration amplifies demographic change and population aging. | LitMetric

Climate migration amplifies demographic change and population aging.

Proc Natl Acad Sci U S A

Climate Central, Princeton, NJ 08542.

Published: January 2024

AI Article Synopsis

Article Abstract

The warnings of potential climate migration first appeared in the scientific literature in the late 1970s when increased recognition that disintegrating ice sheets could drive people to migrate from coastal cities. Since that time, scientists have modeled potential climate migration without integrating other population processes, potentially obscuring the demographic amplification of this migration. Climate migration could amplify demographic change-enhancing migration to destinations and suppressing migration to origins. Additionally, older populations are the least likely to migrate, and climate migration could accelerate population aging in origin areas. Here, we investigate climate migration under sea-level rise (SLR), a single climatic hazard, and examine both the potential demographic amplification effect and population aging by combining matrix population models, flood hazard models, and a migration model built on 40 y of environmental migration in the United States to project the US population distribution of US counties. We find that the demographic amplification of SLR for all feasible Representative Concentration Pathway-Shared Socioeconomic Pathway (RCP-SSP) scenarios in 2100 ranges between 8.6-28 M [5.7-53 M]-5.3 and 18 times the number of migrants (0.4-10 M). We also project significant aging of coastal areas as youthful populations migrate but older populations remain, accelerating population aging in origin areas. As the percentage of the population lost due to climate migration increases, the median age also increases-up to 10+ y older in some highly impacted coastal counties. Additionally, our population projection approach can be easily adapted to investigate additional or multiple climate hazards.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10801880PMC
http://dx.doi.org/10.1073/pnas.2206192119DOI Listing

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