JOURNAL ARTICLE

The Risk of Climate-Induced Migration in Tuvalu: Lessons and Way Forward.

  • Published In: International Journal of Interdisciplinary Civic & Political Studies, 2025, v. 20, n. 1. P. 125 1 of 3

  • Database: Political Science Complete 2 of 3

  • Authored By: Bazela, Maciej; Robinson, José Carlos 3 of 3

Abstract

This article examines the risks posed by climate change to Tuvalu, a Pacific Island nation highly vulnerable to rising sea levels. It explores a series of short-term and long-term risks, such as the potential disappearance of its territory and the resulting displacement of its population, alongside impacts on natural resources, coastal erosion, saltwater intrusion, and extreme storms. The article discusses measures that the Government of Tuvalu, in collaboration with the international community, has implemented to strengthen community resilience so far. These actions include the use of adaptation technologies to mitigate the impacts of climate hazards, as well as the search for legal and financial solutions to compensate for losses or plan for possible migration in the future. The article concludes by reflecting on the implications for national governance and the international community. Are these interventions effective or, on the contrary, are they perpetuating global inequalities in the fight against climate change? [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Interdisciplinary Civic & Political Studies. 2025/06, Vol. 20, Issue 1, p125
  • Document Type:Article
  • Subject Area:Power and Energy
  • Publication Date:2025
  • ISSN:2327-0071
  • DOI:10.18848/2327-0071/CGP/v20i01/125-141
  • Accession Number:186547397
  • Copyright Statement:Copyright of International Journal of Interdisciplinary Civic & Political Studies is the property of Common Ground Research Networks and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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