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Reimagining Climate Relocation after Hurricane Fiona in Channel-Port aux Basques: Unmasking the Hidden Aspects of Relocation Decision Making

Year: 2026
Type: preprint
Abstract: Coastal communities are increasingly required to adapt to climate change. Relocation is emerging as an important yet contested adaptation strategy. As climate-related impacts intensify, there remains limited empirical research on relocation, including examining why and under what conditions people are willing to relocate. The gap in knowledge is especially wide in Global North contexts such as Canada. In response, this study presents a qualitative case study of climate change-driven relocation in the Town of Channel-Port aux Basques, Newfoundland and Labrador, following Hurricane Fiona, marking one of the first documented cases of climate-related relocation in the province. Drawing on in-depth interviews, the study examines core assumptions typically associated with relocation and climate adaptation policy and scholarship. It focuses on the belief that relocation can be encouraged by exposure to extreme events, that risk awareness leads to relocation readiness, and that financial incentives increase willingness to relocate. Our findings demonstrate that while these are often preconditions in relocation decisions (influence relocation reasoning), they do not act in isolation to trigger retreat (determine outcomes). This article contributes to managed retreat scholarship by demonstrating that exposure, risk perception, and financial incentives do not independently determine relocation willingness. Instead, retreat decisions are mediated through emotional attachment, social embeddedness, identity, grief, and perceptions of agency, which complicates linear models of climate adaptation behaviour. We conclude that relocation research and policy must account for these broader social, experiential and psychosocial dimensions of decision-making in support of just and socially sustainable coastal retreat initiatives.
DOI: 10.31223/x52v45
Language: English
Open Access status: green
OpenAlex ID: W7225692295
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