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Home > GCR > Vol. 35 > Iss. 1 (2024)

 

Alternate Title

Applying the Disaster Risk Assessment Framework to Sargassum Inundation in Barbados

Document Type

Gulf and Caribbean Fisheries Institute Partnership

Abstract

Episodic influxes of pelagic Sargassum into the Caribbean result in inundation of coastlines with significant negative impacts to the environment, society, and economy. The spatial complexities of this issue demand a strategy that combines spatial planning with an analytical framework that can systematically unpack the underlying factors to inform effective management. We test the application of the United Nations Disaster Risk Reduction (UNDRR) conceptual framework for disaster risk assessment to Sargassum inundation, with a focus on the hazard and exposure components of risk, using Barbados, a Caribbean Small Island Developing State (SIDS), as a case study. We first consider in general terms how assessment of hazard, exposure, and ultimately vulnerability would contribute to management and broader spatial planning. As a trial, we use publicly available remotely sensed images to develop Sargassum inundation hazard maps together with spatially explicit secondary data on fisheries, tourism, and coastal ecosystem assets to examine their exposure to this hazard. This research establishes a proof of concept for application of the DRR framework to Sargassum inundation. Despite the data poor environment, the resulting broad coverage, low resolution hazard and exposure map outputs are useful planning tools, and the approach provides a template for future iterations, replications, and/or expansions, while highlighting important data needs. This trial application should be of considerable interest to the many developing countries affected by Sargassum inundation who typically have low capacity and budgets for data collection and technological tools to support management planning necessary to deal with this emergent marine hazard.

First Page

GCFI14

Last Page

GCFI29

Artificial Intelligence (AI) Use Statement

No artificial intelligence (AI) was used in the preparation of this manuscript

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