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A Coastal Vulnerability Framework to Guide Natural Infrastructure Funds Allocation in Compressed Time

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Abstract

Hurricane Maria, a category 4 tropical cyclone, hit the US non-incorporated territory of Puerto Rico on September 20, 2017. Widespread physical and natural infrastructure damage was observed, especially in already vulnerable coastal communities. As public sector funding availability for natural infrastructure (ex. coastal ecosystems) increases, mechanisms for its efficient and equitable allocation are lacking. An accessible and replicable coastal vulnerability indicator framework is presented to assist state and federal policy makers in the allocation of funding for coastal natural infrastructure recovery. To assess funding priorization gaps and test the applicability of the proposed framework, spatial patterns in the estimated funding need identified in state-led post-Hurricane Maria assessments for natural infrastructure rehabilitation efforts were compared to physical and social coastal vulnerability estimations. Three main challenges that emerge during the implementation of a vulnerability indicator framework were considered for its design: (1) the compressed time frame in which decisions are made after an extreme weather event, (2) the availability of data to calculate indicators in a reduced time frame, and (3) the accessibility of results to a broad variety of stakeholders. We propose a vulnerability indicator framework that can become operational in a relatively short period of time, attempts to simplify data gathering efforts, and uses methods that aim to be more transparent and understandable to a broad group of stakeholders.

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Acknowledgements

Financial support for this study was provided by a grant from the University of Puerto Rico Institutional Funding for Research (FIPI UPRRP 21120.293.146 FIP3570018).

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Correspondence to Luis Santiago.

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Santiago, L., Barreto, M., Montañez-Acuña, A. et al. A Coastal Vulnerability Framework to Guide Natural Infrastructure Funds Allocation in Compressed Time. Environmental Management 67, 67–80 (2021). https://doi.org/10.1007/s00267-020-01397-z

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  • DOI: https://doi.org/10.1007/s00267-020-01397-z

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