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Barriers and enablers for upscaling coastal restoration

Version 2 2024-03-12, 20:38
Version 1 2024-03-04, 11:26
journal contribution
posted on 2024-03-12, 20:38 authored by Agustín Sánchez-Arcilla, Iván Cáceres, Christophe Briere, Nuno Caiola, Vicente Gracia, Carles Ibáñez, Silvia Torresan, Xavier Le Roux, Jochen Hinkel, Mark Schuerch, Robert J Nicholls, Maria del Mar Otero, Joanna Staneva, Mindert de Vries, Umberto Pernice
<p>Coastal restoration is often distrusted and, at best, implemented at small scales, which hampers its potential for coastal adaptation. Present technical, economic and management barriers stem from sectoral and poorly coordinated local interventions, which are insufficiently monitored and maintained, precluding the upscaling required to build up confidence in ecosystem restoration. The paper posits that there is enough knowledge, technology, financial and governance capabilities for increasing the pace and scale of restoration, before the onset of irreversible coastal degradation. We propose a systemic restoration, which integrates Nature based Solutions (NbS) building blocks, to provide climate-resilient ecosystem services and improved biodiversity to curb coastal degradation. The result should be a reduction of coastal risks from a decarbonised coastal protection, which at the same time increases coastal blue carbon. We discuss barriers and enablers for coastal adaptation-through- restoration plans, based on vulnerable coastal archetypes, such as deltas, estuaries, lagoons and coastal bays. These plans, based on connectivity and accommodation space, result in enhanced resilience and biodiversity under increasing climatic and human pressures. The paper concludes with a review of the interconnections between the technical, financial and governance dimensions of restoration, and discusses how to fill the present implementation gap.</p>

History

School affiliated with

  • Department of Geography (Research Outputs)

Publication Title

Nature-Based Solutions

Volume

2

Pages/Article Number

100032

Publisher

Elsevier

ISSN

2772-4115

Date Submitted

2022-10-12

Date Accepted

2022-09-16

Date of First Publication

2022-09-20

Date of Final Publication

2022-12-01

Open Access Status

  • Open Access

Date Document First Uploaded

2022-09-23

ePrints ID

51834

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