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Predicting marsh vulnerability to sea-level rise using Holocene relative sea-level data

Horton, B.P.; Shennan, I.; Bradley, S.; Cahill, N.; Kirwan, M.; Kopp, R.E.; Shaw, T.A.

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Authors

B.P. Horton

S. Bradley

N. Cahill

M. Kirwan

R.E. Kopp

T.A. Shaw



Abstract

Tidal marshes rank among Earth’s vulnerable ecosystems, which will retreat if future rates of relative sea-level rise (RSLR) exceed marshes’ ability to accrete vertically. Here, we assess the limits to marsh vulnerability by analyzing >780 Holocene reconstructions of tidal marsh evolution in Great Britain. These reconstructions include both transgressive (tidal marsh retreat) and regressive (tidal marsh expansion) contacts. The probability of a marsh retreat was conditional upon Holocene rates of RSLR, which varied between −7.7 and 15.2 mm/yr. Holocene records indicate that marshes are nine times more likely to retreat than expand when RSLR rates are ≥7.1 mm/yr. Coupling estimated probabilities of marsh retreat with projections of future RSLR suggests a major risk of tidal marsh loss in the twenty-first century. All of Great Britain has a >80% probability of a marsh retreat under Representative Concentration Pathway (RCP) 8.5 by 2100, with areas of southern and eastern England achieving this probability by 2040.

Citation

Horton, B., Shennan, I., Bradley, S., Cahill, N., Kirwan, M., Kopp, R., & Shaw, T. (2018). Predicting marsh vulnerability to sea-level rise using Holocene relative sea-level data. Nature Communications, 9, Article 2687. https://doi.org/10.1038/s41467-018-05080-0

Journal Article Type Article
Acceptance Date May 21, 2018
Online Publication Date Jul 12, 2018
Publication Date Jul 12, 2018
Deposit Date Jun 5, 2018
Publicly Available Date Mar 28, 2024
Journal Nature Communications
Publisher Nature Research
Peer Reviewed Peer Reviewed
Volume 9
Article Number 2687
DOI https://doi.org/10.1038/s41467-018-05080-0

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.






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