Reevaluating the wave power-salt marsh retreat relationship
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Published version
Date
2023-02-01
Authors
Houttuijn Bloemendaal, Lucila
Hughes, Zoe
FitzGerald, Duncan
Novak, Alyssa
Georgiou, Ioannis
Version
Published version
OA Version
Citation
L. Houttuijn Bloemendaal, Z. Hughes, D. FitzGerald, A. Novak, I. Georgiou. 2023. "Reevaluating the wave power-salt marsh retreat relationship" Scientific Reports, Volume 13, Issue 1, pp.2884-2884. https://doi.org/10.1038/s41598-023-30042-y
Abstract
Salt marshes are threatened by rising sea levels and human activities, and a major mechanism of marsh loss is edge retreat or erosion. To understand and predict loss in these valuable ecosystems, studies have related erosion to marsh hydrodynamics and wave characteristics such as wave power. Across global studies, erosion is reported to be largely linearly related to wave power, with this relationship having implications for the resilience of marshes to extreme events such as storms. However, there is significant variability in this relationship across marshes because of marsh heterogeneity and the uniqueness of each physical setting. Here, we investigate the results of individual studies throughout the world that report a linear relationship and add a new dataset from the Great Marsh in Massachusetts (USA). We find that most marsh wave power and erosion data are not normally distributed and when these datasets are properly plotted to account for their distributions, the resulting relationships vary from previously published curves. Our Great Marsh data suggest that events from specific wind directions can have an outsized impact on edge erosion due to their larger fetch and wind speeds. We also find that factors other than wave attack such as edge erosion along tidal channels, can have a measurable impact on retreat rates. We show the importance of maintaining statistical assumptions when performing regressions, as well as emphasize the site-specificity of these relationships. Without calibration of a marsh erosion-wave power relationship using robust regressions for each individual marsh, such a relationship is not fully constrained, resulting in unreliable predictions of future marsh resilience and response to climate change.
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© The Author(s) 2023. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http:// creativecommons. org/ licenses/ by/4. 0/.