Nonlinear Patterns of Surface Elevation Change in Coastal Wetlands: the Value of Generalized Additive Models for Quantifying Rates of Change

In the face of accelerating climate change and rising sea levels, quantifying surface elevation change dynamics in coastal wetlands can help to develop a more complete understanding of the implications of sea-level rise on coastal wetland stability. The surface elevation table-marker horizon (SET-MH...

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Bibliographic Details
Published in:Estuaries and coasts 2024-11, Vol.47 (7), p.1893-1902
Main Authors: Feher, Laura C., Osland, Michael J., Johnson, Darren J., Grace, James B., Guntenspergen, Glenn R., Stewart, David R., Coronado-Molina, Carlos, Sklar, Fred H.
Format: Article
Language:English
Subjects:
Climate change
Climate models
Coastal marshes
Coastal Sciences
Earth and Environmental Science
Ecology
Environment
Environmental Management
Freshwater & Marine Ecology
Generalized linear models
Mangrove swamps
Mangroves
Nonlinear dynamics
Regression analysis
Regressions
Sea level
Sea level changes
Sea level rise
Special Issue: Wetland Elevation Dynamics
Statistical models
Surface stability
Water and Health
Water quality
Wetlands
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Summary:In the face of accelerating climate change and rising sea levels, quantifying surface elevation change dynamics in coastal wetlands can help to develop a more complete understanding of the implications of sea-level rise on coastal wetland stability. The surface elevation table-marker horizon (SET-MH) approach has been widely used to quantify and characterize surface elevation change dynamics in coastal marshes and mangrove forests. Whereas past studies that utilized the SET-MH approach have most often quantified rates of surface elevation change using simple linear regression analyses, several recent studies have shown that elevation patterns can include a diverse combination of linear and non-linear patterns. Generalized additive models (GAMs) are an extension of generalized linear models (GLMs) that have previously been used to analyze a variety of complex ecological processes such as cyclical changes in water quality, species distributions, long-term patterns in wetland area change, and palaeoecological time series. Here, we use long-term SET data to demonstrate the value of generalized additive models for analyzing non-linear patterns of surface elevation change in coastal wetlands. Additionally, we illustrate how the GAM approach can be used to effectively quantify rates of elevation change at both landscape- and local site-level scales.
ISSN:1559-2723
1559-2731
DOI:10.1007/s12237-023-01268-w