Michael Osland Darren Johnson James Grace Glenn R. Guntenspergen David R. Stewart Carlos A. Coronado-Molina Fred H. Sklar Laura Feher 2024 <div id="Abs1-section" class="c-article-section"><div id="Abs1-content" class="c-article-section__content"><p>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.</p></div></div> application/pdf 10.1007/s12237-023-01268-w en Springer Nonlinear patterns of surface elevation change in coastal wetlands: The value of generalized additive models for quantifying rates of change article