Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157204
Title: Incorporating temporal and spatial variability of salt-marsh foraminifera into sea-level reconstructions
Authors: Walker, Jennifer S.
Cahill, Niamh
Khan, Nicole S.
Shaw, Timothy Adam
Barber, Don
Miller, Kenneth G.
Kopp, Robert E.
Horton, Benjamin Peter
Keywords: Science::Geology
Issue Date: 2020
Source: Walker, J. S., Cahill, N., Khan, N. S., Shaw, T. A., Barber, D., Miller, K. G., Kopp, R. E. & Horton, B. P. (2020). Incorporating temporal and spatial variability of salt-marsh foraminifera into sea-level reconstructions. Marine Geology, 429, 106293-. https://dx.doi.org/10.1016/j.margeo.2020.106293
Project: MOE2018-T2-1-030 
Journal: Marine Geology 
Abstract: Foraminifera from salt-marsh environments have been used extensively in quantitative relative sea-level reconstructions due to their strong relationship with tidal level. However, the influence of temporal and spatial variability of salt-marsh foraminifera on quantitative reconstructions remains unconstrained. Here, we conducted a monitoring study of foraminifera from four intertidal monitoring stations in New Jersey from high marsh environments over three years that included several extreme weather (temperature, precipitation, and storm surge) events. We sampled four replicates from each station seasonally (four times per year) for a total of 188 samples. The dead foraminiferal assemblages were separated into four site-specific assemblages. After accounting for systematic trends in changes in foraminifera over time among stations, the distribution of foraminiferal assemblages across monitoring stations explained ~87% of the remaining variation, while ~13% can be explained by temporal and/or spatial variability among the replicate samples. We applied a Bayesian transfer function to estimate the elevation of the four monitoring stations. All samples from each station predicted an elevation estimate within a 95% uncertainty interval consistent with the observed elevation of that station. Combining samples into replicate- and seasonal-aggregate datasets decreased elevation estimate uncertainty, with the greatest decrease in aggregate datasets from Fall and Winter. Information about the temporal and spatial variability of modern foraminiferal distributions was formally incorporated into the Bayesian transfer function through informative foraminifera variability priors and was applied to a Common Era relative sea-level record in New Jersey. The average difference in paleomarsh elevation estimates and uncertainties using an informative vs uninformative prior was minimal (<0.01 m and 0.01 m, respectively). The dead foraminiferal assemblages remained consistent on temporal and small spatial scales, even during extreme weather events. Therefore, even when accounting for variability of modern foraminifera, foraminiferal-based relative sea-level reconstructions from high marsh environments remain robust and reproducible.
URI: https://hdl.handle.net/10356/157204
ISSN: 0025-3227
DOI: 10.1016/j.margeo.2020.106293
Rights: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
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