MURAL - Maynooth University Research Archive Library



    Incorporating temporal and spatial variability of salt-marsh foraminifera into sea-level reconstructions


    Walker, Jennifer S., Cahill, Niamh, Khan, Nicole S., Shaw, Timothy A., Barber, Don, Miller, Kenneth G., Kopp, Robert E. and Horton, Benjamin P. (2020) Incorporating temporal and spatial variability of salt-marsh foraminifera into sea-level reconstructions. Marine Geology, 429 (106293). ISSN 0025-3227

    [thumbnail of NC-salt-marsh-foraminifera-2020.pdf]
    Preview
    Text
    NC-salt-marsh-foraminifera-2020.pdf

    Download (10MB) | Preview

    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.
    Item Type: Article
    Additional Information: © 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/). Cite as: Jennifer S. Walker, Niamh Cahill, Nicole S. Khan, Timothy A. Shaw, Don Barber, Kenneth G. Miller, Robert E. Kopp, Benjamin P. Horton, Incorporating temporal and spatial variability of salt-marsh foraminifera into sea-level reconstructions, Marine Geology, Volume 429, 2020, 106293, ISSN 0025-3227, https://doi.org/10.1016/j.margeo.2020.106293. (https://www.sciencedirect.com/science/article/pii/S002532272030181X)
    Keywords: Foraminifera; Salt marsh; Transfer function; Relative sea level;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15530
    Identification Number: 10.1016/j.margeo.2020.106293
    Depositing User: Niamh Cahill
    Date Deposited: 18 Feb 2022 14:56
    Journal or Publication Title: Marine Geology
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/15530
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only (login required)

    Item control page
    Item control page

    Downloads

    Downloads per month over past year

    Origin of downloads