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.
Highlights
High-resolution relative sea-level (RSL) reconstructions from saltmarsh proxies have extended the historical record of sea level to before the instrumental period of the 19th and 20th centuries (e.g. Varekamp et al, 1992; Gehrels, 2000; Kemp et al, 2013, 2017a)
The maximum total counts of foraminifera were found in the last sampling date, Summer of Year 3, when a total of 7552 dead foraminifera were identified from the four replicates
The dead foraminiferal distributions from the high marsh and high marsh-upland transition monitoring stations in the Mullica River-Great Bay estuary are similar to other studies in New Jersey and on the U.S Atlantic coast (e.g. Culver et al, 1996; Hippensteel et al, 2000; Kemp et al, 2009, 2011)
Summary
High-resolution relative sea-level (RSL) reconstructions from saltmarsh proxies (e.g. foraminifera, diatoms, flora) have extended the historical record of sea level to before the instrumental period of the 19th and 20th centuries (e.g. Varekamp et al, 1992; Gehrels, 2000; Kemp et al, 2013, 2017a). Salt-marsh for aminifera have been found to vary temporally on seasonal and inter annual timescales (Buzas et al, 2002; Hippensteel et al, 2002; Martin et al, 2002; Horton and Edwards, 2003; Horton and Murray, 2006; Berkeley et al, 2008), as well as spatially at small (sub-meter) scales (Buzas, 1968; Swallow, 2000; Morvan et al, 2006; Kemp et al, 2011) These variations have been shown to affect elevation boundaries of foraminiferal zones by as much as 15% of the tidal range Such temporal and spatial variability has not been formally quantified in transfer functions used for RSL reconstructions
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