Influence of Foraminifera Count Size and Rare Species on Transfer Function Results Used in Sea-Level Reconstructions

Abstract

Abstract Salt-marsh foraminifera have been instrumental in the production of quantitative high-resolution Holocene relative sea-level reconstructions using both traditional and Bayesian transfer function approaches. To produce the most accurate and precise elevation estimates using a transfer function, the influence of the particular input data must be understood. Here, we used a foraminifera dataset from New Jersey to examine how count size and rare species affect elevation estimates generated by a Bayesian transfer function. We found that increasing count size can reduce elevation estimate uncertainties, but increasing or decreasing total counts does not have a consistent influence on the estimates themselves. Further, the inclusion or exclusion of rare species do not have consistent trends; however, the results vary by location, highlighting the significance of unique foraminiferal assemblages. Finally, we found that count sizes of 60–80 tests minimizes elevation estimate uncertainties and any greater counts will not contribute to further reduced uncertainties.