Assessing sea-level data from Connecticut, USA, using a foraminiferal transfer function for tide level

Concerns surrounding possible future climate change, sea level rise, and their potential impacts on coastal environments, have stimulated research seeking to elucidate the relationship between ocean levels and climate at the (sub)century-scale. The need for increasingly precise reconstructions of relative sea-level change has, in-turn, driven the development of new methodologies capable of resolving fine-scale variability within salt-marsh sedimentary sequences. The use of salt-marsh foraminifera as precise indicators of past tide levels has played a central role in this process and is exemplified by a number of detailed studies conducted in Connecticut, USA. In this paper, we apply the most recent methodological advance in the reconstruction of relative sea-levels using salt-marsh foraminifera. We develop a foraminiferal transfer function for tide level, derived from the modern foraminiferal distributions of four Connecticut salt-marshes. In contrast to existing approaches that employ site-specific interpolations of local vertical foraminiferal assemblage zones, this transfer function can provide objective, quantitative and reproducible estimates of palaeomarsh-surface elevation with explicitly stated error terms for marshes throughout Connecticut, irrespective of differences in tidal range. We demonstrate the foraminiferal transfer function approach by employing it to reconstruct changes in palaeomarsh-surface elevation from three cores recovered from Hammock River marsh, Connecticut. The resulting reconstructions, which are precise to ±0.09 m, are tested using an independent dataset from the neighbouring state of Maine, and are used to assess a pivotal record of mean high water (MHW) change from this site. We conclude that the transfer function reconstructions show good general agreement with previous records of palaeomarsh-surface elevation, but with the advantages of quantified error terms and a transparent, reproducible methodology. This replicability will assist in the comparison or combination of local records of MHW change to infer large-scale, regional sea-level variations.