A foraminiferal-based transfer function: Implications for sea-level studies

A dataset consisting of 165 contemporary foraminiferal samples and associated tide level information was compiled by combining data from ten intertidal study areas situated on the east, south and west coasts of the UK, The relationship between the foraminiferal data and a series of environmental variables (elevation, pH, salinity, substrate and vegetation cover) are examined using canonical correspondence analysis (CCA) and partial CCA, To facilitate comparisons between study areas with different tidal ranges, the elevational data are expressed as a standardised water level index (SWLI), The foraminiferal distributions show a strong and highly statistically significant relationship with SWLI. A predictive transfer function has been developed for SWLIs using weighted averaging calibration with inverse and classical deshrinking regression (inverse r(jack)(2) = 0.74; classical r(jack)(2) = 0.75). Statistical measures assessing the performance of this model suggest that reliable reconstructions of former sea levels are possible. The transfer function has important implications for establishing continuous records of relative sea-level change or sedimentation.