Quantifying the potential bias of planktonic foraminifera-based temperature reconstructions using a numerical foraminifera-assemblage model

PhD student: Igaratza Fraile Ugalde
Project partners:
Bremen: Michael Schulz, Stefan Mulitza
Amsterdam: Gerald Ganssen

The objective of this study is to quantify the potential bias of foraminifera-based sea-surface temperature estimates due to climate-change induced variations in the seasonal succession of the planktonic foraminifera typically used in transfer functions. To study the seasonal succession of planktonic foraminifera species, we propose to develop a foraminifera module to be coupled to an existing marine ecosystem model (Moore et al., 2002). This ecosystem model has been successfully implemented on our Linux-cluster. The foraminifera module will take information from the ecosystem model (e. g. “food type”, zooplankton flux) and from an ocean circulation model (e.g. temperature, mixed-layer depth) to predict the species composition of foraminifera assemblages. Information on flux and ecological preferences of planktonic foraminifera is available from a global set of moored sediment traps on a weekly to monthly basis from the main hydrographic provinces of the present-day ocean. This data set has been used to decipher the ecological preferences of foraminifera species (optimum conditions and sensitivity) with respect to temperature, stratification and food supply (Zaric et al., in prep.).

The main tasks of the Ph.D. candidate are:

1. To implement a numerical foraminifera-assemblage model based on the existing set of parameterizations (Zaric et al., in prep.) and to couple this model to the existing marine ecosystem model.
2. To carry out a series of sensitivity experiments to optimize the model parameters such that an optimal match between observed and modeled modern sea-floor assemblage of planktonic foraminifera is achieved.

To conduct sensitivity experiments that allow for the quantification of the potential bias of foraminifera-based sea-surface temperature estimates linked to differential seasonality of the foraminifera. Experiments will be carried out for modern and last-glacial-maximum conditions. Glacial environmental conditions are derived from available model results (Paul and Schäfer-Neth, 2003). This task includes an assessment of the potential bias in faunal temperature as well as in isotopic and trace-element estimates.