Mg∕Ca, Sr∕Ca and stable isotopes from the planktonic foraminifera T. sacculifer : testing a multi-proxy approach for inferring paleotemperature and paleosalinity

• Published in: Biogeosciences
• Main Authors: D. Dissard, G. J. Reichart, C. Menkes, M. Mangeas, S. Frickenhaus, J. Bijma
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: Ecology; QH540-549.5; Life; QH501-531; Geology; QE1-996.5; Planktonic foraminifera
• Online Access: https://doi.org/10.5194/bg-18-423-2021; https://doaj.org/article/179860bb551944d0aec27c0f88bd3dc3

Over the last decades, sea surface temperature (SST) reconstructions based on the Mg∕Ca of foraminiferal calcite have frequently been used in combination with the δ 18 O signal from the same material to provide estimates of the δ 18 O of water ( δ 18 O w ), a proxy for global ice volume and sea surface salinity (SSS). However, because of error propagation from one step to the next, better calibrations are required to increase the accuracy and robustness of existing isotope and element to temperature proxy relationships. Towards that goal, we determined Mg∕Ca , Sr∕Ca and the oxygen isotopic composition of Trilobatus sacculifer (previously referenced as Globigerinoides sacculifer ) collected from surface waters (0–10 m) along a north–south transect in the eastern basin of the tropical and subtropical Atlantic Ocean. We established a new paleotemperature calibration based on Mg∕Ca and on the combination of Mg∕Ca and Sr∕Ca . Subsequently, a sensitivity analysis was performed in which one, two or three different equations were considered. Results indicate that foraminiferal Mg∕Ca allows for an accurate reconstruction of surface water temperature. Combining equations, δ 18 O w can be reconstructed with a precision of about ± 0.5 ‰. However, the best possible salinity reconstruction based on locally calibrated equations only allowed for a reconstruction with an uncertainty of ± 2.49. This was confirmed by a Monte Carlo simulation, applied to test successive reconstructions in an “ideal case” in which explanatory variables are known. This simulation shows that from a purely statistical point of view, successive reconstructions involving Mg∕Ca and δ 18 O c preclude salinity reconstructions with a precision better than ± 1.69 and hardly better than ± 2.65 due to error propagation. Nevertheless, a direct linear fit to reconstruct salinity based on the same measured variables ( Mg∕Ca and δ 18 O c ) was established. This direct reconstruction of salinity led to a much better estimation of salinity ( ± 0.26) than the ...