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Variability in Neogloboquadrina pachyderma stable isotope ratios from isothermal conditions: implications for individual foraminifera analysis
Jonkers, L.; Brummer, G.-J. A.; Meilland, J.; Groeneveld, J.; Kucera, M. (2022). Variability in Neogloboquadrina pachyderma stable isotope ratios from isothermal conditions: implications for individual foraminifera analysis. Clim. Past 18(1): 89-101. https://dx.doi.org/10.5194/cp-18-89-2022
In: Climate of the Past. Copernicus: Göttingen. ISSN 1814-9324; e-ISSN 1814-9332, meer
Peer reviewed article  

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  • Jonkers, L.
  • Brummer, G.-J. A., meer
  • Meilland, J.
  • Groeneveld, J.
  • Kucera, M.

Abstract

    Individual foraminifera analysis (IFA) holds promise to reconstruct seasonal to interannual oceanographic variability. Even though planktonic foraminifera are reliable recorders of environmental conditions on a population level, whether they also are on the level of individuals is unknown. Yet, one of the main assumptions underlying IFA is that each specimen records ocean conditions with negligible noise. Here we test thisassumption using stable isotope data measured on groups of four shells of Neogloboquadrina pachyderma from a 16–19 d resolution sediment trap time series from the subpolar North Atlantic. We find a within-samplevariability of 0.11 ‰ and 0.10 ‰ for δ18O and δ13C respectively that shows no seasonal pattern and exceeds water column variability in spring when conditions are homogeneous down to hundreds of metres. We assess the possible effect of life cyclecharacteristics and delay due to settling on foraminifera δ18O variability with simulations using temperature and δ18Oseawater as input. These simulations indicate that the observed δ18O variability can onlypartially be explained by environmental variability. IndividualN. pachyderma are thus imperfect recorders of temperature and δ18Oseawater. Based on these simulations, we estimate the excess noise on δ18O to be 0.11±0.06 ‰. The origin and nature of the recording imprecision require further work, but our analyses highlight the need to take such excess noise into account when interpreting the geochemical variability among individual foraminifera.


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