Preprints
https://doi.org/10.5194/bg-2021-202
https://doi.org/10.5194/bg-2021-202

  27 Sep 2021

27 Sep 2021

Review status: this preprint is currently under review for the journal BG.

Testing the effect of bioturbation and species abundance upon discrete-depth individual foraminifera analysis

Bryan Lougheed1 and Brett Metcalfe2,3 Bryan Lougheed and Brett Metcalfe
  • 1Department of Earth Sciences, Uppsala University, Sweden
  • 2Department of Earth Sciences, Vrije Universiteit Amsterdam, the Netherlands
  • 3Laboratory of Systems and Synthetic Biology, Department of Agrotechnology and Food Sciences, Wageningen University & Research, the Netherlands

Abstract. We use a single foraminifera enabled, holistic hydroclimate-to-sediment transient modelling approach to fundamentally evaluate the efficacy of discrete-depth individual foraminifera analysis (IFA) for reconstructing past sea surface temperature (SST) variability from deep-sea sediment archives, a method that has been used for, amongst other applications, reconstructing El Niño Southern Oscillation (ENSO). The computer model environment allows us to strictly control for variables such as sea surface temperature (SST), foraminifera species abundance response to SST, as well as depositional processes such as sediment accumulation rate (SAR) and bioturbation depth (BD), and subsequent laboratory processes such as sample size and machine error. Examining a number of best-case scenarios, we find that IFA-derived reconstructions of past SST variability are sensitive to all of the aforementioned variables. Running 100 ensembles for each scenario, we find that the influence of bioturbation upon IFA-derived SST reconstructions, combined with typical samples sizes employed in the field, produces noisy SST reconstructions with poor correlation to the original SST distribution in the water. This noise is especially apparent for values near the edge of the SST distribution, which is the distribution region of particular interest for, e.g., ENSO. The noise is further increased in the case of increasing machine error, decreasing SAR and decreasing sample size. We also find poor agreement between ensembles, underscoring the need for replication studies in the field to confirm findings at particular sites and time periods. Furthermore, we show that a species’ abundance response to SST could in theory bias IFA-derived SST reconstructions, which can have consequences when comparing IFA-derived SST from markedly different mean climate states. We provide a number of idealised simulations spanning a number of SAR, sample size, machine error and species abundance scenarios, which can help assist researchers in the field to determine under which conditions they could expect to retrieve significant results.

Bryan Lougheed and Brett Metcalfe

Status: open (until 08 Nov 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Bryan Lougheed and Brett Metcalfe

Bryan Lougheed and Brett Metcalfe

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Short summary
Measurements on sea-dwelling shelled organisms called foraminifera retrieved from deep-sea sediment cores have been used to reconstruct sea surface temperature (SST) variation. To evaluate the method, we use a computer model to simulate millions of single foraminifera and how they become mixed in the sediment after being deposited on the sea floor. We compare the SST inferred from the single foraminifera in the sediment core to the true SST in the water, thus quantifying method uncertanties.
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