Age-Heterogeneity in Marine Sediments Revealed by Three-Dimensional High-Resolution Radiocarbon Measurements

Abstract

Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from. However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions. To shed light on 1) the age-depth relationship and its full uncertainty, 2) the magnitude of mixing processes affecting the downcore proxy variations, and 3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle. Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( ∼ 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 × 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth. Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met. Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples. We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.

The Impact of Leaching on Radiocarbon Ages of Small-Sized Foraminifera Samples

“…Besides analytical precision, the beneficial effect of leaching is further limited by natural variability and sample heterogeneity. The standard deviation of the mean F 14 C values reported for young T. sacculifer replicate analyses greatly exceeded the analytical precision, highlighting that sample heterogeneity has a very large effect on the reliability of reported radiocarbon ages in line with findings by Dolman et al (2021) and Zuhr et al (2022). Dolman et al (2021) reported on replicate small-scale (3-30 tests of foraminifera) radiocarbon analyses and could show that due to bioturbation variance of the measured F 14 C means is a function of sample size (number of tests per sample) and sediment accumulation rate.…”

Testing the reliability of global surface temperature reconstructions of the last glacial cycle

“…Corrections from seasonally biased records have been suggested (e.g. Bova et al, 2021), but rely on assumptions that must be verified beforehand (Laepple et al, 2022).…”

Assessing Seasonal and Inter‐Annual Marine Sediment Climate Proxy Data

“…Even further, we should aim to quantitatively test our understanding of the proxy signal at different steps of the proxy formation. Replication inside one core allows to determine the variability due to measurement uncertainty and (sediment) archive heterogeneity (Zuhr et al., 2022). Comparison of different proxies for the same physical variable such as temperature measured in the same sample or core (Groeneveld et al., 2019; Ho & Laepple, 2015) allows to test the interpretation and attribution of the climate signal in the proxies.…”

“…Even further, we should aim to quantitatively test our understanding of the proxy signal at different steps of the proxy formation. Replication inside one core allows to determine the variability due to measurement uncertainty and (sediment) archive heterogeneity (Zuhr et al, 2022). Comparison of different The power spectral density of the tuned timeseries shows a clear peak at the annual frequency, whereas the original noise timeseries does not.…”