Hülscher, J., Sobel, E., Kallnik, N., Hoffmann, E., Millar, I., Hartmann, K. & Bernhardt, A. (2022). Apatites Record Sedimentary Provenance Change 4–5 Myrs Before Clay in the Oligocene/Miocene Alpine Molasse. Frontiers in Earth Science, 10:914409. doi: 10.3389/feart.2022.914409

Hülscher et al. (2022) investigate the sedimentary provenance of a Oligocene/Miocene basin in the Eastern European Alps and its response to a change in tectonic signal at around 28 Ma (tectonically induced exhumation of the Tauern Window metamorphic dome). The sedimentary record of apatite single-grain distributions and bulk-rock clay-sized fraction is investigated. Focus lies on a possible delay in the recording of the provenance change depending on the grain-size fraction and the implications for processes in the sediment-routing system.

This section will focus on the Nd isotope analyses in the clay-sized fraction and the conducted Monte Carlo simulation for estimating the sample mean and testing an observed shift in \(\varepsilon\)Nd values. For further details on the sand-sized apatite single-grain analysis and the interpretations please look into the original paper. The analyzed data is available in the Supplementary Material.

Method

The clay-sized fraction was separated from thirty drill-cutting samples and analyzed for the Nd isotopic composition. Normalized ¹⁴³Nd/¹⁴⁴Nd ratios are reported in \(\varepsilon\)Nd notation (DePaolo and Wasserburg, 1976) with \(2\sigma\) uncertainties.

As depicted by the following Figure, the five youngest samples (above 1420 m) show higher \(\varepsilon\)Nd values (mean: −9.12 ± 0.54) than the remaining older 25 samples (mean: −9.67 ± 0.52):

Results of the Nd isotope analysis of clay-sized samples (Figure 6, Hülscher et al. (2022). Used under a Creative Commons Attribution 4.0 International License / Clipped from original).

In order to test for significance of this shift in Nd isotope composition a Monte Carlo simulation was conducted. For each measurement random samples with n=10000 were drawn from a normal distribution with the according \(\varepsilon\)Nd (mean) and \(2\sigma\) (standard deviation) values. Then the distribution of means for younger (<19 Ma) and older (>19 Ma) subsamples were tested for normality, variance homogeneity and a Welch two sample t-test conducted.

Results

The distribution of the sample means generated by the Monte Carlo simulation are normally distributed for both, older and younger, samples:

Mean distributions for older (gray) and younger (blue) sediments resulting from the Monte Carlo simulation (Figure 6, Hülscher et al. (2022). Used under a Creative Commons Attribution 4.0 International License / Clipped from original).

The test for variance homogeneity indicates that heteroscedasticity has to be assumed for the t-test. Finally, the results of the Welch two sample t-test show that \(\varepsilon\)Nd mean values of the younger sediments are significantly (95 %) higher than \(\varepsilon\)Nd values of the older sediments. Thus, the two subsamples are assumed to be significantly different and interpreted as marking a change in clay-sized provenance.

In connection with the other sedimentary analysis results the clay-sized fraction are interpreted as recording the provenance change 4–5 Myrs later (at 19 Ma) than the apatite single-grain (at 23.3 Ma). This delay is explained by the different contributions to the distributions. While bulk-rock methods average out basin-wide erosion rates, single-grain distributions can reflect locally high erosion rates and preserve extreme values. These results deliver valuable information on environmental signal propagation and the extent of perturbations affecting the sediment-routing system.

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Citation

The E-Learning project SOGA-R was developed at the Department of Earth Sciences by Kai Hartmann, Joachim Krois and Annette Rudolph. You can reach us via mail by soga[at]zedat.fu-berlin.de.

You may use this project freely under the Creative Commons Attribution-ShareAlike 4.0 International License.

Please cite as follow: Hartmann, K., Krois, J., Rudolph, A. (2023): Statistics and Geodata Analysis using R (SOGA-R). Department of Earth Sciences, Freie Universitaet Berlin.