A chronological and palaeoenvironmental re‐evaluation of two loess‐palaeosol records in the northern Harz foreland, Germany, based on innovative modelling tools
The continuing development of analytical methods for investigating sedimentary records calls for iterative re‐examination of existing data sets obtained on loess‐palaeosol sequences (LPS) as archives of palaeoenvironmental change. Here, we re‐investigate two LPS (Hecklingen, Zilly) in the northern H...
Published in: | Boreas |
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Main Authors: | , , , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2021
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Subjects: | |
Online Access: | http://dx.doi.org/10.1111/bor.12510 https://onlinelibrary.wiley.com/doi/pdf/10.1111/bor.12510 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/bor.12510 |
Summary: | The continuing development of analytical methods for investigating sedimentary records calls for iterative re‐examination of existing data sets obtained on loess‐palaeosol sequences (LPS) as archives of palaeoenvironmental change. Here, we re‐investigate two LPS (Hecklingen, Zilly) in the northern Harz foreland, Germany, being of interest due to their proximity to the Scandinavian Ice Sheet (SIS) and the position between oceanic climatic influence further west and continental influence towards the east. First, we established new quartz OSL and polymineral IRSL chronologies. Both methods show concordant ages in the upper part of the Hecklingen profile (~20–40 ka), but in the lower part IRSL underestimates OSL ages by up to ~15 ka for the period 40–60 ka. Interpretations hence refer to the OSL data set. Second, we applied Bayesian age‐depth modelling to data sets from Hecklingen to resolve inversions in the original ages, also reducing averaged 1σ uncertainty by ~19% (OSL) and ~12% (IRSL). Modelled chronologies point out phases of increased (MIS 2, early MIS 3) and reduced (middle and late MIS 3) sedimentation, but interpretation of numerical rates is problematic because of intense erosion and slope wash particularly during MIS 3. Finally, previously obtained grain‐size data were re‐investigated by end member modelling analyses. Three fundamental grain‐size distributions (loadings) explain the measured data sets and offer information on intensity and – combined with modelled OSL ages – timing of geomorphic processes. We interpret the loadings to represent (i) primary loess accumulation, (ii) postdepositional pedogenesis and/or input of aeolian fine fractions, and (iii) input of coarse aeolian material and/or slope wash. The applied modelling tools facilitate detailed understanding of site‐formation through time, allowing us to correlate a strong peak in mean grain size at ~26–24 ka to the maximum extent of the SIS and increased influence of easterly winds. |
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