Erratics selection for cosmogenic nuclide exposure dating – an optimization approach

Abstract

The paper presents a method for the selection of large erratics to be sampled for terrestrial cosmogenic nuclide exposure dating (TCNED) in areas previously covered by Pleistocene ice sheets. Our approach is based on (1) a GIS analysis of an extensive dataset of erratics, (2) field inspection of pre-selected boulders and (3) Schmidt hammer (SH) testing of erratics selected for sampling. An initial database of 491 erratic boulders in NW Poland was filtered using a GIS software, based on their characteristics, digital elevation and surface geology. The secondary data set of pre-selected erratics consisted of 135 boulders – i.e. proper targets for field inspection. Ground-truthing in the field resulted in the final selection of 63 boulders suitable for sampling for TCNED. These erratics are located on moraine plateaux and hills formed during the Saalian glaciation (Marine Isotope Stage 6) as well as Leszno/Brandenburg, Poznań/Frankfurt and Pomeranian Phase ice marginal belts from the Weichselian glaciation (Marine Isotope Stage 2). The GIS desk-based analysis of erratics properties resulted in a 73% reduction of the initial dataset, which demonstrates the added value of this selection technique. The field inspection of pre-selected boulders resulted in a 53% reduction of the number of boulders suitable for TCNED. SH testing of the sampled erratics provided a quantitative proxy of their surface hardness. This allowed the quantification of their weathering degree and identification of erratics potentially affected by postglacial erosion. Our systematic approach to selecting erratics and their SH testing could be a useful tool for other researchers facing the problem of choosing appropriate erratics for TCNED in areas of continental Pleistocene glaciations.

The Local Last Glacial Maximum of the southern Scandinavian Ice Sheet front: Cosmogenic nuclide dating of erratics in northern Poland

“…1A). The region is large enough to find a considerable number of erratics suitable for TCN exposure dating (Tylmann et al, 2018) and to track the last SIS retreat from its maximum limit.…”

Geomorphological record and equilibrium line altitude of glaciers during the last glacial maximum in the Rodna Mountains (eastern Carpathians)

“…Similarly, anomalously “too young” 36 Cl ages (90–20 ka) were obtained for postulated penultimate glaciation moraines in the High Tatra Mountains (Dzierżek, 2009; see Kłapyta and Zasadni, 2018) and for 10 Be-dated moraines (63.5–38.8 ka) formed during the Saalian glaciation (MIS 6) in the Polish lowlands (Tylman et al, 2018). These facts indicate that the distribution of 10 Be exposure ages in the Rodna Mountains may highlight a common problem in the absolute dating of older Pleistocene moraines in temperate climates, where relatively humid conditions enhanced accelerated surface disintegration of the rock surface by chemical weathering and effective erosional processes.…”

Moraine crest or slope: An analysis of the effects of boulder position on cosmogenic exposure age

“…However, it is often challenging to assess landform stability based on geomorphological evidence alone. Our approach, in light of strong regional evidence for an inverse correlation between SH R-values and exposure ages for granitic surfaces (Tomkins et al, 2018a(Tomkins et al, , 2018b, indicates that preliminary SH sampling could be a useful method to assess landform stability, to identify boulders affected by post-depositional processes, and to prioritise individual boulders for analysis based on R-value clustering (Tylmann et al, 2018).…”

“…However, given that it is not possible to ascertain the underlying distribution a priori, a relatively large sample size is ultimately required. For most landforms, sampling a minimum of ∼30 boulders would be a reasonable approach to estimate a depositional age within 2σ (n ≥ 23), but more would be required (n ≥ 40) to improve precision to 1σ for complex datasets or if Schmidt hammer R-values were being used as a basis for cosmogenic nuclide sample selection (Tylmann et al, 2018). Collecting a minimum of 30 -40 samples is necessary to ensure a full understanding of the underlying age distribution, even for complex datasets.…”