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Helena Alexandersson

Helena Alexanderson

Professor

Helena Alexandersson

Thin loess in Southwestern Sweden

Författare

  • Anna Hedeving
  • Fanny Ekström
  • Mark D. Johnson
  • Helena Alexanderson
  • Yunus Baykal
  • Thomas Stevens

Summary, in English

A thin (20–80 cm), patchy layer of silt-rich sediment occurs at the surface throughout Svartedalen, a nature reserve 30 km north of Gothenburg, Sweden. This surface silt mantles a bedrock-dominated, fracture-valley landscape. Using data from grain-size analysis, OSL dating and detrital-zircon U-Pb dating, we argue that the silt is loess sourced from glacial sediment that was eroded from local bedrock. The sediment has a grain-size distribution typical of wind-blown silt and is especially similar to thin deposits of loess overlying coarser material. OSL ages on five samples range from 1 to 8 ka, although analysis of equivalent dose distributions of one may suggest an age as old as 11 ka. The dates may represent true depositional ages and represent several Holocene eolian events. However, we consider as more likely that the loess was deposited during deglaciation, and quartz-grain signals have been partially reset during bioturbation. U-Pb ages on 273 zircon grains from the loess show prominent peaks at 1.6 and 1.8 Ga, as well as smaller numbers of grains from 1.0 to 1.6 Ga. These ages match dates from the Idefjord Terrane which comprises the bedrock of the study area. We argue that during ice-margin retreat, debris in the glacier was dominated by locally derived debris. This glacial sediment was left in thin patches uplands and particularly in large ice-marginal deltas. These deposits served as the proximal source for the loess. The presence of thin loess in Svartedalen suggests loess to be common in soils of southwest Sweden.

Avdelning/ar

  • Kvartärgeologi

Publiceringsår

2024

Språk

Engelska

Sidor

182-201

Publikation/Tidskrift/Serie

GFF

Volym

145

Issue

3-4

Dokumenttyp

Artikel i tidskrift

Förlag

Taylor & Francis

Ämne

  • Geology

Nyckelord

  • artificial neural networks
  • Computer virus propagation
  • Levenberg Marquardt backpropagation
  • MSE
  • SEIRQ model

Aktiv

Published

ISBN/ISSN/Övrigt

  • ISSN: 1103-5897