EGU25-10974, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-10974
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 30 Apr, 08:30–10:15 (CEST), Display time Wednesday, 30 Apr, 08:30–12:30
 
Hall X3, X3.79
Using modern associations of microfauna to improve local relative sea-level reconstructions – a local transfer function for the Shetland Islands (UK)
Juliane Scheder1,2, Sue Dawson3, Thomas Goovaerts1, Max Engel4, Pedro Costa5,6, Maarten Van Daele7, Rikza Nahar7,8, Marc De Batist7, and Vanessa M.A. Heyvaert1,7
Juliane Scheder et al.
  • 1Royal Belgian Institute of Natural Sciences, Geological Survey of Belgium, Brussels, Belgium (jscheder@naturalsciences.be)
  • 2Institute of Geography, University of Cologne, Cologne, Germany
  • 3Geography and Environmental Science, University of Dundee, Dundee, UK
  • 4Institute of Geography, Heidelberg University, Heidelberg, Germany
  • 5Department of Earth Sciences, University of Coimbra, Coimbra, Portugal
  • 6Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
  • 7Renard Centre of Marine Geology, Department of Geology, Ghent University, Ghent, Belgium
  • 8Faculty of Industrial Technology, Sumatera Institute of Technology, South Lampung, Indonesia

High-resolution relative sea-level (RSL) reconstructions are important for managing coastal-protection challenges and for a complete hazard assessment. For the determination of palaeo-tsunami run-up heights in the Shetland Islands, United Kingdom, within the NORSEAT Project (Storegga and beyond – North Sea tsunami deposits offshore Shetland Islands), reconstructions of the RSL far beyond existing data are crucial. Existing RSL data are limited to two time periods (ca. 7900–5990 cal BP and around 3500 cal BP) and extrapolation of these data leads to a large vertical error (±8 m around the time of the Storegga tsunami). More detailed Holocene RSL reconstructions shall be enabled by a combined modern training set of foraminifers and ostracods from three different voes of Shetlands largest island, Mainland. A RSL transfer function, which relates the elevation, hence the duration of water coverage, of surface samples to the modern microfaunal associations, will be derived from the training set. This transfer function will be a valuable tool for high-resolution RSL reconstructions from the Holocene stratigraphic record around the Shetland Islands.

44 surface samples were collected from three salt marshes and adjacent tidal flats (southern Dales Voe, Dury Voe and northern Dales Voe). Most salt-marsh samples contain exclusively agglutinated foraminifers, with lower occurrences in the upper marsh, whereas in a small pond with permanent water coverage (Dury Voe), also calcareous foraminifers and living ostracods where found. Abundances decrease in most tidal-flat samples, with coarser areas almost void of microfauna, and increase again towards the low-tide and subtidal level. Aside from the investigation of the microfaunal distribution, analyses of environmental parameters like the grain-size distribution and the carbonate and organic matter content are still in progress. Multivariate statistics will determine the main influencing factor of the microfauna distribution between these environmental proxies and the elevation relative to mean sea level.

The final transfer function will be applied to Holocene deposits from offshore cores around Shetland that were conducted within the NORSEAT Project. The resulting new RSL reconstructions will enable a more accurate determination of run ups of the currently identified palaeo-tsunamis (Storegga and two younger events).

How to cite: Scheder, J., Dawson, S., Goovaerts, T., Engel, M., Costa, P., Van Daele, M., Nahar, R., De Batist, M., and Heyvaert, V. M. A.: Using modern associations of microfauna to improve local relative sea-level reconstructions – a local transfer function for the Shetland Islands (UK), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10974, https://doi.org/10.5194/egusphere-egu25-10974, 2025.