Proximal surface pedogeophysical characterization in Maritime Antarctica: assessing pedogeomorphological, periglacial, and landform influences

Abstract. Maritime Antarctica (M.A.) contains the most extensive and diverse lithological exposure compared to the entire continent. This lithological substrate reveals a rich history encompassing lithological, pedogeomorphological, and glaciological aspects of M.A., all of with are influenced by periglacial processes. Although pedogeophysical surveys can detect and provide valuable information to understand Antarctic lithologies and their history, such surveys are scarce on this continent and, in practice, almost non-existent. In this sense, we conducted a pioneering and comprehensive γ-spectrometric (natural radioactivity) and magnetic susceptibility (κ) survey on various igneous rocks. This study aimed to improve the geoscientific understanding of periglacial and pedogeomorphological processes in Keller Peninsula by integrating radiometric and magnetic data with advanced spatial analysis. It investigates the spatial variability of natural radiouclides and magnetic susceptibility across different substrates, evaluates a machine learning approach for data modelling, and interprets γ-ray and κ maps to reveal soil and landscape-forming processes. For that, we used proximal γ-spectrometric and κ data in different lithological substrates associated to terrain attributes. The pedogeophysical variables were collected in the field from various lithological substrates, by use field portable equipment. The pedogeophysical variables were collected in the field from various lithological substrates using portable equipment. These variables, combined with relief data and lithology, served as input data for modeling to predict and spatially map the content of radionuclides and κ by random forest algorithm (RF). In addition, we use nested-LOOCV as a form of external validation in a geophysical data with a small number of samples, and the error maps as evaluation of results. The RF algorithm successfully generated detailed maps of γ-spectrometric and κ variables. The distribution of radionuclides and ferrimagnetic minerals was influenced by morphometric variables. Nested-LOOCV method evaluated algorithm performance accurately with limited samples, generating robust mean maps. The highest thorium levels were observed in elevated, flat, and west beach areas, where detrital materials from periglacial erosion came through fluvioglacial channels. Lithology and pedogeomorphological processes-controlled thorium contents. Steeper areas formed a ring with the highest uranium contents, influenced by lithology and geomorphological-periglacial processes (rock cryoclasty, periglacial erosion, and heterogeneous deposition). Felsic rocks and areas less affected by periglacial erosion had the highest potassium levels, while regions with sulfurization-affected pyritized-andesites near fluvioglacial channels showed the lowest potassium contents. Lithology and pedogeochemical processes governed potassium levels. The κ values showed no distinct distribution pattern. Hydrothermal alteration affected the pyritized andesites, with heat and magmatic fluids driving iron enrichment and the formation of hydrothermal magnetite, which in turn led to elevated κ values. Conversely, Cryosol areas, experiencing freezing and thawing activity, had the lowest κ values due to limited ferrimagnetic mineral formation. In regions characterized by diverse terrain attributes and abundant active and intense periglacial processes, the spatial distribution of geophysical variables does not reliably reflect the actual lithological composition of the substrate. The complex interplay of various periglacial processes in the area, along with the morphometric features of the landscape, leads to the redistribution, mixing, and homogenization of surface materials, contributing to the inaccuracies in the predicted-spatialized geophysical variables.