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Research in Antarctica is of great importance for understanding the Earth's climate system and the processes that drive it. This study evaluated the spatial distribution of glacial sediment properties on the Bellingshausen Dome or Collins Ice Cap (King George Island, Antarctica). The particle-size distribution, pH H2O, total organic carbon (TOC), mobile forms of ammonium nitrogen (N–NH4), potassium (K2O), and phosphorus (P2O5) were measured and then spatially modelled using regression kriging (RK) and ordinary kriging (OK) approaches. The terrain attributes (elevation, aspect, slope) derived from a digital elevation model with 10-m spatial resolution and distance from a coast were used as explanatory variables. Multiple linear regression models were fitted to describe the relationships between the covariates and properties. The performance of the models was evaluated by the mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), and Nash–Sutcliffe efficiency coefficient (NSE) indices. Overall, model performance statistics showed that RK models performed better than OK and the spatial patterns of some properties were closely related to the character of the glacier topography. Thus, the application of the RK method in combination with auxiliary environmental covariates improved the accuracy of spatial prediction. [ABSTRACT FROM AUTHOR]

Digital soil maps find application in numerous fields, making their accuracy a crucial factor. Mapping soil properties in homogeneous landscapes where the soil surface is concealed, as in forests, presents a complex challenge. In this study, we evaluated the spatial distribution of soil organic carbon stocks (SOCstock) under forest vegetation using three methods: regression kriging (RK), random forest (RF), and RF combined with ordinary kriging of residuals (RFOK) in combination with Sentinel-2A satellite data. We also compared their accuracies and identified key influencing factors. We determined that SOCstock ranged from 0.6 to 10.9 kg/m2 with an average value of 4.9 kg/m2. Among the modelling approaches, we found that the RFOK exhibited the highest accuracy (RMSE = 1.58 kg/m2, NSE = 0.33), while the RK demonstrated a lack of spatial correlation of residuals, rendering this method inapplicable. An analysis of variable importance revealed that the SWIR B12 band of the Sentinel-2A satellite contributed the most to RFOK predictions. We concluded that the RFOK hybrid approach outperformed the others, potentially serving as a foundation for digital soil mapping under similar environmental conditions. Therefore, it is essential to consider spatial correlations when mapping soil properties in ecosystems that are inaccessible for capturing the spectral response of the soil surface. [ABSTRACT FROM AUTHOR]

The paper discussed the influence of the forms of sediment accumulation on the surface of glaciers on their chemical and physicochemical properties. The materials sampled from the surface of five glaciers of the Svalbard Archipelago was analyzed. We studied such forms of sediment accumulation as dirt cones - the ice core covered with sediments and cryoconite holes - hollows on the glacier surface containing cryoconite material. Parameters such as total organic carbon content, microbiological activity, pH, the content of mobile forms of potassium and phosphorus, and concentrations of heavy and trace metals were studied. Also, mesomorphological studies were carried out and the polydisperse composition of the sediments was determined. According to the results of this work, it was found that the content of organic carbon in the material selected from dirt cones and cryoconite holes can be up to 2.5%, but the content of clay particles in it is mainly at the 10–15% level. Potassium concentrations are up to 250 mg/kg, and phosphorus is up to 800 mg/kg. The content of metals is typical or lower than in the previously published data. The main influence on the chemical composition of materials has a geographical factor of the sampling site, rather than the form of material accumulation. [ABSTRACT FROM AUTHOR]

Rapid deglaciation is one of the most important challenges in the Earth science today. One reason of this is specific supraglacial sediments — cryoconites, which represent carbon-containing dust with organomineral matter and living organisms. Investigation of physical and chemical characteristics of cryoconites in the Central Caucasus is necessary in order to understand their influence on alpine territories biogeochemical cycles, pollution and development in conditions of intensive glacial melting and active anthropogenic influence. For this research cryoconites as well as moraines, soil-like bodies and soils have been sampled from the alpine Bezengi Glacier and adjacent Khulamo-Bezengi Gorge. Key physicochemical features (pH values, total organic carbon content, microbial respiration, particle-size distribution) as well as content of trace elements have been defined in sampled materials and several pollution indices (Geoaccumulation index, Contamination factor and Degree of pollution) have been calculated. Results obtained show low values of total organic carbon in cryoconites (max. 0.23%) but high values (max. 7.54%) in top horizon of soils located in floodplain, indicating its active fluvioglacial transfer which may further accelerate the development of soils. Microbiological activity in the studied soils was mostly influenced by additional input of labile organic carbon from cryoconites with water flows. Particle-size distribution was similar among the studied cryoconites, indicating dominance of sand fraction (up to 85.28%) while studied soils showed higher variability due to influence of weathering. Among the trace elements, cryoconites were mostly polluted by Zn (max. 85.70 mg·kg−1) which corresponds to high pollution according to pollution indices; Pb (max. 24.90 mg·kg−1) and Cu (max. 17.40 mg·kg−1), up to moderate pollution level. Redistribution of polluted cryoconite material as well as local anthropogenic activities increased pollution of periglacial soils by Zn (max. 89.20 mg·kg−1), Pb (max. 15.00 mg·kg−1) and Cu (max. 12.80 mg·kg−1), which was also proven by the pollution indices with up to high level of pollution. [ABSTRACT FROM AUTHOR]