This study aims to evaluate the effects of soil management practices on SOC pools and microbial properties of Haplic Chernozem in the Rostov oblast. Soil under conventional tillage, no-till, and virgin steppe were studied. In the 0–5, 5–10, 10–20, and 30–40 cm layers, total organic carbon and the sizes of particulate and mineral-associated (C-MAOM) organic matter pools, isolated by particle-size fractionation, were determined. Microbial abundance, biomass, and taxonomic composition were assessed using quantitative real-time PCR and high-throughput sequencing. Compared with conventional tillage, no-till increased TOC content in the surface soil layer (0–5 cm) by 0.38
The damaging effects of oil pollution on oligotrophic peat bog soil (Rheic Fibric Histosol), as well as the patterns of its natural attenuation processes, were studied in a long-term field experiment with varying oil concentrations (oil product content from 11 to 45
This study examines the possibility for detecting bare soil surface (BSS), using remote sensing data and for applying this approach to model texture and total soil carbon in the topsoil. The study area comprises agricultural fields within the North Caucasus Federal Agricultural Research Center in the northeastern spurs of the Stavropol Upland. Landsat 5/8 imagery and spectral indices (NDVI, NBR2, and BSI) were used to classify BSS. Optimal discrimination of BSS from green and non-photosynthetic vegetation was achieved, using a BSI threshold of >0.18 (F1-score = 0.98). Spatial modeling of topsoil properties was conducted by comparing five regression models (Linear Regression, K-Nearest Neighbors, Random Forest, Extreme Gradient Boosting, and Cubist). A linear regression model demonstrated the highest performance; key predictors included the mean and standard deviation of SWIR2. The model exhibits strong predictive capability for sand, silt, clay, and total carbon (adjusted R 2 = 0.82, 0.75, 0.78, and 0.74, respectively). The topsoil is characterized by the range of clay content from 5 to 30
The study of the elemental composition of soils developing under minimal influence of anthropogenic activity (background reference soils) is of key importance for an objective assessment of the geochemical state of landscapes. In this paper, we consider the features of accumulation and vertical distribution patterns of a wide range of trace elements (V, Cr, Co, Ni, Cu, Zn, As, Sr, Pb), as well as manganese (in the form of MnO), in the profiles of chernozems within the specially protected natural areas of the Rostov region. The content of all the studied trace elements in the genetic horizons does not exceed the environmental norms (maximum and tentative permissible concentrations), and their average concentrations in the humus-accumulative horizon correspond to the regional geochemical background. The leading factor in geochemical differentiation of soils is the lithological features of parent rocks: statistically significant differences between chernozems on loesslike loams and on the eluvium of hard carbonate rocks are seen for 7 of 10 elements (p < 0.05), which is confirmed by the principal component analysis (50.3
Distribution patterns of arsenic (As) were studied in background tundra soils of the European northeast of Russia. Its content, differentiation in the vertical soil profiles, and accumulation factors in soils of different geneses were assessed. The total As content was determined using inductively coupled plasma atomic emission spectrometry, and GIS technologies were used to analyze its spatial distribution. It was found that As distribution in tundra soils is characterized by high spatial heterogeneity and is determined by the complex influence of soil physicochemical properties and landscape-geochemical conditions. Calculation of the geoaccumulation index (Igeo) confirmed that all the studied soils are uncontaminated. The upper 95
