Dataset on chemical properties, macro and micromorphological features of forest - steppe native soils in 2022 (Oka-Don plane)

Published: 23 November 2023| Version 1 | DOI: 10.17632/9j7rkbphsv.1
Danila Bardashov


This dataset contains data from two soil pits (S1 and S2) in the Tokarevsky district, Tambov region, Russian Federation. The pits have been classified as Albic Mollic Gleyic Stagnosol (S1) and Gleyic Chernozem (S2). The data on soil physical and chemical properties include pH levels, soluble salts content, oxalate and dithionite extractable iron content, grain size distribution, and exchangeable cations content. The dataset also includes descriptions of soil macromorphological features such as texture class, colour, structure, water status, pedofeatures, biological features, artifacts, boundaries, and depths recorded during field sampling. The data for both pits are organized in accessible spreadsheets in an Excel file. The dataset also includes 160 images in plane polarized light (PPL), 160 images in cross-polarized light (XPL), and 47 images in reflected light (RL). All images are organized into six folders, each named according to the number of the soil pit and replication. The folder “p.S1_n1” contains 93 images, the folder “p.S1_n2” contains 42 images, the folder “p.S1_n3” contains 50 images, the folder “p.S2_n1” contains 58 images, the folder “p.S2_n2” contains 53 images, the folder “p.S2_n3” contains 71 images. The images are named based on the following convention: the pit number comes first, then the number of replication, then the sampling depth, then the number of the field of vision, and then the type of light (plane polarized light (PPL), cross-polarized light (XPL), reflected light (RL)). These data are valuable for evaluating dynamic changes and trends in soil properties influenced by changing climate patterns and are valuable for soil scientists studying black soils and general soil genesis. Other researchers can reuse these data for modelling soil substance flows, both vertically and across the landscape. The data significantly contribute to a better understanding of the pedodiversity within the forest-steppe region.



Pochvenniy Institut imeni V V Dokuchaeva


Soil Science, Cation Exchange, Soil, Soil Chemistry, Soil Micromorphology, Agricultural Soil, Mollisols, Soil Texture, Eurasian Steppe