Articles

The normative yield and cadastral value of agricultural lands of Altai Krai have been estimated. 123 soils from sodpodzolic to mountain soils in different agroclimatic conditions and landscape elements were characterized. The cadastral value varies in the range of values from 17.2 rub.∙м-2 for leached chernozems to 0.02 rub.∙м-2 for automorphous typical solonchaks. The increase in cadastral value is associated with the growth of agroclimatic potential. The highest values of cadastral value and normative yield correspond to the zone of podzolized and leached chernozems,
dark gray and gray forest soils of Salair foothills, the lowest values of cadastral value and normative yield are characteristic of the zone of chestnut soils of dry steppes. According to median values of specific indicators of cadastral value in a number of chernozems the following dependence can be distinguished: typical chernozems> leached chernozems> podzolized chernozems> ordinary chernozems> southern chernozems. The sensitivity of cadastral value to degradation processes is shown: soil washout reduces specifi c indicators of cadastral value from 5% to 88%, deflation — by 5–92%, salinization — from 13 to 36%, gleying — up to 66%.

The article analyzes the features of the radioecological situation in the zone of possible influence of the State Scientific Center «Scientific Research Institute of Atomic Rectors» (SSC NIIAR, Dimitrovgrad, Ulyanovsk region). Field studies were conducted according to the methods recommended for conducting radioecological monitoring. Measurements of the specific activity of natural and man-made radionuclides were carried out on a scintillation gamma-ray spectrometer «Multirad» (Russia) with a scintillation detector NaI(Tl) 63×63 mm in 3-fold repetition. It is shown that at present the radioecological situation in the forests in the territory under consideration is satisfactory: the power of the equivalent absorbed dose of gamma radiation, the density of soil pollution and the levels of specific activity of 137Cs in biota do not exceed the normative indicators, with the exception of fungi, the specific activity of which is close to the maximum normative —2500 Bq∙kg-1. In the Cheremshansky Bay of Volga River the volume activity of 137Cs in the surface and bottom waters does not exceed the standard (11 Bq∙l-1), however, significant amounts of technogenic radionuclides such as 137Cs, 134Cs, 60Co were found in the bottom sediments. In forest and aquatic ecosystems, «critical components» can be distinguished, which are characterized by an increased storage capacity in relation to man-made radionuclides. In forest ecosystems, this is the litter of gray typical forest soil and the dark humus horizon of the urban quasi-ecosystem, and the components of the biota are higher fungi. In aquatic ecosystems — there are bottom sediments.

The soils of two pairs of catena were studied under conditions of petroleum hydrocarbon (PH) contamination and lack of exposure within the Middle Taiga subzone (Tyumen region). 1st pair of catena: Gleyic Albic Podzol, Dystric Gleyic Histic Fluvisols, Dystric Gleyic Fluvisols; 2nd pair of catena:Albic Gleyic Retisols, Albic Gleyic Histic Retisols, Dystric Histic Gleysols . The effects of PH contamination on the biological characteristics of soils (respiration and catalase activity) and the possibility of their use for rationing the content of PH in soils were evaluated. The lateral migration of PH in soils prevailed over the radial one. The highest concentrations of PH were adsorbed in the upper peat layer (from 83 to 399 g∙kg-1). For soils of the superaqual position, a radial monotonously decreasing distribution of PH along the profile was revealed (from 40–50 to 3–4 g∙kg-1). PH contamination of soils led to a violation of the barrier and transformational hydrosphere functions of soils. The pH reaction of soils significantly changed towards alkalinization (0,5 to 2,0 pH units). The accumulation of chlorides (up to 0,7 g∙kg-1) with a maximum in the soils of the superaqual position was recorded; a reliable correlation was established between the pairs: the content of PH – pH, PH – Cl- and Cl- – pH, which indicated the income of crude oil into the soil as a result of emergency pipeline holes. PH underwent changes over time: heavy high-boiling hydrocarbons (99.9%) were present in the soils after 3 years of pollution. A significant correlation was revealed between PH and basal respiration (BR): direct for humic and reverse for organic soil horizons. It was found the microbial coefficient of qCO2 in organic soils of Western Siberia under oil contamination decreased with an increase in the concentration of PH. A negative correlation was found between PH concentrations and catalase activity in soils (R = –0,80 – (–0,90), p<0,05). Th e levels of PH content at which stable soil functioning occurs are justifi ed: no more than 6,8 g∙kg-1 for soils with 1-year contamination and 2,3 g∙kg-1 for soils with 3-year contamination and high concentrations of salts.

In the territories of urban specially protected natural areas in intact ecosystems, the predominance of nemoral species (larch, spruce, linden), meadow species (birch forest), and weed-ruderal species (pine forest) in the living ground cover was revealed. This species composition is not typical for natural zonal phytocenoses. Boreal species are found in small numbers in all plantings, only in larch their share reaches 35%. At the same time, in terms of typology, reserves and spatial distribution of litter of deciduous and coniferous plantations, protected areas correspond to similar characteristics of natural plantations, with the exception of pine plantations. Among the tree species studied, spruce exhibits the most stable influence on the conditions of formation of terrestrial detritus as an edificator. The intensity of the biological cycle in deciduous plantings is higher than in coniferous ones, as evidenced by data on the typology and stocks of litter. Litters, as a component of the ecosystem and as an important link in the biological cycle, are very stable in urban environments and can retain the properties of natural analogues in the absence of significant anthropogenic impact, unlike living ground cover. To expressly indicate the impact of a megacity on forest ecosystems, it is proposed to use an integrated approach based on the analysis of a number of informative and most accessible indicators of grass cover and litter. It has been established that litter of pine plantations is more sensitive to the influence of the metropolis.

The paper characterizes the profiles of virgin chestnut soils and solonetz in the north of the Caspian lowland adjacent to the Djanibek reserve. The objective of the study was to analyze the morphology, physical properties and chemical and mineralogical composition of the so-called xerometamorphic horizons of chestnut soils in the research area. The initial hypothesis was the general genetic similarity of xerometamorphic horizons with natric horizons in the corresponding conjugate soils. With the general similarity of morphological features, mineralogical and chemical composition of these horizons, there was a significant difference in the content of exchangeable sodium and in the presence of signs of clay illuviation in the natric horizons. It is suggested that xerometamorphic horizons reflect the initial stages of formation of alkaline soils, further diluted by divergent pedogenesis. The proposal of a number of specialists on the allocation of the BMK horizon in soils used in agriculture and, accordingly, the type of agro-soils is supported.

Remote sensing data is an important source of information for monitoring and mapping vegetation cover. Machine learning methods are a modern and powerful tool for data processing. However, machine learning methods combined with remote sensing data were practically not used for soil salinity assessment and mapping in the southern steppe zone of Russia. This paper examines the possibility of applying various spectral characteristics to soil salinity mapping in solonetzic complexes in the southern steppe zone of Russia (Republic of Kalmykia) using machine learning methods. A number of predictors were considered, including reflectance coefficients in blue, green, red, infrared spectral zones, vegetation indices (NDVI, NDVIt, TVI, SAVI, MSAVI, EVI1-EVI4), salinity indices (SI1-SI6), intensity indices (Int1, Int2), brightness index (BI), and an index proposed by the authors. High-resolution images from QuickBird (2.4 m) and SuperView-1 (2 m) satellites were used. Soil salinity was assessed using two indicators: specific electrical conductivity in water suspension (EC1:5) and sodium activity (aNa1:5). Two different machine learning models were applied in the study: linear regression and neural networks. According to the results obtained, the linear regression model for EC1:5 in 0–30, 0–50, 0–100 cm layers has coefficients of determination (R2) of 0.53, 0.59, 0.79 on the training sample; the test sample managed to obtain coefficients of determination of 0.49, 0.58, 0.70, respectively. The neural network model has significantly higher coefficients of determination: R2 for EC1:5 in layers 0–30, 0–50, 0–100 cm on the training sample is equal to 0.68, 0.91, 0.97; on the test sample is 0.87, 0.86, 0.88, respectively. This indicates a greater potential of this model for cartographic modeling of soil salinity. The best predictors were the following indices: NDVIt, TVI, EVI1, Int1. The study showed the potential of using the neural network model and spectral indices obtained with SuperView-1 images for soil salinity mapping of solonetzic complexes in the south of the steppe zone of Russia.

The physical, chemical and physico-chemical properties of soils and man-made surface formations of the territories of coal dumps in the southeastern part of the Donetsk ridge within the Grushevsko-Nesvetaevskaya syncline (Rostov region), differing in age, lithological properties of the overburden and host rocks composing them, and pyrogenic dynamics, have been studied. The main characteristics of the soil properties of the studied territories have been established to assess the geoecological situation, patterns of the spread of potentially toxic substances and the development of projects for the restoration of territories. The unequal influence of soil formation factors was revealed, manifested in high variability and contrast of soil properties. Electron microscopic studies of technogenic samples have shown that the coarse microstructure was formed as a result of the impact of modern compaction, cementation and sintering processes on the rock.

Microbial production and CO2 emission in Albic Retisol (Loamic) and Albic Retisol (Aric, Loamic) of Lomonosov Moscow State University carbon polygon «Chashnikovo»≫ in the Moscow region were studied during the peak of vegetation activity. The object represents monitoring sites in two natural ecosystems (secondary spruce forest and mixed-grass meadow) and in two agroecosystems (perennial grasses and bare fallow). The soils differed in their stocks
of organic matter carbon (Corg), microbial carbon (Cmic), and potentially mineralizable carbon (Cpm). The highest values of microbial indicators and carbon content were observed in the upper 30 cm with a maximum in the upper 10 cm. Corg stocks in the 0–30 cm layer were 1.1–1.3 times higher in agricultural soils (72.7–75.6 t ha-1) compared to natural ones (59.4–65.0 tha-1). The contribution of Cmic stocks to Corg stocks in meadow soils and agricultural soils under perennial grasses (1.8 and 1.4%) was higher than in forest soils and soils under bare fallow. Сpm stocks in natural soils (1.34 and 0.97 tha-1 for a layer of 0–10 cm) were 1.3–2.3 times greater than in agricultural soils, but the intensity of mineralization of organic matter in agricultural soils was 1.4–2.9 times lower than in soils of natural ecosystems. For ecosystems with similar vegetation, the influence of Сpm stocks on the amount of microbial CO2 production was shown; its proportional increase was noted. Maximum potential microbial CO2 production (4.8 gCm-2day-1 for the 0–10 cm layer and 10.5 gCm-2day-1 for the 0–30 cm layer), Cmic stocks (0.50 tha-1), as well as CO2 emission (11.09±0.29 gCm-2day-1) were characteristic of the soils of a dry meadow. In other ecosystems, CO2 production by microorganisms was lower by approximately 2 times. Since CO2 emission, in addition to microbial respiration, is also caused by the respiration of plant roots, its minimum values were observed in agricultural soils under bare fallow (5.01±1.43 gCm-2・day-1). CO2 emission from forest soils and agricultural soils under perennial grasses was statistically not significantly lower compared to the meadow.

The FAO methodology within the Global Soil Nutrient and Nutrient Budget Maps (GSNmap) project was tested for the first time for mapping humus content with a spatial resolution of 250 meters per pixel in soils of the Russian Federation at the regional scale, using the Bryansk Region as an example. The map was created in the R soft ware environment using data from Agrochemical Service and remote sensing, global databases and soil maps. The centroids of the sites from which the composite samples were taken by Agrochemical Service were selected as sampling points. The set of predictors available under the FAO project was expanded by additional data, including soil maps and maps of soil-forming rocks. The importance of the predictors was assessed using the Boruta algorithm, which is usually used as an initial stage for a random forest. The model was created using the caret package with the quantile regression forest method. The modeling efficiency coefficient (MEC) was 55%, the coefficient of determination (R2) was 0.57. The map reflects current information that can be used to monitor the dynamics of organic matter content in the soil and assess the state of the arable soils in the Bryansk region.

Soils are the largest terrestrial reservoir of organic carbon, so even small changes in soil carbon stocks can have significant eff ects on the atmosphere and climate. To select effective strategies to mitigate climate change, predictions of how soils will respond to future changes in climate and land use are needed. Achieving meaningful predictions requires a deep understanding of the highly complex, open, multicomponent soil organic matter system. One of the most effective methods for predicting the dynamics of soil organic matter is mathematical modeling. Process-oriented (physically based) models make it possible to present the basic concepts about the mechanisms that determine the behavior of this system in a mathematically formalized form and conduct a quantitative analysis. The uncertainty of the forecasts depends on the level of development of the theory explaining the dynamics of soil organic matter, the models representing it and their experimental support. This review examines the achievements of the last decade in modeling the role of microorganisms in the stabilization of soil organic matter, the concept of soil saturation with organic carbon, temperature control, as well as the development of reactive transport models describing the dynamics of organic carbon in the soil profile, and the representation of the dynamics of soil organic matter in global climate models. Unsolved problems associated with the high variability in the structure of new generation soil organic matter dynamics models are discussed.