Moscow University Soil Studies Bulletin. 2026. 2.

Digital soil mapping (DSM) incorporates the most advanced approaches and methods in the computer analysis and modeling of spatial soil data. Currently, over 90% of all publications in the field of soil mapping are related to DSM. An analysis of scientometric databases and publications shows that the number of publications is growing annually, yet the declared quality of the resulting soil maps remains virtually unchanged. This is due to a number of factors, and the purpose of this article is to identify them through a review of scientific publications. The conducted research has shown that maps created using DSM approaches vary in quality. The accuracy of the models used to create digital soil maps, as declared by the authors, typically ranges from 30–40% to 70–80%. Sixteen potential sources of error in digital soil maps were identified, grouped into errors in the initial data on soil properties, initial data on predictors, errors in model selection, and errors in soils as a modeling object. Some sources of error can be eliminated now or in the near future, but there are errors whose elimination seems impossible at the current stage of scientific and technological development. The greatest potential for significant improvement in the quality of digital soil maps of surface soil horizon properties is present, while the least promising is for maps of soil classification names. The presence of errors in soil maps created using digital soil mapping methods should be disclosed during the creation of any soil map, including masking out areas of the map with the greatest errors.

 

To mitigate the effects of climate change and preserve and enhance soil fertility, considerable attention is being paid to the development of effective land management methods. Reliable forecasts of soil responses to future climate change and anthropogenic impacts are essential for selecting optimal management strategies. Mathematical modeling is a leading method for analyzing and predicting the spatiotemporal variability of soil organic carbon stocks. It is currently being developed in two main directions. The first uses empirical models obtained using digital soil mapping methods. The second direction represents process-based models of the biogeochemical carbon cycle. Each has strengths and weaknesses. Digital soil mapping models are empirical, based only on the analysis of data on soil properties and environmental characteristics, and therefore are limited in explaining the spatial variability of soil carbon stocks. The uncertainty of forecasts based on these models depends on the volume and quality of the training data. They demonstrate the superiority of process-based models in predicting the spatial distribution of soil organic carbon stocks in cases where large, high-quality data sets were used. The advantage of biogeochemical models is that they are based on accumulated soil science knowledge of the processes that determine the carbon cycle, making them effective in studying the mechanisms of soil carbon stock dynamics. However, forecasts using these models, especially at regional and global scales, are characterized by high uncertainty. Currently, ensemble modeling (the integration of various artificial intelligence algorithms used in digital soil mapping with process-based models) is proposed to reduce forecast uncertainty. Effective development of this strategy requires a thorough understanding of the role of key biogeochemical processes in soil organic carbon stock dynamics to improve the conceptual foundations of the models and increase confidence in the predictions. This article discusses the sources of uncertainty in biogeochemical models and the potential use of minimal models to inform the selection of the required set of key processes and mathematical formalisms for their explicit description in models of different spatiotemporal scales. This can reduce the structural uncertainty of nonlinear biogeochemical models.

The study aimed to perform a systematic study and meta-analysis of national and foreign data (687 data points in total) on the effect of humic preparations (HPs) on crop yields. Specific objectives included evaluating the efficiency range of HPs (yield increase as a percentage of the control) accounting for statistical uncertainty estimated via absolute median deviation, and assessing the influence of HPs characteristics, crop types, and soil properties on this metric. HPs efficiency varied from –59% to +540% (mean 18%) and followed a non-normal distribution. The median efficiency was 12 %, with lower and upper quartiles at 5% and 21%, respectively, and uncertainty of 99 %. Kruskal–Wallis test revealed that soil granulometric composition and HPs enrichment with trace elements did not significantly affect efficiency of HPs. Key influencing factors included: cation salts of humate in HPs (Na salts were the least effective); HPs application method (combined soil and foliar application was most effective); soil acidity and humus content (higher efficiency at pH > 6.6 and humus content < 1%). Plants in the aster family showed the greatest responsiveness to HPs, while legumes and nightshades exhibited significantly lower efficiency. Under nitrogen deficiency, HPs efficiency rose to 22%, and most studies reported increased nitrogen and/or protein content in crop products. These findings suggest that HPs primarily enhance field yields by improving plant nitrogen assimilation. The results indicate that promising future research should evaluate HPs effectiveness against reduced nitrogen fertilizer rates. Given rising fertilizer costs, even modest effects could prove economically viable. Further field studies should optimize HPs use conditions and methods, prioritizing identification of factors driving efficiency uncertainty — preliminarily, application method and soil conditions (pH, humus content, and available nitrogen).

This study investigates the potential of the WOFOST crop growth simulation model for yield forecasting and crop condition assessment for several key agricultural crops across large extents of Russia over a fifteen-year analysis period (2005–2020) using soil and climatic datasets. Specific emphasis was placed on adapting information from the 1:2,500,000-scale Soil Map (V.M. Fridland edition) to ensure the model's correct performance. Within the study, model parameters for regional hybrids of barley, sunflower, and maize were obtained for several hundred districts within the Russian agricultural belt, including characteristics of phenology, photosynthesis, respiration, and assimilates partitioning. Parameterization was performed using loss functions based on the Brent, Nelder-Mead, and Differential Evolution algorithms to minimize phenology and yield estimation errors. To enable parameterization and independent accuracy assessment, the initial dataset was divided into a training set and a control set in an 80:20 ratio. The regionally parameterized models provided a good match between the error histograms for the training and control sets, with a near-zero systematic bias, while the mean relative absolute deviation of yield estimates ranged from 20% to 26% depending on the crop. Furthermore, it was demonstrated that the model estimates are not only close to the actual yield values for the studied period but also that the model forecast is capable of capturing multi-year trends in the yield dynamics of the studied crops. Finally, the obtained model crop hybrids were used to assess crop state in terms of the deviation of simulated yield from the yield of an optimal season, with the generation of deviation cartogram maps. The results obtained in this study can be used for decision support system of the agricultural sector, including yield forecasting and state assessment of the studied key crops over large areas using simulation modeling, including forecasts made under various climatic scenarios.

Abstract The RothC-26.3 model was used to reproduce the 62-year dynamics of soil organic carbon (SOC) in Retisols within a long-term field experiment conducted by the Federal State Budget Research Institution «Federal Research Center for Bast Fiber Crops». Simulation modeling was employed to assess the potential for increasing SOC stocks by 2090 through modifications in agrotechnological practices under two climate scenarios and two adaptive economic scenarios. The feasibility of utilizing alternative fertilizer sources and minimal tillage as supplementary approaches for SOC accumulation was examined. The results indicate that under existing management practices and future climate conditions, SOC stocks in the topsoil (0–20 cm) of the studied soils could increase by up to 34% of the initial content by 2090. Furthermore, the implementation of carbon-saving technologies—including adjustments to crop rotation structure, as well as the rates and sources of organic fertilizer application—could enhance SOC accumulation, leading to a potential increase of up to 82% by 2090. Under different climate scenarios, the maximum sequestration rate was projected to reach up to 11‰ per year. Among the alternative organic fertilizers evaluated, the application of composts and peat mixtures yielded the most favorable outcomes, facilitating an additional SOC accumulation of up to 10.6 tha–1 compared to the use of cattle manure. In contrast, the use of green-manure fallows and minimal tillage cannot be considered an optimal strategy for SOC sequestration, as these practices resulted in lower accumulation relative to cattle manure application. It was demonstrated that the studied soils possess considerable potential for organic carbon accumulation while remaining under agricultural cultivation.

Information on natural variation in the soil bulk density values is an essential component in analyzing the uncertainty of organic matter reserves in biogeocenoses. The aim of this study was to assess the bulk density variation in a secondary birch-spruce forest in the Moscow region on sod-podzolic soils. Five test sites measuring 50×50 m were established on an area of approximately 2 ha. At each test site, a section and two semi-pits were established, in which soil density was determined at 10 cm vertical intervals using Kachinsky cutting rings with a volume of 100 cm3 in double replicates. Nested ANOVA was used to analyze the data, allowing for quantitative analysis of density variation at different distances (between sites and variation within sites between sections) and depths. The results showed that for the humus horizons themselves at a depth of 0-10 cm, the average density was 0.83 gcm‒3.It then increased with depth for the AE transitional horizons. The eluvial horizons were characterized by a density of about 1.50 gcm‒3 and occurred at a depth of 30‒40 cm. The density of the lower part of the profile varied from 1.65 to 1.85 gcm‒3. For the coefficient of variation, as for the standard deviation, a decrease in variation with depth is observed. The upper part of the profile is characterized by values of the coefficient of variation from 10 to 14%, and from a depth of 40 cm, the coefficient does not exceed 5%. The greatest contribution to density variation, 90%, at a depth from 0 to 30 cm is made by vertical soil heterogeneity. For individual 10-centimeter layers down to a depth of 30 cm, more than half of the dispersion is due to heterogeneity between pits at a distance of 10‒20 meters. The results of the work can be used to calculate the uncertainty of organic carbon stocks in the forest biogeocenoses of the southern taiga.

Soil respiration (SR) is characterized by high spatial and temporal variability, which entails a significant uncertainty in estimates of CO2 emission from soils at the levels of individual ecosystems, regions, and the world as a whole. The primary objective of this study was to quantify the contribution of temporal and spatial variability to SR at the annual and seasonal scales by analyzing year-round SR monitoring data from November 2024 to October 2025 in six different biotopes in the southern Moscow region, which belongs to the temperate continental climate zone. SR measurements were conducted 3–4 times per month using the chamber method with parallel monitoring of soil hydrothermal characteristics. The biotopes differed in vegetation type (forest, meadow, agrocenosis) and soil (Entic Podzol (Arenic) or sandy podbur and Haplic Luvisols (Siltic) or gray loamy soil). It was revealed that differences between the average SR values in paired comparisons of the studied biotopes were more often statistically significant in the warm (May–October) and summer (June–August) periods and were least pronounced in the cold season and spring. The use of the nonparametric analysis of variance (PERMANOVA) showed that the contribution of the time factor (seasonality) to the total SR variability over the annual measurement cycle was 85%, while the spatial factor, determined by the type of biotope, was responsible for only 4% of the total SR variance. The "Time" factor was decisive in forming the total SR variability in all seasons of the year except winter, with the highest values of share participation (62–67%) in the warm, spring, and autumn periods, when the dynamics of air and soil temperature, which are the main predictors of SR intensity, are most pronounced. The contribution of the "Biotope" factor was greatest in the winter and summer seasons, amounting to 39% and 25%, respectively. These results should be considered when planning field experiments, for identifying spatial and temporal relationships with other variables, and for predicting carbon emission losses from soils to reduce its uncertainty.

In the context of global climate transformation and the implementation of national low-carbon development strategies, precise assessment of the sequestration potential of agroecosystems is a critical task. This study analyzes the interannual dynamics of carbon dioxide fluxes (NEE, GPP, Reco) in spring barley (Hordeum vulgare L.) agroecosystems on sod-podzolic soils in the southern taiga zone (Moscow region). The research is based on Eddy Covariance measurements obtained during growing seasons with contrasting hydrothermal conditions (2013, 2016, and 2023). A non-linear response of carbon exchange to climatic drivers was revealed: while the maximum gross primary production was recorded in the warmest year, 2016 (GPP=775 g Cm−2), the record net uptake occurred in 2013 (NEE=−245 g Cm−2) under optimal moisture conditions. It was established that the determining factors for productivity are the moisture regime and the proportion of diffuse radiation, rather than heat supply alone. A pattern of decreasing carbon exchange efficiency (GPP:Reco ratio) from 2.27 in moderately productive years to 1.25 in highly productive seasons was discovered, indicating an outstripping growth of ecosystem respiration during the intensification of assimilation processes. The results are of fundamental importance for the verification of carbon cycle models and the development of regional greenhouse gas monitoring systems

In a model experiment, the effect of polymer sorbents of different origins on the content of mobile species of heavy metals (HM) in zonal soils of the East European Plain was examined in a case study using soils of the Tula Region. Both synthetic and natural sorbents were used: hydrolyzed polyacrylonitrile (HYPAN), a binary structure of HYPAN and potassium humate (Humate “Sakhalinsky”), and a fungi mycelium powder (Micosorbent A). The experiment was conducted on four types of agricultural soils (Umbric Albeluvisols, Greyic Phaeozems, Voronic Chernozems) sampled in the Tula region in 2024 and spiked with Cu+2, Zn+2, Pb+2, and Cd+2 salts in 6 threshold limit values (TLV). It has been established that the same sorbent showed a significantly different remediation effect on different soil types with the same level of metal contamination: copper was bind from 30% on Voroic Chernozems to 50% on Greyic Phaeozems soils. For lead, the highest percent of mobile species to total was observed in Umbric Albeluvisoils (72%) and the lowest in Voronic Chernozems (56%). The application of Alternaria alternata mycelium had an effective effect on the sorption of zinc and cadmium in the studied soils: up to 70% in Voroic Chernozems for cadmium and up to 85% in Umbric Albeluvisoils for zinc.

Spatial variability in metal content in soils can lead to an unreasonably overestimated or underestimated level of contamination in an area, as determined by the total contamination coefficient ZС. Calculating this indicator based on sample experimental data yields only one value. For more reliable estimates, it is necessary to understand the possible range of this indicator, which describes the spectrum of reliability of contamination knowledge, ranging from low to high probability. Modeling the statistical distributions of heavy metal content under the assumption of logarithmic normality of their contents in both contaminated and background areas allows us to estimate the probability of ZС values falling into specific pollution categories. When classifying an area into a given pollution level, it is proposed to focus on the probability of obtaining individual high ZС values, even if the value itself is in a safe zone.

The most important factor affecting the soil organic carbon (SOC) stocks is the degree and nature of soil moisture content. This factor is especially important when assessing SOC in forest soils. In this paper, the results of a comparative statistical analysis of the variability of SOC in automorphic, semihydromorphic and hydromorphic forest soils in Karelia are discussed. To estimate SOC stocks and calculate quantitative indicators of their variability, soil survey data were used over an area of 1 km2. The information was collected into a single array, which includes the characteristics of 95 soil profiles of forest ecosystems. Of these, 61 profiles characterize automorphic soils, 12 profiles characterize semihydromorphic soils and 22 profiles characterize hydromorphic soils. The results of the studies showed that the mineral horizons of forest soils are largely heterogeneous in terms of SOC content, while organogenic horizons are more heterogeneous in terms of thickness and density. The results of statistical analysis showed that the average SOC stocs in the 0–30 and 0–50 cm soil layers increase depending on the degree of hydromorphism. The results of statistical analysis showed that SOC stocks in semihydromorphic soils are characterized by higher variability, as evidenced by a larger range of changes, higher standard deviations and coefficient of variation. In automorphic soils, the 0–5 cm layer, corresponding to the litter, accounts for up to 30% of the total organic carbon reserves in the 0–50 cm layer. With increasing hydromorphism, this share decreases to 17% in semihydromorphic soils and to 6% in hydromorphic soils. The share of SOC reserves in the 30–50 cm layer in total reserves increases from 23% in automorphic soils to 43% in hydromorphic soils.

The study of variation of soil properties of the subzone of ordinary chernozems was carried out on the basis of mathematical models of zonal and regional etalons of soils of the Altai Territory. These etalons are developed using information-logical analysis. The main indicators of soil heterogeneity are conditional uncertainty of soil properties within a taxon (Shannon index), information content, and the efficiency coefficient of information transfer. It has been shown that, given equal scale and area, the choice of classification system influences the variation in properties within soil taxonomic groups. The proximity of the classify boundaries of the properties of soils of different taxons indirectly indicates an increase an entropy in them. The evolution of agrogenic soils in line the agrochernozeme-agrozeme-agroabrozeme is accompanied by nonlinear dependence of changes of variation indicators. The Shannon index increases in agrozemsand decreases in agroabrozems. With an increase of scale and a decrease in the area of the estimated territory, the variation is determined by the geomorphological features of the soil region. Entropy decreases in soil areas confined to watersheds and slopes and increases in terraced areas of ancient hollows. The detailization of taxonomic groups at the genus level in regional etalons of meadow-chernozem soils is mainly accompanied by an increase in entropy compared to their zonal etalons.

The article presents an algorithmic approach for separation of integral CO2 fluxes, allowing for a quantitative assessment of the contribution of field areas with different topsoil bulk densities to the overall carbon balance. The methodology is based on integrating eddy covariance data, dynamic footprint modeling, and digital soil mapping. The experiment was conducted in 2023 on spring barley crops under conditions of pronounced soil bulk density heterogeneity (1.45–1.80 g cm⁻³). The developed approach enabled the partitioning of the total net ecosystem exchange (NEE) into gross primary production (GPP) and ecosystem respiration (Reco) components, specific to the identified zones with contrasting densities. It was established that under the dry conditions of June 2023, overcompacted areas (>1.65 gcm⁻³) were characterized by higher values of gross primary production (up to 14 μmolm⁻2s⁻1) and water use efficiency compared to less compacted areas (<1.65 gcm⁻³), where these values did not exceed 10 μmol Cm⁻2s⁻1. In the second half of the growing season, during the ripening stage and with an increase in precipitation in August, an inversion was observed: GPP values in the overcompacted areas were 2.8 μmol C m⁻2s⁻1, and Reco intensity was 2.1 μmol C m⁻² s⁻¹, which is half the values recorded in areas with lower bulk density (4.2 μmolm⁻2s⁻1). The proposed approach made it possible to quantitatively capture the within-field variability of carbon balance components without using spatial averaging.

The characteristics of urban ecosystems, the morphological structure of profiles, the content of organic carbon, the amount of petroleum hydrocarbons, the pHН2О, and the density of soils were studied at 9 control sites in the floodplain along the Likhoborka River in the Northern Administrative District of Moscow. The river floodplain was dominated by Gleyic Fluvisol (Turbic) and UrbicTechnosol, which were heterogeneous in their morphological structure and properties. The organic carbon content in the AYtr horizon of reclaimed soils reaches 4% or more, while it is less than 1% in the UR and TCH horizons of UrbicTechnosol. Alkalization to pHН2О7.4–8.5 was observed not only in the upper horizons, but also in deeper layers (30–50 cm) of the soil, due to the numerous inclusions of construction materials and other waste. The density of the AY and AYtr horizons of Fluvisol varies from 0.8 to 1.3 gcm–3, while the TCH and UR horizons are compacted above 1.4 gcm–3. A paired analysis of the content of petroleum hydrocarbons in soils and bottom sediments was conducted, and contamination above 1000 mgkg–1.  was recorded along almost the entire 30-kilometer length of the Likhoborka River. Different types of distribution of petroleum hydrocarbons in soil profiles have been identified. Using correlation analysis, it has been found that a decrease in organic carbon content is accompanied by compaction and alkalization of the upper soil horizons. An increase in the level of petroleum hydrocarbon contamination is associated with an increase in organic carbon content and a decrease in pHН2О. The content of petroleum hydrocarbons is correlated across all layers of the upper 30-centimeter layer, but there is no correlation between the content of petroleum hydrocarbons in floodplain soils and bottom sediments along the Likhoborka River.

Based on the results of a green pot experiment with mineral fertilizers on chernozem, a new method of plant diagnostics has been proposed, using the analysis of individual barley plants (Hordeum vulgare L.) according to their morphological characteristics of vegetative and generative development. Each plant was divided into three parts: the primary shoot, secondary shoots (together forming mature grain), and non-productive shoots. The dominant group of plants (Group D) was identified by total biomass, while the other two groups (Groups A and B) were distinguished by their level of generative development, determined by the quality of grain formed by different shoots. Structural differences among plants, shoots, and groups reflect the dynamics of barley development during the growing season. Different application methods for potassium fertilizer, namely localized and uniform, create different spatial heterogeneities of their content in the soil and, consequently, different dynamics of potassium's effect on the plants. Potassium fertilizers applied uniformly have the most significant effect during the first half of the vegetative period, when the primary shoot is most actively developing. The localization of potassium fertilizers in the soil, conversely, by promoting weaker fixation of potassium by the soil, prolongs its effect into the second half of the barley's vegetative period, when secondary-order shoots develop more actively. Therefore, the new method of structural division of individual plants made it possible to diagnose the physiological effect of the spatial heterogeneity of potassium fertilizer application on barley plants and crop quality. The traditional biomass accounting scheme, which averages all plants in a pot, was not sensitive enough to detect the effect of fertilizers on the formation of generative organs. Thus, the obtained data confirm the previously proposed concept linking the spatial heterogeneity of freshly applied potassium in the soil with its distribution within the plant throughout the vegetative period.

The work provides a detailed description of four stacked soil profiles that make up the “crimson clay” pedocomplex in two Urzhumian reference sections of the Middle Volga region, Cheremushka ravine and Grebeni. Paleosol profiles have a similar structure with eluvial-gley, illuvial-carbonate and structural differentiation of the profile. Pedogenic processes were reconstructed: gleyization from the surface and along the root network, redistribution and segregation of iron oxides, slitogenesis, redistribution of carbonates. Four stages of pedogenesis have been identified, with a total duration of at least 20–25 thousand years, which occurred on flat fluviolacustrine plains in conditions of a warm semi-arid climate with pronounced seasonality of precipitation. The difference in the structure of the pedocomplex in the studied sections is determined by differences in the facies conditions of pedosedimentogenesis: an alluvial-floodplain regime for the Cheremushka ravine section and a lake-playa regime for the Grebeni section. The pedocomplex of “crimson clays” reflects a long stage of geomorphic stability of the landscape, it has been traced in sections of the right bank of the Volga River over a distance of about 100 km and is a pedostratigraphic marker, or Geosol.
To discuss the actual results obtained, the article provides a review of the author's data on paleosols on Permian red beds of the Middle Volga region, including Ufimian, Kazanian, Urzhumian, Severodvinian and Vyatkian deposits. For each stratigraphic interval, characteristic pedogenic and sedimentary features of paleosols and host rocks are given, on this basis, soil-forming processes and landscape-climatic factors were reconstructed. In general, the Permian red paleosols have a chemical and mineralogical composition inherited from the host rocks and a high degree of weathering of the siliciclastic material associated with ancient soils and weathering crusts of the provenance areas. The autochthonous nature of the gley features of paleosols formed during the process of pedosedimentogenesis are shown. Most mature soils are classified as chromic stagnicvertic calcic Paleocambisols or chromic stagnicverticPaleocalcisols. Mean annual precipitation calculated from geochemical indicators of illuvial horizons of paleosols shows cyclical changes. The minimum amount of precipitation — 400 mmyear–1 — was typical for the Urzhumian (Wordian) time, the maximum values — 777 mmyear–1 — were revealed for the Severodvinian (Capitanian) time.
Evaluation of the pedostratigraphic potential of Permian red-bed deposits and identification of the role of microorganisms and organic matter in the formation of paleosols are tasks for further study.

Thearticlepresents the results of a comprehensivestudy of the soilcover of the islands of UrupandSimushir, which are partoftheKurilRidge. The mainfocus is on analyzing the impact of environmentalconditionssuchasclimate,vegetation,topography, andvolcanicactivityonsoilformationanddiversity.Duringthefieldwork, keysiteswithsoilsectionswerelaid,ageobotanicaldescription of plantcommunities was carried out, and samples were selected forlaboratoryanalysis. It has been establishedthat the soil-forming processesontheseislandsareintermittentand are associatedwith the periodicburial of soilhorizons with pyroclasticmaterial. Based on the morphological descriptions of the profiles of the surveyed territories, a stratotype of the soil pyroclastic cover (SPC) was compiled separately for the sites on Urup Island and Simushir Island, reflecting the history of the profile formation. A special feature of the soilsis the highcontent of organic carbon in the surfacehorizons,whichvariesfrom5.1to15.1%,reachingmaximumvaluesunderthickets of KurilbambooonUrup Island,as well as the presence of horizons with andic properties, usually associated with volcanic soils.Soilacidity(pH)rangesfrom3.7to6.4,increasingwithdepth. A CKrmarkerashhorizon with an age of ~2100years has been identified, which plays a keyroleinstratigraphy. The soils forming on Urup Island are characterized by a large accumulation of organic carbon compared to the soils of Simushir Island, where the soil cover is younger and formed on a substrate that is initially poor in organic matter, the slag from the eruption of Zavaritsky volcano (195 y. a.). The andicpropertiestestconfirmed the presence of reactivehorizonsin the lowerparts of the profiles. The density of the soilcompositionvariesfrom0.42to0.66gcm–3,which is typicalforvolcanicsoils. It is shownthatplantassociationsplay a keyrolein the processes of humus accumulationandsoilprofileformation. The dataobtained are importantforunderstanding the mechanisms of soil formation involcanicislandecosystems.

Despite the widespread adoption of modern, high-precision methods for assessing ecosystem carbon budgets, most primary data for calculating monthly, seasonal, and annual gas fluxes are obtained through daily soil or ecosystem respiration measurements. The question remains whether such one-time, albeit regular, measurements can reliably reflect the average daily flux. The objectives of this study included assessing patterns in the diurnal dynamics of soil CO2 emissions for two northern taiga ecosystems (green moss pine forests and frozen hummocky peatlands) and three spotted-medallion tundra ecosystems (mineral spot, overgrown area, and dwarf birch area) in northern Western Siberia. In August2016 and 2017, CO2 emissions from the soil surface were measured every four hours for two days using a chamber method, as well as soil temperature and volumetric moisture at a depth of 10 cm. Significant diurnal dynamics were observed for all studied ecosystems, despite different absolute values of CO2 emissions. Minimum fluxes were observed in the pre-dawn hours, around 2:00 AM, for all sites. Maximum fluxes were recorded at various times but generally occurred between 2:00 PM and 6:00 PM. For most sites, the diurnal variation in emission values correlated with soil temperature, but a pronounced hysteresis was observed in this relationship. This phenomenon is explained by both biological factors—root respiration dynamics depend more on photosynthesis than on soil temperature—and physical factors—impeded gas diffusion in dense mineral horizons. The most favorable hours for measuring CO2 emissions, in terms of subsequent calculations of diurnal fluxes for most of the studied ecosystemsduring peak vegetation, are morning (before 10:00 AM) and evening (from 6:00 PM to 10:00 PM).