Yulia Lvovna Meshalkina

The aim of the work was to assess the contribution of the following components – biomass and mortmass of tree stands, undergrowth, living ground cover, and forest litter — to the total organic matter’s pool of plant community. The object of the study was a territory of coniferous-deciduous forest located in Solnechnogorsk City District of the Moscow region, in which five permanent sample trial plots of 50×50 m were allocated. The greatest contribution to the total organic matter mass of studied plant communities was made by forest stand perennial parts (up to 87%) and forest stand mortmass (up to 14%), and phytomass of deciduous trees in stand containing 32 to 98%, which was connected with incompleteness of forest restoration succession process. The contribution of forest litter was no more than 3%; litter deposit was low (0,18–1,21 kg×m^-2), which is not typical for spruce forests, as is the fact that all litter is of the destructive type. Living ground cover in terms of floristic composition and ecological-coenotic structure was typical for the subzone of coniferous-deciduous forests; its contribution to the overall productivity of forest biogeocenosis was insignificant. The spatial intrabiogeocenotic structure of litter reserves and living ground cover biomass distribution was disturbed compared to typical spruce forests due to the high proportion of deciduous species in the forest stand. Deciduous species inclusion in the tree tier, typical of the final stage of formation of a secondary coniferous forest during succession, caused a slight increase in the intensity of the biological cycle, which was indicated in this case by a decrease in the supply of litter and a simplification of their structure. Since the biomass and mortmass of tree stand make the greatest contribution to the sequestration of carbon by forest biogeocenoses, it is these components that require the most detailed assessment during monitoring observations, the purpose of which is to assess the carbon reserves of terrestrial ecosystems.

The dependence of soil bulk density on penetration resistance, moisture content, soil organic carbon content and particle size distribution was investigated for Retisols of the Educational and Experimental Soil and Ecological Center of Lomonosov Moscow State University “Chashnikovo”. Penetration resistance was measured with a penetrologger at six key sites with different land-use types, in areas in front of three soil profiles. Soil samples for bulk density were taken from the same profiles using 100 cm³ cutting rings. The samples were subsequently analyzed for moisture content, organic carbon (by the Tyurin method), and particle-size distribution using a laser diffraction analyzer. Within the study, 24 regression models for predicting soil bulk density were developed and analyzed. The quality of these models varied; the coefficients of determination (R²) ranged from 0.23 to 0.89 and the root mean square error (RMSE) from 0.07 to 0.18 g×cm^–3. Based on the modelling results, the greatest contribution to predicting bulk density was made by organic carbon content, depth and penetration resistance, in descending order. Adding specific particle-size fractions to the model is more informative than using the principal components of particle-size fractions as predictors. The use of specific particle-size fractions is more informative than using principal components as predictors. In many models, field soil moisture proved to be an insignificant predictor for bulk density. Given the labour-intensive nature of determining a full set of predictors, models with a reduced set of predictors were proposed: 1) depth and penetration resistance; 2) organic carbon content and penetration resistance; and 3) organic carbon content alone. The data from the first of these models are automatically collected during the use of the penetrometer, making it convenient for monitoring surveys. The method has important limitations relating to the particle size distribution of soils and how this is determined. For example, it is impossible to take a top-down measurement of penetration resistance with a penetrologger in the presence of large boulders in the soil, as the measuring tool hits them and cannot be pushed into the underlying horizons. The use of regression equations in which particle-size distribution is determined by a method other than laser diffraction is incorrect. The choice of which particle-size fraction to use as a predictor should be based on a correlation analysis for each territory in question.