Èkologiâ

The aim of the work was to assess CO₂ emission from soil when adding several types of biochars. In a laboratory experiment, the effects of adding different biochars to the soil were studied. They were recommended for different purposes based on their properties: soil melioration (from Amaranthus cruentus biomass) or carbon sequestration (from Betula sp. wood and Miscanthus sacchariflorus biomass). Soil respiration (in the absence of vegetative plants) and ecosystem respiration (in the presence of vegetative M. sacchariflorus individuals) were assessed. Addition of all biochar varieties resulted in a decrease in CO₂ emission from the soil surface. The CO₂ flux in the absence of living M. sacchariflorus plants in the vegetation vessels decreased to a similar extent when adding biochars of all varieties. However, in the presence of living M. sacchariflorus plants in the vegetation vessels, differences were found in the intensity of ecosystem respiration in the variants with different biochar varieties. In the presence of M. sacchariflorus plants, the highest CO₂ flux was observed with the addition of biochar from A. cruentus, and the lowest with the addition of biochar from Betula sp. Thus, firstly, the addition of biochar reduced the CO₂ flux from the soil and, secondly, the presence of vegetative plants is a significant factor modifying the differences in respiratory activity between substrates with biochars of different origins.

In the upper treeline ecotone the relationships between the values of biometric parameters of Siberian larch (average radius of the horizontal projection of the crown, the diameter of the tree at the root collar and its height) were studied using ground-based measurements on circular sample plots and ultra-high spatial resolution aerial photographs obtained by an unmanned aerial vehicle. A nonlinear regression model, a model using the random forest method and an ensemble of models using machine learning methods were created, establishing the relationship between the values of the diameter at the root collar and the crown radius of a specimen of Siberian larch. The resulting models have a high level of adequacy at the qualitative and quantitative (R² > 0.95) levels. The predictive capabilities of the nonlinear regression model outside the training set were better than those of the machine learning models, so it was used together with allometric equations to quantify the phytomass of Siberian larch based on the root collar diameter and carbon sequestration in the study area using data obtained from the interpretation of the crowns of 88 608 Siberian larch trees. It was found that in the ecotone of the upper boundary of tree vegetation on an area of 7.32 km², the aboveground and belowground phytomass of Siberian larch is 1355.2 tons of dry mass, which contains 677.6 tons of carbon, or 2484.5 tons of CO₂ equivalent.

Annual carbon dioxide flux from soils of different biomes plays a key role in creating global climate models and in analyzing carbon cycles in terrestrial ecosystems. However, there are significant gaps in such studies at a regional scale. Due to the high complexity of obtaining daily soil respiration values, various modeling methods are used. In this work, based on 2760 soil respiration measurements in spruce forests of the «Ural-Carbon» carbon measurement supersite (Middle Urals) carried out in autumn 2021 and from April to October 2022, annual soil respiration values were estimated using classical regression approaches and machine learning. We also investigated the dependence of the results on the complexity of the model (number of predictors) and the methods used (extrapolation by the random forest model and combined approaches to estimate winter CO₂ fluxes). The «simplified» model with 7 predictors showed only a slight decrease in accuracy compared to the full model with 21 predictors (R² = 0.89, MSE = 0.31 vs. R² = 0.92, MSE = 0.22). Predictors based on remote sensing turned out to be more significant for the accuracy of the model than data measured in the field. Although the initial results of different approaches varied, adding winter respiration values taken from the literature to the random forest model and averaging the values of the combined approaches allowed us to achieve similar values of annual soil respiration: 830.3 ± 6.4 and 851.6 ± 8.0 g C/m²year, respectively.

A remote assessment of carbon deposition was carried out on former arable lands (Republic of Bashkortostan, Eurasian Carbon Polygon, «Yangan-Tau» Geopark, «Nasibash» site) overgrown with pine (Pinus sylvestris L.). Samples of woody and herbaceous plants were collected from 8 sample plots located in stands at different stages of succession (1st, 3rd, 4th and 4th sparse). The stock of phytomass and the carbon content in living phytomass (trunk, needles, branches, herbaceous plants) and mortmass are estimated. The carbon reserve is calculated for each stage of succession. The largest change in carbon reserve was noted for pine stands at the 4th stage of succession, averaging of 2.7 t / ha per year. A correlation analysis of the relationship between carbon reserve values and data on the height of trees obtained as a result of laser scanning, as well as the values of some vegetation indices, was carried out. The results showed that it is possible to estimate the dynamics of changes in carbon stock in the carbon stock in the stand based on data on the height of trees (R² = 0.85) and on the values of the vegetation index NDVI (R² = 0.79).