Tatyana V. Koroleva

In 2024, eight Soyuz launch vehicles launched from the Baikonur Cosmodrome created 40 falling sites in Central and Northern Kazakhstan. During field work at all falling sites, the area of disturbances was assessed. The average area of zones containing large fragments was 63 m², and the average area of scatter fields of small fragments was 11,605 m². The maximum area of jet fuel spills reached 125 m², and that of hydrogen peroxide spills reached 196 m². In 2024, due to falling debris, total mechanical disturbances covered 6912 m², and total pyrogenic impact effected 1,211,453 m². At the first stage falling sites during the plant growing season, the area affected by fires and H₂O₂ spills was significantly larger, while the area of very weak mechanical disturbance was smaller (p < 0.05). During the mud season, the area with very strong mechanical impact was greater compared to winter and summer (p < 0.002). Compared to the first stage falling sites, the Soyuz abort mode falling sites were characterized by a larger area of very strong mechanical impact (p < 0.02), evidenced by deep craters, and a smaller area covered by large fragments. The data obtained can be used when planning launch dates from the Baikonur Cosmodrome to minimize negative environmental impact on the fragile and slow-recovering arid ecosystems of Central and Northern Kazakhstan. Information on disturbance areas can be used to monitor the natural recovery of affected ecosystems and to calculate the environmental damage caused by rocket and space activities in 2024.

The state of meadow vegetation in areas with different ages of experimental spring burnout (from 1 to 12 years ago) was studied in the Tomsk region for 3 years. On experimental plots of 1 m² and 100 m² (small- and middle-scale levels, respectively), the dynamics of species richness, total projective cover of vegetation, and aboveground phytomass reserves were characterized, and the structure of communities was analyzed. It was revealed that a single fire in the spring significantly reduces species richness for small-scale plots and increases the total projective cover for middle-scale plots. Structural differences from control plots can be traced from 1 to 4 years for different characteristics. The effects of fire are more prominent for small-scale plots. To suppress tree growth and maintain the existence of meadows, grass fires seem to be a less effective practice than mowing. At the same time, the results obtained potentially allow us to consider prescribed burning as a tool for maintaining the stability of meadow plant communities in the south of Western Siberia, preventing them from becoming overgrown with tree undergrowth, in cases with a controlled frequency of burning and the use of appropriate fire safety measures.

Understanding the rate and direction of pyrogenic succession in arid ecosystems, which depends on many factors, including the intensity of grazing and the frequency of pyrogenic expo-sure, will allow for more accurate predictions of the consequences of fire onplant communities, and will assist with better fire management. We studied the vegetation on 55 sites in and near the “Chernye Zemli” Natural Biosphere Reserve that burned at different times or were not affected by fires over the past 35 years and characterized the changes in vegetation cover associated with the impact of wildfire and grazing. The descriptions were grouped into chronological stages according to the time elapsed since the last fire, or into groups according to the frequency of fires. In pairwise comparison of the projective cover of plant species between chronological stages, it correlated most strongly between successive initial stages (for stages 1 and 2, p = 0.003, r = 0.73; for stages 2 and 3, p < 0.001, r = 0.78). Species with an initially higher projective cover were more likely to grow on plots in the first year after the fire: p < 0.03. Plots with rare and frequent fires had similar projective cover of individual species (r = 0.64, p < 0.001). We conclude that in the course of pyrogenic succession, communities are gradually replaced over at least ten years. At the same time, the composition of a plant community at the initial point of succession depends on the prevalence of species in the community before the fire. No fundamental effect of the frequency of fires on the composition of plant communities has been revealed.

One of the most important problems of environmental sciences is to determine limits for the sustainable functioning of affected ecosystems. The effects of volatile hydrocarbons (such as gasoline and kerosene) on plants in natural ecosystems have been poorly studied to date. The present work outlines the data of a field experiment on the effects of kerosene on the plants of forest and bog communities in Central Russia. In this paper, we model the influence of kerosene spillage on plants growing in a coniferous broad-leaved (aspen–spruce) forest and a raised bog with a subshrub–sphagnum pine forest. We used TS-1 kerosene, which is the most commonly used fuel for commercial aviation in Russia. The applied pollutant (loads of 1 to 100 g/kg) had a significant impact on herbaceous plants, leading to the death of individuals even at minimal doses. The shrubs of the bog community as well as the mosses of both communities were more resistant to kerosene. The recovery processes of plant communities were clearly pronounced as early as 2 years after the application of the pollutant. The level of kerosene threshold exposure, which significantly affects the dominant plants of the herb–shrub layer, can be defined as 1–5 g/kg for the forest community and 5–10 g/kg for the bog community.

One of the most important challenges for soil science is to determine the limits for the sustainable functioning of contaminated ecosystems. The response of soil microbiomes to kerosene pollution is still poorly understood. Here, we model the impact of kerosene leakage on the composition of the topsoil microbiome in pot and field experiments with different loads of added kerosene (loads up to 100 g/kg; retention time up to 360 days). At four time points we measured kerosene concentration and sequenced variable regions of 16S ribosomal RNA in the microbial communities. Mainly alkaline Dystric Arenosols with low content of available phosphorus and soil organic matter had an increased fraction of Actinobacteriota, Firmicutes, Nitrospirota, Planctomycetota, and, to a lesser extent, Acidobacteriota and Verrucomicobacteriota. In contrast, in highly acidic Fibric Histosols, rich in soil organic matter and available phosphorus, the fraction of Acidobacteriota was higher, while the fraction of Actinobacteriota was lower. Albic Luvisols occupied an intermediate position in terms of both physicochemical properties and microbiome composition. The microbiomes of different soils show similar response to equal kerosene loads. In highly contaminated soils, the proportion of anaerobic bacteria-metabolizing hydrocarbons increased, whereas the proportion of aerobic bacteria decreased. During the field experiment, the soil microbiome recovered much faster than in the pot experiments, possibly due to migration of microorganisms from the polluted area. The microbial community of Fibric Histosols recovered in 6 months after kerosene had been loaded, while microbiomes of Dystric Arenosols and Albic Luvisols did not restore even after a year.

Significant environmental impacts of mining activities connected with high-sulfur materials result from the production of acid mine drainage and potentially toxic elements, which easily migrate to adjacent ecosystems due to the typical absence of vegetation on spoil heaps and toeslope talus mantle. In this paper, we present the results of the first comprehensive study of the ecosystems affected by acidic and metal-enriched (Al, Ca, Co, Cu, Fe, Mg, Mn, Ni, and Zn) mine drainage conducted at spoil heaps and adjacent talus mantle under semihumid climate conditions within the Moscow Brown Coal Basin (Central Russian Upland, Tula Region, Russia). A total of 162 samples were collected, including 98 soil samples, 42 surface water samples, and 22 plant samples (aerial tissues of birch). Coal talus mantle materials of Regosols were characterized by the increased concentration of water-soluble Ca, K, Mg, and S, and all mobile fractions of Al, Co, S, and Zn. The chemical composition of birch samples within the zones affected by acid mine drainage differed insignificantly from those in the unpolluted ecosystems with black soils, due to the high tolerance of birch to such conditions. Differences between the affected and undisturbed sites in terms of the chemical composition decreased in the following order: waters > soils > plants. The geochemical characterization of plants and soils in coal mining areas is essential for the mitigation of negative consequences of mining activities.

In arid lands of Central Kazakhstan, fires commonly occur due to both man-made (e.g. space rocket launches) and natural factors. Remote sensing is the best method to identify burned landscapes and to assess their long-term dynamics. In this paper, we assessed total areas and seasonal features of fires using Landsat 8 OLI data of high spatial and temporal resolution, corrected for atmospheric effects. We defined data requirements, considered various spectral indices, and evaluated their suitability for automated delineation of burned areas. Spectral indices included special burn indices (NBRT, MIRBI, NBR, NBR2, BAI) and vegetation indices (MSAVI, MSAVI2, MTVI2, GEMI3) that allowed us to determine the boundaries and severity of fires indirectly based on the state of vegetation. Our study showed that burned areas were most accurately identified using indices of NBR2 (normalized burn ratio 2) and MSAVI2 (modified soil adjusted vegetation index 2). They were extracted using image segmentation and natural breaks classification methods. We have assessed MSAVI2 and NBR2 segmentation results with machine learning metrics, i.e. for Soyuz drop zone (landing area of rocket stages) precision of NBR segmentation equaled 99.5%, recall − 99.5%, accuracy − 98.5%. For Proton drop zone NBR segmentation precision equaled 99.3%, recall − 99.7%, accuracy − 99.4%. MSAVI2 results are less accurate. The accuracy of segmentation significantly depended on the vegetation state which was predetermined by the frequency and severity of previous fires within certain territory.

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