Microbial Composition of Natural, Agricultural, and Technogenic Soils of Both Forest and Forest-Tundra of the Russian North

Abstract

Technogenic processes and agrodevelopment of the soil cover lead to significant transformations of soil chemical and biological properties. New methods of soil microbiology, including next-generation sequencing, allows us to investigate soil microbial composition in detail, including the taxonomy and ecological functions of soil bacteria. This study presents data on the taxonomic diversity of mature and anthropogenically disturbed soils in various ecosystems of Russia. Natural soils in the southern taiga (Leningrad region and Novgorod region), northern taiga (Komi republic), forest-tundra, and tundra (Nadym city and Salekhard city) were investigated using next-generation sequencing (16S rDNA amplicon sequencing). In each natural bioclimatic zone, anthropogenically disturbed quarry soils or agriculturally transformed soils were also investigated. It was found that Proteobacteria, Actinobateriota, Acidobateriota, Bacteroidota, Chroloflexi, Planctomycetota, Verrucomicrobiota and Firmicutes phyla were dominant in natural soils, with minor differences between agrosoils and mature soils. In the soils of quarries, there were revealed processes of declining diversity of microbiome communities and the replacement of them by bacterial communities, different from natural and agrogenic soils. Thus, the microbial community is the most sensitive indicator of anthropogenic soil amendments and can serve to assess the success of soil self-restoration after human intervention.

1. Introduction

The direction of soil microbiology has been developing very rapidly in recent years, but often these studies are very specialized and focused on individual objects; currently, the global picture of the soil microbiome is in the stage of formation [1,2,3].

The soils of Russia’s boreal forests zone and polar belt are the most important agricultural resource in Eurasia, forming a kind of “hidden” food basket of the continent [4]. These soils accumulate essential storages of carbon and key nutrients, whose cycles may be essentially affected by microbial activity. Nevertheless, soil surveys conducted even by routine methods in northern and central Eurasia are severely limited in space and clustered for logistical reasons. This is even more important for the molecular studies of soil bacteriomes that are investigated with the use of modern technology. Moreover, current climatic challenges force us to think about the possible shift of current agricultural practices to the northern regions. The soils of northern Eurasia contain enormous reserves of organic matter, which will be released in the form of carbon dioxide and dissolved organic matter and transformed during warming, changing the chemical composition of the atmosphere and hydrosphere. Despite the fact that soils of boreal and polar ecosystems are used in agriculture less than soils of the chernozemic sub-boreal belt of Eurasia, their agrogenic transformation also takes place, as well as deeper and irreversible disturbances in the form of destruction during open-pit mining. Agrogenic impacts on soils change their humus state and radically transform the microbiome. Farming practices are carried out not only in the northern taiga and forest-tundra subzones but also in the highest latitudes, including the tundra [5]. Open-cast mining of minerals from quarries is still popular, and this leads to the formation of soils on heap dumps, which are not always typical of zonal soil formation. In this regard, post-technogenic soils are an interesting object in the study of the transformation of the microbiome on disturbed lands. By the end of the 21st century, the amount of land relatively suitable for agriculture in the boreal belt may double [6], and warming will not necessarily automatically improve conditions for agriculture due to the possible aridity of the summer months. According to the studies, there is a certain skepticism among researchers of northern agriculture, although interest in the problem has not diminished [4,5,7]. The problem of agricultural expansion also exists in mountain areas [7]. An example of this is the densely populated areas of the Central Caucasus, where deglaciation takes place and the freed areas are occupied by pastures and hayfields [8]. Thus, the expansion of agriculture into the polar and mountain regions will increase, which requires soil and microbiological research.

The soil microbiome has a crucial role in the soil profile development and implementation of major soil–biochemical processes [1,3,9]. Soil microbial community is one of the critical factors in the realization of elementary soil processes [2]. It is especially important during the very early stages of soil recovery after strong anthropogenic influences [10,11]. Biogenic and abiogenic interactions are assumed to be most active in the primary stages of soil formation, so initial soil formation can be used as an informative model to parameterize pedogenesis [12]. New-generation sequencing techniques now provide a huge amount of data on the taxonomic and functional diversity of the soil microbiome [9]. Data on changes in the taxonomic composition of the soil microbiome in the zonal aspect are clearly insufficient, especially for northern regions with harsh climatic conditions and limited soil fertility. Thus, there is a direct task to understand how the taxonomic and functional composition of the microbiome changes depending on external conditions. In the future, it is possible to solve the reverse problem—to find out how soil quality can be regulated through the composition of the microbiome. These data can be used to manage the microbial factors of soil formation. Key soil formation processes are directly or indirectly related to the activities of the soil microbiome. The soil cover is constantly under anthropogenic impact. Initial soils in all natural zones change under the influence of anthropogenic factors (oil and natural gas production, and the mining of ores and other fossil fuels) and agrogenic impact. Therefore, it is also necessary to analyze the microbiological diversity in disturbed soils to obtain a complete picture of the soil microbiome in different natural conditions. Disturbed soils can also serve as model objects for understanding the rate of formation of climax microbial communities and the processes of self-recovery of the soil microbiome after technogenic and anthropogenic impacts [13,14]. The study of the microbiome of agrogenic soils, especially in the northern latitudes, is extremely important in the context of studying the potential of northern soils for efficient agriculture in the Arctic and Subarctic. This is especially important for the very initial stages of soil recovery after severe anthropogenic impacts. Therefore, the accumulation of data on the soil microbiome in various technogenic and anthropogenic environments is very useful for creating evidence-based databases for environmental engineers and decision-makers in soil and vegetation restoration [12].

There are numerous studies devoted to the dynamic in the taxonomic composition of the microbiome of various soils. There are also studies related to various geochemical variations in the soil [15], changes in soil microbial communities under the influence of various external factors [16,17,18,19], the microbiome of uranium deposit dumps [20], and various soils and soil-like bodies on mining deposit dumps [21,22,23]. However, studies of the soil microbiome in Russia are few, although its territory is covered by many natural zones. There are a few studies about the soil microbiome in Russia using modern high-throughput sequencing methods [9,10]. There are sporadic publications on the soil microbiome of large cities in the boreal belt [24] and in arctic regions [25]. Most of the published data concern the European part of Russia [11,12]. Less data are available for Western Siberia [26]. For Eastern Siberia, the data are generally sparse [27]. This indicates that both natural and anthropogenically disturbed soils are extremely understudied from the standpoint of soil microbiology and taxonomy.

A very low amount of microbiological research of soils in northern and central Eurasia is largely connected with logistical problems and the vast areas not covered even by traditional soil surveys. Nevertheless, these areas are the most important land resource that can be involved in agriculture in the coming decades. Therefore, it is very important to know what happens to the microbiome of already disturbed soils of polar and boreal taiga ecosystems. Thus, the current hypothesis of our study was that boreal and polar soils can be an informative model for analyzing the role of external factors—soil quality and types of soil disturbance in the formation of taxonomic and functional composition of the microbiome. The methodology of the study consisted of the study of invariant combinations of soil formation under the influence of anthropogenic factors in comparison with natural undisturbed soils in order to analyze the principle vectors of soil bacteriome development.

Knowing this, the aim of the current study was to investigate the taxonomic composition of the microbiomes of mature, agrogenic, and anthropogenic soils of the polar and boreal belts of the European territory and the North of Western Siberia. The objectives of the study included: (1) to investigate the basic chemical parameters of soils; (2) to investigate the agrochemical parameters of soils; (3) to investigate the taxonomic composition and biodiversity parameters of the microbiome of natural, agrogenic, and technogenic soils of the taiga and forest tundra.

2. Materials and Methods

2.1. The Study Sites

All samples of investigation were sampled in several key points in different natural zones in Russia, with natural and anthropogenic disturbed soils. Six key sites for soil sampling were selected. Sampling locations vary from the natural region of the southern taiga to the southern tundra. The locations of the sampling areas are presented in a geographic map (Figure 1).

The first site—South taiga—Umbric Retisols in the surroundings of Borovichy city (sample code—B, Novgorod region, European part of Russia) with agricultural soils and newly formed soils of dumps of former heaps of mines. The climate in the region is continental, specifically humid continental. The site is located on the Msta River 170 km from Veliky Novgorod, 320 km from St. Petersburg, and 430 km from Moscow. The Novgorod region is located in the forest zone, which is divided into two subzones—taiga and mixed forests. Along with coniferous and softwood species, there is a small admixture of hardwood species (oak, linden, maple, elm, and ash). Significant areas of the southern taiga subzone are occupied by swamps and meadows.

The second site—South taiga—Rendzic Leptosols in the vicinity of the Elizavetino settlement (sample code—E, Gatchina district, Leningrad region, European part of Russia) with agricultural soils and the soil of the bottom of a limestone quarry. The climate is transitional from marine to continental. The region is located in the southern taiga belt with a predominance of coniferous forests.

The third site—Northern taiga—in the vicinity of Ukhta city (sample code—U, Komi republic, European territory of Russia) with sandy Podzol as mature soils and various Technosols. Located in the central part of the Komi Republic. The climate is continental subarctic with long, cold winters and short, warm summers.

The fourth site—Tundra—in the vicinity of Vorkuta city (sample code—V, Komi republic, European territory of Russia) with Histic Gelisols as zonal soils and various primary soils on mining heaps and agricultural soils. Vorkuta is located in the Polar Urals about 150 km north of the Arctic Circle and 180 km from the coast of the Arctic Ocean. The climate is moderately continental. Winters are long and cold, summers are short, and warm in the south and cold in the north. The forests are dominated by spruce, pine, birch, aspen, larch, fir, and Siberian cedar occur. In tundras willows, bogwood, and dwarf birch prevail. The greatest species diversity is characterized by grasses, mostly perennial.

The fifth site—the northern part of the Western Siberia investigation was conducted in the vicinity of Nadym city (sample code—N, forest tundra). Located on the left bank of the Nadym River, 290 km southeast of Salekhard. Nadym has a continental subarctic climate. The flora includes spruce, larch, gray alder, birch, Siberian cedar, and many shrubs (cowberries, blueberries, blueberries, etc.).

The sixth site—Salekhard city (sample code—S, south tundra). The mature soils were Podzols and Gelisols, correspondingly, with agriculturally transformed soils and soils of the mining heaps of sandy quarries. The city is located on the Polui Upland of the West Siberian Plain at the confluence of the Polui River into the Ob River. Salekhard has a subarctic climate with short, mild summers and severely cold winters. The flora is represented by birch (mostly dwarf), willow, and the like. Diversity in low plants, herbs, and shrubs: Ledum, lingonberries, etc., are common.

Thus, a wide spectra of locations have been included in our research. To maintain the comparability of results, samples were performed from a depth of 0–10 cm in all cases. The topsoils were presented by A (humus) horizons, Ap (arable humus horizons), and Au (sod horizons of initial primary soils).

2.2. Chemical and Microbiological Analysis

For the topsoil horizons, an average sample weighing 500 g was formed for routine soil analyses. The high mass of soil samples was used to avoid the influence of soil heterogeneity in case of agrogenic and mining factors (e.g., lots of stones). For microbiological analysis, 2 g samples were taken in sterile tubes (in 3 replications). Samples for microbiological analysis were transported at +4 °C and stored at −20 °C.

For agrochemical analyses, samples were air-dried, ground, and passed through a 2 mm sieve. The pH of the soil solution was measured by the pH meter Milwaukee Mi106 (Milwaukee Electronics (USA)). The soil solution was prepared in a ratio of 1:2.5 with distilled water [28] after sedimentation of fine particles on the bottom of a measuring glass. Soil organic carbon (SOC) content was determined by the Tyurin (Walkley-Blak) method, based on the oxidation of soil organic matter with a mixture of potassium dichromate and concentrated sulfuric acid [29]. Then, the remnant of potassium dichromate was titrated by Mohr salt (NH₄)₂Fe(SO₄)₂·6H₂O) with the presence of phenilantranile acid solution in the role of a red-ox indicator. The content of available forms of ammonium nitrogen (N−NH₄) and nitrate nitrogen (N−NO₃) was determined using a potassium chloride solution. The amount of free potassium and phosphorus was determined by the Kirsanov method by phosphorus and potassium extraction with 0.2 N hydrochloric acid solution [30,31]. Ammonium and nitrate nitrogen concentration was determined photometrically. Potassium concentrations were fixed with the use of flame photometry.

The total soil DNA was isolated from 0.5 g of soil by using the MN NucleoSpin Soil Kit (Macherey-Nagel, Dueren, Germany), using a Precellys 24 homogenizer (Bertin, Montigny-le-Bretonneux, France) according to the manufacturer’s protocol. Quality control was carried out by PCR and agarose gel electrophoresis. DNA was purified and diluted according to Illumina sequencing requirements (200–400 ng per sample). The sequencing of the V4 variable region of the 16S rRNA gene was performed on the Illumina MiSEQ sequencer (Illumina, San Diego, CA, USA), using the primers 515f (GTGCCAGCMGCCGCGGTAA) and 806r (GGACTACVSGGGTATCTAAT) [32].

The general processing of sequences was carried out in R 4.0 [33], using dada2 (v. 1.14.1) [34] and phyloseq (v. 1.30.0) [35] packages, according to the authors’ recommendations. The 16S rDNA amplicon sequences were processed according to the dada2 pipeline. Sequences were trimmed by length (minimum 220 bp for forward and 180 bp for reverse reads) and quality (absence of N, maximum error rates maxEE were 2 for both forward and reverse reads). ASVs were determined according to the dada2 algorithm, and chimeric ASVs were removed by the “consensus” method. The taxonomic annotation was performed by the naive Bayesian classifier (provided in the dada2 package, default settings), with the SILVA 138 database [36] used as the training set; phyla names were corrected according to LPSN [37]. The software was fetched from the “conda forge” channel (https://conda-forge.org/, accessed on 15 July 2023) and GitGub repositories (https://github.com/, accessed on 15 July 2023).

The alpha- (observed ASV and Simpson indices) and beta-diversity (Bray–Curtis distance) metrics were calculated using the phyloseq and vegan packages [38]. The PCoA ordination of Bray–Curtis distances were drawn using the phyloseq package. The PERMANOVA analysis was carried out using the vegan package. Alongside the specific parameters mentioned earlier, the protocol of data processing was performed according to standard protocol (link) on quality control that can be found on https://github.com/a-zverev/16s-amplicon-processing (accessed on 15 July 2023).

3. Results and Discussion

General soil chemical characteristics for superficial soil samples are provided in Table 1. Normally, the highest content of soil organic carbon was in agrosoils and the lowest in primary soils of mines. This is typical for these compared pare of soils, because in the bottom of quarries and on mining heaps the soil formation starts from the zero stage [39,40]. The time lag in organic carbon accumulation in quarry soils compared to agrosoils can be up to 100 years and more. Agrosoils start their development from the already prepared organic–mineral matrix, while quarry soils start theirs from a stage with a minimal content of organic material [41,42].

The pH values are quite varied within the sampling places, and thus, leached sandy-textured soils (Nadym) were the most acidic (pH—5.2–5.4), while the loams of the Salekhard soils were closer to neutral (pH—6.1–6.7). The majority of soils sampled were close to neutral pH values. The most alkaline soils were from Elizavetino (pH—7.2–8.3). The temporal change of soil acidity–alkalinity strongly depends on the initial state of the soil fine earth and the composition of soil parent materials [43,44]. Therefore, the reaction of the medium is the most important predictor of variation in the taxonomic composition of the soil microbiome and Bactreriome in particular.

Only some acidification of agrosoils in comparison with mature ones has been revealed, as is known for arable soils of the boreal climate [45]. As for the key forms of nutrients, they were variable as well, and the lowest percentages of available forms of elements were typical for primary soils mines, and the highest for agricultural soils. The SOC concentrations were highest in agrogenic or natural soils. In primitive quarry soils, SOC concentrations were often below 1%.

Table 1. Chemical soil characteristics of the superficial soil horizons.

Sample	SOC	pH	P	K	N-NO3	N-NH4
	%		mg/kg
Bmature	2.50	7.40	15	156	1	32
Bagro	2.30	7.20	19	170	2	33
Bmine	0.45	5.60	10	100	1	21
Emature	2.15	7.40	25	120	1	12
Eagro	2.45	7.20	23	150	1	11
Emine	0.35	8.30	12	80	1	10
Umature	1.70	7.15	8	120	2	24
Uagro	1.90	7.00	12	125	2	27
Umine	0.50	7.10	8	45	2	12
Vmature	0.80	6.90	13	80	2	25
Vagro	0.70	6.70	12	67	2	29
Vmine	0.70	6.70	9	60	2	12
Nmature	1.20	5.20	5	20	2	12
Nagro	2.00	5.40	5	30	2	11
Nmine	0.30	5.00	2	12	2	9
Smature	2.16	6.70	5	55	3	13
Sagro	2.40	6.50	5	40	5	13
Smine	1.45	6.10	3	20	3	12

Table 1. Chemical soil characteristics of the superficial soil horizons.

Sample	SOC	pH	P	K	N-NO3	N-NH4
	%		mg/kg
Bmature	2.50	7.40	15	156	1	32
Bagro	2.30	7.20	19	170	2	33
Bmine	0.45	5.60	10	100	1	21
Emature	2.15	7.40	25	120	1	12
Eagro	2.45	7.20	23	150	1	11
Emine	0.35	8.30	12	80	1	10
Umature	1.70	7.15	8	120	2	24
Uagro	1.90	7.00	12	125	2	27
Umine	0.50	7.10	8	45	2	12
Vmature	0.80	6.90	13	80	2	25
Vagro	0.70	6.70	12	67	2	29
Vmine	0.70	6.70	9	60	2	12
Nmature	1.20	5.20	5	20	2	12
Nagro	2.00	5.40	5	30	2	11
Nmine	0.30	5.00	2	12	2	9
Smature	2.16	6.70	5	55	3	13
Sagro	2.40	6.50	5	40	5	13
Smine	1.45	6.10	3	20	3	12

The Characteristics of the Soil Microbiome

The relative abundance of the soil microorganisms at the phyla level is provided in Figure 2. Here, we compared mature soils with agrogenic and technogenic soils, where the last two were combined into one group, which aimed to highlight the anthropogenic effect on the soil microbiome. In total, 29 phyla of microorganism have been identified in the investigated soils. The most abundant phyla of microorganisms were: Proteobacteria, Actinobateriots, Acidobateriota, Bacteroidota, Chroloflexi, Planctomycetota, Verrucomicrobiota, and Firmicutes. This list well corresponds with previously obtained data [10]. It follows from the figure that, in any case, in the course of anthropogenic impact on soils there is a change in the composition and structure of the soil microbiome. Alongside the parameters of alpha- and beta-diversity, it will become clearer which reasons are the main ones for these changes.

The alpha-diversity metrics are given in Figure 3. It is clear that agrosoils, soils of mines, and natural soils form separated groups in terms of alpha-diversity indexes. The highest deviation of biodiversity is typical for soils of mines in comparisons with the other two types of soils. In the soils of quarry-dump complexes, a great number of ecological microniches and factorial conditions are formed, which is most likely the main reason for the shift in microbiological diversity compared to more homogeneous soil ecosystems of agrocenoses and natural landscapes.

According to the taxonomic composition (Figure 2), a very high proportion of Firmicutes characterizes the soils of Yamal, even more than Proteobacteria, which is generally atypical for soils. This is probably due to the ability of Firmicutes to form spores and thus their ability to tolerate low temperatures [39,40,45]. The use of soils of Yamal in agriculture reduces the share of Firmicutes, but it is still the most frequent phyla in abundance, i.e., even using the soil in an agricultural crop does not allow for the removal of the microbiome inherited from the natural soil. In addition, the undisturbed quarry soil has more Bacteroids, probably as a result of using the soils as pasture soils. In contrast, agrosoils have more Acidobacteria and Chloroflexi, typical soil phyla [46,47]. This may be a consequence of intense plant–microbe interactions when plants release a whole range of organic substances into the soil. This hypothesis is well supported by the alpha-diversity data: for the Yamal agrosoils, an increase in the number of ASV compared to the undisturbed soil is shown, which may be associated with the application of nutrients as a result of both agrotechnical and simple plant growth.

According to beta-diversity data (Figure 4), samples of undisturbed soils and agrosoils are not far apart, indicating that the development of agrosoil microbiota is formed by changes in the number of minor bacterial taxa of the original soils (using “heritaged” taxa), rather than by forming our own bacterial pool. Quarry soils are quite different from agrosoils and natural soils, which are associated with the formation of the microbiome as if from scratch [48,49,50].

For soil communities near Vorkuta, the composition of phyla is typical of soils, and the low proportion of Firmicutes in undisturbed soils is interesting. Perhaps, despite the cold climate, suboptimal conditions are formed in these soils, where spore formation does not prove to be a competitive advantage [27,51,52,53]. In contrast, in disturbed soils, conditions are worse (openness to the cold), and the abundance of Firmicutes is significantly larger. The alpha-diversity values between the disturbed and undisturbed soils do not reliably differ, but the beta-diversity values indicate greater and substantial variability in the composition of disturbed soils, including both communities generally similar to undisturbed ones, and two separate isolated clusters. Communities of soils in the vicinity of Ukhta, sampled in the region adjacent to Vorkuta, also demonstrate a similar pattern: with typical for soils taxonomic composition without a significant difference in the representation of phyla in disturbed and undisturbed soils, and equal values of alpha-diversity, communities differ in the representation of individual taxa (forming different clusters in the analysis of beta diversity).

A high proportion of Chloroflexi and Cyanobacteria in disturbed soils characterizes the soils around Nadym, probably; autotrophy plays an important role in these soils. In anthropogenically disturbed soils, it is also worth noting the increased proportion of Firmicutes as compared to undisturbed soils. According to the alpha-diversity data, these soils have less species richness than the average for the compared soils, but the number of species in the disturbed/undisturbed soils does not reliably differ. According to the beta-biodiversity results, the samples of disturbed and undisturbed soils form an extended cluster, which indicates a low change in the taxon representation for the compared soils [54].

In the samples of carbonate from the southern taiga soils of the Leningrad region (sample code—E), in the taxonomic composition at the level of phylum in the disturbed soils compared to undisturbed ones, we can note the increase in Verrucomicrobiota and decrease in Chloroflexi, Gemmatimonadota, and Cyanobacteria. According to alpha- and beta-diversity, the samples of disturbed and undisturbed soils are close to each other, which can be explained by relatively comfortable climatic conditions and increased reclamation activity by plants.

Podzolic southern taiga soils near Borovichi are characterized by a very clear variability in both alpha- and beta-diversity data. It is connected with acidic poor substrates analyzed on a par with the mining plots. This separation can be clearly seen from the beta-diversity data, where some disturbed soils form a cluster with undisturbed ones, and some form their own, different from all the others. Because of the merging of single samples, the phyla representation data show moderate differences: we can note a slightly higher proportion of Actinobacteria, Nitrospirota, and Firmicutes characteristic of disturbed soils [25]. The obtained data do not answer questions about the features of the cycle of biogenic elements in the studied soils. This requires more detailed studies within each soil horizon in the time dimension. However, data on the taxonomic diversity of the microbial community substantially close knowledge gaps about the core and minor components of soil bacteriome of the East European Plain [10].

In general, alpha-diversity indices are not very informative, since different disturbed soils can have different characteristics—they can be both very poor in species and, conversely, very rich in minor members of the microbial community. The general trend here is rather in the hypervariability of the index values of disturbed communities as compared to undisturbed ones, which well corresponds with data obtained earlier [55]. This variability is clearly visible in Borovichi and Yamal, and to a less extent it is expressed in Elizavetino and the vicinity of Nadym. In the case of soils in the vicinity of Ukhta, the index values practically do not differ. It is also interesting to note the sharp increase in diversity in the agrosoils of Yamal compared to natural soils. This is most likely due to agropractices, which radically change the agrosoils compared to the original permafrost-affected Gelisols. An additional factor is the relatively low species richness of natural soils.

Based on the beta-diversity, we can distinguish two types of distribution: grouping by location (soil disturbance is not expressed) or by soil condition (soil disturbance is significantly expressed). The soils around Elizavetino, Salekhard, and Ukhta are grouped by location. The extended, but still rather unified cluster is characteristic of soil samples from Nadym, where apparently, the specifics of acidic sandy sediments, on which all soils of this object are formed, are in the formation of microbial biodiversity here. However, in the case of a series of samples from the southern taiga ecosystems near Borovichi, the undisturbed soils are already distanced from the disturbed ones into a separate cluster; the same can be said about Vorkuta. These distances are set by the number of differences in soil microbiomes, i.e., Borovichi and Vorkuta are subjected to the highest changes, while the composition of communities in Elizavetino is not so different.

The wide diversity of soils in Northern European Russia and Western Siberia is caused by a combination of natural factors of soil formation and various types of anthropogenic activity. Meanwhile, we have very limited and fragmentary data on the microbiome of key soil types of the center and north of Eurasia, listed by single publications [9,10,12]. Therefore, in order to compile a complete “microbiome portrait” of such large territories, one should consider not only the metagenome of mature (natural) soils in various natural zones but also the features of microbial diversity in anthropogenic disturbed soils (technogenic and post-technogenic, agrogenic and post-agrogenic, post-meliorative, etc.). There is also a need to recognize the metagenome of soils on the parent material of different mineralogical and particle size distributions since this initial microbiome is the basis for the imposition of other factors that determine the final structure of microbial communities [13]. For modeling research of the formation of climax microbial communities, it is convenient to use different aged technogenic and agrogenic disturbed landscapes in combination with analysis of the microbiome of reference (museum) soil samples [13,14], as well as to study separately the microbiome functions of urban soils and soils of urban agglomerations [56]. The best overview of the ecological and service functions of the soil microbiome in soils of different natural zones and different landscapes can be obtained by applying metagenomic sequencing methods in combination with the analysis of soil biomarkers (lipids, phenolic derivatives, lignin markers, oil markers, etc.). In addition, investigations should take into account the enzymatic activity of soils, in order to assess their ecological and physiological activity. Thus, to make a complete view of the functioning of the soil microbiome, an integrated approach and optimization of the methodology in further research is necessary [13,57,58,59,60,61]. It is evident that agrogenic exposure and open mining lead to a differentiation of ecological niches in soils compared to natural soils. Meanwhile, the study is interesting for not so much environmental niches, but potentially implemented environmental licenses [62].

4. Conclusions

The carried-out studies of the soil microbiome of the taiga-forest and forest-tundra regions of Northern European Russia and Western Siberia have significantly supplemented the information on the taxonomic diversity of the soil microbiome and largely filled the existing gaps in the geographic coverage of microbiome studies of the soil cover of Northern Eurasia. At the principal taxonomic level, the composition of the microbiome is comparable for all the soils we studied, and the key dominant phyla were: Proteobacteria, Actinobateriota, Acidobateriota, Bacteroidota, Chroloflexi, Planctomycetota, Verrucomicrobiota, and Firmicutes. Representatives of another 21 phyla play a less quantitative role but are still very important for the formation of a complete picture of the microbial diversity of soils of the northern taiga and tundra regions. For natural soils and agrosoils, the differences in the microbiome composition are not so great, still, in agrosoils, the essential part is inherited from the natural soil, and then, in technogenic soils of quarries, the differences in comparison with natural soils become very significant. Differences in microbiological diversity between technogenic-disturbed soils in different natural zones may be related to abiotic factors (pH, SOC, or nutrient content) resulting from the natural recovery processes of disturbed soils or from recultivation processes. A similar pattern holds for agrogenically disturbed soils. The microbial pool of organisms in them is greater than in pristine soils. Agricultural usage leads to the formation of new soil types, especially in the tundra and forest-tundra zones, which were not initially found there.