Wildfires’ Effect on Soil Properties and Bacterial Biodiversity of Postpyrogenic Histic Podzols (Middle Taiga, Komi Republic)

Abstract

Data on the main properties of Histic Podzols in the pine forests of semi-hydromorphic landscapes in the middle taiga of the Komi Republic after forest fires are presented. A decrease in topsoil horizon thickness by more than 7.6 times, an increase in litter density by 6 times, and a decrease in litter stock by 4 times were observed in postfire soil. There was an increase in carbon content in the pyrogenic horizon (48%) and in the upper part of the podzolic horizon—from 0.49 at the control plot to 1.16% after the fire. The accumulation of all studied trace metals (Cu—from 2.5 to 6.8 mg × kg⁻¹; Zn—from 35.7 to 127.4 mg × kg⁻¹; Ni—from 2.2 to 8.1 mg × kg⁻¹; Pb—from 1.4 to 28.3 mg × kg⁻¹; Cd—from 0.3 to 1.1 mg × kg⁻¹) in soils after wildfires was recorded. The effect of the fire can be traced to a depth of approximately 20–30 cm. A significant influence of the pyrogenic factor on the alpha and beta bacterial diversity was noted. The bacterial response to a forest fire can be divided into an increased proportion of spore-forming and Gram-negative species with complex metabolism as well.

1. Introduction

The human impact on natural terrestrial ecosystems, which has recently expanded, leads to changes in the ecosystem’s functioning and makes monitoring work extremely relevant. One of the factors influencing these changes is forest fires [1,2,3].

Wildfires play a significant role in the modern dynamics of taiga ecosystems in the Northern Hemisphere [4,5]. Depending on the fire intensity and type, the forest stand density, productivity and the dominants of the upper and subordinate layers of the vegetation cover change [6]. Pine forests are most susceptible to pyrogenic effects. This is probably determined by the drier forest growth conditions. The effect of fires on soils has been studied quite well in the driest pine lichen forests [7]. A significant number of works have been devoted to the assessment of pyrogenic activity using charcoal in Histosols during the Holocene period [8]. However, at the same time, the greatest indicator role under climate change can be played by the soils of semi-hydromorphic landscapes, with the thickness of the organic horizon ranging from 20 to 50 cm. Histic Porzols and Histic Albeluvisols in the middle taiga are exposed to pyrogenic effects in extremely dry years. The soils of semi-hydromorphic landscapes are widespread in the European North [9] and occupy one third of the forest territory of the Komi Republic. Research concerning the assessment of the impact of fire on such soils is sporadic.

Pyrogenesis is one of the main natural or anthropogenic factors that changes the soil properties [10,11,12]. As a result of the pyrogenesis impact, the pH and morphological soil properties change [13,14,15,16,17]. The fire’s influence on tree vegetation and its subsequent post-pyrogenic change have been studied in sufficient detail. A literature analysis reveals that most studies aimed at pyrogenic changes in forests characterize the territory of Siberia [14,15,16]. Modern research describing soil changes during fires in the European North is rare, with a predominance of publications on the vegetation dynamics during post-pyrogenic successions. A significant part of the boreal forest soils is now at a stage of postpyrogenic restoration, but, at the same time, investigations on the postpyrogenic dynamics of soil properties in the European North of the Russian Federation are sporadic [17]. Meanwhile, all available studies have been conducted in postfire areas a certain time after the fire (the minimum is 1.5–2 months), and research results obtained immediately after a forest fire (2–5 days later) are not available in the literature. Moreover, there are no microbiological studies of postpyrogenic soils in the European North. Soil microorganisms are a key factor in soil formation during demutation changes; they are characterized by high sensitivity to changes (natural and anthropogenic) in the environment [18], which allows them to be used as a criterion to assess the soil’s condition after various disturbances [19,20]. Several studies have been described in the literature devoted to changes in the soil microbiome using 16S rRNA gene sequencing both a few weeks after a forest fire [21,22] and with longer chronoseries [23,24]. Despite the increasing number of studies about soil structure and aggregation, there are still a few common aspects that can be established for microbiota effects, especially during fire events. Among the most common bacterial genera and species referenced in soils subjected to different fire intensities, the following can be found: Pseudomonas spp. (for example, Pseudomonas fluorescens), Arthrobacter spp., Burkholderia spp., Cohnella spp., Massilia spp., Blastococcus spp., Microvirga spp., Stenotrophomonas spp., Bacillus spp., and Clostridium spp. [25,26,27].

Unfortunately, data on the soil microbiome after pyrogenic impact are incomplete and often contradictory, which could be caused by differences in the soil type studied and the geographical features of the study area [28,29]. Differences in the research methodology should also be taken into account [25].

The behavior of various chemical elements during forest fires depends on a broad complex of factors, which include the fire type (surface, crown, or peat fires), the state of forest combustible materials, the weather conditions, and the distribution nature of the elements in the components of the forest ecosystem, in addition to the geochemical characteristics of the elements and fire intensity as a major factor that determines the impact of fire on the soil’s physical, chemical, and biological properties. Substances of the first hazard class, such as mercury, cadmium, arsenic, radioactive cesium, and strontium, actively migrate through the atmosphere during forest fires; lead, plutonium, and some other elements migrate to a lesser extent; and the least dangerous elements are zinc, manganese, and stibium [30]. The elements’ emissions during a strong fire can reach up to half of their initial content. However, a large role among pyrogenic emissions belongs to various organic and inorganic compounds and chemical elements, including heavy metals, polycyclic aromatic hydrocarbons (PAHs), and radionuclides found in the soil, litter, bark, and wood of trees. Their deposition in new places, undoubtedly, will change the geochemical background of soil and vegetation cover. These substances, together with aerosol particles, can be transported over thousands of kilometers. Studies of the migration of heavy metals, PAHs, and radionuclides during forest fires are devoted mainly to the composition of smoke aerosols [31,32,33,34,35]. However, it is possible to obtain valuable information about the behavior of these elements not only “outside” but also “inside” the ecosystem using land-based techniques.

In this regard, a comprehensive assessment of the ecological and biogeochemical state of postpyrogenic soils in a freshly burned area in the European North is proposed. The following objectives were formulated: (1) to analyze the soil morphology and chemical characteristics of the fine earth; (2) to characterize the heavy metal concentrations in postpyrogenic soil and assess the regularity of their migration throughout the soil profile; (3) to investigate the taxonomy composition of soil bacteria; and (4) to analyze the parameters of the alpha- and beta biodiversity of soil microorganisms in relation to pyrogenic impacts.

2. Materials and Methods

In order to study pyrogenic changes in the soils of the Komi Republic, a postpyrogenic plot in the territory of the Syktyvdinsky district, which was burned in August 2022, was chosen. Immediately after the fire (fire detection date was 4 August 2022, fire extinguishing date was 7 August 2022), a field object description and sampling were carried out (14 August 2022). The study site was located 2 km away from the Pychim village to the south (28th quarter of the Sludsky district forestry), with approximate coordinates of 61°56′38.4″ N, 50°22′17.4″ E (Figure 1).

The climate of the study area is moderate continental, with short but rather warm summers and a rather cold, long winter. Frosts are possible even in July, and autumn and spring are cold and long. The average annual temperature is +1.3 °C. The average annual wind speed is 2.6 m/s. The average annual air humidity is 77%. The rainfall in the Komi Republic is significant, with precipitation even during the driest month: about 700 mm of precipitation falls annually.

A wildfire at the study area occurred in 2022 and overtook the entire lower forest canopy. A mossy tirr burned out completely. The total fire area was 1.02 hectares. The fire severity at the study area was moderate, according to data from the Ministry of Natural Resources and Environmental Protection of the Komi Republic [36,37]. Organic horizons were damaged throughout the entire burnt area, but to various degrees: they were charred and only the forest litter was burned in a number of locations; in other cases, they were completely burned out. The litter burning occurred in patches in areas with the driest plant material. The plot occupied a flat area without any slopes.

An unburned forest plot with the same soil type at a distance from pyrogenic influence was used as a control (Figure 2). The vegetation before the wildfire at the studied plot was represented by blueberry–spruce–pine forest with an admixture of birch (Figure 2). The species included Pinus sylvestris L., Picea abies (L.), Betula pubescens Ehrh., Populus tremula L. (about 7 years old), Sorbus aucuparia L. (about 7 years old), Frangula alnus Mill. (about 4 years old), Juniperus communis L., Vaccinium myrtillus L., Vaccinium uliginosum L., Ledum palustre L., Equisetum sylvaticum L., and Sphagnum L.

The vegetation after the fire in the studied area was represented by pine forests with an admixture of birch (Figure 2). A boundary between the postfire and control areas was an ameliorative ditch. The predominant species of the plant community were Pinus sylvestris L., Betula pubescens Ehrh., Populus tremula L. (about 7 years old), Cladonia Hill ex P. Browne, Ledum palustre L., and Vaccinium uliginosum L.

Two objects were studied: postfire and control. Three soil profiles in each study plot (both from control objects and after the fire) were investigated; in this paper, generalized soil profiles for both situations are described. Soil samples at each sampling point were taken from each depth of soil horizons using the volume-weight method to determine a soil density of undisturbed structure. The total number of soil samples was 40. Soil identification was carried out using the World Reference Database of Soil Resources [38].

All samples were dried at room temperature at the Department of Applied Ecology of St. Petersburg State University and then sieved through a 2 mm sieve (2 g soil samples were taken for microbiological analyses in sterile tubes in 4 replications and transported at +4 °C and stored at −20 °C). All soil properties were studied in fine earth. The complex analytical soil characteristics included the determination of chemical, physical, and physicochemical soil indicators (such as soil moisture content, pH_H2O, soil density, particle size distribution, and content of carbon and nitrogen) using generally accepted methods [39,40]. The carbon content (C_tot) and nitrogen content (N_tot) were determined by dry combustion on an EA-1100 analyzer (Carlo Erba, Milano, Italy).

The particle size distribution was determined by the Kachinsky pipette method with the pyrophosphate peptization of microaggregates. The determination of phosphorus and potassium mobile compounds was carried out according to the Kirsanov method modified by the Central Scientific Research Institute of Agrochemical Service of Agriculture (CSRIASA) (Russian National Standard GOST R 54650-2011 [41]). Available forms of nitrogen (NO₃⁻) were determined according to the ISO 14256-1 standard [42], which first extracts exchangeable ammonium (NH₄⁺) from the soil with a solution of potassium chloride and then photometrically measures the colored solution. The level of basal respiration (V_basal) was measured according to a method based on recording the CO₂ response in native soil [43]. The microbial biomass content (C_mic) in soil was determined by the fumigation method [44,45,46].

The content of heavy metals (Cu, Pb, Cd, Zn, Ni) in the studied soils was determined via atomic absorption spectrometry using an atomic absorption spectrophotometer, the Kvant 2M (Moscow, Russia), following the “Soil quality—determination of cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), manganese (Mg), nickel (Ni) and zinc (Zn) in aqua regia extracts of soil—flame and electrothermal atomic absorption spectrometric” method (ISO 11047:1998 [47]).

The values thus obtained were compared to the available approximate permissible concentrations (APC) and maximum permissible concentrations (MPC) in the Russian Federation, specified in sanitary regulations and standards 1.2.3685-21 “Hygienic standards and requirements for ensuring the safety and (or) harmlessness of habitat factors to humans” [48] and methodology instructions 2.1.7.730-99 “Hygienic assessment of soil quality in populated areas” [49].

The radial differentiation coefficient (R), proposed by Perelman and Kasimov [50], is intended to study the heterogeneity of the vertical distribution of chemical element concentrations in soil profiles. The radial differentiation coefficient, as opposed to the form of the profile distribution graph, which provides only a qualitative characteristic of distribution heterogeneity, demonstrates a quantitative assessment of the soil formation influence on the accumulation and dispersion of individual chemicals in soil horizons. Studies of the profile distributions of chemical elements in pyrogenic soils are a very promising direction in modern landscape geochemistry for the following reasons. The study of the radial water migration of elements and compounds in pyrogenic soils can be useful from the point of view of their participation in biogeochemical cycles, which are not fully studied in postpyrogenic ecosystems.

The radial differentiation coefficient is calculated by the following formula:

Ri = Ci_hor/Ci_rock,

(1)

where Ci_hor is the i chemical element content in the soil horizon, and Ci_rock is its content in the soil-forming material, where the influence of soil-forming processes on the chemical composition is conditionally negligible.

Moreover, in order to analyze the taxonomic diversity and structure of soil bacteria in the soil chronoseries of postfire ecosystems, total DNA was obtained from soil samples in quadruplicate using metagenomic sequencing methods, and high-throughput 16S rRNA gene sequencing was carried out. Sequencing and primary data processing were carried out on an Illumina MiSeq device (Illumina, Inc., San Diego, CA, USA) at the Research Equipment Sharing Center “Genomic Technologies and Cell Biology” of the All-Russia Research Institute of Agricultural Microbiology. The data obtained were processed using the dada2 package in the R software v. 4.3 (R Foundation for Statistical Computing, Vienna, Austria) [51,52]. An analysis of biodiversity and taxonomic composition and a comparative analysis of microbiomes was carried out for them.

A total of 16 amplicon libraries of the variable region 16S rRNA gene were obtained, the total size of which was 276,429 reads. These sequences were divided into 1529 phylotypes using the dada2 package v. 1.28. The taxonomic phylotypes’ annotation was performed with the SILVA 132 (v. 132) database (SILVAngs, Bremen, Germany) [53], used as the training set. A complete description of the metagenomic sequencing method and workflow was presented by [54].

A wrapper from the estimate_richness function from the phyloseq library, which used the diversity function from the vegan package, was used for alpha diversity (for the equations used, see https://rdrr.io/cran/vegan/man/diversity.html, accessed on 22 September 2023). Then, plot_ordination from the package phyloseq, which used the vegdist function from the vegan library, was used for Bray–Curtis analysis (for the equations used, see https://rdrr.io/cran/vegan/man/vegdist.html, accessed on 22 September 2023).

Statistical data processing and analysis were carried out using standard methods in the software packages MS Excel 2016, Past (version 3.20; Microsoft Corp., Redmond, WA, USA), and Statistica 64 (version 10; StatSoft Inc., St. Tulsa, OK, USA).

The normal distribution of the data was verified, and a variance analysis (ANOVA) and post hoc test (Fisher’s least significant difference) were performed. Differences were considered significant at p < 0.05. Moreover, we used principal coordinate analysis (PCoA) to reveal the relationships between the studied components. Both ANOVA and PCoA were carried out for every soil horizon of postfire soil compared to the appropriate soil horizon of control soil.

3. Results and Discussion

3.1. The Effect of Fire on the Soil Properties

The occurrence of a forest fire can be caused by natural causes not related to human activity [55]. However, additional anthropogenic pressure increases both the frequency and distribution area of forest fires [1,56]. In order to assess the human role, it is necessary to study the results of natural forest fires, the origin of which is not due to an anthropogenic factor, as a background. An example of such fires can be found, in particular, on the forested slopes of the Khamar-Daban ridge, where tree fires often occur due to lightning discharges [57].

Due to climate change and increased dry periods, fires in the European part of the Russian Federation have recently spread northward, affecting large areas that are usually less susceptible to pyrogenesis. Forest fire statistics during the fire hazard period are determined by the climatic conditions of the summer. The forest areas affected by fires in the most fire-dangerous years reach values close to those of harvest areas [58]. Therefore, a postfire area in the Komi Republic was chosen as the object of study. The studied areas were semi-hydromorphic before the fire, but, due to dry conditions in the summer of 2022 and lightning, a forest fire broke out in an area where it was not expected.

The soils of the study area are represented by peat-podzol ferruginous illuvial on terminal moraine (Histic Podzols—WRB) with a typical soil profile of Tirr–Oe–Oa,pyr–Epyr–E–Bs–BC–C (Figure 3 and

Table 1. Morphological features of pyrogenic effects on the studied soils.

Plot, Horizon		Change in Organic Horizon	Thickness of Topsoil, cm		Coal Inclusions	Compaction of Topsoil	Soil Density, g/cm3	Litter Stock, g/m2
Control	Tirr	Not detected	23	5	-	-	0.03	25,400	1500
	Oe	Not detected		13	-	-	0.13		16,900
	Oa,pyr	Individual coal particles		5	+	-	0.14		7000
Postfire	Qpyr	Complete burnout	3		+	+	0.19	5700

). The control soil is characterized by a typical morphological structure: a thick podzolic horizon, the lightest in profile, is formed under the forest litter. The ferruginous illuvial horizon Bs, which smoothly passes into the soil-forming rock (BC) horizons, lies beneath it. The soil of this area is characterized by a large thickness of organic horizon (more than 20 cm), represented by mossy tirr; a fermentation horizon Oe with brown, slightly decomposed material; and Oa,pyr with well-decomposed organic matter with signs of former pyrogenic influence.

The top layer of moss organic horizon was exposed to the surface fire impact. The soil of the pyrogenic area is represented by illuvial-ferruginous postpyrogenic podzol on a moraine (Folic Podzols—WRB) with the following soil profile: Qpyr–Epyr–E–Bs–BC–C. Disturbances represented by the complete burning of thick mossy tirr and forest litter are confined to areas of outbreaks where organic horizon burning occurs near tree root systems. Pyrogenic horizons and subhorizons were identified in the studied postfire soil (Figure 3, Table 1).

The pyrogenic impact on soils is largely associated with the burning of organic horizons, downed deadwood, and large woody debris. It should be noted that the fire influence can be traced to a depth of approximately 20–30 cm (Figure 3, Table 1). The pyrogenic horizon was identified in the upper part of the soil profile as a thin layer represented by coals and combustion products. The thickness of the pyrogenic horizon decreases by more than 7.6 times and is equal to 3 cm compared to the total thickness of organic horizons at the control plot of 23 cm. The organic horizon burned unevenly throughout the studied area. The upper part of the organic horizon, mostly represented by fresh litter, burned out in a significant part of the study territory affected by the fire. In places where the litter is drier, burning occurs in patches, and, in this case, it burned almost completely. The partial burning of litter was revealed in some areas where the fermentation and humification subhorizons of litter were preserved (“transformative evolution”, according to [59]). The pyrogenic horizon has a higher density compared to the control plot. Moreover, darkening of the underlying mineral horizons at the postpyrogenic plot is observed due to migratory pyrogenic organic matter. In particular, two different layers were diagnosed in the podzolic horizon, both at the postfire and control plots: Epyr and E. They have equal thickness for both study plots: 7 and 10–13 cm, correspondingly. The podzolic horizon (its upper part) is saturated with flowing organic matter, and the hydrophobization and overconsolidation of the upper mineral horizon Oa,pyr are observed. The Epyr horizon at the control plot appears beneath the forest litter horizon with pyrogenic features. Morphological differences in the middle and lower mineral soil horizons between control and postpyrogenic plots are practically absent or are covered by the sediments’ heterogeneity.

Generally, postfire soils fit poorly into the framework of existing soil classifications. Postfire succession soils are represented by surface organogenic horizons that retain traces of pyrogenic impact: burnt moss tirr. Only the upper part of the organic horizon was burned and charred by the fire and transformed into a pyrogenic horizon. The necessity to change the classification (to include soils disturbed by pyrogenesis) has been discussed by several researchers, including Yu. N. Krasnoshchekov [10,14,16,17,21]. The effect of the fire on the soil macromorphology was pronounced only in the topsoil or superficial soil horizons.

The density of the charred organic horizon is greater in the postfire plot (Table 1), its layering is more noticeable, and the proportion of the living phase is smaller. The density of upper horizons in the postpyrogenic area is 0.19 g/cm³, and, in the control area, it is 0.03 g/cm³. Apparently, this is due to a change in soil cover: the upper, loosest layers of the litter mainly burn out during fires [60], and it also receives such denser components as coal and ash particles [10,21], which can be judged by a significant, on average, twofold (from 20 to 45%) increase in its ash content. Lower horizons do not differ significantly: the podzolic horizon is characterized by a density of 0.9–1.19 g/cm³; then, there is the slight compaction of the soil profile in the middle horizon up to 1.35–1.48 g/cm³ (

Table 2. General soil properties of studied soils.

Horizon, Depth, cm	Soil Moisture Content, %	pHH2O	Ctot, %	Ntot, %	C/N	Vbasal, µg CO2-C/g × hour	Cmic, mg/g	NO3−, mg/kg	NH4+, mg/kg	P2O5, mg/kg	K2O, mg/kg	Soil Density, g/cm3
Control
Tirr 0–5	12.88 ± 0.22	4.7 ± 1.1 **	47.6 ± 1.7	1.4 ± 0.2 ***	34 ***	105.8 ± 1.6 ***	0.06 ± 0.5	1.5 ± 1.12	13.6 ± 1.1	578.0 ± 1.0 ***	350.0 ± 1.5 **	0.03 ± 1.1 **
Oe 5–18	27.54 ± 1.1	4.3 ± 1.0 ***	46.7 ± 1.6 *	1.1 ± 0.1 ***	42 ***	82.2 ± 1.8 ***	0.01 ± 0.0	0.0 ± 1.3	3.4 ± 1.2	236.0 ± 1.1 ***	52.0 ± 1.9 ***	0.1 ± 1.0
Oa,pyr 18–23	25.01 ± 1.2	4.4 ± 1.2 ***	41.7 ± 1.5 **	1.4 ± 0.2 ***	30 ***	4.2 ± 1.4 ***	0.01 ± 0.3	0.6 ± 0.9	10.5 ± 1.0	86.0 ± 1.2 ***	17.0 ± 1.4 ***	0.1 ± 1.2
Epyr 23–30	0.18 ± 0.91	4.6 ± 0.2	0.5 ± 0.1 ***	0.1 ± 0.0	5 **	6.4 ± 0.8 *	nd	0.1 ± 0.55	0.5 ± 0.8	3.0 ± 0.6 **	4.0 ± 0.5 **	1.1 ± 0.0
E 30–40	0.12 ± 0.05	4.7 ± 0.2 *	0.3 ± 0.1	0.1 ± 0.0	3	4.2 ± 0.9 **	nd	0.0 ± 0.8	0.6 ± 0.9	2.0 ± 0.5	6.0 ± 0.6 **	1.1 ± 0.6
Bs 40–55	0.44 ± 0.45	5.2 ± 0.5	2.1 ± 0.3 *	0.1 ± 0.1	21 *	11.1 ± 0.5 **	nd	0.1 ± 0.05	1.0 ± 0.0	71.0 ± 0.2 *	9.0 ± 0.1 *	1.2 ± 0.4
BC 55–80	0.85 ± 0.2	5.0 ± 0.6 *	0.5 ± 0.1	0.1 ± 0.0	5	nd	nd	0.1 ± 0.0	0.5 ± 0.0	23.0 ± 0.2	16.0 ± 0.2 *	1.5 ± 0.6
Postfire
Qpyr 0–3	13.15 ± 1.8	5.5 ± 1.0 ***	48 ± 1.7 ***	4.2 ± 0.5 ***	11 ***	55.6 ± 1.2 ***	0.02 ± 0.4	0.01 ± 1.0	55.5 ± 1.2	6532.0 ± 1.0 ***	526.0 ± 1.5 ***	0.2 ± 0.1 **
Epyr 3–10	0.20 ± 0.34	4.6 ± 0.7	1.2 ± 0.3 ***	0.1 ± 0.0	12 **	5.6 ± 0.9 *	0.01 ± 0.3	0.1 ± 0.0	1.8 ± 0.6	16.0 ± 0.1 **	14.0 ± 0.2 **	0.9 ± 0.1
E 10–23	0.13 ± 0.07	4.5 ± 0.4 *	0.3 ± 0.1	0.1 ± 0.0	3	7.8 ± 0.1 **	nd	0.01 ± 0.0	0.4 ± 0.7	2.0 ± 0.4	12.0 ± 0.3 **	1.2 ± 0.9
Bs 23–30	1.28 ± 0.15	5.2 ± 0.0	1.9 ± 0.4 *	0.1 ± 0.0	19 *	6.4 ± 0.6 **	nd	0.03 ± 0.0	0.6 ± 0.5	47.0 ± 0.1 *	15.0 ± 0.4 *	1.1 ± 0.4
BC 30–40	0.56 ± 0.5	5.3 ± 0.6 *	0.5 ± 0.1	0.1 ± 0.0	5	nd	nd	0.03 ± 0.2	5.2 ± 0.1	22.0 ± 0.1	6.0 ± 0.8 *	1.4 ± 0.0
C 40–65	0.63 ± 0.02	5.3 ± 0.1	0.3 ± 0.1	0.1 ± 0.0	3	nd	nd	0.1 ± 0.1	0.6 ± 0.1	21.0 ± 0.1	11.0 ± 0.1	1.4 ± 0.0
Post hoc test Postfire—Control	0.20	p << 0.05	p << 0.05	p << 0.05	p << 0.05	p << 0.05	0.15	0.13	0.11	p << 0.05	p << 0.05	p << 0.05
Significance of differences	Insign.	Sign.	Sign.	Sign.	Sign.	Sign.	Insign.	Insign.	Insign.	Sign.	Sign.	Sign.

Note: C_tot—carbon content; N_tot—nitrogen content; C/N—humus enrichment with nitrogen; V_basal—basal respiration; C_mic—microbial biomass content; * p < 0.05; ** p > 0.01; *** p > 0.001.

); furthermore, this indicator increases with depth.

There is also a decrease in litter stock, calculated as the multiplication of its volume and density (Table 1). It was found to be much less (80%) than in the control. The main reason for this is the significant increase in organic horizon density, which increased more than five times after the fire (especially in the upper part of the organic horizon) (Table 1), and the significant decrease in the total thickness of the organic horizons. On the one hand, this is explained by the entry of coal and ash into the part of the organic horizon remaining after the fire [61,62].

The data of some soil properties of the studied soils are given in Table 2.

The control soil has an acidic pH; the lower part of the organic horizon is characterized by the greatest acidity (pH 4.4), as well as the maximum values of soil moisture content (25%–27%). After a slight decrease in pH in the Epyr and E horizons, an increase in pH with depth is observed in the lower mineral horizons; therefore, the studied soils are characterized by an eluvial–illuvial profile distribution of pH. The acidity in this case is determined by low-molecular-weight organic acids. The carbon content is the maximum in organic horizon horizons, and it is characterized by an eluvial–illuvial profile distribution with the minimum content in the podzolic horizon. The carbon content in the organic horizon of the control plot is 40%–47%, and it does not exceed 2.1% in the mineral horizons. The total nitrogen content in the organic horizons varies from 1.14 to 1.44%; it decreases to 0.02%–0.08% in the mineral horizons. The humus enrichment with nitrogen (C/N) in the surface horizons of the studied soils is low (C/N > 10).

A change in acidity (its decrease) compared to the control plot was detected only in the upper Qpyr horizon. In the newly formed Qpyr horizon, consisting of partial combustion products and ash, the pH value was 1 unit higher than in the O horizons before burning. The increase in pH in the burned area is caused by the formation of water-soluble compounds containing alkaline earth elements, which saturate the soil-absorbing complex, causing a shift in pH to the neutral range. Short-term changes in acidity after a fire due to ash input have been described previously [63]. According to previous studies [64,65], the increase in the pH of the upper organic horizons is associated with the influence of coal formed as a result of fire, due to the fact that some of the low-molecular-weight organic compounds, present in the soil solutions of burnt areas, can be occluded on the surface. Higher pH values, resulting from neutral or alkaline reactions, are a consequence of heavy metal accumulation in postfire soils [66], which will be discussed below.

During the fire, the dry organic horizon (O) serves as fuel, burns out, and forms a thin Qpyr horizon in its place, where the main products of the partial pyrolysis of organic matter are concentrated (Figure 3). The carbon content increases in the pyrogenic horizon (48%), and there is a slight increase in the upper part of the podzolic horizon—from 0.49 at the control plot to 1.16% after the fire. This increase in the mineral horizon probably occurs due to soluble and small-sized coal particles capable of migration in aqueous solutions towards underlying horizons. Moreover, a more significant increase in the nitrogen content is observed in the pyrogenic horizon. The increasing N_tot content in the Qpyr horizon results in a significant decrease in the C:N ratio. Fires lead to an increasing concentration of N_tot in the pyrogenic horizon, which is apparently associated with the formation of pyridine-like structures [67].

The content of available forms of nitrogen (NO₃⁻ and NH₄⁺) changed slightly after the fire (Table 2). The NH₄⁺ content after the fire was slightly higher in both the organic and the podzolic horizons: 55.51 mg/kg in the postfire soil versus 3.35–13.62 mg/kg in the control soil (O horizon) and 1.78 mg/kg in the postfire soil versus 0.52 mg/kg in the control soil (E horizon). The content of NO₃⁻ in the postfire organic horizon did not exceed the detection limits—only traces were found—while there was no effect of fire on this indicator in the podzolic horizon. It is assumed that the increase in available nitrogen, especially NH₄⁺, is usually temporary and rapid immobilization can reduce its content after 6 months [68,69].

The phosphorus content (P₂O₅) in the postpyrogenic soil increased 11 times compared to the control soil (from 86–578 mg/kg to 6532 mg/kg). The potassium content (K₂O) increased 1.5 times after the pyrogenic impact compared to the control (from 17–350 mg/kg to 526 mg/kg). The distribution pattern of phosphorus and potassium along the soil profile is eluvial–illuvial, with minimal content in the podzolic horizon.

The increase in the content of P₂O₅ and K₂O in pyrogenic soils is due to their higher content in the ash formed after a forest fire. Researchers have previously noted that the concentration of nutrients in soil, such as potassium, calcium, magnesium, and phosphorus, which are contained in the ash of burned plants, increases after fires [70,71]. A further reduction in their content depends on the leaching of ions and their interaction with the mineral part of the soil [72].

The level of basal respiration between postpyrogenic (55.64 µg CO₂-C/g × hour) and control (82.18–105.81 µg CO₂-C/g × hour) soils differed significantly (p < 0.05). The control soil showed a higher level of carbon dioxide emissions compared to postfire soil (especially in the topsoil horizon).

The intensity of basal respiration in soils is mainly determined by two factors—the presence of available nutrients and the number and physiological status of microorganisms. In this case, the number of microorganisms decreases during a fire, and the content of biophilic elements increases, but this does not mean that they are available to the biota [73]. The decrease in the rate of CO₂ release by soil after a fire is obviously associated with the death of microorganisms and plant roots, which are the main agents of this gas formation. The content of microbial biomass decreases as a result of fires (Table 2). The microbial biomass content in the upper horizons of the control soil was 0.06 mg/g, while it was below 0.02 mg/g in postpyrogenic soil. However, these data do not differ significantly. Secondly, due to the destruction of the soil biota by high temperatures on the soil surface, mineralization processes in these partly charred materials can be slowed down.

The pyrogenic soil belongs to cohesive silty sands according to particle size distribution analysis, while the control soil belongs to silty sandy loams. The content of physical clay fractions is in the range of 7.7%–16.3%. Significant differences between the control and postfire plots were not detected according to the particle size distribution. However, there is a slight increase in the content of the 1–0.25 mm fraction after a forest fire due to the processes of cementation and the adhesion of aggregates [74].

3.2. The Effect of Fire on Soil Heavy Metals

Many studies on heavy metal translocation in postfire soils [75,76,77,78] clearly indicate a high rate of trace metal migration, mainly during the first few years after a fire. Important changes were observed in the content of heavy metals in the surface layers of the studied soils. These changes were mainly noticeable for all analyzed elements, especially in the case of lead and zinc (Figure 4 and Figure S1,

Table 3. Content of trace metals in postfire and control soils through the soil profile, mg × kg⁻¹.

Horizon	Depth, cm	Cu	Zn	Ni	Pb	Cd
Control
Tirr	0–5	2.5 ± 1.0 **	35.7 ± 1.5 ***	2.2 ± 1.0 **	1.4 ± 1.3 ***	0.3 ± 0.3 **
Oe	5–18	2.2 ± 1.2 **	29.2 ± 1.0 ***	6.8 ± 1.0 *	10.5 ± 1.1 ***	0.3 ± 0.0 **
Oa,pyr	18–23	3.1 ± 1.1 **	20.5 ± 1.6 ***	3.7 ± 1.0 **	2.6 ± 1.6 ***	0.2 ± 0.0 **
Epyr	23–30	<0.1	0.2 ± 0.9 *	0.6 ± 0.1	<0.1	0.2 ± 0.0
E	30–40	1.2 ± 0.1 *	0.5 ± 0.9 *	0.6 ± 0.5	<0.1	0.2 ± 0.0
Bs	40–55	2.7 ± 0.0 **	8.6 ± 0.1	6.9 ± 0.5 *	2.1 ± 0.1 *	0.1 ± 0.1
BC	55–80	1.1 ± 0.1 *	5.6 ± 0.0 *	5.5 ± 0.0 *	0.2 ± 0.4	0.1 ± 0.1
Postfire
Qpyr	0–3	6.8 ± 1.0 **	127.4 ± 1.0 ***	8.1 ± 1.0 **	28.3 ± 1.9 ***	1.1 ± 1.0 **
Epyr	3–10	0.3 ± 0.6	0.5 ± 0.5 *	0.8 ± 0.6	<0.1	0.1 ± 0.0
E	10–23	<0.1 *	<0.1 *	0.5 ± 0.4	<0.1	0.1 ± 0.0
Bs	23–30	1.8 ± 0.1 **	8.8 ± 0.9	8.2 ± 0.4 *	1.5 ± 0.6 **	0.1 ± 0.1
BC	30–40	1.8 ± 0.6 *	6.9 ± 0.1 *	7.5 ± 0.1 *	0.9 ± 0.7	0.1 ± 0.1
C	40–65	2.6 ± 0.4	5.9 ± 0.0	8.1 ± 0.3	0.9 ± 0.1	0.1 ± 0.0
Post hoc test Postfire—Control		p << 0.05	p << 0.05	p << 0.05	p << 0.05	p << 0.05
Singnificance of differences		Sign.	Sign.	Sign.	Sign.	Sign.

Note: bold indicates values that exceed the maximum permissible concentration according to [48]; * p < 0.05; ** p > 0.01; *** p > 0.001.

). Statistically significant differences were observed in all heavy metals between the control and postfire plots. Generally, the threshold values set by the soil quality standard [48] were not exceeded, except for the zinc and cadmium content in the organic horizon after the forest fire. This was mainly due to changes in pH and organic matter loss. The obtained results support studies that have confirmed an increase in trace metal concentrations after the fire effect [79].

The pattern of distribution of all studied heavy metals along the profile (as in the case of carbon content), except for cadmium, is eluvial–illuvial, with minimal content in the podzolic horizon. Cadmium is characterized by an accumulative type of distribution.

Moreover, the radial differentiation coefficient was calculated, which makes it possible to determine the accumulation (R > 1.0) or removal (R < 1.0) of chemical elements in each horizon of the soil profile in comparison with parent rocks [50].

The enrichment of topsoil horizons in pyrogenic soil with all the studied trace metals (R from 2.6 to 32.5) is clearly observed compared to the control soil, except for copper and nickel (Figure 4 and Figure S1). The removal of Cu, Zn, Ni, and Pb from the podzolic horizon of both soil profiles is typical. The R coefficients of these elements in the E horizon are equal to 0.1.

The contrast in the soil profile distributions of the studied elements in the soils differs as follows: if only Pb differs in the contrasting profile distribution in the case of the control soil (even then to a greater extent in the organic horizon that was once pyrogenic—Oa,pyr), then the majority of the studied elements are distributed contrastingly within the profile in postpyrogenic soil, and the enrichment of the soil profiles is twofold or more (for example, R_Zn = 21.6).

Despite the removal and accumulation processes being unidirectional in both study sites, we noticed greater removal for all trace metals in the control plot and greater accumulation in the postfire soil. The most considerable difference observed for Zn, Pb, and Cd is that these heavy metals accumulated from 3 to 20 times more on the postfire site than on the control site. The observed regularities could be attributed to the effects of the fire-altered environment and soil properties.

It is possible that these elements will be mobilized and transported to the lower part of the soil profile sometime after the fire, and soil self-recovery processes will reach the stage after which the original content of elements is achieved [80]. However, a different picture is observed in the soil immediately after a forest fire, as described above, when the concentrations of these chemical elements reach a temporary maximum, after which they are again involved in radial migration cycles and the formation of radial distributions begins again.

The leaching soil water regime of sands and sandy loams ensured active radial elements’ migration in the studied soil profiles. This explains the reduced content of elements in the E horizon, in which almost all the considered elements, except for Cd, are dispersed (R varies from 0.1 to 1).

The main aspects of heavy metals’ behavior during forest fires in the studied area are passive accumulation in the fire plot, redeposition on the leeward side of the fire with the enrichment of all components of the forest ecosystem, and possibly long-distance atmospheric transfer [81,82]. The organic horizons of higher thickness in the control plot also have an ability to accumulate elements compared to lower horizons, but not as much as in the postfire plot.

The principal coordinate analysis (PCoA) (Figure 5) indicates the accumulation of Zn in postpyrogenic soil. Two clouds are distinguished on the two component planes. Differences between these data areas are determined by the heavy metal content—podzol horizons, middle horizons, and transitional rock material. The points of the upper organic horizons are united in one cloud, but they are separated from each other depending on the decomposition degree of organic matter, and the point of topsoil in the pyrogenic area is located at a considerable distance.

3.3. The Effect of Fire on Soil Bacterial Community

Forest fires’ effects on the studied soil microorganisms are discussed below. Recent studies claim that fires can sterilize the soil [25,83,84]. The loss of these microorganisms not only affects biodiversity and interaction networks with plants or animals, but also their structures, such as filaments or biofilms, which are very relevant as adhesive agents aggregating particles and improving the soil structure [83,84,85].

The alpha diversity across all soil samples was significantly different (Figure 6). The Shannon index characterizes evenness in the community structure and shows the degree of dominance of certain species in the community structure. The pyrogenic Qpyr horizon is characterized by the lowest diversity in all calculated indices compared to all control organic horizons. At the same time, the organic horizons of the control soil also differ from each other: the lowest abundance is characteristic of the Oe horizon. Moreover, the greatest diversity was shown for the topsoil horizon of the control, represented by mossy tirr, according to the alpha diversity index, which reflects evenness (the inverse Simpson index). This is most likely due to the strong heterogeneity of the microbiome, caused by its low moisture content. To conclude, forest ecosystems had more developed microbial biodiversity.

The analysis of the beta diversity of bacterial communities showed that the postfire microbiome was significantly different from the control (Figure 7). The different organic horizons of the control plot were different from each other as well. The PCoA and CCA analysis (Figure S2) showed a trend in the difference between the pyrogenic organic layer and the control horizons and similarity in the microbiomes of the Oe and Oa,pyr horizons for the control soil. This similarity may be caused by the mutual influence of moistened, deeper organic horizons.

The analysis of the taxonomic composition of soil samples showed significant differences between the postfire soil and the control organic horizon (three horizons) already at the phylum level (Figure 8). It is known that the dominance of Acidobacteriota is characteristic of organogenic and organomineral soil horizons [86]. The dominance of Alpha- and Gammaproteobacteria, Actinobacteriota, Verrucomicrobiota, and Planctomycetota is characteristic of surface podzol organomineral horizons with an acidic reaction [87].

The pyrogenic horizon was characterized by the presence of the phyla Pseudomonadota, Bacteroidota, Bacillota, and Actinobacteriota, while such soil-specific phyla as Acidobacteriota, Verrucomicrobiota, and Planctomycetota were not detected. The decrease in the number of uncultured groups of microorganisms in postpyrogenic soils indicates the destruction of the complex metabolic relationships existing in the soil. In the literature, a decrease in the number of representatives of Acidobacteria, Verrucomicrobiota, and Planctomycetes in postpyrogenic soils is associated both with changes in the soil carbon cycle and with the disruption of plant–fungal associations [88].

All control organic horizons had a similar phyla structure, consisting predominantly of Pseudomonadota, Actinobacteriota, Acidobacteriota, Verrucomicrobiota, Planctomycetota, Bacteroidota, and Chloroflexota. A plot of old-growth spruce forest in semi-hydromorphic landscapes in the Komi Republic was characterized by similar species abundance and complexity of the microbiome structure in accordance with [89] (in particular, representatives of the phyla Actinobacteriota, Acidobacteriota, Verrucomicrobiota, and Chloroflexota). Significant changes between different organic control horizons across major phyla were shown only for Bacillota, which predominated in the Oa,pyr horizon (Figure S3). At the same time, the growth of Bacillota was also characteristic for the postfire plot, which was apparently due to the presence of coal that was noted in the topsoil pyrogenic horizon of both the control and the disturbed soils. Generally, differences between various parts of the control soil litter were noted only at a low taxonomic level, which is typical when analyzing the microbiomes of soil horizons. Representative species of Chloroflexota were abundant in the control soil compared to postfire, which may be due to the greater amount of fresh organic matter in an undisturbed forest ecosystem, as this group of microorganisms has recently been noted to play an important role in organic matter decomposition [90]. Thus, organic matter content may be a key factor in the specificity of the soil microbiome of the studied soils.

The differences between the pyrogenic and control organic horizons at the genus level are the most pronounced (Figure 9). The postpyrogenic litter community is represented by a relatively small set of microorganisms that have been identified at the genus and even species level, such as Acinetobacter, Sphingobacterium, Flavobacterium, Domibacillus, Paenibacillus, Comamonas, Pseudomonas, Herminiimonas, etc. At the same time, numerous microorganisms not identified at the genus level that are characteristic of diverse soil communities were present in the control soil. The major representatives of the control organic horizon were attributed to Burkholderia, Acidothermus, and Streptacidiphius.

The postpyrogenic horizon is characterized by a significant change in the representativity of Bacillota, Bacteroidota, and Gammoproteobacteria and individual representatives of Alphaproteobacteria (Brevundimonas) and Actinobacteriota (Glutamicibacter) (Figure 10). The microbiome’s response to a forest fire can be divided into an increased proportion of spore-forming microorganisms, including those with a complex set of catalytic enzymes (Domibacillus, representatives of penibacillus), and an increased proportion of Gram-negative microorganisms with complex metabolism as well (Bacillota—Sphingobacterium alimentarium, Flavobacterium lindanitolerans; Gammoproteobacteria—Acinetobacter). It is interesting that actinobacteria, with slow-growing cellulolytics (Acidothermus, Mycobacterium), were replaced by faster-growing micrococcaceae (Gammaproteobacteria—Acidocter, Burkholderia) in the postfire plot compared to the control. The proportion of poorly cultivated and nonculturable microorganisms—representatives of Verrucomicrobiota, Chloroflexota, and Acidobacteriota—decreased significantly in the postfire plot as well.

The transformation of the microbial community between organic horizons in the control soil was observed. The initial stages of soil formation and the replacement of the epiphyte microbiome with a specific soil microbiome, associated precisely with plant residue decomposition and active substrate acidification (Actinobacteriota (Streptacidiphilus, Mycobacterium) and Acidobacteriota (Acidipila, etc.) correspondingly), occurred in the Oe horizon. This explains the difference between the abundance and uniformity of this horizon—when moving to a lower horizon, the number of phylotypes increases, while the Oe and Oa,pyr horizons have a generally similar microbiome.

A comparative analysis of the postpyrogenic and control microbial communities of the studied soils showed the fire-induced reorientation of the microbial community from the complex cellulolytic community of the control litter (Acidothermus, Puia, Mycobacterium), associated with an acidic environment (Acidobacteriota, Acidocter, Streptacidiphilus) and rhizosphere nitrogen-fixing microbiota (Burkholderia, Roseiarcus, Aquisphaera), to a simpler postpyrogenic community, which is generally not typical for northern forest soils. The resulting taxonomic profile of the postpyrogenic microbiome suggests that these microorganisms could be of interest as possible degraders of complex polycyclic aromatic compounds.

4. Conclusions

The soils of semi-hydromorphic landscapes are very sensitive to the effects of fire. Changes in morphological soil properties are associated with the burning of organic horizons, dead wood, and large tree residues located on the soil surface. The pyrogenic horizon in the upper part of the soil profile is a compacted thin layer represented by coals and combustion products. The fire impact is traced to a depth of approximately 20–30 cm. Differences in physicochemical soil properties are expressed as an increase in pH values, an increase in the carbon content of organic compounds, and a significant increase in the content of phosphorus and potassium in pyrogenic horizons due to their higher content in ash formed after a forest fire. Forest fires cause an increase in heavy metal concentrations, mainly in the surface layers. In most cases, the maximum permissible concentrations established by sanitary requirements for soil quality were not exceeded, except for the zinc and cadmium content in the topsoil horizon after a forest fire. The radial differentiation of trace element concentrations in the studied soils represents various patterns of profile distributions; the following main patterns are most often encountered: the enrichment of most organic horizons with elements, as well as the removal of most of the elements in the podzolic soil horizon. Fires in the future will contribute to the removal of chemical elements from landscapes, especially in boreal and subarctic regions, since a significant part of the ecosystem pool of chemical elements in these regions is concentrated in organic soil horizons. Once the organic horizons burn out, this pool becomes vulnerable to leaching from the ash.

A significant impact of fires on the state of the soil’s bacterial community was revealed. It is expressed by a decrease in the microbial production of carbon dioxide and a change in the bacterial community structure. High temperatures have a significant impact on the taxonomic diversity of microorganisms inhabiting the soil, which leads to a decrease in its biological activity. An increase in the proportion of taxa reported as possible degraders of complex polycyclic aromatic compounds formed after combustion was shown. Thus, fires lead to the restructuring of the soil’s bacterial community. It has been established that the key factors in changing the soil’s bacterial composition are the soil organic matter content and the content of nutrients. Analyzing the influence of the pyrogenic factor on soil microbial communities, it can be noted that the high-temperature effect has a significant impact on carbon dioxide emission rates and the carbon content of the microbial biomass.