Impact of Coal Waste Rock on Biological and Physicochemical Properties of Soils with Different Agricultural Uses

Abstract

During the mining process in mines, a problem arises with the formation of coal post-mining waste, which is waste rock. It is often stored by mines on various types of land to manage the resulting spoil. However, this is not without its impact on the soil. In this study, we determined the biological and physicochemical properties of rhizosphere soils of the podzolic type, subjected to waste rock reclamation and without the influence of waste rock (control), differing in the type of agricultural use and type of plant cover: field-monocotyledonous (oat cultivation), field-dicotyledonous (buckwheat cultivation), and wasteland covered with very species-poor vegetation. Research has shown that long-term cultivation (buckwheat) contributed to the elimination (leveling out) of the microbial and biochemical differences. The addition of waste rock significantly reduced the number of microorganisms synthesizing siderophore, especially on wasteland (decreased by 1.5 log₁₀/gDW). The abundant presence of the genera Acidocella and Acidphilum, absent in wasteland without waste rock, in the unused soil under the influence of waste rock was strongly associated with the effect of lowering the pH by waste rock in soil not used for agriculture. Increased levels of 77 types of bacteria were observed in samples from buckwheat cultivation compared to wasteland. The number of microorganisms resistant to heavy metals as well as microorganisms capable of producing specific Fe-binding ligands—siderophores—decreased under the influence of waste rock. Moreover, the dehydrogenase activity in long-term cultivation both under the influence of waste rock and without its influence was at a similar level. In contrast, an almost 100-fold decrease in dehydrogenase activity was observed in soils with oat cultivation and a more than 4-fold decrease in acid phosphatase (ACP) and alkaline phosphatase (ALP) activity. These parameters provide an effective system for monitoring soil health, from inexpensive and fast methods to advanced and precise techniques. The results can be applied to solve the problems associated with coal mining wastes by developing methods for their use in soils with long-term agricultural use.

1. Introduction

Over the last two hundred years, human activity has significantly influenced changes in the Earth’s surface. For many millennia, humans have been changing and shaping terrestrial ecosystems through agriculture, urbanization, industrial activities, and technical barriers (roads, railroads, fences, etc.). Fragmentation and homogenization involve more than 50% of habitats [1,2,3]. This in turn affects the biodiversity of many groups of living organisms [4,5]. However, there are areas such as Polesie in Eastern Europe where the diversity of species and natural habitats is still well preserved. Polesie is a special area with primeval wetlands that have been continuously accumulating, e.g., CO₂, for over 11,000 years [6,7] and hosts a very well-preserved biodiversity, called the Amazon of Europe [8,9]. Many areas of Polesie are protected, but are simultaneously degraded and threatened by decades of land improvement, peat and hard coal exploitation, and other plans to change natural ecosystems [10,11,12].

In Poland, in the area of Western Polesie, hard coal mining has been operating since 1982 [13]. Waste rock is stored next to the Bogdanka Mine, but part of the waste rock is used to harden local roads and fill excavations after sand mining sites as a reclamation method [14,15,16]. There are cases of waste rock being stored in the immediate vicinity of protected areas, such as Polesie National Park, Natura 2000 Area (e.g., Jeziora Uściwierskie PLH060009), Polesie Landscape Park, and the UNESCO International Biosphere Reserve “Western Polesie” [15]. Thus far, the significance of the impact of waste rock on protected areas has not been determined, which is why it is important to monitor its storage sites in and near protected areas. Mining exploitation also causes destruction of the area through changes in topography, leads to changes in the existing flora and fauna, affects the deterioration of air quality, and causes changes in hydrological systems and the quality of surface water [17]. Long-term contact with air and water can lead to the oxidation process, which in turn can lead to intensive process desulfurization, especially from inorganic sulfur (occurring in the form of pyrite) involving the formation of Fe₂O₃ on pyrite surfaces and strong chemical and physical changes with significant consequences for the environment, such as an increase in the content of oxygen-containing functional groups as well as the hydrophilicity and adsorption of water molecules [18]. Therefore, cyclical wetting, for example, by rainfall, may to some extent affect the hydrophobic properties of the material and the soil as a result of interaction with water [19].

The economic development of countries is significantly related to the exploitation of mineral resources [17,20]. The role of the mining industry, including the development of mines, is a very important and strategic part of the economic development of many countries [21]. On the one hand, the mining industry provides work for thousands of people, contributing to social well-being, but on the other hand, the exploitation of resources has a negative impact on the natural environment [12]. The development of the mining industry causes improper use of soil and changes in the landscape [22]. Other empirical studies indicate that mineral extraction is also associated with socio-economic benefits, while contributing to regional economic growth and employment. On the other hand, mine closures negatively affect the lives of local communities and local economic entities related to services [23,24]. In addition, the mining industry is crucial to the global energy transformation in the case of developing countries. Resource extraction contributes significantly to the development and economic stability of more than 80 countries [25]. On the one hand, the functioning of the mining industry causes socio-environmental conflicts. However, the limited availability of some fossil fuels poses a threat to energy security, and on the other hand, it is necessary to achieve a sustainable energy future [23,26]. However, technological progress in the use of energy from renewable sources is a component of sustainable development [26,27,28]. Changing the forms of energy acquisition and the new technologies developing at the same time are referred to as the energy revolution [29]. One of the perspectives is local and regional development strategies based on this type of energy source. This developing energy industry can improve the living conditions of the population and at the same time is a sustainable response to conflicts and environmental problems [26,27,30]. While economic development is essential to improving living standards, it must be balanced with environmental sustainability to ensure long-term prosperity. Of the 42 European countries, Poland is roughly in the middle of the European ecological footprint in terms of the human development index, despite the fact that a large share of energy comes from fossil fuels. Policymakers must implement and monitor policies that promote sustainable development [31]. Ensuring a balance among society, the environment, and the economy is defined by the idea of sustainable development [17,32]. In particular, the idea of sustainable development improves the quality of life for a large part of the world’s population, in all its forms: social, economic, environmental, and therefore it is still a key requirement during the 21st century [26,30]. The protection and maintenance of terrestrial and aquatic ecosystems and the preservation of biodiversity affect human well-being, hence the validity of the idea of sustainable development [33].

An important part of solving problems related to mining activities is identifying adverse effects on environmental conditions in the impact zone [17]. Additionally, mining activities, along with the development of related infrastructure, negatively affect the landscape and local ecosystems. Threats resulting from mining activities include reduced availability, contamination and depletion of groundwater, large-scale disruptions to hydrological and geological systems, noise pollution, mine spills, excess waste, deforestation, habitat changes, aridification and desertification, loss of landscapes and aesthetic degradation, reduction in and loss of biodiversity, threats to food security, soil pollution, floods, soil erosion, reduction in and limitation of hydrological connectivity, and air pollution [34]. An important threat is waste rock used for the recultivation of degraded areas [35]. Waste rock presence in the soil leads to changes in the population of microorganisms, which, depending on the concentration of metals and the period of exposure to contamination, results in a strong reduction in the total abundance of microorganisms and the creation of a population of microorganisms adapted to contamination [36,37].

At the same time, degradation conditions vary depending on the area and should be considered in detail due to strong physical (water, soil) and biological (microorganisms, fauna, flora) pollution and other components of ecosystems [17,35,38]. When using waste rock for reclamation, the reclamation procedures should be adapted to specific field conditions [39]. Moreover, when used, they must be monitored for at least five years, and the responsibility rests with the same company (or government) that must carry out the reclamation [17,35,38]. Considering the scope of the potential effects of the use of waste rock, it is highly justified to monitor the biological condition of soils, especially those used for agriculture, because of the potential possibility of contamination.

It is necessary to monitor the biological condition of soils exposed to various types of contamination from coal mining waste, particularly in soils used for agriculture, because the plants grown in these areas are a direct threat to human health. At the same time, such comprehensive research will allow the identification of the best indicators of environmental hazards from waste rock contamination. Studies concerning the impact of various factors on the restoration of vegetation cover on coal mine heaps have shown that the biotic characteristics of the soil substrate and the plant–soil microbiota interaction are more important for vegetation development than abiotic parameters, and that the activity of microorganisms related to nutrient cycling is particularly important in such difficult ecosystems [40]. Moreover, the introduction of waste into the soil to cause soil remediation must also have an impact on fertility and ecosystem productivity through its impact on biological activity, which consists of biochemical processes carried out by living organisms, mainly soil-inhabiting microorganisms [41]. Groups of microorganisms differing in their requirements in relation to the amount of carbon and nitrogen compounds that develop mainly at low (oligotrophs) and high (copiotrophs) concentrations of these elements can be distinguished. Most often, there is a clear dominance of bacterial oligotrophs [42]. There are also microorganisms capable of degrading organic compounds such as protein, starch, and cellulose, as well as making elements available: phosphorus via phosphate dissolution metals such as Fe, but also heavy metals via non-specific (e.g., acids) and specific (siderophores) chelating compounds [43]. In coal seams and associated rocks, the composition of the microbial community depends on the composition of nutrient elements (i.e., C, S, P, and N) and elements such as Fe and As [44]. The main indicator of soil biological activity is the enzyme participating in the respiration process of all organisms, dehydrogenase. This indicator is commonly used to assess the factors that exert adverse effects on soil microorganisms [43]. EcoPlate Biolog^® tests to determine ecophysiological indicators are useful tools for monitoring biodiversity changes. The usefulness of measuring the activity of this enzyme as an ecological test has been confirmed by numerous studies on the changes in biological activity in various cultivation and fertilization systems in the case of soil contamination with heavy metals, pesticides, or petroleum compounds [45]. The problem of contamination of soils by coal mining waste occurs worldwide, but so far only a few research teams have analyzed such soils in terms of changes in soil properties (pH and especially biochemical and biological parameters) (

Table 1. Characteristics of agricultural land affected by coal mine waste.

Location	Type of Development/Cultivation	Predominant Microbial Groups/ Enzymatic Activity	Literature
Muli coal mine site in Qinghai, China	Grasslands	Proteobacteria (~32%), Actinobacteria (~28%), Acidobacteria (~15%)	[46]
Coal mine drainage from Onyeama, Nigeria	Derelict coal fields	Proteobacteria (50.8%) and Bacteroidetes (18.9%) dominate the bacterial community, Ascomycota fungi (60.8%) and Ciliophora (12.6%) dominate the eukaryotic community	[47]
Coal fly ash soil amendment in Hebei province, China	Corn	Acidobacteria (77.05%), Sphingomonas (25.60%), Nitrospira (20.78%), Streptomyces (11.32%), Gaiella (10.20%)	[48]
Coal mine spoil heaps in the Silesian Uplands, Poland	Grasses (Poa compressa, Calamagrostis epigejos)	pH, dehydrogenase, and alkaline phosphatase higher than in bulk soil; acid phosphatase lower than in bulk soil	[49]
Coal mine spoil heaps in the Silesian Uplands, Poland	Forbs (Daucus carota, Tussilago farfara)	pH, dehydrogenase, alkaline phosphatase, and acid phosphatase higher than in bulk soil	[49]
Bulianta coal mine in Yijin Horo Banner, China	Pinus sylvestris, Prunus sibirica, and Hippophae rhamnoides forests	Soil organic carbon content higher after 15 years of vegetation restoration than after 5 and 10 years	[50]

).

We hypothesized that fields subjected to waste rock reclamation are a threat to protected areas (e.g., national park) and agricultural crops, and their presence in the soil affects the state of the microorganism population and the biological and physicochemical properties of the soil. In monitoring the condition of soils, it is necessary to give simultaneous attention to both the physicochemical and biological properties, including the enzymatic activity of the soil and, in particular, the abundance of the main systematic and physiological groups of microorganisms, the physiological profile and diversity of soil microorganisms, and the balance between these parameters. We assumed that the parameters analyzed are helpful in monitoring the condition of the soils and in selecting the appropriate agricultural use of polluted soils for specific crops.

The aim of this study was to determine the biological and physicochemical properties of soils subjected to reclamation using waste rock, which was used for agricultural purposes in protected areas. This study provides a comparison of complex changes in soil properties (their microbiological, biochemical, and physical parameters) between agriculturally managed soils and wasteland influenced by the impact of waste rock, as well as between soils subjected to the short-term and long-term impact of coal mine waste rock. There is also a complete lack in the literature on comprehensive analyses of post-coal waste in affected soils on the diversity of the microbiota by cultivating and genetic methods, nor comparisons of ecophysiological indicators reflecting the metabolic activity of the soil microbiota.

2. Materials and Methods

2.1. Soil Collection Site

The research material consisted of rhizosphere soils of the podzolic type formed from light loamy sand subjected to waste rock reclamation and without the influence of waste rock (control), differing in the type of agricultural use and type of plant cover: field-monocotyledonous (oat cultivation), field-dicotyledonous (buckwheat cultivation), and wasteland covered with very species-poor ruderal vegetation (grasses, fescue Festuca sp., Helichrysum arenarium, Oenothera sp.). The research sites were located in eastern Poland, in the Lublin Voivodeship, in the communes of Urszulin (Włodawa County), and Siedliszcze (Chełm County) (Figure S1). Materials for research were collected from places where waste rock from a hard coal mine was deposited as part of the reclamation in 2010 Andrzejów (geographical coordinates: 51.39091659373544, 23.243677450864734) and Wola Wereszczyńska (51.422832965028725, 23.14591751618067) and in 2020 Chojeniec (51.212092390547845, 23.072456542552718). After reclamation, two sites (Andrzejów and Chojeniec) were returned for agricultural use and the third site (Wola Wereszczyńska) was an agricultural wasteland. One of the sites where waste rock was deposited was located only about 0.6 km from the border of Polesie National Park (Figure S1).

Two different points were sampled at each location (Figure 1). The samples were collected from fields with identical cropping histories:

• A_bu_in—field with buckwheat, influenced (>10 years) by waste rock, Andrzejów
• A_bu_win—field with buckwheat, without influence of waste rock, Andrzejów
• Ch_oat_in—field with oats, influenced (2 years) by waste rock, Chojeniec
• Ch_oat_win—field with oats, without influence of waste rock. Chojeniec
• WW_wa_in—wasteland, influenced (>10 years) by waste rock, Wola Wereszczyńka
• WW_wa_win—wasteland, without influence of waste rock, Wola Wereszczyńka

Using the following list of methods (

Table 2. Summary of methodology used in the study.

Methodology	Soil Sample	Main Information	Literature
Soil dry matter	10 g FW	Dry in a laboratory dryer to constant dry mass: 3 cycles, 105 °C after 8 h	-
pH	1 g FW	Preparation of soil suspensions at a ratio of 1:2.5 dH2O or 1M KCl * and pH determination/measured potentiometrically by glass electrode (with CP-505, Elmetron, Poland pH meter)	-
Humic acid content	100 g FW	Humic acids extracted from the soil with 0.5M NaOH are precipitated from the solution with 6M HCl	[51]
Total organic carbon	0.5 g DW	0.2 g of AgSO4 and 10 mL of 0.4N potassium dichromate were added to the soil sample and boiled for 5 min. After cooling, the mixture was titrated with 0.2N Mohr’s salt until bottle green	[51]
Fungal abundance	1 g FW	The soil suspension was cultivated on Martin’s substrate, with the incorporation of 1% Rose Bengal dye and 1% streptomycin	[52]
Copiotroph and oligotroph abundance	1 g FW	Determined on a PYS medium containing soil extract. For oligotrophic abundance, the PYS substrate was diluted 100 times	[51]
Abundance of cellulolytic microorganisms	1 g FW	Determined on CMC supplemented medium. Abundance was determined after inducing zones with 0.1% Congo Red and 1M NaCl.	[53]
Abundance of amylolytic microorganisms	1 g FW	Determined on starch-supplemented medium. Abundance was determined after inducing zones with Lugol’s liquid	[54]
Abundance of proteolytic microorganisms	1 g FW	Determined on skimmed milk-supplemented medium. After incubation, the zones were visible as translucencies	[55]
Abundance of microorganisms capable of solubilizing phosphates	1 g FW	Abundance was determined on Na3PO4 + CaCl2 supplemented medium. After incubation, the zones were visible as translucencies	[56]
Microorganisms resistant to heavy metals	1 g FW	Determined on Schlegel 284 medium supplemented with heavy metal solutions: CdSO4, NiCl2, CuSO4, ZnSO4	[36,57]
Microorganisms capable of synthesizing siderophores	1 g FW	Determined on “blue” agar medium supplemented with CAS-Fe(III)-HDTMA complex	[58]
Dehydrogenase activity	3 g FW	Determined spectrophotometrically (485 nm) based on the conversion of TTC to formazan after 48 h incubation at 37 °C	[59]
Phosphatase activity	1 g FW	Determined spectrophotometrically (410 nm) based on the concentration of p-nitrophenol released from p-nitrophenyl phosphate at pH 5.5 for ACP and 11.0 for ALP	[60]
Community level physiological profiling	1 g FW	The soil suspension was applied to an EcoPlate Biolog plate and incubated at 20 °C. Spectrophotometric measurements at 590 nm were performed every 24 h for 8 days; coefficients were calculated from the results: AWCD, substrate richness (R), and Shannon index (H)	[61,62]
Bacterial community	0.5 g FW	DNA was isolated with FastDNA™ SPIN Kit for Soil; results obtained were then subjected to bioinformatic and statistical analysis, obtaining a picture of the microbial population in the soil	[63,64,65]

FW—fresh weight; DW—dry weight; CMC—carboxymethylcellulose; CAS—chromazurol S; ACP—acid phosphatase; ALP—alkaline phosphatase; AWCD—average well color development; HDTMA—hexadecyltri-methylammonium bromide. * pH values measured in the water suspension correspond to the concentration of hydrogen ions present in the soil solution and the pH values measured in the soil suspension obtained in 1MKCl reflect the sum of the concentration of hydrogen ions present in the soil solution and hydrogen ions weakly bound to the solid fraction of the soil.

), the soil was subjected to microbiological, biochemical, ecopsychological and genetic analyses.

2.2. Determination of Dry Weight and pH Value

Soil dry matter was obtained by drying the soil at 105 °C for 8 h in three cycles in a laboratory dryer (MOV–112S, Sakata, Oizumi–Machi, Ora–Gun, Gunma Panasonic, Japan) until constant dry matter mass was obtained. The soil pH was assessed in water and 1M KCl at a ratio of 1:2.5 (CP-505, Elmetron, Poland).

2.3. Total Organic Carbon Content and Humus Content

The humic acid content was determined in 100 g of the sieved soil. To the weights, 100 mL of 0.5M NaOH was added and shaken for 2 h at RT. The suspension was centrifuged at 10,000 rpm for 15 min (MPW 350-R, Warsaw, Poland) and filtered through a cellulose filter to obtain clear supernatant. The supernatant was acidified with 50 mL of 6M HCl and allowed to precipitate humic acids for 2 h. The suspension was deacidified at 10,000 rpm for 15 min, and the resulting precipitate was dried at 80 °C for 8 h in three cycles until a stable dry mass was obtained. Total organic carbon content was determined using the Tiuren method. Air-dried soil was ground in a mortar to silty dust and then weighed into Erlenmayer flasks (0.5 g); 0.2 g of AgSO₄ was added to each flask, and 10 mL of 0.4N acidic potassium dichromate solution was also added. The mixture was placed on a hotplate (Ceran 11 A, Harry Gestigkeit GmbH, Düsseldorf, Germany) and subjected to constant uniform boiling for 5 min. Subsequently, the flasks were cooled and the condensate from the septum was rinsed with 5 mL of distilled water. The resulting solution was then titrated with 0.2N Mohr’s salt solution (0.2M ferric ammonium sulfate) against diphenylamine as an indicator (10 drops per flask). The solution was then titrated until a bottle-green color was obtained [51].

2.4. Determination of Soil Microbial Abundance

The soil samples were sieved through a sieve with a mesh diameter of 5 mm. Then, 5 g of soil was transferred to 45 mL of water and shaken for 15 min at 120 rpm at 20 °C (Biosan PSU-10i, Józefów, Poland). Subsequently, a series of decimal dilutions were prepared, which were sown onto microbial media to assess the abundance of culturable microorganisms. All cultures were incubated at 20 °C for 7 days (Innova 4900, Edison, NJ, USA).

2.4.1. Fungal Abundance

Fungal abundance was determined on Martin’s medium with the following composition: glucose 10 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), peptone 5 g·L⁻¹ (BTL, Łódź, Poland), KH₂PO₄ 1 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), MgSO₄·7H₂O 1 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), and agar 15 g·L⁻¹ (Biomaxima, Lublin, Poland) supplemented with 1% streptomycin and 1% Rose Bengal after sterilization (3 mL/L) [52].

2.4.2. Copiotrophs and Oligotrophs Abundance

Copiotrophic abundance was determined on PYS medium with the following composition: glucose 1 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), peptone 0.2 g·L⁻¹, yeast extraxt 0.1 g·L⁻¹ (BTL, Łódź, Poland), K₂HPO₄ 0.4 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), MgSO₄·7H₂O 0.05 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), horticulture soil extract 100 mL/L, and agar 15 g·L⁻¹ (Biomaxima, Lublin, Poland). The abundance of oligotrophs was determined using a medium diluted 100 times [51].

2.4.3. Abundance of Cellulolytic Microorganisms

The abundance of cellulolytic microorganisms was determined on CMC Agar with the following composition: carboxymethylcellulose (CMC) 10 g·L⁻¹ (Sigma-Aldrich, St. Louis, MO, USA), K₂HPO₄ 0.5 g·L⁻¹ (POCH, Gliwice, Poland), KCl 0.5 g·L⁻¹ (POCH, Gliwice, Poland), MgSO₄·7H₂O 0.2 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), CaCl₂ 0.1 g·L⁻¹ (POCH, Gliwice, Poland), (NH₄)₂SO₄ 0.1 g·L⁻¹ (POCH, Gliwice, Poland), and agar 15 g·L⁻¹ (Biomaxima, Lublin, Poland). After incubation, the cellulose decomposition zone was eluted using 0.1% Congo Red (Park Scientific, Northampton, UK) for 15 min. The excess dye was washed with 1M NaCl (POCH, Gliwice, Poland) for 15 min [53].

2.4.4. Abundance of Amylolytic Microorganisms

The abudance of amylolytic microorganisms was determined on starch agar with the following composition: soluble starch 10 g·L⁻¹ (POCH, Gliwice, Poland), KH₂PO₄ 0.5 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), K₂HPO₄ 0.5 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), MgSO₄·7H₂O 0.2 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), (NH₄)₂SO₄ 0.2 g·L⁻¹ (POCH, Gliwice, Poland), and agar 15 g·L⁻¹ (Biomaxima, Lublin, Poland). After incubation, amylolysis zones were induced using Lugol’s liquid (POCH, Gliwice, Poland) [54].

2.4.5. Abundance of Proteolytic Microorganisms

The abundance of proteolytic microorganisms was determined on milk agar with the following composition: meat extract 15 g·L⁻¹ (BTL, Łódź, Poland) and skimmed milk 200 mL/L (Łaciate, Mlekpol, Poland) [55].

2.4.6. Abundance of Microorganisms Capable of Solubilizing Phosphates

The abundance of microorganisms capable of solubilizing phosphates was determined on PS medium with the following composition: glucose 10 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), asparagine 1 g·L⁻¹ (POCH, Gliwice, Poland), casein hydrolysate 0.2 g·L⁻¹ (POCH, Gliwice, Poland), MgSO₄·7H₂O 0.4 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), K₂SO₄ 0.2 g·L⁻¹ (POCH, Gliwice, Poland), and agar 15 g·L⁻¹ (Biomaxima, Lublin, Poland) in 800 mL of H₂O. Solutions of Na₃PO₄·12H₂O 10 g/100 mL (POCH, Gliwice, Poland) and CaCl₂ 22 g/100 mL (POCH, Gliwice, Poland) were sterilized separately and added after autoclaving [56].

2.4.7. Microorganisms Resistant to Heavy Metals

The abundance of microorganisms resistant to heavy metals was determined on Schlegel 284 medium with the following composition: Tris-HCl 6.06 g·L⁻¹ (Sigma-Aldrich, Hamburg, Germany), NaCl 4.68 g·L⁻¹ (POCH, Gliwice, Poland), KCl 1.49 g·L⁻¹ (POCH, Gliwice, Poland), NH₄Cl 1.07 g·L⁻¹ (Sigma-Aldrich, Hamburg, Germany), Na₂SO₄ 0.43 g·L⁻¹ (POCH, Gliwice, Poland), MgCl₂·6H₂O 0.2 g·L⁻¹ (POCH, Gliwice, Poland), CaCl₂·2H₂O 0.03 g·L⁻¹ (POCH, Gliwice, Poland), Na₂HPO₄·2H₂O 0.04 g·L⁻¹ (POCH, Gliwice, Poland), Fe(III)NH₄Citrate 10 mL/L (solution 48 mg/100 mL) (Sigma-Aldrich, Hamburg, Germany), and agar 20 g·L⁻¹ (Biomaxima, Lublin, Poland). Prepared separately was C-mix containing sodium lactate (solution 50%) 0.7 mL/L, glucose 0.52 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), D-gluconic acid sodium salt 0.66 g·L⁻¹ (Sigma-Aldrich, Hamburg, Germany), fructose 0.54 g·L⁻¹ (Sigma-Aldrich, Hamburg, Germany) and sodium succinate·6H₂O 0.81 g·L⁻¹ (Sigma-Aldrich, Hamburg, Germany). Heavy metal solutions were prepared and sterilized separately: 0.4 mM CdSO₄·3H₂O (Sigma-Aldrich, Hamburg, Germany), 0.8 mM NiCl₂·6H₂O (Sigma-Aldrich, Hamburg, Germany), 0.6 mM ZnSO₄·7H₂O (Sigma-Aldrich, Hamburg, Germany), and 0.4 mM CuSO₄·5H₂O (Sigma-Aldrich, Hamburg, Germany). After sterilization, all solutions were mixed together [36,57].

2.4.8. Microorganisms Capable of Synthesizing Siderophores

The abundance of microorganisms capable of synthesizing siderophores was determined on CAS agar with the following composition: glucose 4.0 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), KH₂PO₄ 3 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), NaCl 0.5 g·L⁻¹ (POCH, Gliwice, Poland), NH₄Cl 1 g·L⁻¹ (POCH, Gliwice, Poland), MgSO₄·7H₂O 0.2 g·L⁻¹ (Chempur, Piekary Śląskie, Poland), and agar 15.0 g·L⁻¹ (Biomaxima, Lublin, Poland) in 860 mL of 0.1M PIPES buffer (Merck, Darmstadt, Germany). Solutions of 10% acidic casein hydrolysate (POCH, Gliwice, Poland) (30 mL), 0.01 M CaCl₂ (POCH, Gliwice, Poland) (10 mL), and a dark blue solution of CAS-complex (100 mL) prepared by mixing 60.5 mg chromazurol S (CAS) (Fulka, Göteborg, Sweden) (50 mL), 1 mM FeCl₃·6H₂O (POCH, Gliwice, Poland) in 10 mM HCl (POCH, Gliwice, Poland) (10 mL), and 72.9 mg of detergent (hexadecyltrimethylammonium bromide (HDTMA) (Sigma-Aldrich, Hamburg, Germany) (40 mL)) were sterilized separately and added after autoclaving [58].

2.5. Dehydrogenase Activity

Three grams of soil was weighed into Falcon tubes, and 2 mL of CaCO₃ (POCH, Gliwice, Poland) suspension (0.6 g·mL⁻¹), 1 mL of 3% TTC (Alfa Aesar, Ward Hill, MA, USA), and distilled water (1.5 mL) were added. The mixture was thoroughly mixed and incubated for 48 h at 37 °C (Panasonic MOV–112S, Sakata, Japan). The formazan (TPF) produced was extracted with 5 mL 96% ethanol. The resulting mixture was centrifuged at 10,000 rpm for 15 min (MPW 350-R, Warsaw, Poland), and absorbance was measured at 485 nm using an Infinite 200 PRO TECAN microplate spectrophotometer (Tecan, Grödig, Austria). Dehydrogenase activity was expressed as µg TPF/h/gDW [59].

2.6. Phosphatase Activity

Acid phosphatase (ACP) and alkaline phosphatase (ALP) activities were determined in the tested soils. One gram of soil was weighed into Falcon tubes, and 200 µL of toluene was added and allowed to stand for 15 min. After this time, 4 mL of modified universal buffer (MUB) with pH 5.5 (for ACP) and 11.0 (for ALP) and 1 mL of 100 mM p-nitrophenylphosphate (p-NPP) (Merck, Darmstadt, Germany) were added to the tubes. The mixture was incubated for 3 h at 37 °C (Panasonic MOV–112S, Sakata, Japan). After this time, 1 mL of 0.5M CaCl₂ (POCH, Gliwice, Poland) and 4 mL of 0.5M NaOH (POCH, Gliwice, Poland) were added to the tubes. The mixture was thoroughly mixed and centrifuged at 10,000 rpm for 15 min (MPW 350-R, Warsaw, Poland). The concentration of released p-nitrophenol (p-NP) was determined at 410 nm using an Infinite 200 PRO TECAN microplate spectrophotometer (Tecan, Grödig, Austria). Activity was expressed as µmol p-NP/h/g DW [60].

2.7. Community Level Physiological Profiling—EcoPlate Biolog^®

The Biolog EcoPlate™ system (Biolog Inc., Hayward, CA, USA) was used to determine variability in the biodiversity of soil microbial populations. One gram of soil was weighed into 99 mL of distilled water and shaken for 15 min at 120 rpm at 20 °C. One hundred microliters of the resulting suspension was transferred to each well of a 96-well Biolog EcoPlate™. The plates were incubated for 8 days at 20 °C (Innova 4900, Edison, NJ, USA) and spectrophotometric measurement at 590 nm (OD₅₆₀) was performed every 24 h using an Infinite 200 PRO TECAN microplate spectrophotometer (Tecan, Grödig, Austria) [61,62]. The average well color development (AWCD), substrate richness (R), and Shannon index (H) were calculated using the following formulae:

$$\mathbf{AWCD}={\displaystyle \frac{{{\displaystyle \sum }}_{i=1}^{N}O{D}_i}{N}}$$

(1)

where AWCD—average well color development, ${{\displaystyle \sum }}_{i=1}^{N}O{D}_i$—Sum of OD₅₉₀ from all wells corrected for the control well, and N—the number of substrates (N = 31).

Substrate richness (R) was calculated from the number of substrates used, where ABS₅₉₀ > 0.25 after 96 h of incubation:

$$\mathbf{H}=-{{\displaystyle \sum }}_{i=1}^N{P}_{i}ln{P}_i$$

(2)

where H—Shannon index, $ln{P}_i$—the natural logarithm of the ratio of the OD₅₉₀ of the well to the sum of the ODs₅₉₀ for all the wells, and N—the number of substrates (N = 31).

2.8. Bacterial Community

DNA was isolated using a commercially available kit (FastDNA™ SPIN Kit for Soil, MP BIOMEDICAL, Burlingame, CA, USA). For processing of demultiplexed fastq files, the DADA2 (1.14) package [66] in R software (3.6.0) [67] was used. Based on the quality plots, the last 20 forward and 20 reverse bases were trimmed off (filter parameters: maxN = 0, maxEE for both reads = 2, truncQ = 2). The next steps of analysis were learnErrors, dada, and removeBimeraDenovo. For taxonomy assignment, the latest version of the modified RDP (Ribosomal Database Project) v18 database [63] was used by applying IDTAXA [68]. The results were input into the phyloseq (1.22.3) package [64] (chloroplast or mitochondrial DNA were deleted). Statistical and graphical analysis were prepared using the microeco package (RStudio for Windows version 2024.09.0+375 (Posit, PBC, GNU Affero General Public Licence v3) [65]. Data were deposited in the NCBI SRA database in bioproject no. PRJNA1087279.

2.9. Statistical Analysis

All experiments were conducted in 3 biological replicates. Data are presented as mean values with standard deviation (SD). The results were subjected to analysis of variance (one-way ANOVA) followed by Tukey’s post hoc test for multiple comparisons at p < 0.05. Statistical analysis and the Shannon and Simpson tests were performed using the open-source software RStudio for Windows version 2024.09.0+375 (Posit, PBC, GNU Affero General Public License v3).

3. Results

3.1. Soil pH Variability and Organic Carbon and Humus Content in Soil

The addition of waste rock to the soils affected both pH values (Figure 2). The addition of waste rock to buckwheat culture fields alkalinized the soils to a pH level of ~7.5–8.0 (Figure 2A,D). These soils also showed the highest pH levels compared with the other samples tested. Soil acidification was most affected by the waste rock in the wasteland, where an up to 2-fold decrease in soil pH values was observed (Figure 2C,F). In the field with oat farming, the effect of waste rock on soil pH levels varied more strongly. Soil alkalinization was observed in water (Figure 2B) and a decrease in pH in KCl (Figure 2E).

The addition of waste rock to the soils was observed to cause an increase in organic carbon content in the case of buckwheat cultivation (1.5%) and wasteland (4-fold increase) (Figure 2G,I). Organic C decreased to 1 µg/g only in fields with oat cultivation (Figure 2H). However, the change in organic C content did not translate into the level of humic substances in the soil, where a decrease in the content of these compounds was observed in all fields compared to the control (Figure 2J,K,L). The wasteland was additionally characterized by the lowest humic substances content in the fields, without the influence of waste rock (Figure 2L).

3.2. Abundance of Soil Microorganisms

The addition of waste rock did not significantly affect the abundance of all microbial groups in the buckwheat cultivation field, where the average abundance was ~5.5 log₁₀/gDW for fungi and 7.5–7.7 log₁₀/gDW for copiotrophs and oligotrophs, respectively (Figure 3A,D,G). On the other hand, in the soil from oat cultivation, a reduction in the abundance of all microbial groups by about 1–1.5 log₁₀/gDW was observed (Figure 3B,E,H). A similar situation was observed for the abundance of copiotrophs and oligotrophs in wasteland, where the influence of waste rock caused a decrease in the abundance of these groups of microorganisms to the level of 6.2 log₁₀/gDW and only the abundance of fungi remained at the same level (Figure 3C,F,I).

High variability in the abundance of individual physiological groups of microorganisms was observed depending on the type of cultivation and addition of waste rock to the soil (Figure 4). The addition of waste rock to the soil had no effect on the abundance of microorganisms in the four main physiological groups during the long-term buckwheat cultivation (Figure 4A,D,G,J). In contrast, the opposite situation was observed for oats cultivation and wasteland, where the effect of waste rock was much shorter. A significant decrease in the abundance of microorganisms from the four main physiological groups was observed in both soils. The greatest impact of the addition of waste rock was on cellulolytic and phosphate-solubilizing microorganisms, where the decrease in abundance was at the level of 1.5–2 log₁₀/gDW (Figure 4B,C,K,L).

The addition of waste rock to soils also decreased the abundance of microorganisms capable of synthesizing siderophores. The greatest decrease was observed in wasteland (1.5 log₁₀/gDW) (Figure 4M,N,O). A similar situation was observed for heavy metal-resistant microorganisms in fields with buckwheat and oat cultivation, where a statistically significant decrease in the abundance of this group of microorganisms was observed (Figure 4P,R). In the case of the wasteland, the abundance of this group of microorganisms remained at the same level as in both soils (Figure 4S).

3.3. Soil Enzyme Activity

For buckwheat cultivation, dehydrogenase activity was at the same level (~0.5 µg TPF/h/gDW) in both soils (Figure 5A). In contrast, a significant decrease in the activity of these enzymes was observed in the soil under the influence of waste rock from oat cultivation and wasteland (Figure 5B,C). An almost 100-fold decrease in the activity of this enzyme was observed in soils under oat cultivation, from ~2 µg TPF/h/gDW to 0.02 µg TPF/h/gDW (Figure 5B).

A decrease in the activity of both acid phosphatase (ACP) and alkaline phosphatase (ALP) in soils under the influence of waste rock addition was observed in all the samples tested (Figure 5D-I). The greatest decrease in the activity of both enzyme groups was observed in oat cultivation, where a more than 4-fold decrease in the activity of these enzymes was observed (Figure 5E,H). In the context of ACP, the activity reduction observed in both buckwheat and wasteland soils due to the impact of waste rock was twice as significant (Figure 5D,F).

The relationships between individual soil physicochemical properties, abundance of individual microbial groups, and soil enzyme activities were tested using principal component analysis (PCA) (Figure 6). For buckwheat soils, principal components Dim1 and Dim2 explained the largest percentage of the variance, with a total of 80.4%, with Dim1 and Dim2 accounting for 58.9% and 21.5%, respectively. For these soils, the studied parameters were not closely correlated with each other. Phosphatase activity, humic substances content, and the abundance of metal-resistant microorganisms and those capable of synthesizing siderophores were most strongly correlated with soils without the influence of waste rock; however, these parameters also showed strong correlations. However, the pH, TOC, and abundance of proteolytic, amylolytic, and cellulolytic microorganisms collared more strongly with soils under the influence of the waste rock. The other tested parameters were separated and showed less correlation with both the described parameters and the type of soil tested (Figure 6A). In the case of soils under oat cultivation, principal components Dim1 and Dim2 explained the largest percentage of the variance, a total of 94.6%, with Dim1 and Dim2 accounting for 88.6% and 6%, respectively. For these soils, differentiation was also observed between the samples with and without the influence of waste rock. However, in the case of these soils, the tested parameters collared more with each other and were shifted toward the soils without the influence of waste rock. Only the pH value in H₂O differed from the other parameters studied and shifted toward soils under the influence of waste rock (Figure 6B). For soils from wasteland, principal components Dim1 and Dim2 explained the largest percentage of the variance, a total of 86.4%, with Dim1 and Dim2 accounting for 75.8% and 10.6%, respectively. A similar relationship was observed between the soils with and without the influence of waste rock in the PCA distribution, as in the case of oat cultivation. Similarly, most of the parameters studied showed a correlation with each other and with soils without the influence of waste rock. In contrast, the TOC content and abundance of metal-resistant microorganisms shifted toward soils under the influence of waste rock (Figure 6C).

3.4. Community Level Physiological Profiling (CLPP)—EcoPlate Biolog^®

For buckwheat and oat cultivation, substrate utilization with EcoPlate Biolog started after 48 h of incubation (Figure 7A,B). In the case of wasteland, the addition of waste rock caused a significant delay in the rate of substrate utilization until 96 h of incubation (Figure 7C). In buckwheat cultivation, very similar levels of AWCD were observed in both soils tested (AWCD560 = 0.387 and AWCD560 = 0.432 after 48 h), which persisted throughout the analysis period (Figure 7A). In contrast, for oats, the mean AWCD was lower in soils under the influence of waste rock (AWCD560 = 0.329 after 48 h) than in soils without the influence (AWCD560 = 0.454 after 48 h) (Figure 7B). The aforementioned delay in the onset of substrate utilization in the waste rock-influenced wasteland persisted throughout the incubation period, where even after 192 h was not at the control soil level (Figure 7C).

The addition of waste rock to the soils did not affect the Shannon diversity index in either buckwheat or oat cultivation soils, which remained at a similar level of H = 3.0 (Figure 7D,E). Only in the case of soils from the wasteland was there a significantly statistical decrease in the H-index in soils influenced by waste rock, from H = 3.1 to H = 2.6 (Figure 7F).

The R-factor showed a similar trend to the AWCD, where soils under buckwheat and oat also showed an increase in the utilization of individual substrates after 48 h of incubation (Figure 7G,H,J,K). Again, soils from wasteland under the influence of waste rock showed a delay in the utilization of individual substrates compared to soil without the influence of waste rock (Figure 7M,N). After 96 h of incubation, the variation in the degree of substrate utilization between the tested soils was assessed (Figure 7F,L,O). In the case of buckwheat cultivation, no statistically significant change in substrate utilization was observed between the test soils, and this trend persisted up to 192 h of incubation (Figure 7G,H,I). In contrast, the R-factor for soils from oat crops was statistically different after 96 h of incubation, and was always 2–3 points lower in samples influenced by waste rock on subsequent incubation days (Figure 7L). The greatest variability in substrate utilization was observed in the wasteland, where the difference between R after 96 h of incubation was R = 10 for soils influenced by waste rock and R = 24 for soils without influence (Figure 7O). This relationship persisted over the subsequent incubation periods (Figure 7M,N).

3.5. Bacterial Community

Analysis of bacteria sequencing data revealed the presence of 241 amplicon sequence variants (ASVs) of which 151 were identified on genera level, belonging to 74 identified family taxa, 32 identified order taxa, 16 identified class taxa, and 11 phyla taxa. The most abundant identified genus was Sphingomonas, followed by Mycobacterium (Figure 8B). Micrococcaceae, Bradyrhizobiaceae, and Acetobacteraceae were the most abundant on family taxa. The most abundant phyla were Proteobacteria followed by Acidobacteria, and Actinobacteria (Figure 8A).

Metastat analysis showed us which taxa determined the differences between samples from different sampling sites. In comparison of buckwheat and oat cultivation samples, a higher number of statistically enriched levels of Lacrimispora were observed in buckwheat cultivation samples. A statistically increased level of 77 bacterial genera was observed in buckwheat cultivation samples compared to wasteland (Figure 8C).

A pooled analysis revealed an abundance of 94 unique bacterial ASVs, most of which were present in samples from oat cultivation, and the core microbiome was represented by 70 ASVs (Figure 8D). The highest number of unique bacterial ASVs was observed in the field with oats cultivation, without influence of waste rock; the lowest in wasteland, without influence of waste rock, and in the field with buckwheat, under the influence of waste rock (Figure 8E).

Alpha diversity indexes calculated based on data from 16S rRNA sequencing showed differences between samples from buckwheat and oat cultivation samples compared to wasteland (Figure 9A,B).

4. Discussion

4.1. Coal Mining Waste Rock and the Problem of Its Management

A separate group of hazards that can lead to negative effects on the environment is waste (coal waste, coal refuse, tailings, rock bank) from the coal industry. Coal waste stored in heaps/piles can be the cause of serious pollution of surface and groundwater and acid drainage of soils, as metallic elements such as iron, manganese, and aluminum are released from this waste in a soluble available form [69], as well as air pollution as a result of the release of toxic compounds during the spontaneous combustion of this waste.

In eastern Poland, one of the largest generators of mining waste is the Bogdanka Mine, which produces approximately 2 million tons of waste per year [70]. Among mining wastes, mining and tailings are distinguished [71]. After separation of the mining spoil, waste rock is produced, among other materials, which is used for land reclamation [14,15,16]. The presence of this waste in environmentally protected areas is particularly problematic for areas described as the “European Amazon”.

4.2. Acid Mine Drainage (AMD) and pH-Decreasing Effect of Waste Rock

The sulfur content of coal mined in Bogdanka [72] is significant and acid mine drainage (AMD) may be formed in the coal mining waste at this mine, contributing to the release of metals, including dangerous heavy metals, from the waste rock into the soil [73,74]. A very pronounced pH-decreasing effect of waste rock was observed in soils not used for agriculture. It has been shown that the cultivation of both monocots and dicotyledonous plants reduced the effect of waste rock and even caused a slight increase in this parameter.

The introduction of waste rock to buckwheat cultivation resulted in soil alkalization, reaching pH_H2O levels in the range of 7.5–8.0. These soils also had the highest pH_H2O and pH_1MKCl values compared to other samples tested (Figure 2A,D). Russell et al. (2024) [75] studies showed that adding mining waste to the soil and the presence of willows (Salix matsudana Koidz. × S. alba L. “Austree”) increased the pH of the soil solution. A higher percentage of mining waste (together with trees) led to a higher pH of the soil solution. Kompała-Bąba et al. (2021) [49] showed that soil from mine dumps covered with grasses (Poa compressa, Calamagrostis epigejos) and forbs (Daucus carota, Tussilago farfara) had higher pH_H2O and pH_1MKCl compared to soil from dumps without vegetation.

An interesting result of the perennial exposure waste rock impact was a 4-fold increase in the organic carbon content in soils unused for agriculture and about 30% in the cultivation of buckwheat, and at the same time the opposite effect (a 4-fold reduction in the organic C content) was observed in soil with a two-year exposure to waste rock and with the cultivation of oats. The AMD, as shown by Oyetibo et al. (2021) [47] for the Onyeama coal mine in Nigeria, contained sulfate (313.0 ± 15.9 mg·L⁻¹), carbonate (253.0 ± 22.4 mg·L⁻¹), and nitrate (86.6 ± 41.0 mg·L⁻¹). This AMD may cause the pollution load index for toxic metals and metalloids to rise to very high values (3110 ± 942 mg·L⁻¹) with a particular risk for release of lead and cadmium and subsequently arsenic, nickel, cobalt, iron, and chromium [47]. However, the microbial communities of these contaminated sites affected by coal waste rock and AMD can actively address these threats, and changes in the composition of the microbiome are therefore one of the best indicators of the impact of these wastes.

4.3. Need to Monitor Biotic and Abiotic Parameters of Soils Treated with Waste Rock

A good solution to avoid the disposal of mining waste seems to be the introduction of this waste in relatively small quantities into wasteland and agricultural land, which could improve the structure of these soils or at least would not have negative environmental effects or inhibit plant growth [76]. However, the use of such a method of disposal of waste rock requires great caution and monitoring the impact of the rock on the condition of the soil, its abiotic and biotic components, and the yield and physiological state of plants. A very good indicator of soil health is the composition, diversity, and abundance of these soils [77]. The results of research on the impact of waste rock, which is a waste rock used for soil reclamation, clearly indicate the need to simultaneously monitor the physical, chemical, and biological parameters of soils along with the state of the soil microbiota in soils used for agriculture and wasteland, which react more strongly to changes in parameters than rhizosphere soils to the addition of waste rock.

4.4. Soil and Plant Microbiota as an Indicator of the Impact of Waste Rock

The biological activity of the environment consists of enzymatic activity (dehydrogenase and phosphatase activity are the main indicators of this activity) and the abundance, physiological activity, and diversity of the main representatives of the microbiota, including oligotrophic and copiotrophic bacteria (adapted to low and high nutrient concentrations, respectively) and microscopic fungi, along with their abundance ratio [45,78,79]. Soil is an environment of diverse organisms interacting with each other, among which the most abundant are microorganisms belonging to the domains of bacteria (Eubacteria) and archaea (Archaea), and to microscopic fungi representing Eukaryota [80]. Many members of the soil microbiota have the ability to colonize the tissues of soil plants and animals, which is their endophytic development for part or the entire life cycle. Among the microbial endophytes of higher organisms, we distinguish both symbionts and parasites, which often develop in the soil as saprotrophs or survive in this environment in spore form [81]. All soil organisms should be considered as a holobiont, that is, a set of organisms that jointly respond to environmental factors [77]. A strong and statistically significant decrease in the abundance of microorganisms was observed with a 2-year exposure of the cereal rhizosphere—oats in the soil. A significant decrease in the abundance of the soil microbiota groups tested—fungi, copiotrophilic and oligotrophic bacteria, microorganisms with cellulolytic, amylolytic, and proteolytic activity, and phosphate-dissolving microorganisms—was observed in soils treated with waste rock when oats were grown on them or when they were wastelands covered with mixed meadow plants (i.e., with long-term waste rock exposure). In the soil from oat cultivation, a decrease in the abundance of microorganisms by 1–1.5 log₁₀/gDW was observed. On the other hand, on wasteland, the influence of waste rock reduced the abundance of copiotrophs and oligotrophs to 6.2 log₁₀/gDW, while the abundance of fungi did not change. Long-term cultivation (buckwheat) contributed to the elimination (leveling out) of the microbial and biochemical differences between the soil under the influence of waste rock and without its influence. The addition of waste rock did not significantly affect the abundance of microorganisms in buckwheat cultivation, reaching values of about 5.5 log₁₀/gDW for fungi and 7.5–7.7 log₁₀/gDW for copiotrophs and oligotrophs.

The presence of heavy metals in the soil, especially in an accessible form, leads to changes in the population of microorganisms, manifested, depending on the concentration of metals and the period of exposure to contamination, by a strong reduction in the overall number of microorganisms and the formation of populations of microorganisms adapted to contamination [36,37]. One of the mechanisms of microorganism interaction with metals contained in artificial and natural substrates (soil) is the ability to chelate metals through non-specific (acids, sugar, and amino acid polymers) and specific (siderophores) complexing compounds [45]. Different relationships could be clearly observed in the case of microorganisms resistant to heavy metals in soils used and not used for agriculture. A significant decrease in the number of microorganisms resistant to heavy metals was recorded in cultivated fields, both in the rhizosphere of monocotyledonous and dicotyledonous plants, regardless of the period of waste rock exposure. On the other hand, in soil not used for agriculture, there was no decrease at all, and even a slight, statistically insignificant, increase in the number of this group of microbiota was observed. It is very interesting in our research that microorganisms capable of complexing metals with the use of strong chelators—siderophores—in cultivated soils treated with waste rock were slightly lower than in those cultivated soils that were not treated with waste rock. However, the greatest decrease in the abundance of microorganisms capable of synthesizing siderophores was recorded on wasteland under the influence of waste rock (1.5 log₁₀/gDW).

4.5. Enzyme Activity as a Reflection of the Influence of Bedrock on Overall Soil Activity

The activity of dehydrogenase in the soil of the rhizosphere of monotyledonous plant—oats was about three times higher than in the soil of the rhizosphere of the dicotyledonous plant—buckwheat, and soil not used for agriculture. The rhizosphere soil from oats exposed to waste had more than 100-times lower dehydrogenase activity (~0.02 µg TPF/h/gDW) than the oat rhizosphere soil without waste rock (~2 µg TPF/h/gDW), and about 4-times less dehydrogenase activity was observed in wasteland soil, whereas in buckwheat cultivation rhizosphere soil, the addition of waste rock did not affect the level of dehydrogenase activity. Very interestingly, were the activity of dehydrogenase (DHA), which in long-term cultivation both under the influence of waste rock and without the influence of waste rock was at a similar level, while much lower activity in soil from short-term cultivation (oats) with waste rock than in soil not under the influence of this rock resulted additionally from a high activity in the soil without the influence of waste rock. As in the case of dehydrogenase activity, the activity of acid and alkaline phosphatase was highest in the rhizosphere of oats not treated with waste rock and was approximately four times higher than that in the rhizosphere of oats under the 2-year term influence of waste rock. In the case of phosphatase activity in the rhizosphere of buckwheat and wastelands (with the long-term impact of waste rock), a decrease in activity was recorded in soils under the influence of waste rock, but the decrease in alkaline phosphatase activity was very small. This is well illustrated in Figure 5. Part of the bacterial microbiota in the waste rock is capable of degrading coal hydrocarbon pollutants and generating hydrogen using formate dehydrogenase enzyme [82]. Kompała-Bąba et al. (2021) [49] showed that the activity of soil enzymes (dehydrogenase, alkaline phosphatase) was higher in soils from hard coal mine spoil heaps covered with vegetation than in those without plants. In turn, the activity of acid phosphatase was lower in soil from hard coal mine spoil heaps covered with grasses (Poa compressa, Calamagrostis epigejos), and higher in soil from hard coal mine spoil heaps overgrown with forbs (Daucus carota, Tussilago farfara) compared to soil from hard coal mine spoil heaps without vegetation.

4.6. Changes in Ecophysiological Parameters as Marker of the Influence of Waste Rock

The physiological activity of microorganisms reflects their ability to participate in various stages of SOM degradation and in the circulation of biogenic elements [83]. The substrate utilization capacity of environmental microorganisms determined by the standard Biolog MicroPlateTM system on EcoPlates enables the determination of the physiological profile and ecophysiological indicators such as AWCD (reflecting overall activity) and the Shannon index (reflecting diversity), and is a very sensitive tool for tracking changes in metabolic activity and diversity occurring in the soil environment under the influence of abiotic and biotic factors [84]. The high metabolic activity in the use of various substrates is conducive to the adaptation of both bacteria and fungi to changing soil conditions and to the colonization of the roots and interior of plants, often by endophytes with properties of plant growth-promotion (PGP), and these properties seem to be largely universal and not limited to specific plant species [85,86]. In all three rhizospheres tested, the AWCD index in the first days of incubation was lower when the soil was under the influence of waste rock, which was particularly evident in soil not used for agriculture, where the rate was close to zero by the 72nd hour. The Shannon index (H), which was significantly lower in the case of wasteland under the influence of waste rock than in the case without the addition of waste rock, is a very clear confirmation that the type of soil use is essential in reducing the impact of waste rock on the physiological activity of the soil microbiome. The values of the R index after 96 h of incubation in non-agricultural soil with waste rock were more than twice lower than in wasteland without the influence of this rock, but also in the cultivation of oats it was slightly, but statistically significantly lower. Similar relationships were indicated by the CLPP analysis, which showed a significant reduction in the metabolic activity of microorganisms in unused soil (wasteland) under the influence of rock, which is indicated by a very low AWCD index—substrate utilization and other indicators calculated on the basis of substrate utilization capacity: Shannon index and, in particular, richness. Similarly, as Wolińska et al. (2020) [87] showed, CLPP proved to be a very sensitive indicator of inhibition of activity reflected by substrate consumption indicators: the AWCD, Shannon index, and richness index, especially, decreased in non-agricultural soil under the influence of waste rock, but the richness index decreased significantly in soil under oat cultivation.

4.7. Soil Organic Matter and Humic Acids as a Marker of Waste Rock Impact on Soil

Abiotic factors cause changes in the soil environment, affecting plants, animals, and their microbiota directly, but mainly indirectly. Plants, in turn, interact with the soil microbiota through rhizodeposits (e.g., root secretions and root border cells) [88]. Higher organisms, both plants and animals, are not only the source of soil organic matter (SOM), but also participate in its degradation, transformation, and nutrient cycling. However, the microbiota inhabiting the soil and the higher organisms that thrive in the soil play a fundamental role in the transformation of SOM. The equilibrium of the soil environment is reflected in the maintenance of its basic physicochemical parameters (pH, organic C and N content and the ratio of these values, concentration of humic acids being the final product of SOM transformations) and biological activity [89]. It was also noted that in soils treated with waste rock used for agricultural purposes for the cultivation of both monocotyledonous and dicotyledonous plants, the decrease in the content of humic acids was very strong, while in the case of wastelands, in which the content of humic acids was the lowest, it was small. In the cultivated soil, the humic acid (KH) content decreased under the influence of the waste rock, but the highest difference from the soil without waste rock observed in short-term oat cultivation was due to the high KH content in the rhizosphere soil of oats, as was the case with dehydrogenase activity.

4.8. Microbiome Diversity as a Marker of Waste Rock Impact on Soil

Our own analysis of bacteria sequencing data showed that differences in the composition of bacteria composition both on genera and phylum level. It was shown that the composition, which was almost identical in cultivated soils, both buckwheat and oats, underwent a marked change under the influence of post-mine rock. Certainly, changes in the abundance and diversity of the microbiota in coal mine waste are influenced by strongly reduced pH, which contributes to the appearance of tolerant microorganisms belonging to both bacteria and fungi adapted to the acidic environment [90,91].

Zhang et al. (2024) [92] noted that different parts of the mine are dominated by different groups of bacteria; Actinobacteria as functional bacteria dominate the rocks accompanying the coal beds and Proteobacteria tolerate poor environments and dominate parts such as mine roadways. Regardless of the type of cultivation, relative abundance of Proteobacteria increased in soil with the addition of waste rock. In soil not used for agriculture, waste rock caused a decrease in the relative abundance of Actinobacteria and a marked increase in the relative abundance of Acidobacteria, which in waste rock soils used for agriculture accounted for approximately 30% of RA of this group of bacteria in wastelands. In the non-cultivated soil, the proportion of Proteobacteria increases under the influence of the waste rock to a level similar to that in the cultivated soil of both plants under the influence of rock, and the share of Actinobacteria was much lower, and in addition to waste rock in unused soil, the level of Acidobacteria. In the wasteland influenced by rock, the abundance of Actinobacteria was reduced 3-fold and without rock influence 2-fold compared to cultivated soils. This is well illustrated in Figure 8A. A study by Lin et al. (2024) [46] showed that the soil from grasslands at the Muli coal mine site in Qinghai was also characterized by the dominance of Proteobacteria (~32%), followed by Actinobacteria (~28%) and Acidobacteria (~15%). The microbiome of drains from the Onyeama coal mine in Nigeria was also distinguished by the dominance of Proteobacteria (50.8%) among the bacteria, and the second dominant group, but with only an 18.9% share of the microbiome, was Bacteroidetes [47]. Similarly to the research on waste from Bogdanka Mine, there was a significant predominance of Ascomycota fungi, which in Nigeria constituted as much as 60.8% of the eukaryotic community. It has been shown that the bacterial community of hyperaccumulator plants (Noccaea caerulescens), capable of accumulating heavy metals such as Pb and Zn, growing on two heavy metal-polluted sites in Belgium, comprised mainly Proteobacteria (seeds) and Actinobacteria in the bulk soil [93]. Plants growing in non-agriculturally unused areas, on poor soils and under stress conditions, shows that N. caerulescens provides an excellent model system to study the mechanisms of heavy metal hyperaccumulation and abundant bacterial and fungal endophytic microbiota [94]. Plants, and especially hyperaccumulator plants, through phytoremediation mechanisms, can significantly contribute to reducing the effects of contamination with both heavy metals and petroleum derivatives, and hyperaccumulator plants, which usually appear naturally in such areas and therefore can be abundant in agriculturally unused wasteland areas, can also support the restoration of these areas to agricultural use [95]. Wolińska et al. (2020) [87] demonstrated that microbial metabolic activity depended on soil properties, varieties of plants, and type of cultivation. In this study, the biodiversity of rhizosphere soils of plants (various varieties of wheat), grown on podzolic soil in a no-tillage system, was determined by two techniques of next generation sequencing (NGS, meta-barcoding of 16S rRNA community) and with the use of Biolog tests to determine the community level physiological profiling (CLPP). This relationship was also confirmed in the study of monoculture of maize by Gałązka and Grządziel (2018) [96]. In this study, the authors showed that fungal diversity was changed under the influence of different cultivation techniques; techniques of maize cultivation and season were important factors that could influence the biochemical activity of soil. Other authors have also confirmed microbial diversity and physical properties depending on the type of soil [97]. The highest biological activity and larger microbial diversity were found in Gleyic Phaeozem, Rendzic Leptosol, and Fluvic Cambisol. This study indicates that a specific edaphone of soil microorganisms may be of great importance when assessing the quality of soil and improving soil health. This effect is particularly important for agricultural soils that are threatened by ongoing land degradation. Changes in the bacterial community are observed in the context of soil pollution [98]. The soils contaminated with oil were characterized by the highest biodiversity indexes. Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria were strongly correlated with biological activity in these soils. Families of Alphaproteobacteria were also dominant, including Bradyrhizobiaceae, Rhizobiaceae, Rhodobacteraceae, Acetobacteraceae, Hyphomicrobiaceae, and Sphingomonadaceae. Gałązka et al. (2020) [98] showed that the long-term contamination of soil changes bacterial communities and their metabolic activity.

The composition of the bacterial community in non-agricultural soil under the influence of bedrock differed significantly from other soils, and in particular from wasteland soils, without the influence of rock. The abundant presence of the genera Acidocella and Acidphilum, absent in wasteland without rock, in the unused soil under the influence of waste rock was strongly associated with the effect of lowering the pH by waste rock in soil not used for agriculture. Significantly lower abundances of Clostridium, Rhizobium, and Blastococcus were recorded in the wasteland soil influenced by waste rock. A very strong impact of waste rock in unused soil on the composition of microorganisms is evidenced by the lack of detection of common genera in long-term cultivated soil and untreated soil treated with waste rock. The metatest analysis made it possible to show the level of individual genera in specific types of use, with particular the influence of buckwheat and oat cultivation on the dominance of Devosia genera, and only buckwheat on the genera Microlunatus and Blasococcus. On the other hand, in soils unused to cultivation, the genera Jatrophihabitans and Dictyobacter clearly dominated, and the genera of diazotrophic bacteria, Mesorhizobium and Bradyrhizobium, were eliminated. Very high numbers of Sphingomonas were found in the rhizospheres of buckwheat and oat crops. The abundance of Mycobacterium and Streptomyces decreased significantly under the influence of the rock.

Coal mining waste in the soil with buckwheat cultivation contributed to the dominance of Sphingomonas, but also such genera as Stenotrophobacter, Microvirga, and Skermanella in the bacterial community, which are absent in the rhizosphere of oats subjected to the action of waste rock. In addition to these three genera, in this oat rhizosphere influenced by the rock, bacteria of the genera were also present in very low numbers: Hyphomicrobium, Dictyobacter, Rhodococcus, Blastococcus, and Streptosporangium. Bacteria from genus Sphingomonas, commonly found in the soil and as endophytes in plant tissues, have great remedial, biostimulatory (through, among other things, the production of auxins and gibberellins), and biocontrol potential to improve plant growth under biotic and abiotic stress conditions such as salinity, drought, and heavy metal pollution [99,100]. In the rhizosphere of buckwheat with waste rock, a significant decrease in the abundance of Rhizobium, Methylobacterium, and Streptosporangium was observed in relation to the rhizosphere of buckwheat without waste rock. This is very unfavorable, as bacteria belonging to diazotrophic Alphaproteobacteria genera Rhizobium and Methylobacterium can colonize not only rhizosphere soil, but also plant tissues and play a significant role in promoting plant growth through nitrogen-fixing processes, making Fe and P available, reducing ethylene levels, producing phytohormones, and inducing plant resistance [101,102]. Streptosporangium, belonging to Actinobacteria, are characterized by high metabolic activity and the ability to produce enzymes that degrade organic matter and numerous antibiotics [103].

Simpson and Shannon alpha diversity indexes also clearly indicate that diversity is high and very similar for soils on which cultivation was carried out, regardless of whether it was buckwheat or oats, while many times lower diversity was found in soils without agricultural cultivation. Venn analysis indicates that the core microbiome was represented by 70 unique bacterial ASVs and at a level similar for common ASVs in soils with buckwheat and oat cultivation, and no common ASVs were found between unused soil and soil with buckwheat cultivation. Shannon and Simpson alpha diversity indexes calculated based on data from 16S rRNA sequencing indicated a huge impact on the type of agricultural use on microbial diversity, with their value, regardless of the plant species cultivated, significant and significantly higher than in soil without cultivation. Almost twice as many unique bacterial ASVs (19) were found in non-agricultural soil than in soils with buckwheat (30) and especially oats (35). The largest, more than a 3-fold decrease in unique bacterial ASVs in soil with the influence of waste rock in relation to soil without effect, was found in the rhizosphere of buckwheat, and a 2-fold decrease in the rhizosphere of oats was observed. In contrast, the complete opposite situation of an increase (almost 2-fold) in ASV numbers in soil influenced by waste rock was observed in the case of a wasteland.

The obtained results indicate that the adverse impact of the coal mining industry is related not only to the mineral itself [39], but to a large extent to the waste rock from this industry. Therefore, there is uncertainty about the attempt to manage this waste from an agricultural point of view. The present research indicates that this waste has a strong effect on the composition of the soil microbiome. At the same time, in soils used for agricultural purposes, the impact of waste rock on the rhizosphere microbiome is much smaller than on the microbiome of wastelands, where the vegetation cover is poor and the impact of root secretions is weak. Comprehensive analysis of the biotic and abiotic parameters of the soils affected by mining waste made it possible to ascertain that very dynamic changes were taking place in the composition of the microbiome and its metabolic activity, as reflected in the values of the ecological indicators. The structure of the soil microbiome, the biochemical processes carried out by the microbiota, and its biodiversity under the influence of the waste rock, leads to a state of equilibrium characteristic of soils not subjected to the impact of waste rock when the soils are used agriculturally and when the process is prolonged. Continuous assessment of microbiome changes is essential to understand the short- and long-term impacts of waste on soil ecosystems, ensuring the implementation of effective reclamation strategies [104].

5. Conclusions

In this article, the biological and physicochemical properties of soils subjected to reclamation with waste rock were examined, in comparison to soils that were not exposed to this type of mining waste. The soils differed in the type of agricultural use and vegetation cover, including field crops—monocotyledons (oats) and dicotyledons (buckwheat)—and wastelands with poor vegetation. Additionally, the soils differed in the duration of the waste rock impact. The following conclusions can be drawn from this study:

(1)

When monitoring the impact of waste rock on the formation, changes, and disturbances of the composition of the microbiome, it is worth combining the indicators of catabolic, ecophysiological (Biolog EcoPlate), and genetic fingerprinting with the determination of physicochemical parameters and indicators of biological activity of soil determined on the basis of determining the activity of soil enzymes and the abundance of various groups of microorganisms cultivated in soils to obtain data on multidirectional changes occurring in the environment, soil structure, and quality, as well as the physiological state, yield, and elemental composition of plants.

(2)

The influence of waste rock on physical parameters, biological and biochemical activity, and the composition of the soil microbiota depended mainly on the method of agricultural use (wastelands, cultivated fields), the type of vegetation cover (monocotyledonous plants, dicotyledonous plants), and, to a much lesser extent, on the duration of waste rock impact. In agriculturally used soil, there is most likely a strong influence of bioremediation processes combining phytoremediation mechanisms supported by the activity of rhizosphere microorganisms, which are characterized by high metabolic activity.

(3)

The introduction of waste rock to soils had a significant effect on pH. The use of these rocks in buckwheat cultivation caused soil alkalization, reaching pH_H2O levels in the range of ~7.5–8.0. These soils were also characterized by the highest pH_H2O and pH_1MKCl values compared to the other soil samples tested.

(4)

Research has shown that long-term cultivation (buckwheat) contributed to the elimination (leveling out) of microbiological and biochemical differences. The addition of waste rock did not significantly affect the abundance of microorganisms in buckwheat cultivation (~5.5 log₁₀/gDW for fungi and 7.5–7.7 log₁₀/gDW for copiotrophs and oligotrophs). In the soil from oat cultivation, a decrease in the abundance of microorganisms by 1–1.5 log₁₀/gDW was observed. On wasteland, the influence of waste rock reduced the abundance of copiotrophs and oligotrophs to 6.2 log₁₀/gDW, while the abundance of fungi remained unchanged.

(5)

The abundance of microorganisms resistant to heavy metals, as well as microorganisms capable of producing specific Fe-binding ligands—siderophores—decreased under the influence of waste rock. The greatest decrease in the number of microorganisms capable of synthesizing siderophores was observed on wastelands (1.5 log₁₀/gDW). The combined analysis revealed an abundance of 94 unique bacterial ASVs, most of which were present in oat cultivation samples, and the core microbiome was represented by 70 ASVs.

(6)

Dehydrogenase activity in long-term cultivation both with and without the influence of waste rock was at a similar level, whereas in the soil from short-term cultivation (oats), it was significantly lower with waste rock (~0.02 µg TPF/h/gDW) than in the soil without its influence (~2 µg TPF/h/gDW). However, in all soil samples tested, a decrease in the activity of both acid phosphatase and alkaline phosphatase was observed due to the addition of waste rock. The most significant decrease in the activity of both enzyme groups was noted in oat cultivation, where the activity of these enzymes decreased more than 4-fold.

(7)

These results allow for the formulation of a recommendation for the introduction of agricultural cultivation in areas under the influence of waste rock. It is recommended to use pre-crop plants, which are intended to supply the soils mainly with elements such as nitrogen and phosphorus, such as phacelia, clover, or other plants entering symbiosis with diazotrophs, that is, plants from the Fabaceae family, but also crops such as mustard or buckwheat.

Waste rock is often used for the reclamation of fields and other agricultural areas. The methods used in this study are planned for application in analyzing the impact of waste rock on rapeseed crops, cereals (rye, wheat), and grass production in meadows.