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Article

Fatty Acids in Lumbricidae as Biomarkers of In Situ Metals Exposure

by
Aleksandra Garbacz
1,*,
Danuta Kowalczyk-Pecka
1,* and
Weronika Kursa
2
1
Department of Zoology and Animal Ecology, Faculty of Environmental Biology, University of Life Sciences in Lublin, Akademicka 13, 20-950 Lublin, Poland
2
Department of Plant Protection, Faculty of Horticulture and Landscape Architecture, University of Life Sciences in Lublin, Akademicka 13, 20-950 Lublin, Poland
*
Authors to whom correspondence should be addressed.
Sustainability 2025, 17(17), 8076; https://doi.org/10.3390/su17178076
Submission received: 6 August 2025 / Revised: 2 September 2025 / Accepted: 3 September 2025 / Published: 8 September 2025
(This article belongs to the Section Hazards and Sustainability)
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Abstract

Hard coal mining activity generates post-mining waste (waste rock). Waste rock is deposited in the environment in large quantities for reclamation of agricultural land. In this study, waste rock was treated as a potential source of metal pollutants. The research material (waste rock, soil, plant roots, and Lumbricidae earthworms) was obtained from sites that had been reclaimed using waste rock as well as sites without waste rock. From each site, 30 individuals (n = 30) were collected, divided into five groups, 6 individuals each. Within the group, individuals were analyzed collectively. The study tested whether selected metals (Cr, Ni, Cd, Ba, Pb, Zn, and Cu) are present in waste rock and whether they can be transferred to the soil, plant root systems, and representatives of Lumbricidae, which are important bioindicators and a source of biomarkers. Particular attention was focused on the assessment of the effects of metals deposited in situ on fatty acids in representatives of Lumbricidae and on selecting a set of fatty acids that can be used as biomarkers of physiological effects, including oxidative stress. A panel of biomarker fatty acids was used, which included a panel of 17 biomarker fatty acids from 35 fatty acids analyzed. To confirm or disprove the usefulness of the biomarker fatty acid panel in earthworms, superoxide dismutase (SOD), catalase (CAT), and thiobarbituric acid reactive substances (TBARS) were determined. The study enabled an effective comparison of reference locations with locations potentially burdened with anthropogenic sediment. The results indicate that selected metals present in the waste rock are transferred to the soil, plant root systems, and soil organisms such as Lumbricidae. Selected metals affected the lipid metabolism of Lumbricidae as stressors, leading to changes in the composition and oxidation of fatty acids. The effect on the physiological state of Lumbricidae depended on the duration of the deposit and the type of use (field, meadow, wasteland) of the land with the waste rock deposit. In earthworms obtained from sites with waste rock deposits, higher contents of biomarker saturated fatty acids and biomarker monounsaturated fatty acids and lower contents of biomarker polyunsaturated fatty acids were found compared to earthworms obtained from sites without waste rock deposits. Only Pb (lead) showed a statistically significant correlation with all analyzed parameters in earthworms obtained from sites with waste rock deposits. The results have significant practical implications for environmental protection management. The proposed set of biomarker fatty acids in Lumbricidae can be used to assess the impact of pollutants and environmental monitoring.

1. Introduction

Earthworms play a key role in terrestrial ecosystems. Owing to their positive effects on soil properties (i.e., physical, chemical, and biological) they are referred to as ecological engineers [1,2,3,4]. They are able to rid the soil of heavy metal contamination due to their ability to detoxify, regulate and eliminate excessive metals [5,6,7]. They take part in the decomposition of organic matter, thus performing an important role in the ecosystem. They are an important link in the food chain, as they connect the underground system to the above-ground system, serving as an important food source for numerous vertebrates, including birds [1,5,8,9]. Underground invertebrates are key components of the diet of nestlings [10]. Earthworms (Oligochaeta, Lumbricidae) in particular are an essential element of the food web and the basis of the diet of many species of birds feeding on invertebrates [11], and they are one of the most common groups of annelids in the diet of birds [12]. Invertebrates are a basic food source for many bird species of the agricultural landscape, and this food significantly influences their breeding success, as nestlings are fed on invertebrates. This food source supplies developing birds with protein essential to their growth and energy [13,14].
Earthworms function as bioindicators due to their ability to accumulate pollutants, such as metals. These invertebrates can be used to monitor soil contamination and assess the ecological effects of these pollutants [15,16,17]. Earthworms are used in standard toxicity tests, such as OECD 207 [18] and OECD 222 [19], and as model organisms in ecotoxicological studies [20]. Bioaccumulation of metals by earthworms can serve as an ecological indicator of the availability of metals [21]. A key factor influencing the accumulation of metals is their content in the environment [22]. Metals enter the body of the earthworm via direct content with the soil, where they are present in the soil solution, or though ingestion, as they are present in food [5]. Depending on need, metals can either be retained or removed from the body [23]. Essential metals which are microelements include zinc (Zn), copper (Cu), chromium (Cr), and nickel (Ni), which can also be toxic in high concentrations, exceeding the physiological requirements of the organism, i.e., the essential levels for the normal course of metabolic processes. Essential metals are controlled and excreted, whereas non-essential metals can be detoxified through binding to organic ligands or sequestration in inorganic matrices. Metals that are non-essential and toxic even at low concentrations include cadmium (Cd), lead (Pb), and barium (Ba). All of these elements are heavy metals, and depending on the concentration and exposure time, they can be potentially toxic to living organisms [6,24,25,26]. Earthworms can reduce the availability of metals in the soil by accumulating and sequestering them in their tissues [27]. The availability of metals can be increased by the decomposition of earthworm tissues which have accumulated large amounts of these elements, and their metabolism has previously increased the bioavailability of metals for other organisms [25]. These invertebrates are able to survive in metal-contaminated soil, but field studies are needed for a better understanding of their physiological activity [28]. Earthworms are able to identify and pass over metal-contaminated soil, which may be an important indicator in the assessment of ecological risk [5].
Coal extraction is an important source of income in many countries. Earthworms are highly sensitive bioindicators of changes in the soil caused by factors originating in mining activity [29]. In some species of earthworms, despite low mortality, a significant reduction in the number of cocoons and juveniles has been observed [30]. Mining waste stored in the environment, including waste rock, poses a threat and affects the physicochemical properties of soil [30,31,32]. The use of earthworms in programmes for monitoring the biological quality of soil has been suggested as a tool for assessing the biodiversity of this environment [30]. Given the sensitivity of organisms to stress associated with various anthropogenic factors, in order to understand the impact of stressors, it is necessary to study their direct effects on organisms. This can be achieved using biomarkers, which are an organism’s measurable biological responses to exposure to pollutants and their consequences [20]. Oxidation processes have been the subject of ecotoxicological studies for many years. They are initiated by various types of environmental stressors: biological, e.g., pathogens [33], physical, e.g., temperature, moisture, or aeration [34], and chemical, e.g., heavy metals or pesticides [35]. Oxidation primarily affects lipids and proteins [36]. Peroxidation of lipids, including phospholipids contained in intra- and extracellular membranes, affects fatty acids (FA), mainly polyunsaturated fatty acids (PUFA), which are attacked by free radicals [37,38]. Earthworms have a diverse range of FAs, of which the predominant acids are C20:4 n−6 and C18:2 n−6c among PUFAs; C16:0 and C18:0 among SFAs (saturated fatty acids); and C18:1 n−9c among MUFAs (monounsaturated fatty acids) [39]. Stressor induction activates defence mechanisms in living organisms: enzymatic, e.g., superoxide dismutase (SOD), catalase (CAT), and glutathione S-transferase (GST), and non-enzymatic, e.g., glutathione (GSH) [38,40,41,42]. These mechanisms can become ineffective, e.g., due to excessive levels of pollutants or long-term exposure even at low concentrations, which can lead to the progression of oxidation, including the initiation of autoxidation processes [43]. Monitoring of the phenomenon of FA peroxidation in Lumbricidae in situ in response to the potential impact of environmental pollutants in the form of metals from waste rock has not previously been considered.
The research hypothesis posits the possibility of transfer of metals deposited in an anthropogenically polluted environment in situ (from waste rock, soil, and plant roots to invertebrate organisms of the family Lumbricidae) and that these metals, as stressors, affect lipid metabolism, leading to changes in the composition and oxidation of fatty acids and in the levels of SOD, CAT and TBARS in the tissues of these organisms. Therefore, these parameters can be treated as biomarkers of physiological status, including oxidative stress. The aim of the study was to assess the impact of selected metals deposited in situ on fatty acids, SOD, CAT and TBARS in representatives of Lumbricidae and to identify a set of fatty acids that can be used as biomarkers of the biological (physiological) impact of environmental pollutants in situ.
The research has significant practical implications for environmental monitoring and management. A novelty is the proposal of a panel of biomarker fatty acids in Lumbricidae as biomarkers of the biological (physiological) effects of environmental pollutants, which has not been widely used in environmental monitoring and management to date. The proposed panel opens up new possibilities for the use of Lumbricidae as bioindicators and broadens the perspective of biomonitoring, as it can be helpful in assessing the impact of pollution and complement existing methods of environmental monitoring. Another important element is the presentation of metal transfer from waste rock (post-mining waste deposited in the environment as part of land reclamation) to soil, root systems, and Lumbricidae as primary consumers, as well as the assessment of the impact of metals on biomarker fatty acids and enzymatic and non-enzymatic biomarkers of oxidative stress in Lumbricidae. This approach could be helpful in monitoring the state of the environment.

2. Materials and Methods

2.1. Experimental Design

The research material consisted of waste rock, soil, plant roots, and earthworms (Lumbricidae) obtained from sites that had been reclaimed using waste rock as well as sites without waste rock (Control), from a depth of up to 0.25 m below ground level. From each site, 30 individuals (n = 30) were collected, divided into 5 groups, 6 individuals each. Within the group, individuals were analyzed collectively. The specimens were of similar size, i.e., 6–8 cm, suggesting similar age, with a distinct clitellum. The sites differed in the type of agricultural use: field, meadow, and wasteland. The sites were located in eastern Poland, in the Polesie region of the Lublin voivodeship (Table 1, Figure 1). The material was collected at sites where waste rock (WR) from a hard coal mine had been deposited for the purposes of reclamation, as well as in sites with no waste rock deposit. The research material was collected in 2022 (September).
Once the material was obtained, the earthworms were left without food for 24 to clean out the digestive tract and remove food residues, minimizing the risk of sample contamination and ensuring reliable and comparable analysis results. The earthworms were then frozen at −80 °C for subsequent analysis.

2.2. Determination of Selected Metals in Waste Rock, Soil, Plant Roots and Lumbricidae

Samples with waste rock, roots and earthworms were crushed and homogenized; soil samples were sifted and crushed. Samples weighing 0.5 g were used for the analyses. Samples were digested in the presence of HNO3 (Suprapur-Merck, Darmstadt, Germany) in a CEM Mars Xpress microwave (USA) (210 °C/7 atm). The digestates were diluted with demineralized water (conductivity 0.055 µS/cm).

2.2.1. Analysis by Inductively Coupled Plasma Mass Spectrometry (ICP-MS)

The solutions were analyzed using the 820-MS ICP-MS mass spectrometer (USA) according to the CLB/ESA/5/2019 procedure (version 3). The following metals were analyzed: Cr, Ni, Cd, Ba, and Pb. The gas used to generate the plasma was argon (Messer, Germany) with 99.999% purity. Ultra Scientific (USA) standards with 99.999% purity were used. No reaction cell (CRI) was used. The settings were as follows: Plasma Flow—16 dm3/min, Nebulizer Flow—0.98 dm3/min, RF Power—1.38 kW, Sampling Depth—6.5 mm. The following isotopes were used: 52Cr, 60Ni, 114Cd, 137Ba, 206Pb, 207Pb and 208Pb. Validation parameters: Cr (LOD-limit of detection = 0.015 mg·kg−1, LOQ-limit of quantification = 0.030 mg·kg−1, recovery = 97%), Ni (LOD = 0.022 mg·kg−1, LOQ = 0.044 mg·kg−1, recovery = 98%), Cd (LOD = 0.004 mg·kg−1, LOQ = 0.007 mg·kg−1, recovery= 99%), Ba (LOD = 0.038 mg·kg−1, LOQ= 0.076 mg·kg−1, recovery = 97%), Pb (LOD = 0.005 mg·kg−1, LOQ = 0.010 mg·kg−1, recovery = 99%). Determinations were made by the standard curve method. The results were expressed in mg/kg fresh weight. Quality was controlled by measuring a blank sample, a double sample and certified reference material: NIST-1577c Bovine Liver (National Institute of Standards & Technology, Gaithersburg, MD, USA). Results are expressed as mg·kg−1.

2.2.2. Analysis by Flame Atomic Absorption Spectrometry (FAAS)

The solutions were analyzed using the Varian SpektrAA 280FS FAAS Spectrometer with the SPS-3 autosampler and SIPS diluter (Varian, Mulgrave, Australia). FAAS analysis was carried out according to the CLB/ASA/2/2019 procedure (version 4). The metals analyzed by FAAS were Zn and Cu. The stock solutions were Zn (10 mg/dm3) and Cu (20 mg/dm3) from CPA Chem (Stara Zagora, Bulgaria). The standards were certified according to ISO 17034 [44]. The operating parameters of the spectrometer were as follows: Zn (flame: acetylene/air, wavelength: 213.9 nm, slit width: 1.0 nm, lamp current: 5.0 mA); Cu (flame: acetylene/air, wavelength: 324.8 nm, slit width: 0.5 nm, lamp current: 4.0 mA). Validation parameters: Zn (LOD = 0.4 mg·kg−1, LOQ = 0.09 mg·kg−1, recovery = 106%), Cu (LOD = 1.3 mg·kg−1, LOQ = 2.6 mg·kg−1, recovery = 99%). The matrix was 2% HNO3. Results are expressed as mg·kg−1.

2.3. Lipid Extraction and Recovery of Fatty Acids from Lumbricidae

Samples of material were crushed and homogenized. Fat samples weighing 100 mg were used for the analyses. Saponification was carried out by adding a methanolic KOH solution (Avantor Performance Materials, Gliwice, Poland), and esterification with a methanolic BF3 solution (Thermo Scientific, China). Esters of fatty acids were obtained according to the CLB/GC/3/2019 procedure (version 4). Esters were isolated with C6H14 (Avantor Performance Materials, Gliwice, Poland) and salted out with a saturated NaCl solution (Avantor Performance Materials, Gliwice, Poland). The fatty acid ester sample was dried by adding anhydrous Na2SO4 (Avantor Performance Materials, Gliwice, Poland), and chromatographic analysis was performed. Samples of fatty acid esters were analyzed using the Varian 450-GC gas chromatograph (Varian, Palo Alto, CA, USA) with the CP-8400 autosampler, an FID detector (temperature 270 °C), and the Select™ Biodiesel capillary column (Agilent Technologies, Santa Clara, CA, USA) for FAME (30 m 0.32 mm 0.25 μm). A 1177 Split/Splitless injector was used (temperature 250 °C). The initial temperature of the furnace column was 100 °C, and the final temperature was 240 °C. The stationary phase of the fused silica Select Biodiesel column for FAME was used, with helium as the carrier gas. The flow rate was 1.5 mL/min. The Galaxie™ Chromatography Data System was used to control the chromatograph and to collect, integrate and calculate the results. Among the 35 fatty acids analyzed, following initial assessment of the differences in the amounts of FAs between locations, a panel of biomarker FAs was selected: C12:0; C14:0; C16:0; C18:0; C20:0; C21:0; C24:0; C16:1 n−7; C18:1 n−9c + C18:1 n−9t; C20:1 n−9; C18:2 n−6c + C18:2 n−6t; C18:3 n−3; C20:2 n−6; C20:3 n−3; C20:4 n−6; C20:5 n−3; and C22:2 n−6. Total SFAs, PUFAs and MUFAs were calculated.

2.4. Peroxidation and Unsaturation Indices

Based on the fatty acid analysis, peroxidation (PI) and unsaturation (UI) indices were calculated. A formula developed by Hulbert et al. (2007) [45] was employed:
Peroxidation index (PI) = 0.025 × (% monoenoics) + 1 × (% dienoics) + 2 × (% trienoics) + 4 × (% tetraenoics) + 6 × (% pentaenoics) + 8 × (% hexaenoics)
Unsaturation index (UI) = 1 × (% monoenoics) + 2 × (% dienoics) + 3 × (% trienoics) + 4 × (% tetraenoics) + 5 × (% pentaenoics) + 6 × (% hexaenoics)

2.5. Analysis of Enzymatic Biomarkers of Oxidative Stress

Superoxide dismutase (SOD) activity was measured by the indirect method described by Atli and Grosell (2016) [46]. Absorbance was measured at 550 nm for 1 min using a microplate spectrophotometer (Varioskan™ LUX Thermo Scientific™, Waltham, MA, USA). Results are expressed as Unit/mg protein.
Catalase activity (CAT) was measured using the method described by Atli and Grosell (2016) [46]. The absorbance decline was examined at 240 nm for 1 min using a microplate spectrophotometer (Varioskan™ LUX Thermo Scientific™, Waltham, MA, USA). Results are expressed as µmol H2O2/mg protein/min.

2.6. Analysis of Non-Enzymatic Biomarkers of Oxidative Stress—TBARS (Thiobarbituric Acid Reactive Substances)

The malondialdehyde (MDA) concentration was used as a marker of lipid peroxidation. It was determined according to the method described by Radwan et al. (2010a, 2010b) [47,48]. Absorbance was measured at 532 nm for 1 min using a microplate spectrophotometer (Varioskan™ LUX Thermo Scientific™, Waltham, MA, USA). Results are expressed as nM of MDA/mg of wet tissue.

2.7. Statistical Analyses

The data were subjected to statistical analysis using Statistica version 13.3 software (1984–2017 TIBCO Software INC, Palo Alto, CA, USA). The normality was assessed using the Kolmogorov–Smirnov test, and the Levene’s homogeneity of variance test was applied to examine the equality of variances. Two-way ANOVA was used to assess the effect of the waste rock deposit (WR deposit, without WR deposit) and the type of land (buckwheat, oats, wasteland I and II, meadow I and II) as well as their interaction on the content of each FAs, PI and UI indices, SOD, CAT and TBARS. One-way ANOVA and Tukey’s multiple range tests were performed to compare all experimental groups and the Control one (sites without WR deposit). Lower and upper 95% confidence intervals (CI) were expressed in the original scale of measurement.
As part of the assessment of the linear relation between FAs and PI and UI indices, SOD, CAT and TBARS content and content of metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu)
Pearson’s linear correlation coefficient (r) were calculated at a significance level of p ≤ 0.01 and the interpretation was based on the following Matyja (2014) [49] scale: negligible correlation: 0 < r < |0.1|; weak correlation: |0.1| ≤ r < |0.3|; moderate correlation: |0.3| ≤ r < |0.5|; strong correlation: |0.5| ≤ r < |0.7|; very strong correlation: |0.7| ≤ r < |0.9|; nearly perfect correlation: |0.9| ≤ r < |1|.
Cluster analyses (area and feature clustering) were conducted using data standardized relative to the FAs, PI and UI indices, SOD, CAT and TBARS content.
Additionally, the full correlation matrix was calculated for variables related to Pb to control the risk of the error in multiple comparisons. The Benjamini–Hochberg procedure was applied with a false discovery rate (FDR) set at 0.01. For each test, the Benjamini–Hochberg (BH) threshold was calculated as:
F D R   B H   t h r e s h o l d s = i m ⋅ α
where i—the rank of the test (1–31), m—the total number of tests (31), and α = 0.01. Tests with p_value ≤ FDR (BH) thresholds were considered statistically significant [50].

3. Results

3.1. Metals: Waste Rock—Soil—Plant Roots—Earthworms

Upon entering the environment, heavy metals contained in waste rock were transferred to the soil, plant roots, and organisms of the family Lumbricidae (Table 2, Table 3, Table 4 and Table 5). In the waste rock (WR) samples collected from all sites, accumulation of barium (Ba) and zinc (Zn) was highest, and that of lead (Pb) and nickel (Ni) was lowest, while cadmium (Cd) was not detected. The highest concentrations of individual elements in the waste rock were noted at the following sites: Pb and Zn—buckwheat field (WR > 10 years), Cr—meadow I (WR > 1 year), and Ba, Ni and Cu—wasteland II (WR < 1 year). The lowest content in WR was noted at the following sites: Cr and Ni—wasteland I (WR > 10 years), Cr and Ba—oat field (WR = 2 years), Pb and Zn—meadow II (WR < 1 year), and Cu—meadow I (WR > 1 year) (Table 2).
In the samples of soil, plant roots, and earthworms from all study sites, the highest accumulation was noted for Zn and the lowest for Cd (Table 3, Table 4 and Table 5). Specifically, the highest concentrations of Pb, Ni, Cu and Zn were noted in the soil from wasteland I with long-term waste rock deposit (WR > 10 years); the highest Cd accumulation was detected in soil from the buckwheat field (WR > 10 years); and Cr and Ba concentrations were highest in soil from the meadow I with a WR deposit of more than one year (WR > 1 year). The lowest soil concentrations of individual elements were observed in samples from the following sites without WR: Pb and Zn—meadow II, Cd and Ba—wasteland I, Cr—oat field, and Ni and Cu—buckwheat field. The content of the analyzed metals was influenced (p ≤ 0.01) by all single factors (WR, S), as well as the interaction between them (WRxS) (Table 3).
In the case of plant roots, accumulation of Pb, Cr, Ni and Cu was greatest in the samples collected from wasteland I (WR > 10 years), Cd and Ba in the samples from meadow II (WR < 1 year), and Zn in the samples from meadow II (−WR), where −WR means no WR deposit. The lowest concentrations of individual elements in the roots were observed at the following site without WR: Pb—wasteland II, Cd—buckwheat field, Cr and Ni—meadow I, Ba—wasteland I, and Zn and Cu—oat field. The content of the analyzed metals was influenced (p ≤ 0.01) by all single factors (WR, S), as well as the interaction between them (WRxS) (Table 4).
The accumulation of metals Pb, Cd, Zn and Cu was greatest in earthworms from the wasteland I with a long-term deposit of waste rock (WR > 10 years). The highest concentrations of Cr, Ba and Ni were noted in earthworms from the meadow I with a waste rock deposit exceeding one year (WR > 1 year). The lowest concentrations of individual metals were detected in earthworms from the following locations without WR: Pb—meadow I, Cd—meadow II, Zn—wasteland II, Cu—oat field, and Cr, Ba and Ni—oat field. The content of the analyzed metals was influenced (p ≤ 0.01) by all single factors (WR, S), as well as the interaction between them (WRxS) (Table 5).
On the crop fields (buckwheat and oat) with a short-term deposit of waste rock, there was not enough time for the metals to be transferred from the plant roots to the earthworms, whereas on the long-term waste rock deposit on wasteland I with species-poor vegetation and in the meadows, plants were able to store certain metals, enabling their transfer to earthworms.

3.2. Biomarker FAs, Peroxidation (PI) and Unsaturation (UI) Indices, Enzymatic (SOD, CAT) and Non-Enzymatic (TBARS) Biomarkers of Oxidative Stress

A set of biomarker fatty acids (FA) in earthworms was proposed—C12:0 (lauric acid); C14:0 (myristic acid); C16:0 (palmitic acid); C18:0 (stearic acid); C20:0 (arachidic acid, eicosanoic acid); C21:0 (heneicosanoic acid); C24:0 (lignoceric acid, tetracosanoic acid); C16:1 n−7 (palmitoleic acid); C18:1 n−9c (oleic acid) + C18:1 n−9t (elaidic acid); C20:1 n−9 (cis-11-eicosenic acid); C18:2 n−6c (linoleic acid) + C18:2 n−6t (linolelaidic acid); C18:3 n−3 (α-linolenic acid); C20:2 n−6 (cis-11-14-eicosadienic acid); C20:3 n−3 (eicosatrienic acid); C20:4 n−6 (arachidonic acid); C20:5 n−3 (cis-5,8,11,14,17-eicosapentaenic acid, EPA); and C22:2 n−6 (cis-13-16-docosadienic acid) (Table 6, Figure 2A).
The analyses showed that in earthworms obtained from the sites with waste rock, the content of saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) was higher than at the sites without waste rock, while that of polyunsaturated fatty acids (PUFAs) was lower. Content of SFAs and MUFAs was highest in earthworms from wasteland I (WR > 10 years) and oat field (WR = 2 years), while PUFAs dominated in the samples from meadow I (−WR), meadow II (−WR) and wasteland II (−WR). The SFA content was lowest in earthworms from meadow I (−WR), meadow II (−WR) and wasteland II (−WR); MUFA content in earthworms from meadow I (−WR) and meadow II (−WR); and PUFAs were lowest in specimens from wasteland I (WR > 10 years) and oat field (WR = 2 years) (Table 6, Figure 2B). The predominant fatty acids were C16:0 and C18:0 among SFAs; C18:1 n−9c + C18:1 n−9t among MUFAs; and C20:4n−6, C18:2 n−6c + C18:2 n−6t among PUFAs. Small amounts of FAs were noted for C20:0 and C24:0 among SFAs; C16:1 n−7 and C20:1 n−9 among MUFAs; and C20:5 n−3 among PUFAs (Table 6). The content of C14:0, C16:0, C18:0, C21:0 and C24:0 was highest in earthworms from wasteland I with a long-term deposit of waste rock (WR > 10 years). Content of C20:0 was highest in earthworms from oat field (WR = 2 years) and wasteland I (WR > 10 years), while C12:0 content was highest in samples from wasteland II (WR < 1 year). The content of C16:1 n−7 was highest in earthworms from wasteland I (WR > 10 year) and wasteland II (WR < 1 year) and lowest in those from the buckwheat field (−WR). The content of C18:1 n−9c + C18:1 n−9t was highest in earthworms from the oat field (WR = 2 years) and wasteland I (WR > 10 years) and lowest in earthworms from meadow I (−WR). The concentration of C20:1 n−9 was highest in earthworms from the buckwheat field (WR > 10 years) and lowest in those from wasteland I (−WR). In the case of PUFAs, the highest content of acids C18:2 n−6c + C18:2 n−6t, C18:3 n−3, and C20:3 n−3 was detected in earthworms from sites without waste rock: meadow I, meadow II and wasteland II. The content of C20:2 n−6 was highest in samples from the buckwheat field, wasteland II and meadow II, while that of C20:4 n−6 was highest in samples from meadow II and from wasteland I and II. The content of C20:5 n−3 was highest in earthworms from meadows I and II, while that of C22:2 n−6 was highest in samples from the buckwheat field and meadow II. The lowest concentrations of PUFAs C18:2 n−6c + C18:2 n−6t, C18:3 n−3, C20:3 n−3, C20:4 n−6, C20:5 n−3 and C22:2 n−6 were observed in earthworms from sites with long-term exposure to waste rock, i.e., the buckwheat field (WR > 10 years) and wasteland I (WR > 10 years). In addition, the content of C18:2 n−6c + C18:2 n−6t was low in earthworms from the oat field (WR = 2 years) (Table 6, Figure 2A). In earthworms from locations with waste rock, the peroxidation index (PI) and unsaturation index (UI) were lower than in the control, i.e., earthworms from locations without waste rock. The highest PI was noted in earthworms from meadow II (−WR), and the highest UI in those from meadow I (−WR). The values of both indices were lowest in earthworms from the wasteland I with a long-term deposit of waste rock (WR > 10 years) (Table 6, Figure 2B). These findings confirm that organisms from the habitats subjected to long-term exposure to waste rock (WR > 10 years) had the most unfavourable physiological response in terms of peroxidation of FAs, whereas deposits of shorter duration resulted in improvement of these parameters in annelids.
To assess the usefulness of the biomarker FAs in earthworms, the activity of antioxidant enzymes—superoxide dismutase (SOD) and catalase (CAT)—was determined, as well as the level of lipid peroxidation end products (TBARS). SOD and CAT activity was reduced in all samples of earthworms from the sites with waste rock, accompanied by an increased TBARS level, in comparison with organisms from sites without waste rock. SOD activity was highest in earthworms from meadow II (−WR) and lowest in those from the buckwheat field (WR > 10 years) and wasteland I (WR > 10 years). CAT activity was highest in samples from the buckwheat field (−WR) and lowest in those from wasteland I with a long-term waste rock deposit (WR > 10 years). The TBARS value was highest in earthworms from wasteland I (WR > 10 years) and lowest in those from meadow I and meadow II (−WR) (Table 6, Figure 2B). The content of the analyzed biomarkers FAs, SFA, MUFA, PUFA, PI and UI indices, SOD, CAT and TBARS was influenced (p ≤ 0.01) by all single factors (WR,S), as well as the interaction between them (WRxS)

3.3. Pearson’s Correlation

Pearson’s correlation analysis was conducted between metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu) and analyzed biomarker FAs, peroxidation (PI) and unsaturation (UI) indices, enzymatic (SOD, CAT) and non-enzymatic (TBARS) biomarkers of oxidative stress in earthworms obtained from sites with (Table 7) and without (Table 8) waste rock deposits.
Only Pb showed a statistically significant correlation with all analyzed parameters. Among the analyzed biomarker fatty acids, only C21:0 showed a positive, statistically significant correlation with all seven metals. For PUFA, PI, and UI, positive, statistically significant correlations were observed with Ba and Ni, while negative, statistically significant correlations were observed with lead (Pb, Cd, and Zn). An inverse relationship was observed for MUFA and PUFA, which showed an opposite trend. Antioxidant enzyme activity also showed significant correlations with metals. SOD was negatively, statistically significantly, correlated with Pb, Cd, Zn, and Cu, while CAT showed negative, statistically significant correlations with Pb, Cd, Cr, Zn, and Cu. TBARS was positively and statistically significantly correlated with Pb, Cd, Cr, Zn and Cu (Table 7).
Among the analyzed FA biomarkers, the highest number of statistically significant correlations with metals were shown by C16:0 and C20:0. PUFAs showed a positive, statistically significant correlation with Ba and a negative, statistically significant correlation with Cd. MUFAs were negatively, statistically significant correlated with Cr, Ba, Ni, and Cu. SFAs showed positive, statistically significant correlations with Cd and Zn, and negative, statistically significant correlations with Ba and Ni. PI and UI were positively, statistically significant correlated with Cr, Ba, Ni, and Cu. PI showed negative, significant correlations with Cd and Zn, while UI with Pb, Cd, and Zn. Among antioxidant enzymes, SOD was positively and statistically significantly correlated with Ni and negatively and statistically significantly correlated with Pb. TBARS showed positively and statistically significantly correlated with Pb, Cd, and Zn, and negatively and statistically significantly correlated with Cr and Ni. For CAT, no statistically significant correlations were found with any of the analyzed metals (Table 8).
The reliability of the results was confirmed using the Benjamini–Hochberg FDR correction, as the associations between Pb and fatty acid profiles as well as oxidative stress parameters remained statistically significant (Table 9). This indicates that they reflect genuine and biologically meaningful relationships.

4. Discussion

Ecotoxicological analyses of soil and animals most often make use of invertebrate organisms, especially Aschelminthes and gastropods [51]. Earthworms are constantly exposed to pollutants in the soil, via both ingestion and passive absorption through the cuticle, which predisposes them to assessment of the ecotoxicological role or impact of soil pollutants. Assessment of the environmental risk associated with soil pollutants is crucial to the protection of soil ecosystems. Earthworms are commonly used as model organisms in studies associated with ecotoxicology [20]. To determine the extent of the impact of potential pollutants on living organisms, widespread bioindicator organisms are currently sought as sources of economically, instrumentally, and constructively optimal biomarkers. Earthworms are a useful source of this type of biomarker, with a proposed novel panel of biomarker fatty acids: C12:0; C14:0; C16:0; C18:0; C20:0; C21:0; C24:0; C16:1 n−7; C18:1 n−9c + C18:1 n−9t; C20:1 n−9; C18:2 n−6c + C18:2 n−6t; C18:3 n−3; C20:2 n−6; C20:3 n−3; C20:4 n−6; C20:5 n−3; C22:2 n−6 and the peroxidation index (PI) and unsaturation index (UI).
Earthworms are an important element in the food chain because they connect underground and above-ground ecosystems [1,5,8]. Their presence in the food chain depends on various soil factors, such as fertilization, climate, plant species, and the interactions between these factors [52]. Metals are absorbed by soil due to its sorption properties [53]. Earthworms are sensitive to sub-threshold quantities of metals in the environment, which means that even minimal concentrations which do not cause acute toxicity or death can induce perceptible (by testing or visually in vivo) physiological changes, such as disturbances in the activity of antioxidant enzymes, indicative of the occurrence of oxidative stress. Upon entering the environment, metals (Cr, Ni, Ba, Pb, Zn, and Cu) present in waste rock are transferred to the soil, to root systems of plants, and to Lumbricidae representatives. Despite the absence of Cd in waste rock, its presence in soil, plant roots, and earthworms suggests that it may originate from atmospheric deposition [54]. In the crop fields (buckwheat and oats) with deposited waste rock, the ability of earthworms to take up metals from the roots of annual plants was limited due to the short growing period; for this reason, the soil was the main source of these elements for invertebrates. In contrast, in the wasteland with a long-term deposit of waste rock, with poor vegetation, and in the meadows with this waste, plants were able to accumulate metals in their root tissue, which created a potential route of transfer of these elements to earthworms. The concentrations of metals present in the soil were nontoxic, as the organisms survived and the available amounts were not lethal to them.
Although bioaccumulation of metals in the food chain may not be harmful to earthworms, it induces detectable physiological responses, e.g., in the form of fatty acid peroxidation in these invertebrates and in organisms at higher trophic levels which feed on earthworms [5]. Absorption of metals by these organisms depends on numerous factors, such as the earthworm’s species, habitat and choice of food; moreover, the speciation, bioavailability and mobility of metals are important factors in this process [5,55]. Metals can be processed in various ways depending on the defence strategies of organisms against their potential harmful effects. Depending on need, metals can either be retained or removed from an earthworm’s body. Each earthworm species has its own unique method of protection against the negative effects of metals [23]. Earthworms are able to accumulate significant quantities of heavy metals, transferring them from areas with high concentrations to areas with a lower concentration [25,56]. On the other hand, they can restrict the mobility of metals by secreting mucus which binds soil and metal particles [56,57].
The main site of metal accumulation in earthworms is chloragogen tissue. Two routes of intracellular binding of metals in this tissue can be distinguished: pathway A and pathway B. Pathway A binds lead (Pb) and zinc (Zn) in insoluble form, replacing calcium (Ca), which leads to detoxification by accumulating and decreasing the availability of these metals at harmful concentrations. Pathway B has various functions depending on the metal concentration in the soil [25]. A key factor in determining the toxic effects of metals on organisms is metal-binding proteins, such as metallothioneins (MT), which play an important role in preventing the toxicity of metals. Two isoforms of metallothionein (MT1 and MT2) have been identified in earthworms; MT1 transports essential metals, such as Zn and Cu at nontoxic concentrations, while MT2 inactivates and detoxifies non-significant metals such as Cd and essential metals such as Zn when their concentrations exceed the toxic threshold [25,58,59]. However, long-term exposure to metals can lead to local adaptation, which can influence the responses of biomarkers in earthworms collected in the field in comparison to those bred in the laboratory [60]. Earthworms are capable of specific regulation of metal uptake [61]. Local adaptation and acclimatization can influence accumulation patterns, i.e., the means, rate, and level of accumulation of metals in their tissues, potentially leading to intraspecific differences [60,61]. Zn plays a dual role in the metabolism of earthworms of the family Lumbricidae, as a microelement and as a potential toxin at elevated concentrations. Whereas a low level of zinc is essential for various metabolic processes, supporting the growth and reproduction of earthworms [26], an elevated Zn level leads to significant weight loss, a reduced growth rate, and a reduction in body length in these invertebrates [62]. Earthworms are particularly sensitive to copper, which plays a dual role in the metabolism of earthworms, exerting both beneficial and harmful effects. Cu is an essential microelement in various metabolic processes and can exert a stimulatory effect at low concentrations [63]. It is crucial to enzymatic functions, including cytochrome P450s [64]. Excessive exposure to copper can lead to toxicity, because it is not degraded and accumulates in soils, potentially harming soil organisms [63]. Studies have shown that high amounts of Cu have a negative impact on various levels of biological organization [35,63,65]. The lowest levels, such as lysosomes, are the most sensitive [63]. However, there are doubts regarding the impact of excessive amounts of Cu on the reproduction and development of earthworms [66]. The toxicity of copper increases the production of reactive oxygen species through mitochondrial dysfunction, which damages DNA and leads to apoptosis [67]. Soils in nature often contain a mixture of pollutants. Analysis of the effect of copper in polluted soils is complicated, because other pollutants can increase the sensitivity of organisms to copper or protect it against toxicity. Moreover, due to the ‘ageing’ process of metals, assessment of the impact of copper becomes more important, as its bioavailability and toxicity depend on the duration of its presence in the soil [63]. Cd, as a heavy metal, exerts toxic effects such as induction of oxidative stress, DNA damage, and carcinogenesis; it also affects the immune system by reducing the number of coelomocytes in earthworms [68,69]. It is one of the most harmful metals. Many studies have shown that the presence of Cd in soil negatively affects the growth and development of earthworms, leading to overproduction of reactive oxygen species and aldehydes. This induces oxidative stress, abnormal gene expression, and inhibition of growth and reproduction. Earthworms exposed to Cd reduce food intake in order to avoid toxic effects. Cadmium also affects metabolism, resulting in weight loss and damage to mitochondrial enzymes and peroxisomes, which accelerates their ageing. Most studies focus on elevated concentrations of Cd (10–1000 mg/kg) and their impact on the behaviour, growth and survival of these organisms [70,71,72,73,74]. The decrease in the body weight of earthworms induced by Cd is the result of their stress response, which leads them to reduce food intake in order to avoid toxins. Earthworms use this strategy to protect themselves from poisoning, including with heavy metals [74,75]. In a polluted environment, earthworms can adapt their metabolic processes to reduce the harmful impact of metals, which often results in weight loss. Cd can bind to specific protein thiols in the mitochondrial membrane, which alters mitochondrial permeability and leads to lipid peroxidation. This metal can also disrupt the functions of mitochondrial enzymes, e.g., citrate synthase, and can accelerate ageing of peroxisomes by increasing the activity of native proteases and enzymes of the glyoxylate cycle [74]. The reactions of earthworms to Pb pollution constitute a basis for the assessment of ecological risk [76,77]. This element is extremely persistent, with a retention time of 150–5000 years in soil. It serves no biological function, which means that there are no safe levels of its presence, and its effects can lead to irreversible damage [78]. Metabolomic studies, i.e., analyses of small molecules (metabolites) in the body, reveal that exposure to low levels of Pb in soil disturbs amino acid metabolism, energy metabolism, and osmotic balance, leading to oxidative stress and neurotoxic effects. Histopathological damage is observed as well [79]. Exposure to Pb inhibits the growth rate of earthworms, and higher concentrations are correlated with reduced growth [80]. Cr plays a complicated role in the metabolism of earthworms; it is present in six oxidation states, among which Cr (III) and Cr (VI) are the most stable forms. Cr (VI) is highly toxic and acts as a strong oxidant, leading to the production of reactive oxygen species (ROS) and cellular damage. It is able to penetrate the cell membrane, enter the cytoplasm, and react with intracellular structures [81]. Although it can be essential in small quantities for certain metabolic processes, higher concentrations are harmful, and its effects are complex. Exposure to chromium increases malondialdehyde and metallothionein levels, which indicates oxidative damage and stress in earthworms [82]. In earthworms exposed to soils with Cr at concentrations of 0.24–893 mg/kg, tissue changes can take place, such as cell fusion and a decrease in the thickness of the epidermis, even at the lowest concentrations [83,84]. Soil contaminated with chrome can also affect reproduction in earthworms [84,85]. Compared to other metals, data on nickel accumulation in earthworms is limited [86]. At low concentrations, Ni can stimulate the activity of antioxidant enzymes such as superoxide dismutase (SOD) and catalase (CAT), which play a key role in protecting cells against oxidative stress [87]. Podolak et al. (2011) [88] showed that earthworms from polluted areas have high accumulation potential, associated with an ineffective Ni regulation mechanism. Moreover, high Ni concentrations only minimally affected the mortality of adult earthworms, which means that accumulation remained high [86,89]. Hirano and Tamae (2010) [90], on the other hand, did not observe Ni uptake by earthworms and determined that it was non-bioaccumulative. Ni pollution can have toxic consequences, such as growth inhibition, problems with reproduction, changes in enzyme activity, and damage to DNA and tissues [91]. There is also little information on the effects of barium on earthworms, but it is known not to be an essential nutrient for these organisms. Barium can be highly mobile in soil, because it mainly associates with soil colloids through ion exchange [92,93,94]. In soluble form it is toxic for soil invertebrates. In nature, barium is primarily present in the form of barite (BaSO4), which is its most stable and insoluble form. Apart from sulfate, barium can also occur as calcium carbonate and in the form of soluble salts, which are rarely encountered in nature but can appear in soils polluted by industrial activity [92,95]. A study by Lamb (2013) [92] demonstrated that in barite-contaminated soils, the body weight of earthworms decreases, which is positively correlated with the barium concentration in the soil. In earthworms collected from locations with waste rock, two indicators, i.e., PI (peroxidation index), indicating the total content of fatty acids in cell membranes, and UI (unsaturation index), reflecting the number of double bonds in membranes [45,96], were lower than in the control group, i.e., earthworms from locations without waste rock. According to the results of the study, the most unfavourable physiological response in terms of peroxidation of fatty acids was observed in earthworms from habitats that had been exposed to waste rock for more than 10 years. As the duration of the waste rock deposit decreased, the physiological parameters in Annelida improved, which indicates that their status depends on the duration of contamination. Apart from the duration of the deposit, the type of land use was important as well; in wasteland, where accumulation and in some cases magnification of metals in the roots of perennial plants is possible, the potential transfer of pollutants to the soil and directly to organisms (by ingestion or through the skin) increases. This leads to disturbances in lipid metabolism and thus to changes in the composition and oxidation of fatty acids. In contrast, the use of land for crops (e.g., cereals) or meadows kept in good agricultural condition limited the negative impact of metals in terms of lipid metabolism in these invertebrates.
The study enabled an effective comparison of reference locations with locations potentially burdened by anthropogenic sediment. In the natural environment, many contaminated soils contain more than one metal, which can lead to synergistic effects between various pollutants. To enhance the reliability of the results for the bioavailability of metals, analyses have been carried out using contaminated soils, both in laboratory conditions and by collecting earthworms directly from contaminated areas [97]. The impact of metal mixtures and the responses of organisms are the result of biological activity, bioavailability, and the characteristics of biochemical processes taking place in specific taxa and specific organisms belonging to these taxa, as well as potential interactions between components of the mixture. These interactions can take place at various levels and may result in higher or lower toxicity than in individual substances. The presence of one pollutant in soil can influence the way another pollutant is bound, which in turn changes its availability for organisms. In organisms, a pollutant can affect the detoxification processes of another pollutant, which in turn can alter its toxicity for a given individual. In effect, the results of analyses of the impact of individual compounds may not reflect the actual impact of mixtures of pollutants present in the environment [20]. Due to the sensitivity of organisms to stress associated with pollutants, their direct impact on the organism can be determined using biomarkers, which are valued as potential tools for assessment of ecological risk [1]. The use of biomarkers in field studies should take into account the possibility of local adaptation of earthworms which have been exposed to long-term pollution, because this can affect their biological reactions in comparison to laboratory samples. Individuals from contaminated areas can exhibit increased tolerance due to the potential occurrence of adaptive genes or altered defence mechanisms [60]. It is worth conducting in situ studies in combination with in vitro studies, with the closest possible levels of exposure to the pollutants analyzed, in order to limit the impact of additional environmental factors and facilitate precise analysis of selected physiological responses—in this case peroxidation of fatty acids, which can be particularly important when saturated fatty acids (SFAs) predominate.
The proposed set of biomarker FAs in earthworms (C12:0; C14:0; C16:0; C18:0; C20:0; C21:0; C24:0; C16:1 n−7; C18:1 n−9c + C18:1 n−9t; C20:1 n−9; C18:2 n−6c + C18:2 n−6t; C18:3 n−3; C20:2 n−6; C20:3 n−3; C20:4 n−6; C20:5 n−3; and C22:2 n−6) differs in some ways from the panel of biomarker FAs determined for other terrestrial invertebrates, e.g., in gastropod tissues (C16:0; C18:0; C23:0; C18:1 n−9; C20:1 n−9; C18:2 n−6; C18:3 n−3; C20:2; C20:4 n−6; C20:5 n−3; C22:4 n−6; and C22:5 n−3) according to Kowalczyk-Pecka et al. (2017a, 2017b) [98,99]. Earthworm tissues naturally have a higher proportion and diversity of saturated fatty acids (SFAs), which means that the panel of biomarker FAs contains more SFAs than in the case of snails. Sampedro at al. (2006) [39] showed that earthworm tissues have higher content of PUFAs than of SFAs. In the present study, SFA and MUFA content was higher in earthworms from sites with waste rock than in the groups without waste rock, while PUFA content was lower. Moreover, in earthworms inhabiting sites with waste rock deposits, compared to sites without this deposit, a higher content of metals such as Pb, Cd, Cr, Ba, Ni, Zn, Cu and a higher content of biomarker fatty acids such as C12:0, C14:0, C16:0, C18:0, C20:0, C21:0, C24:0, C16:1 n−7, C18:1 n−9c + C18:1 n−9t and C20:1 n−9 was observed, with a simultaneous reduction in the content of biomarker fatty acids such as C18:2 n−6c + C18:2 n−6t, C18:3 n−3, C20:2 n−6, C20:3 n−3, C20:4 n−6, C20:5 n−3 and C22:2 n−6. The predominant FAs were C20:4n−6 and C18:2 n−6c + C18:2 n−6t among PUFAs; C16:0 and C18:0 among SFAs; and C18:1 n−9c + C18:1 n−9t among MUFAs. Small amounts were detected for FA C20:5 n−3 among PUFAs; C20:0 and C24:0 among SFAs; and C16:1 n−7 and C20:1 n−9 among MUFAs. PUFAs play a role in cell membrane permeability; in particular, the balance between n−6 and n−3 acids in cell membranes and lysosome membranes is essential to their normal functioning [100]. Apart from the protective function of PUFAs in preserving cell membrane integrity, some of these acids have antibacterial effects [99]. Some peroxidation processes have been shown to stop at monounsaturated fatty acids. There were probably factors that arrested the degradation of polyunsaturated acids, so that inversion to monounsaturated fatty acids took place, but not necessarily to saturated fatty acids. To verify the suitability of the panel of biomarker FAs in earthworms, enzymatic (superoxide dismutase and catalase) and non-enzymatic (thiobarbituric acid reactive substances) biomarkers of oxidative stress were determined. Superoxide dismutase (SOD) is an enzyme with antioxidant properties which catalyzes dismutation of superoxide anions (O2−) to molecular oxygen (O2) and hydrogen peroxide (H2O2), protecting cells against damage induced by these reactive oxygen species. Catalase (CAT) functions as an enzyme decomposing hydrogen peroxide into water and oxygen, preventing the accumulation of this harmful compound [101]. Thiobarbituric acid reactive substances (TBARS) are by-products of lipid peroxidation whose determination enables assessment of the level of lipid peroxidation in tissues [102]. The values of these biochemical parameters were consistent with the changes observed in the oxidation of fatty acids. From a practical perspective, this research could have significant implications for land reclamation and soil engineering. The analysis of biomarker fatty acids, as well as enzymatic and non-enzymatic biomarkers of oxidative stress in earthworms, could provide a valuable tool for environmental monitoring, including processes related to reclamation activities. Integrating a biomarker-based approach into practical environmental monitoring framework could complement traditional methods of assessing environmental status, while also providing clearer guidelines for practical application in environmental management. Incorporating biomarkers of physiological status into soil engineering practices could be an important element of this approach, supporting the development of sustainable environmental monitoring and management strategies.
Earthworms, through their soil activity, influence the microbiological properties of soil, which is crucial for the stability of soil ecosystems. Their intestine creates a unique ecologic niche with stable conditions, in contrast to the surrounding environment. Bacteria in the digestive tract of earthworms represent those present in the soil only to a limited degree, i.e., mainly those that are resistant to the conditions prevailing there. This means that the microbiota of the digestive tract of these invertebrates is a selective portion of soil microorganisms [68]. Exposure to metals influences the composition of fatty acids, leads to lipid peroxidation, and damages cell membranes [6,103,104]. Heavy metals such as Pb and Cd deactivate key sulfhydryl groups, which induces oxidative stress [6]. In situ, the fatty acid profile can be affected not only by the transfer of metals themselves (waste rock, soil, and plant roots to invertebrates of the family Lumbricidae), but also to some extent by fatty acids from the intestinal microbiome.
Some of the observed patterns, such as increased SFA and decreased PUFA in earthworms from sites with waste rock deposits, may not solely reflect the influence of waste rock. Alternative explanations include differences in diet, variation in gut microbiome composition, and seasonality, which may also contribute to the observed variability. Despite detailed analysis of biomarker FA, PI and UI indices, and enzymatic and non-enzymatic biomarkers of oxidative stress, these potential confounding factors must be considered. Future studies could eliminate or control these confounding factors by using a controlled diet, monitoring the gut microbiome, and repeating experiments at different times of the year.

5. Conclusions

Earthworms are a source of useful biomarker fatty acids (FAs), and the proposed panel comprises C12:0; C14:0; C16:0; C18:0; C20:0; C21:0; C24:0; C16:1 n−7; C18:1 n−9c + C18:1 n−9t; C20:1 n−9; C18:2 n−6c + C18:2 n−6t; C18:3 n−3; C20:2 n−6; C20:3 n−3; C20:4 n−6; C20:5 n−3; and C22:2 n−6. The composition of this panel differs from the panel in gastropod tissues, as earthworm tissues naturally contain a greater number of diverse saturated fatty acids (SFAs) than gastropods. Therefore, the panel of biomarker FAs in earthworms contains more SFAs. In turn, selected metals contained in the waste rock, once released into the environment, were transferred to the soil, plant roots, and Lumbricidae. The potential primary source of metals for earthworms in fields was soil, while in wasteland and meadows, plant roots were sources as well. In crop fields (buckwheat and oat) with waste rock, there was not enough time for metals to be transferred from the roots of annual plants to earthworms. In contrast, on wasteland with a long-term deposit of waste rock, with very species-poor vegetation, and on meadows with waste rock, plants were able to store metals in their roots for a long time, even for many years, which enabled the potential transfer of these metals from plant roots to the body of earthworms. The type of use of land with a waste rock deposit and the duration of the deposit influenced the physiological status of the organisms. In wasteland, it was possible for metals to accumulate and sometimes magnify in the roots of perennial plants. This in turn could affect the transfer of pollutants to the soil and to the body of earthworms per os or per cutis, with pronounced negative physiological consequences. The use of the study sites for cereal cultivation or meadows kept in good agricultural condition reduced the physiologically perceptible negative impact of metals on these invertebrates. The least favourable physiological response for Oligochaeta at the level of FA peroxidation was observed in organisms from the habitats that had been exposed to waste rock for more than 10 years. According to the duration of the deposit, i.e., the shorter the duration, the more favourable the physiological parameters in Annelida. Waste rock as an environmental stressor and a potential source of pollutants that cause disturbances in the functioning of Lumbricidae, influenced lipid metabolism and thus changes in the composition and oxidation of fatty acids treated as biomarkers of physiological status, including oxidative stress. To confirm or disprove the usefulness of the panel of biomarker FAs in earthworms, superoxide dismutase (SOD), catalase (CAT) and thiobarbituric acid reactive substances (TBARS) were determined; the levels of these parameters were consistent with the changes noted in the composition and oxidation of fatty acids. The results confirm that earthworms, like other invertebrates, are sensitive to small changes in the content of metals in the environment due to their position as primary consumers in the food chain. Invertebrates belonging to Lumbricidae can be a useful biomonitoring tool as effective bioindicators of the state of the soil environment. At the same time, waste rock can be a potential source and a theoretical and experimental basis for further, more extensive research. In future studies, it is planned to use microbiological and metagenomic analyses to assess the impact of metals deposited in the environment, a key element of which is the deposition of waste rock on terrestrial invertebrates.

Author Contributions

Conceptualization, A.G. and D.K.-P.; methodology, A.G. and D.K.-P.; formal analysis, A.G.; investigation, A.G. and D.K.-P.; resources, A.G.; writing—original draft preparation, A.G. and D.K.-P.; writing—review and editing, A.G.; visualization, W.K.; project administration, A.G.; funding acquisition, A.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by project no. SD/50/NB/2022 and SD/74/NB/2023 provided by the University of Life Sciences in Lublin, Poland.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data will be made available on request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Shi, Z.; Tang, Z.; Wang, C. A Brief Review and Evaluation of Earthworm Biomarkers in Soil Pollution Assessment. Environ. Sci. Pollut. Res. 2017, 24, 13284–13294. [Google Scholar] [CrossRef]
  2. Edwards, C.A. Earthworm Ecology; CRC Press: Boca Raton, FL, USA, 2004. [Google Scholar]
  3. Bartlett, M.D.; Briones, M.J.; Neilson, R.; Schmidt, O.; Spurgeon, D.; Creamer, R.E. A Critical Review of Current Methods in Earthworm Ecology: From Individuals to Populations. Eur. J. Soil Biol. 2010, 46, 67–73. [Google Scholar] [CrossRef]
  4. Capowiez, Y.; Lévèque, T.; Pelosi, C.; Capowiez, L.; Mazzia, C.; Schreck, E.; Dumat, C. Using the Ecosystem Engineer Concept to Test the Functional Effects of a Decrease in Earthworm Abundance Due to an Historic Metal Pollution Gradient. Appl. Soil Ecol. 2021, 158, 103816. [Google Scholar] [CrossRef]
  5. Sivakumar, S. Effects of Metals on Earthworm Life Cycles: A Review. Environ. Monit. Assess. 2015, 187, 530. [Google Scholar] [CrossRef] [PubMed]
  6. Yadav, R.; Kumar, R.; Gupta, R.K.; Kaur, T.; Kour, A.; Kaur, S.; Rajput, A. Heavy Metal Toxicity in Earthworms and Its Environmental Implications: A Review. Environ. Adv. 2023, 12, 100374. [Google Scholar] [CrossRef]
  7. Luo, W.; Verweij, R.A.; van Gestel, C.A. Determining the Bioavailability and Toxicity of Lead Contamination to Earthworms Requires Using a Combination of Physicochemical and Biological Methods. Environ. Pollut. 2014, 185, 1–9. [Google Scholar] [CrossRef]
  8. Jager, T. Mechanistic Approach for Estimating Bioconcentration of Organic Chemicals in Earthworms (Oligochaeta). Environ. Toxicol. Chem. 1998, 17, 2080–2090. [Google Scholar] [CrossRef]
  9. Barras, A.G.; Candolfi, I.; Arlettaz, R. Spatio-Temporal Patterns of Earthworm Abundance Suggest Time-Limited Food Availability for a Subalpine Bird Species. Pedobiologia 2022, 93–94, 150826. [Google Scholar] [CrossRef]
  10. Rhymer, C.M.; Devereux, C.L.; Denny, M.J.; Whittingham, M.J. Diet of Starling Sturnus vulgaris Nestlings on Farmland: The Importance of Tipulidae Larvae. Bird Study 2012, 59, 426–436. [Google Scholar] [CrossRef]
  11. Orłowski, G.; Książkiewicz-Parulska, Z.; Karg, J.; Bocheński, M.; Jerzak, L.; Zub, K. Using Soil from Pellets of White Storks Ciconia ciconia to Assess the Number of Earthworms (Lumbricidae) Consumed as Primary and Secondary Prey. Ibis 2016, 158, 587–897. [Google Scholar] [CrossRef]
  12. Navedo, J.G.; Gutiérrez, J.S.; Salmón, P.; Arranz, D.; Novo, M.; Díaz-Cosín, D.J.; Herrera, A.G.; Masero, J.A. Food Supply, Prey Selection and Estimated Consumption of Wintering Eurasian Curlews Feeding on Earthworms at Coastal Pastures. Ardea 2020, 107, 263–274. [Google Scholar] [CrossRef]
  13. Basedow, T. Changes in Agriculture in an Area in Northern Germany between the Years 1971 and 2000, and the Reactions of Populations of Predatory Carabids (Col., Carabidae), of Other Predators, and of Cereal Aphids, to These Changes. J. Plant Dis. Prot. 2002, 109, 1–14. [Google Scholar]
  14. Holland, J.M.; Hutchison, M.A.S.; Smith, B.; Aebischer, N.J. A Review of Invertebrates and Seed-bearing Plants as Food for Farmland Birds in Europe. Ann. Appl. Biol. 2006, 148, 49–71. [Google Scholar] [CrossRef]
  15. Zhang, Z.S.; Zheng, D.M.; Wang, Q.C.; Lv, X.G. Bioaccumulation of Total and Methyl Mercury in Three Earthworm species (Drawida sp., Allolobophora sp., and Limnodrilus sp.). Bull. Environ. Contam. Toxicol. 2009, 83, 937–942. [Google Scholar] [CrossRef] [PubMed]
  16. Georgescu, B.; Georgescu, C.; Daraban, S. Use of Lumbricides Species as Biological Indicators of Environmental Pollution with Metalodisrupters. Lucr. Ştiinţifice 2011, 55, 63–67. [Google Scholar]
  17. Wang, X.; Cairang, S.; Du, J.; Wei, Z.; Wu, Q.; Hu, L.; Xu, M. A Large-Scale Assessment of Soil Heavy Metal Pollution Using Field-Collected Earthworms as Bio-Indicators in Shaoguan, South China. Environ. Heal. 2025, 3, 616–625. [Google Scholar] [CrossRef] [PubMed]
  18. OECD. Test No. 207: Earthworm, Acute Toxicity Tests. In OECD Guidelines for the Testing of Chemicals; OECD Publishing: Paris, France, 1984. [Google Scholar]
  19. OECD. Test No. 222: Earthworm Reproduction Test (Eisenia fetida/Eisenia andrei). In OECD Guidelines for the Testing of Chemicals; OECD Publishing: Paris, France, 2016. [Google Scholar]
  20. Velki, M.; Ečimović, S. Important Issues in Ecotoxicological Investigations Using Earthworms. Environ. Contam. Toxicol. 2016, 239, 157–184. [Google Scholar] [CrossRef]
  21. Van Gestel, C.A.; Koolhaas, J.E.; Hamers, T.; van Hoppe, M.; van Roovert, M.; Korsman, C.; Reinecke, S.A. Effects of Metal Pollution on Earthworm Communities in a Contaminated Floodplain Area: Linking Biomarker, Community and Functional Responses. Environ. Pollut. 2009, 157, 895–903. [Google Scholar] [CrossRef]
  22. Hobbelen, P.H.F.; Koolhaas, J.E.; van Gestel, C.A.M. Bioaccumulation of Heavy Metals in the Earthworms Lumbricus rubellus and Aporrectodea caliginosa in Relation to Total and Available Metal Concentrations in Field Soils. Environ. Pollut. 2006, 144, 639–646. [Google Scholar] [CrossRef]
  23. Ardestani, M.M.; van Straalen, N.M.; van Gestel, C.A. Uptake and Elimination Kinetics of Metals in Soil Invertebrates: A Review. Environ. Pollut. 2014, 193, 277–295. [Google Scholar] [CrossRef]
  24. Spurgeon, D.J.; Hopkin, S.P. Comparisons of Metal Accumulation and Excretion Kinetics in Earthworms (Eisenia fetida) Exposed to Contaminated Field and Laboratory Soils. Appl. Soil Ecol. 1999, 11, 227–243. [Google Scholar] [CrossRef]
  25. Sizmur, T.; Hodson, M.E. Do Earthworms Impact Metal Mobility and Availability in Soil?–A Review. Environ. Pollut. 2009, 157, 1981–1989. [Google Scholar] [CrossRef]
  26. Lev, S.M.; Matthies, N.; Snodgrass, J.W.; Casey, R.E.; Ownby, D.R. Effects of Zinc Exposure on Earthworms, Lumbricus terrestris, in an Artificial Soil. Bull. Environ. Contam. Toxicol. 2010, 84, 687–691. [Google Scholar] [CrossRef]
  27. Liu, X.; Hu, C.; Zhang, S. Effects of Earthworm Activity on Fertility and Heavy Metal Bioavailability in Sewage Sludge. Environ. Int. 2005, 31, 874–879. [Google Scholar] [CrossRef] [PubMed]
  28. Yuvaraj, A.; Govarthanan, M.; Karmegam, N.; Biruntha, M.; Kumar, D.S.; Arthanari, M.; Govindarajan, R.K.; Tripathi, S.; Ghosh, S.; Kumar, P.; et al. Metallothionein Dependent-Detoxification of Heavy Metals in the Agricultural Field Soil of Industrial Area: Earthworm as Field Experimental Model System. Chemosphere 2021, 267, 129240. [Google Scholar] [CrossRef] [PubMed]
  29. Tirado-Ballestas, I.P.; Taylor, M.K.; Caballero-Gallardo, K.; Olivero-Verbel, J.; Callaham, M.A., Jr. Effects of Bituminous Coal Dust Exposure on Reproduction of Sinella curviseta (Collembola) and Eisenia fetida (Clitellata). Appl. Soil Ecol. 2025, 209, 106038. [Google Scholar] [CrossRef]
  30. Römbke, J.; Dorow, W.H.; Jänsch, S. Distribution and Diversity of Earthworms (Lumbricidae) in Hesse (Central Germany): Current Knowledge. Soil Org. 2018, 90, 171–185. [Google Scholar] [CrossRef]
  31. Garbacz, A.; Nowak, A.; Marzec-Grządziel, A.; Przybyś, M.; Gałązka, A.; Jaroszuk-Ściseł, J.; Grzywaczewski, G. Impact of Coal Waste Rock on Biological and Physicochemical Properties of Soils with Different Agricultural Uses. Sustainability 2025, 17, 2603. [Google Scholar] [CrossRef]
  32. Joniec, J.; Kwiatkowska, E.; Walkiewicz, A.; Grzywaczewski, G. Changes in Microbial Activity Associated with the Nitrogen Biogeochemical Cycle in Differently Managed Soils, Including Protected Areas and Those Reclaimed with Gangue. Sustainability 2025, 17, 4343. [Google Scholar] [CrossRef]
  33. Ghosh, S. Environmental Pollutants, Pathogens and Immune System in Earthworms. Environ. Sci. Pollut. Res. 2018, 25, 6196–6208. [Google Scholar] [CrossRef]
  34. Edwards, C.A.; Arancon, N.Q. The Influence of Environmental Factors on Earthworms. In Biology and Ecology of Earthworms; Springer: New York, NY, USA, 2022; pp. 191–232. [Google Scholar]
  35. Uwizeyimana, H.; Wang, M.; Chen, W.; Khan, K. The Eco-Toxic Effects of Pesticide and Heavy Metal Mixtures towards Earthworms in Soil. Environ. Toxicol. Pharmacol. 2017, 55, 20–29. [Google Scholar] [CrossRef]
  36. Musakhanian, J.; Rodier, J.D.; Dave, M. Oxidative Stability in Lipid Formulations: A Review of the Mechanisms, Drivers, and Inhibitors of Oxidation. AAPS PharmSciTech 2022, 23, 151. [Google Scholar] [CrossRef] [PubMed]
  37. Singh, V.; Mathew, B.J.; Rai, R.; Chaurasiya, S.K. Phospholipase C in Bacterial Infections. In Phospholipases in Physiology and Pathology; Academic Press: Cambridge, MA, USA, 2023; pp. 217–234. [Google Scholar]
  38. Chakraborty, N.; Mitra, R.; Dasgupta, D.; Ganguly, R.; Acharya, K.; Minkina, T.; Popova, V.; Churyukina, E.; Keswani, C. Unraveling Lipid Peroxidation-Mediated Regulation of Redox Homeostasis for Sustaining Plant Health. Plant Physiol. Biochem. 2024, 206, 108272. [Google Scholar] [CrossRef] [PubMed]
  39. Sampedro, L.; Jeannotte, R.; Whalen, J.K. Trophic Transfer of Fatty Acids from Gut Microbiota to the Earthworm Lumbricus terrestris L. Soil. Biol. Biochem. 2006, 38, 2188–2198. [Google Scholar] [CrossRef]
  40. Wang, Z.; Li, C.; Shao, Y.; Xue, W.; Wang, N.; Xu, X.; Zhang, Z. Antioxidant Defense System Responses, Lysosomal Membrane Stability and DNA Damage in Earthworms (Eisenia fetida) Exposed to Perfluorooctanoic Acid: An Integrated Biomarker Approach to Evaluating Toxicity. RSC Adv. 2021, 11, 26481–26492. [Google Scholar] [CrossRef]
  41. Roubalová, R.; Procházková, P.; Dvořák, J.; Škanta, F.; Bilej, M. The Role of Earthworm Defense Mechanisms in Ecotoxicity Studies. Invertebr. Surviv. J. 2015, 12, 203–213. [Google Scholar]
  42. Chaitanya, R.K.; Shashank, K.; Sridevi, P. Oxidative Stress in Invertebrate Systems. In Free Radicals and Diseases; Ahmad, R., Ed.; IntechOpen: London, UK, 2016; Volume 19, pp. 51–68. [Google Scholar]
  43. Ahmad, S. Oxidative Stress and Antioxidant Defenses in Biology; Springer Science & Business Media: Berlin/Heidelberg, Germany, 1995. [Google Scholar]
  44. ISO 17034; General Requirements for the Competence of Reference Material Producers. ISO: Geneva, Switzerland, 2016.
  45. Hulbert, A.J.; Pamplona, R.; Buffenstein, R.; Buttemer, W.A. Life and Death: Metabolic Rate, Membrane Composition, and Life Span of Animals. Physiol. Rev. 2007, 87, 1175–1213. [Google Scholar] [CrossRef]
  46. Atli, G.; Grosell, M. Characterization and Response of Antioxidant Systems in the Tissues of the Freshwater Pond Snail (Lymnaea stagnalis) during Acute Copper Exposure. Aquat. Toxicol. 2016, 176, 38–44. [Google Scholar] [CrossRef]
  47. Radwan, M.A.; El-Gendy, K.S.; Gad, A.F. Biomarkers of Oxidative Stress in the Land Snail, Theba pisana for Assessing Ecotoxicological Effects of Urban Metal Pollution. Chemosphere 2010, 79, 40–46. [Google Scholar] [CrossRef]
  48. Radwan, M.A.; El-Gendy, K.S.; Gad, A.F. Oxidative Stress Biomarkers in the Digestive Gland of Theba pisana Exposed to Heavy Metals. Arch. Environ. Contam. Toxicol. 2010, 58, 828–835. [Google Scholar] [CrossRef]
  49. Matyja, M. Social Side of Agricultural Co-Operatives. The Case of Agricultural Production Co-Operatives in the Opole Voivodship. J. Agribus. Rural Dev. 2014, 33, 113–124. [Google Scholar]
  50. Benjamini, Y.; Drai, D.; Elmer, G.; Kafkafi, N.; Golani, I. Controlling the False Discovery Rate in Behavior Genetics Research. Behav. Brain Res. 2001, 125, 279–284. [Google Scholar] [CrossRef]
  51. Traczewska, T.M. Biologiczne Metody Oceny Skażenia Środowiska; Oficyna Wydawnicza Politechniki Wrocławskiej: Wroclaw, Poland, 2011; ISBN 978-83-7493-597-5. [Google Scholar]
  52. Gębski, M. Czynniki Glebowe Oraz Nawozowe Wpływające Na Przyswajanie Metali Ciężkich Przez Rośliny. Postępy Nauk. Rol. 1998, 45, 3–16. [Google Scholar]
  53. Bori, J.; Vallès, B.; Navarro, A.; Riva, M.C. Ecotoxicological Risks of the Abandoned F–Ba–Pb–Zn Mining Area of Osor (Spain). Environ. Geochem. Health 2017, 39, 665–679. [Google Scholar] [CrossRef] [PubMed]
  54. Bouida, L.; Rafatullah, M.; Kerrouche, A.; Qutob, M.; Alosaimi, A.M.; Alorfi, H.S.; Hussein, M.A. A Review on Cadmium and Lead Contamination: Sources, Fate, Mechanism, Health Effects and Remediation Methods. Water 2022, 14, 3432. [Google Scholar] [CrossRef]
  55. Sizmur, T.; Tilston, E.L.; Charnock, J.; Palumbo-roe, B.; Watts, M.J.; Hodson, M.E. Impacts of Epigeic, Anecic and Endogeic Earthworms on Metal and Metalloid Mobility and Availability. J. Environ. Monit. 2011, 13, 266–273. [Google Scholar] [CrossRef]
  56. Hansda, A.; Kumar, V. A Comparative Review towards Potential of Microbial Cells for Heavy Metal Removal with Emphasis on Biosorption and Bioaccumulation. World J. Microbiol. Biotechnol. 2016, 32, 170. [Google Scholar] [CrossRef]
  57. Zhang, D.; Yin, C.; Abbas, N.; Mao, Z.; Zhang, Y. Multiple Heavy Metal Tolerance and Removal by an Earthworm Gut Fungus Trichoderma brevicompactum QYCD-6. Sci. Rep. 2020, 10, 6940. [Google Scholar] [CrossRef]
  58. Sturzenbaum, S.R.; Winters, C.; Galay, M.; Morgan, A.J.; Kille, P. Metal Ion Trafficking in Earthworms. J. Biol. Chem. 2001, 276, 34013–34018. [Google Scholar] [CrossRef]
  59. Stürzenbaum, S.R.; Kille, P.; Morgan, A.J. The Identification, Cloning and Characterization of Earthworm Metallothionein. Febs Lett. 1998, 431, 437–442. [Google Scholar] [CrossRef]
  60. Pauwels, M.; Frérot, H.; Souleman, D.; Vandenbulcke, F. Using Biomarkers in an Evolutionary Context: Lessons from the Analysis of Biological Responses of Oligochaete Annelids to Metal Exposure. Environ. Pollut. 2013, 179, 343–350. [Google Scholar] [CrossRef] [PubMed]
  61. Terhivuo, J.; Pankokoski, E.; Hyvärinen, H.; Koivisto, I. Pb Uptake by Ecologically Dissimilar Earthworm (Lumbricidae) Species near a Lead Smelter in South Finland. Environ. Pollut. 1994, 85, 87–96. [Google Scholar] [CrossRef] [PubMed]
  62. Mahmood, S.M.; Mohammed, A.M. Effects of Zinc Accumulation on Earthworm Aporrectodea caliginosa (Haplotaxida: Lumbricidae). J. Ris. Biol. Dan. Apl. 2023, 5, 8–15. [Google Scholar] [CrossRef]
  63. Pelosi, C.; Gavinelli, F.; Petit-dit-Grezeriat, L.; Serbource, C.; Schoffer, J.T.; Ginocchio, R.; Yáñez, C.; Concheri, G.; Rault, M.; van Gestel, C.A.M. Copper Toxicity to Earthworms: A Comprehensive Review and Meta-Analysis. Chemosphere 2024, 362, 142765. [Google Scholar] [CrossRef]
  64. Yang, X.X.; Zhang, W.; Cao, X.F. Long-Term Effect of Copper with Sublethal Dose on Cytochrome P450 and Antioxidant Enzyme Activities of Earthworms. Acta Sci. Circumstantiae 2012, 32, 745–750. [Google Scholar]
  65. Bart, S.; Pelosi, C.; Nélieu, S.; Lamy, I.; Péry, A.R. An Energy-Based Model to Analyze Growth Data of Earthworms Exposed to Two Fungicides. Environ. Sci. Pollut. Res. 2020, 27, 741–750. [Google Scholar] [CrossRef]
  66. Marini, E.; De Bernardi, A.; Tagliabue, F.; Casucci, C.; Tiano, L.; Marcheggiani, F.; Vaccari, F.; Taskin, E.; Puglisi, E.; Brunetti, G.; et al. Copper Toxicity on Eisenia fetida in a Vineyard Soil: A Combined Study with Standard Tests, Genotoxicity Assessment and Gut Metagenomic Analysis. Environ. Sci. Pollut. Res. 2024, 31, 13141–13154. [Google Scholar] [CrossRef]
  67. Bundy, J.G.; Sidhu, J.K.; Rana, F.; Spurgeon, D.J.; Svendsen, C.; Wren, J.F.; Stürzenbaum, S.R.; Morgan, A.J.; Kille, P. “Systems Toxicology” Approach Identifies Coordinated Metabolic Responses to Copper in a Terrestrial Non-Model Invertebrate, the Earthworm Lumbricus rubellus. BMC Biol. 2008, 6, 25. [Google Scholar] [CrossRef]
  68. Šrut, M.; Menke, S.; Höckner, M.; Sommer, S. Earthworms and Cadmium–Heavy Metal Resistant Gut Bacteria as Indicators for Heavy Metal Pollution in Soils? Ecotoxicol. Environ. Saf. 2019, 171, 843–853. [Google Scholar] [CrossRef]
  69. Höckner, M.; Piechnik, C.A.; Fiechtner, B.; Weinberger, B.; Tomanek, L. Cadmium-Related Effects on Cellular Immunity Comprises Altered Metabolism in Earthworm Coelomocytes. Int. J. Mol. Sci. 2020, 21, 599. [Google Scholar] [CrossRef]
  70. Sinkakarimi, M.H.; Solgi, E.; Hosseinzadeh, C.A. Interspecific Differences in Toxicological Response and Subcellular Partitioning of Cadmium and Lead in Three Earthworm species. Chemosphere 2020, 238, 124595. [Google Scholar] [CrossRef]
  71. Urionabarrenetxea, E.; Garcia-Velasco, N.; Marigómez, I.; Soto, M. Effects of Elevated Temperatures and Cadmium Exposure on Stress Biomarkers at Different Biological Complexity Levels in Eisenia fetida Earthworms. Comp. Biochem. Physiol. Part C Toxicol. Pharmacol. 2020, 231, 108735. [Google Scholar] [CrossRef]
  72. Žaltauskaitė, J.; Sodienė, I. Effects of Cadmium and Lead on the Life-Cycle Parameters of Juvenile Earthworm Eisenia fetida. Ecotoxicol. Environ. Saf. 2014, 103, 9–16. [Google Scholar] [CrossRef]
  73. Du, Y.-L.; He, M.-M.; Xu, M.; Yan, Z.-G.; Zhou, Y.-Y.; Guo, G.-L.; Nie, J.; Wang, L.-Q.; Hou, H.; Li, F.-S. Interactive Effects between Earthworms and Maize Plants on the Accumulation and Toxicity of Soil Cadmium. Soil Biol. Biochem. 2014, 72, 193–202. [Google Scholar] [CrossRef]
  74. You, R.; Li, H.; Li, X.; Luo, L.; Wang, P.; Xia, H.; Zhou, Y. Ecotoxicological Impacts of Cadmium on Soil Microorganisms and Earthworms Eisenia foetida: From Gene Regulation to Physiological Processes. Front. Environ. Sci. 2024, 12, 1479500. [Google Scholar] [CrossRef]
  75. Wu, S.; Xu, X.; Zhao, S.; Shen, F.; Chen, J. Evaluation of Phenanthrene Toxicity on Earthworm (Eisenia fetida): An Ecotoxicoproteomics Approach. Chemosphere 2013, 93, 963–971. [Google Scholar] [CrossRef]
  76. Wijayawardena, M.A.; Megharaj, M.; Naidu, R. Bioaccumulation and Toxicity of Lead, Influenced by Edaphic Factors: Using Earthworms to Study the Effect of Pb on Ecological Health. J. Soils Sediments 2017, 17, 1064–1072. [Google Scholar] [CrossRef]
  77. Karpov, M.A.; Hobbs, C.; Jayasinghe, S.N.; Stürzenbaum, S.R. Metallomic Mapping of Gut and Brain in Heavy Metal Exposed Earthworms: A Novel Paradigm in Ecotoxicology. Biochem. Biophys. Res. Commun. 2024, 709, 149827. [Google Scholar] [CrossRef] [PubMed]
  78. Das, A.; Osborne, J.W. Enhanced Bioremoval of Lead by Earthworm–Lumbricus terrestris Co-Cultivated with Bacteria–Klebsiella variicola. J. Photochem. Photobiol. B Biol. 2017, 175, 65–72. [Google Scholar] [CrossRef] [PubMed]
  79. Tang, R.; Ding, C.; Ma, Y.; Wang, J.; Zhang, T.; Wang, X. Time-Dependent Responses of Earthworms to Soil Contaminated with Low Levels of Lead as Detected Using 1 H NMR Metabolomics. RSC Adv. 2017, 7, 34170–34181. [Google Scholar] [CrossRef]
  80. Žaltauskaitė, J.; Kniuipytė, I.; Kugelytė, R. Lead Impact on the Earthworm Eisenia fetida and Earthworm Recovery after Exposure. Water Air Soil Pollut. 2020, 231, 49. [Google Scholar] [CrossRef]
  81. Sharma, P.; Chouhan, R.; Bakshi, P.; Gandhi, S.G.; Kaur, R.; Sharma, A.; Bhardwaj, R. Amelioration of Chromium-Induced Oxidative Stress by Combined Treatment of Selected Plant-Growth-Promoting Rhizobacteria and Earthworms via Modulating the Expression of Genes Related to Reactive Oxygen Species Metabolism in Brassica juncea. Front. Microbiol. 2022, 13, 802512. [Google Scholar] [CrossRef] [PubMed]
  82. Gao, C.; Xu, J.; Li, J.; Liu, Z. Determination of Metallothionein, Malondialdehyde, and Antioxidant Enzymes in Earthworms (Eisenia fetida) Following Exposure to Chromium. Anal. Lett. 2016, 49, 1748–1757. [Google Scholar] [CrossRef]
  83. Fernando, V.K.; Perera, I.C.; Dangalle, C.D.; Premawansa, S.; Wijesinghe, M.R. Histological Alterations in the Body Wall of the Tropical Earthworm Eudrilus eugeniae Exposed to Hexavalent Chromium. Bull. Environ. Contam. Toxicol. 2015, 94, 744–748. [Google Scholar] [CrossRef]
  84. Liu, P.; Song, Y.; Wei, J.; Mao, W.; Ju, J.; Zheng, S.; Zhao, H. Synergistic Effects of Earthworms and Plants on Chromium Removal from Acidic and Alkaline Soils: Biological Responses and Implications. Biology 2023, 12, 831. [Google Scholar] [CrossRef]
  85. Gupta, S.K.; Srivastava, R.; Mathur, N.; Saxena, P.N. The Comparative Effects of Metals on the Hatching of Earthworm Cocoons. Altern. Lab. Anim. 2006, 34, 491–498. [Google Scholar] [CrossRef]
  86. Tőzsér, D.; Mizser, S.; Karaffa, K.; Málik-Roffa, H.; Magura, T. A Meta-Analysis-Based Evaluation of Metallic Element Accumulation in Earthworms. Environ. Int. 2022, 169, 107546. [Google Scholar] [CrossRef]
  87. Gavrish, I.A.; Lebedev, S.V. Effect of Nanoparticles of Nickel on Morphobiochemical Parameters Eisenia fetida. IOP Conf. Ser. Earth Environ. Sci. 2019, 341, 012167. [Google Scholar] [CrossRef]
  88. Podolak, A.; Piotrowska, E.; Klimek, M.; Klimek, B.A.; Kruk, J.; Plytycz, B. Effects of Nickel, Zinc, and Lead-Contaminated Soil on Burrowing Rate and Coelomocytes of the Earthworm, Allolobophora chlorotica. Folia Biol. 2011, 59, 91–97. [Google Scholar] [CrossRef]
  89. Lock, K.; Janssen, C.R. Ecotoxicity of Nickel to Eisenia fetida, Enchytraeus albidus and Folsomia candida. Chemosphere 2002, 46, 197–200. [Google Scholar] [CrossRef]
  90. Hirano, T.; Tamae, K. Heavy Metal-induced Oxidative DNA Damage in Earthworms: A Review. Appl. Environ. Soil Sci. 2010, 2010, 726946. [Google Scholar] [CrossRef]
  91. Wang, G.; Xia, X.; Yang, J.; Tariq, M.; Zhao, J.; Zhang, M.; Huang, K.; Lin, K.; Zhang, W. Exploring the Bioavailability of Nickel in a Soil System: Physiological and Histopathological Toxicity Study to the Earthworms (Eisenia fetida). J. Hazard. Mater. 2020, 383, 121169. [Google Scholar] [CrossRef] [PubMed]
  92. Lamb, D.T.; Matanitobua, V.P.; Palanisami, T.; Megharaj, M.; Naidu, R. Bioavailability of Barium to Plants and Invertebrates in Soils Contaminated by Barite. Environ. Sci. Technol. 2013, 47, 4670–4676. [Google Scholar] [CrossRef] [PubMed]
  93. Menzie, C.A.; Southworth, B.; Stephenson, G.; Feisthauer, N. The Importance of Understanding the Chemical Form of a Metal in the Environment: The Case of Barium Sulfate (Barite). Hum. Ecol. Risk Assess. 2008, 14, 974–991. [Google Scholar] [CrossRef]
  94. Zhang, P.C.; Brady, P.V.; Arthur, S.E.; Zhou, W.Q.; Sawyer, D.; Hesterberg, D.A. Adsorption of Barium (II) on Montmorillonite: An EXAFS Study. Colloids Surf. A Physicochem. Eng. Asp. 2001, 190, 239–249. [Google Scholar] [CrossRef]
  95. Lasley, K.K.; Evanylo, G.K.; Kostyanovsky, K.I.; Shang, C.; Eick, M.; Lee Daniels, W. Chemistry and Transport of Metals from Entrenched Biosolids at a Reclaimed Mineral Sands Mining Site. J. Environ. Qual. 2010, 39, 1467–1477. [Google Scholar] [CrossRef]
  96. Hulbert, A.J.; Kelly, M.A.; Abbott, S.K. Polyunsaturated Fats, Membrane Lipids and Animal Longevity. J. Comp. Physiol. B 2014, 184, 149–166. [Google Scholar] [CrossRef]
  97. Nahmani, J.; Hodson, M.E.; Black, S. A Review of Studies Performed to Assess Metal Uptake by Earthworms. Environ. Pollut. 2007, 145, 402–424. [Google Scholar] [CrossRef]
  98. Kowalczyk-Pecka, D.; Kowalczuk-Vasilev, E.; Pecka, S. The Effect of Heterogeneous Copper Micro-Supplementation on Fatty Acid Profiles in the Tissues of Snails Helix pomatia (Gastropoda Pulmonata). Ecol. Indic. 2017, 76, 335–343. [Google Scholar] [CrossRef]
  99. Kowalczyk-Pecka, D.; Pecka, S.; Kowalczuk-Vasilev, E. Changes in Fatty Acid Metabolism Induced by Varied Micro-Supplementation with Zinc in Snails Helix pomatia (Gastropoda Pulmonata). Ecotoxicol. Environ. Saf. 2017, 138, 223–230. [Google Scholar] [CrossRef]
  100. Puca, A.A.; Chatgilialoglu, C.; Ferreri, C. Lipid Metabolism and Diet: Possible Mechanisms of Slow Aging. Int. J. Biochem. Cell Biol. 2008, 40, 324–333. [Google Scholar] [CrossRef]
  101. Kamińska, A.; Garbacz, A.; Sadurski, J. Katalaza i Dysmutaza Ponadtlenkowa Jako Wybrane Enzymatyczne Biomarkery Stresu Oksydacyjnego. In Wybrane Zagadnienia z Zakresu Ochrony i Zagrożeń Środowiska; Babicz, M., Nowakowicz-Dębek, B., Gawryluk, A., Eds.; Wydawnictwo Uniwersytetu Przyrodniczego w Lublinie: Lublin, Poland, 2024; pp. 85–91. ISBN 978-83-7259-448-8. [Google Scholar]
  102. Osowska, S.; Rogulska, J. Wskaźniki Peroksydacji Lipidów w Żywieniu Pozajelitowym. Prospect. Pharm. Sci. 2023, 21, 24–32. [Google Scholar] [CrossRef]
  103. Wang, Q.L.; Zhu, L.; Huang, B.J.; Li, Y. Toxicity Effects of Lead in Polluted Soil on Earthworm Coelomocyte Lysosome. J. Agro-Environ. Sci. 2007, 36, 1874–1878. [Google Scholar]
  104. Oves, M.; Saghir Khan, M.; Huda Qari, A.; Nadeen Felemban, M.; Almeelbi, T. Heavy Metals: Biological Importance and Detoxification Strategies. J. Bioremediation Biodegrad. 2016, 7, 334. [Google Scholar] [CrossRef]
Sustainability 17 08076 g001
Figure 1. Distribution of sampling sites (Sustainability 17 08076 i001—material collection points; ▬▬—border of Polesie National Park).
Figure 1. Distribution of sampling sites (Sustainability 17 08076 i001—material collection points; ▬▬—border of Polesie National Park).
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Sustainability 17 08076 g002
Figure 2. Heat map based on the analysis of the content of: (A) biomarker FAs; (B) SFA, MUFA, PUFA, PI, UI, SOD, CAT and TBARS in earthworms obtained from sites with and without waste rock deposits. Groups: EI10HFB—WR deposit > 10 years, buckwheat field; EWFB—without WR deposit, buckwheat field; EI10HWI—WR deposit > 10 years, wasteland I; EWWI—without WR deposit, wasteland I; EI2FO—WR deposit = 2 years, oat field; EWFO—without WR deposit, oat field; EI1HMI—WR deposit > 1 year, meadow I; EWMI—without WR deposit, meadow I; EI1LWII—WR deposit < 1 year, wasteland II; EWWII—without WR deposit, wasteland II; EI1LMII—WR deposit < 1 year, meadow II; EWMII—without WR deposit, meadow II. n = 60. Parameters: biomarker FAs [%]: C12:0—lauric acid; C14:0—myristic acid; C16:0—palmitic acid; C18:0—stearic acid; C20:0—arachidic acid, eicosanoic acid; C21:0—heneicosanoic acid; C24:0—lignoceric acid, tetracosanoic acid; C16:1 n−7—palmitoleic acid; C18:1 n−9c + C18:1 n−9t—oleic acid + elaidic acid; C20:1 n−9—cis-11-eicosenic acid; C18:2 n−6c + C18:2 n−6t—linoleic acid + linolelaidic acid; C18:3 n−3—α-linolenic acid; C20:2 n−6—cis-11-14-eicosadienic acid; C20:3 n−3—eicosatrienic acid; C20:4 n−6—arachidonic acid; C20:5 n−3—cis-5,8,11,14,17-eicosapentaenic acid, EPA; C22:2 n−6—cis-13-16-docosadienic acid. SFA [%]—saturated fatty acids, MUFA [%]—monounsaturated fatty acids; PUFA [%]—polyunsaturated fatty acids. PI—peroxidation index; UI—unsaturation index. SOD [Unit/mg protein]—superoxide dismutase; CAT [µmol H2O2/mg protein/min]—catalase; TBARS [nM of MDA/mg of tissue]—thiobarbituric acid reactive substances.
Figure 2. Heat map based on the analysis of the content of: (A) biomarker FAs; (B) SFA, MUFA, PUFA, PI, UI, SOD, CAT and TBARS in earthworms obtained from sites with and without waste rock deposits. Groups: EI10HFB—WR deposit > 10 years, buckwheat field; EWFB—without WR deposit, buckwheat field; EI10HWI—WR deposit > 10 years, wasteland I; EWWI—without WR deposit, wasteland I; EI2FO—WR deposit = 2 years, oat field; EWFO—without WR deposit, oat field; EI1HMI—WR deposit > 1 year, meadow I; EWMI—without WR deposit, meadow I; EI1LWII—WR deposit < 1 year, wasteland II; EWWII—without WR deposit, wasteland II; EI1LMII—WR deposit < 1 year, meadow II; EWMII—without WR deposit, meadow II. n = 60. Parameters: biomarker FAs [%]: C12:0—lauric acid; C14:0—myristic acid; C16:0—palmitic acid; C18:0—stearic acid; C20:0—arachidic acid, eicosanoic acid; C21:0—heneicosanoic acid; C24:0—lignoceric acid, tetracosanoic acid; C16:1 n−7—palmitoleic acid; C18:1 n−9c + C18:1 n−9t—oleic acid + elaidic acid; C20:1 n−9—cis-11-eicosenic acid; C18:2 n−6c + C18:2 n−6t—linoleic acid + linolelaidic acid; C18:3 n−3—α-linolenic acid; C20:2 n−6—cis-11-14-eicosadienic acid; C20:3 n−3—eicosatrienic acid; C20:4 n−6—arachidonic acid; C20:5 n−3—cis-5,8,11,14,17-eicosapentaenic acid, EPA; C22:2 n−6—cis-13-16-docosadienic acid. SFA [%]—saturated fatty acids, MUFA [%]—monounsaturated fatty acids; PUFA [%]—polyunsaturated fatty acids. PI—peroxidation index; UI—unsaturation index. SOD [Unit/mg protein]—superoxide dismutase; CAT [µmol H2O2/mg protein/min]—catalase; TBARS [nM of MDA/mg of tissue]—thiobarbituric acid reactive substances.
Sustainability 17 08076 g002
Table 1. Sampling collection sites and group designations with and without waste rock deposits.
Table 1. Sampling collection sites and group designations with and without waste rock deposits.
Number of MapsSitesGeographic
Coordinates		With or Without WR Deposit/
Time of WR Exposure		Research Material (Group)
1.Buckwheat field
(Fagopyrum esculentum)		N: 51°23′27.16″; E: 23°14′35.84″WR deposit > 10 yearsWaste rockWI10HFB
SoilSI10HFB
Plant rootsRI10HFB
EarthwormsEI10HFB
2.Oat field
(Avena sativa)		N: 51°14′18.23″; E: 23°05′15.98″WR deposit 2 yearsWaste rockWI2FO
SoilSI2FO
Plant rootsRI2FO
EarthwormsEI2FO
3.Meadow I
with Filipendulion ulmariae herb communities		N: 51°14′06.32″; E: 23°05′07.15″WR deposit > 1 yearWaste rockWI1HMI
SoilSI1HMI
Plant rootsRI1HMI
EarthwormsEI1HMI
4.Meadow II
with vegetation belonging to the Molinio-Arrhenatheretea class		N: 51°14′12.74″; E: 23°05′10.93″WR deposit < 1 yearWaste rockWI1LMII
SoilSI1LMII
Plant rootsRI1LMII
EarthwormsEI1LMII
5.Wasteland I
overgrown with pine and birch forest with dominant sand reed grass Calamagrostis epigejos and the presence of herb communities and clear-cut grasses Epilobion angustifolii		N: 51°25′22.12″; E: 23°08′44.81″WR deposit > 10 yearsWaste rockWI10HWI
SoilSI10HWI
Plant rootsRI10HWI
EarthwormsEI10HWI
6.Wasteland II
with communities of ruderal thermophilic plants Onopordion acanthii		N: 51°08′52.15″; E: 23°01′32.98″WR deposit < 1 yearWaste rockWI1LWII
SoilSI1LWII
Plant rootsRI1LWII
EarthwormsEI1LWII
7.Buckwheat field (Fagopyrum esculentum)N: 51°23′29.93″; E: 23°14′31.36″Without WR deposit (control)SoilSWFB
Plant rootsRWFB
EarthwormsEWFB
8.Oat field
(Avena sativa)		N: 51°14′34.98″; E: 23°05′23.72″Without WR deposit (control)SoilSWFO
Plant rootsRWFO
EarthwormsEWFO
9.Meadow I
with vegetation from the Calthion association		N: 51°19′36.42″; E: 23°15′01.63″Without WR deposit (control)SoilSWMI
Plant rootsRWMI
EarthwormsEWMI
10.Meadow II
with vegetation from the Molinion association		N: 51°21′16.57″; E: 23°14′49.31″Without WR deposit (control)SoilSWMII
Plant rootsRWMII
EarthwormsEWMII
11.Wasteland I
overgrown with pine and birch forest with vegetation belonging to the Koelerio glaucae-Corynephoretea canescentis class		N: 51°25′21.63″; E: 23°08′47.66″Without WR deposit (control)SoilSWWI
Plant rootsRWWI
EarthwormsEWWI
12.Wasteland II
with vegetation belonging to the Koelerio glaucae-Corynephoretea canescentis class		N: 51°20′12.81″; E: 23°13′57.74″Without WR deposit (control)SoilSWWII
Plant rootsRWWII
EarthwormsEWWII
Table 2. Metals analyzed in waste rock obtained from sites with and without waste rock deposits.
Table 2. Metals analyzed in waste rock obtained from sites with and without waste rock deposits.
Metals + CI
[mg·kg−1]		GroupsSEM
WI10HFBWI10HWIWI2FOWI1HMIWI1LWIIWI1LMII
Pb
[CI]		30 b
19.8–40.7		30 b
25.2–34.0		24 ab
20.0–28.2		20 ab
16.0–23.0		16 a
12.5–20.1		15 a
9.8–19.7		1.36
Cd
[CI]		0
-		0
-		0
-		0
-		0
-		0
-		-
 
Cr
[CI]		77 b
59.8–94.3		26 a
16.1–35.2		26 a
18.5–32.9		82 b
72.3–90.7		67 b
612.0–71.5		66 b
51.9–80.4		4.51
Ba
[CI]		109 ab
97.1–120.7		101 a
88.3–112.5		91 a
82.1–99.5		124 b
112.5–136.3		158 c
145.8–169.3		226 d
209.5–241.6		8.68
Ni
[CI]		29 b
25.3–33.3		19 a
16.0–21.9		26 ab
23.8–29.0		46 c
39.5–52.9		51 c
47.3–54.6		26 ab
22.2–30.4		2.21
Zn
[CI]		101 c
81.2–120.3		43 ab
40.3–46.2		56 b
49.6–62.0		54 b
46.4–60.8		45 b
40.4–49.0		26 a
23.44–27.6		4.46
Cu
[CI]		35 a
29.6–40.5		46 b
42.5–48.9		32 a
23.3–34.8		30 a
24.5–34.8		48 b
43.1–52.8		45 b
40.0–50.7		1.50
Groups: WI10HFB—WR (waste rock) deposit > 10 years, buckwheat field; WI10HWI—WR deposit > 10 years, wasteland I; WI2FO—WR deposit = 2 years, oat field; WI1HMI—WR deposit > 1 year, meadow I; WI1LWII—WR deposit < 1 year, wasteland II; WI1LMII—WR deposit < 1 year, meadow II. n = 30. CI—95% confidence interval (lower–upper); SEM—standard error of mean; a–d—values in rows with different letters differ significantly at the level p ≤ 0.01; significant at p ≤ 0.01.
Table 3. Metals analyzed in soil obtained from sites with and without waste rock deposits.
Table 3. Metals analyzed in soil obtained from sites with and without waste rock deposits.
Metals + CI
[mg·kg−1]		GroupsSEM
SI10HFBSWFBSI10HWISWWISI2FOSWFOSI1HMISWMISI1LWIISWWIISI1LMIISWMII
Pb
[CI]		9.8 c
2.7–17.0		4.2 abc
1.9–6.5		16.2 d
13.3–19.1		3.0 ab
1.5–4.4		8.3 bc
4.7–11.7		3.7 abc
0.7–6.8		5.2 abc
1.3–9.0		0.9 a
0.3–1.6		2.1 a
0.4–3.7		1.1 a
0.3–1.8		1.1 a
0.3–2.0		0.9 a
0.3–1.4		0.20
Cd
[CI]		4.5 f
3.7–5.3		0.2 a
0.1–0.2		0.5 ab
0.1–0.9		0.1 a
0.1–0.1		0.4 ab
0.3–0.5		0.1 a
0.0–0.2		3.3 def
2.8–3.7		1.2 abc
0.8–1.6		3.5 ef
2.1–4.7		2.3 cde
0.8–3.8		2.9 de
1.8–4.1		1.7 bcd
1.3–2.2		0.16
Cr
[CI]		10.9 d
9.7–12.1		4.6 ab
4.0–5.1		8.4 e
7.2–9.6		3.8 a
3.4–4.3		4.5 ab
3.7–5.2		3.8 a
3.1–4.6		15.0 f
12.5–17.6		6.9 cd
6.3–7.6		5.7 abc
4.9–6.4		6.5 bcd
5.5–7.5		6.0 abc
5.6–6.3		5.4 abc
4.6–6.1		0.27
Ba
[CI]		19.5 b
16.9–22.2		0.2 a
0.1–0.2		1.2 a
1.0–1.4		0.2 a
0.1–0.2		1.6 a
1.3–1.9		0.3 a
0.3–0.4		27.5 c
23.9–31.1		2.4 a
2.0–2.7		19.5 b
17.4–21.6		18.8 b
17.3–20.3		25.6 c
23.7–27.5		1.5 a
1.3–1.7		0.08
Ni
[CI]		6.0 cd
5.2–6.8		1.9 a
1.6–2.1		9.2 e
7.9–10.4		1.9 a
1.5–2.3		3.1 ab
2.0–4.1		2.4 a
2.0–2.9		6.5 d
5.9–7.0		5.2 cd
4.7–5.7		4.8 cd
3.1–6.6		5.5 cd
4.76–6.2		4.5 bc
4.0–5.0		3.2 ab
2.8–3.5		0.13
Zn
[CI]		16.8 c
14.6–19.0		1.6 ab
8.3–14.9		25.3 e
20.8–29.8		9.4 ab
7.3–11.5		10.8 ab
9.0–12.6		8.5 a
7.4–9.7		13.9 bc
13.0–14.9		10.3 ab
8.3–12.3		12.7 abc
10.8–14.6		11.5 ab
7.1–15.8		11.7 abc
10.4–13.1		8.1 a
7.5–8.8		0.24
Cu
[CI]		4.4 abc
3.7–5.2		2.2 a
1.7–2.6		25.6 e
22.2–29.1		5.9 c
4.2–7.6		3.6 abc
2.7–4.4		2.6 ab
2.1–3.2		5.3 bc
4.6–6.0		4.1 abc
3.0–5.2		4.5 abc
3.2–5.8		4.0 abc
3.3–4.7		4.4 abc
4.0–5.0		3.8 abc
3.4–4.2		0.15
InteractionsWR************
S************
WRxS************
Groups: SI10HFB—WR deposit > 10 years, buckwheat field; SWFB—without WR deposit, buckwheat field; SI10HWI—WR deposit > 10 years, wasteland I; SWWI—without WR deposit, wasteland I; SI2FO—WR deposit = 2 years, oat field; SWFO—without WR deposit, oat field; SI1HMI—WR deposit > 1 year, meadow I; SWMI—without WR deposit, meadow I; SI1LWII—WR deposit < 1 year, wasteland II; SWWII—without WR deposit, wasteland II; SI1LMII—WR deposit < 1 year, meadow II; SWMII—without WR deposit, meadow II. n = 60. CI—95% confidence interval (lower–upper); SEM—standard error of mean; WR—waste rock; S—sampling sites; WRxS—interaction of waste rock with the sampling site; a–f—values in rows with different letters differ significantly at the level p ≤ 0.01; * significant at p ≤ 0.01.
Table 4. Metals analyzed in plant roots obtained from sites with and without waste rock deposits.
Table 4. Metals analyzed in plant roots obtained from sites with and without waste rock deposits.
Metals + CI
[mg·kg−1]		GroupsSEM
RI10HFBRWFBRI10HWIRWWIRI2FORWFORI1HMIRWMIRI1LWIIRWWIIRI1LMIIRWMII
Pb
[CI]		3.8 abc
1.7–5.8		1.9 ab
1.1–2.7		14.2 d
10.3–18.0		6.5 c
3.5–9.5		4.0 abc
2.9–5.0		1.7 a
1.2–2.3		3.9 abc
1.1–6.7		2.2 ab
1.0–3.4		5.8 bc
4.7–7.0		1.7 a
0.9–2.4		2.8 abc
1.0–4.7		2.0 ab
1.4–2.5		0.48
Cd
[CI]		0.9 ab
0.7–1.1		0.3 a
0.1–0.5		1.4 ab
0.8–2.0		0.5 ab
0.3–0.8		0.7 ab
0.5–1.0		0.5 ab
0.3–0.6		2.9 b
1.5–4.4		1.3 ab
0.9–3.6		0.9 ab
0.6–1.2		0.8 ab
0.1–2.0		3.1 b
0.6–5.5		2.3 ab
0.3–4.2		0.17
Cr
[CI]		4.5 bc
3.4–5.6		3.7 abc
2.4–5.1		37.0 f
34.1–40.0		20.9 e
17.8–24.0		6.5 c
5.7–7.3		4.8 bc
4.1–5.6		4.1 abc
3.6–4.6		1.5 a
0.9–2.2		3.3 ab
2.9–3.8		2.9 ab
2.2–3.7		10.5 d
9.7–11.3		1.5 a
1.5–1.6		1.31
Ba
[CI]		8.7 b
7.9–9.5		0.3 a
0.3–0.4		0.6 a
0.5–0.8		0.2 a
0.1–0.2		0.8 a
0.6–0.9		0.6 a
0.5–0.7		9.7 b
8.5–11.0		7.9 b
6.5–9.3		24.0 c
20.3–27.7		9.7 b
7.6–11.7		48.4 d
42.7–54.0		7.8 b
6.3–9.2		1.75
Ni
[CI]		13.3 c
12.4–14.3		8.6 ab
7.7–9.5		21.1 f
18.9–23.4		18.6 de
16.8–20.5		9.4 ab
7.1–11.8		7.3 a
6.2–8.3		11.4 bc
10.4–12.4		7.1 a
6.2–7.9		12.8 c
11.0–14.5		9.0 ab
7.8–10.3		17.2 d
15.6–18.8		7.4 a
6.3–8.5		0.61
Zn
[CI]		27.0 bcd
23.7–30.3		22.9 abc
19.3–26.4		28.3 cd
24.5–32.0		27.4 cd
23.6–31.1		18.3 a
16.6–20.1		18.3 a
17.0–19.6		20.3 ab
18.0–22.7		27.3 cd
20.9–33.7		52.6 e
47.9–57.2		24.5 abcd
22.0–27.0		28.9 cd
27.0–20.8		30.6 d
28.6–32.5		1.17
Cu
[CI]		10.4 ef
8.2–12.6		7.0 bcd
5.4–9.7		17.3 g
15.4–19.2		5.4 abc
4.4–6.5		4.9 ab
3.8–6.0		3.8 a
3.1–4.5		8.6 de
7.4–9.9		8.5 de
7.6–9.5		7.7 cd
7.0–8.5		4.5 ab
3.8–5.4		11.5 f
10.2–12.7		8.6 de
7.8–9.4		0.48
InteractionsWR************
S************
WRxS************
Groups: RI10HFB—WR deposit > 10 years, buckwheat field; RWFB—without WR deposit, buckwheat field; RI10HWI—WR deposit > 10 years, wasteland I; RWWI—without WR deposit, wasteland I; RI2FO—WR deposit = 2 years, oat field; RWFO—without WR deposit, oat field; RI1HMI—WR deposit >1 year, meadow I; RWMI—without WR deposit, meadow I; RI1LWII—WR deposit < 1 year, wasteland II; RWWII—without WR deposit, wasteland II; RI1LMII—WR deposit < 1 year, meadow II; RWMII—without WR deposit, meadow II. n = 60. CI—95% confidence interval (lower–upper); SEM—standard error of mean; WR—waste rock; S—sampling sites; WRxS—interaction of waste rock with the sampling site; a–g—values in rows with different letters differ significantly at the level p ≤ 0.01; * significant at p ≤ 0.01.
Table 5. Metals analyzed in earthworms obtained from sites with and without waste rock deposits.
Table 5. Metals analyzed in earthworms obtained from sites with and without waste rock deposits.
Metals + CI
[mg·kg−1]		GroupsSEM
EI10HFBEWFBEI10HWIEWWIEI2FOEWFOEI1HMIEWMIEI1LWIIEWWIIEI1LMIIEWMII
Pb
[CI]		3.5 cd
1.6–5.3		1.0 ab
0.6–1.4		5.3 e
4.1–6.5		2.3 abc
1.5–3.1		2.7 bc
2.0–3.4		1.0 ab
0.7–1.3		1.2 ab
0.5–1.8		0.6 a
0.4–0.8		3.5 cd
1.7–5.3		2.1 abc
1.8–2.4		1.0 ab
0.5–1.5		0.6 a
0.3–0.9		0.20
Cd
[CI]		0.9 ab
0.4–1.3		0.6 a
0.0–1.1		2.5 c
1.8–3.1		1.3 b
0.6–2.0		0.8 ab
0.7–0.9		0.5 a
0.4–0.7		0.5 a
0.4–0.6		0.3 a
0.3–0.4		0.4 a
0.2–0.6		0.4 a
0.1–0.6		0.3 a
0.3–0.4		0.2 a
0.1–0.3		0.09
Cr
[CI]		6.2 e
5.3–7.1		1.2 ab
0.8–1.5		6.0 de
5.0–7.0		2.5 abc
1.7–3.4		2.0 ab
1.4–2.6		0.6 a
0.5–0.6		12.1 f
10.5–13.7		5.2 de
3.4–7.1		2.8 bc
1.5–4.0		1.5 ab
0.9–2.1		4.2 cd
3.7–4.7		3.1 bc
2.7–3.6		0.41
Ba
[CI]		2.6 c
1.5–3.7		0.0 a
0.0–0.01		0.0 a
0.0–0.1		0.0 a
0.0–0.0		0.0 a
0.0–0.0		0.0 a
0.0–0.0		4.0 d
3.3–4.8		1.3 b
0.4–2.3		2.7 c
2.0–3.4		2.2 bc
2.0–2.4		1.8 bc
1.4–2.3		1.4 b
1.2–1.7		0.18
Ni
[CI]		1.9 c
1.3–2.5		0.8 ab
0.7–0.8		0.9 ab
0.8–0.9		0.2 a
0.1–0.2		0.1 a
0.1–0.1		0.1 a
0.1–0.1		3.1 d
2.3–4.0		2.1 c
1.6–2.5		1.6 bc
0.6–2.5		0.2 a
0.1–0.4		2.3 cd
1.8–2.8		1.8 c
1.6–2.0		0.14
Zn
[CI]		66.6 d
59.0–74.1		50.4 bc
46.5–54.4		115.9 f
107.4–124.3		95.5 e
88.1–102.9		57.9 cd
52.9–63.0		34.6 a
28.0–41.2		88.3 e
72.2–104.5		45.3 abc
37.0–53.7		36.7 ab
32.5–41.0		33.6 a
31.7–35.5		48.7 abc
44.2–53.2		41.1 ab
37.1–45.2		3.41
Cu
[CI]		3.8 de
2.9–4.6		1.7 ab
0.9–2.5		4.3 e
4.0–4.6		2.3 abc
1.6–3.1		1.7 ab
1.3–2.1		1.2 a
0.8–1.6		3.8 de
3.2–4.4		3.1 cd
2.9–3.2		2.6 bc
1.8–3.4		1.8 ab
1.5–2.0		2.8 bcd
2.5–3.1		2.6 bcd
2.3–3.0		0.13
InteractionsWR************
S************
WRxS************
Groups: EI10HFB—WR deposit > 10 years, buckwheat field; EWFB—without WR deposit, buckwheat field; EI10HWI—WR deposit > 10 years, wasteland I; EWWI—without WR deposit, wasteland I; EI2FO—WR deposit = 2 years, oat field; EWFO—without WR deposit, oat field; EI1HMI—WR deposit > 1 year, meadow I; EWMI—without WR deposit, meadow I; EI1LWII—WR deposit < 1 year, wasteland II; EWWII—without WR deposit, wasteland II; EI1LMII—WR deposit < 1 year, meadow II; EWMII—without WR deposit, meadow II. n = 60. CI—95% confidence interval (lower–upper); SEM—standard error of mean; WR—waste rock; S—sampling sites; WRxS—interaction of waste rock with the sampling site; a–f—values in rows with different letters differ significantly at the level p ≤ 0.01; * significant at p ≤ 0.01.
Table 6. Biomarker fatty acids, peroxidation and unsaturation indices, enzymatic and non-enzymatic biomarkers of oxidative stress analyzed in earthworms obtained from sites with and without waste rock deposits.
Table 6. Biomarker fatty acids, peroxidation and unsaturation indices, enzymatic and non-enzymatic biomarkers of oxidative stress analyzed in earthworms obtained from sites with and without waste rock deposits.
Parameters + CIGroupsSEM
EI10HFBEWFBEI10HWIEWWIEI2FOEWFOEI1HMIEWMIEI1LWIIEWWIIEI1LMIIEWMII
C12:0
[CI]		1.0 bcd
0.9–1.1		0.6 a
0.4–0.8		1.2 d
0.8–1.7		1.1 cd
0.9–1.2		0.8 abc
0.7–0.9		0.6 ab
0.6–0.7		0.8 abc
0.7–0.9		0.5 a
0.3–0.7		2.7 f
2.6–2.9		0.7 abc
0.5–1.0		2.0 e
1.8–2.1		0.5 a
0.4–0.6		0.09
C14:0
[CI]		2.1 abc
1.9–2.3		1.8 ab
1.8–1.9		4.5 d
2.5–6.3		1.1 ab
0.3–3.3		3.9 cd
3.2–4.4		2.8 bcd
2.1–3.5		2.0 ab
1.7–2.3		1.4 ab
1.1–1.6		2.1 abc
1.9–2.2		0.9 a
0.7–1.1		1.5 ab
1.4–1.7		1.1 ab
0.9–1.4		0.16
C16:0
[CI]		24.8 g
21.4–28.1		19.8 e
18.7–20.3		27.2 g
25.2–29.2		24.4 fg
23.6–25.3		24.8 g
23.2–26.4		21.1 ef
19.2–23.1		10.7 bc
8.4–13.0		5.7 a
4.8–6.7		16.0 d
14.5–17.4		8.2 ab
6.6–9.7		14.0 cd
12.9–15.0		6.0 a
5.1–6.9		0.99
C18:0
[CI]		9.0 fg
8.0–10.0		8.1 defg
7.9–8.2		9.3 g
8.4–10.1		8.3 efg
7.9–8.7		7.7 bcdef
6.7–8.8		6.8 abcd
6.3–7.3		7.8 cdef
6.8–8.7		6.5 ab
6.0–7.0		7.1 abcde
6.9–7.2		6.0 a
5.7–6.2		6.8 abc
6.2–7.3		6.0 a
5.7–6.2		0.15
C20:0
[CI]		0.6 bcd
0.4–0.7		0.4 abc
0.4–0.4		1.0 e
0.8–1.1		0.7 cde
0.6–0.8		1.0 e
0.6–1.4		0.8 de
0.7–1.0		0.7 cde
0.5–1.0		0.2 a
0.1–0.2		0.4 abc
0.4–0.5		0.3 ab
0.2–0.3		0.2 ab
0.2–0.4		0.1 a
0.1–0.2		0.04
C21:0
[CI]		4.8 e
3.9–5.7		0.8 ab
0.7–0.9		7.6 f
6.3–9.0		0.7 a
0.6–0.9		3.3 d
2.7–3.9		1.4 abc
0.9–1.9		5.5 e
4.7–6.3		2.0 bc
1.7–2.3		4.8 e
4.5–5.2		2.3 cd
2.1–2.6		3.4 d
2.9–3.9		1.8 abc
1.5–2.0		0.27
C24:0
[CI]		0.6 bc
0.3–1.0		0.3 a
0.2–0.3		0.8 c
0.7–0.9		0.4 ab
0.3–0.6		0.6 bc
0.4–0.8		0.3 a
0.2–0.4		0.4 ab
0.3–0.5		0.2 a
0.1–0.3		0.3 a
0.3–0.4		0.2 a
0.2–0.3		0.3 a
0.2–0.4		0.2 a
0.2–0.2		0.03
SFA
[CI]		42.2 bcd
34.9–49.5		37.0 abc
33.7–40.3		52.1 e
46.5–57.7		46.8 de
41.2–51.8		45.1 cde
41.3–48.9		36.8 abc
31.5–42.2		33.3 a
28.5–38.0		29.8 a
27.1–32.6		35.5 ab
32.8–38.1		28.5 a
24.9–32.1		31.1 a
28.4–33.9		28.4 a
26.1–30.1		1.05
C16:1 n−7
[CI]		0.8 bc
0.6–1.0		0.3 a
1.2–1.4		1.6 d
1.4–1.8		1.0 bc
0.8–1.1		1.6 d
1.4–1.8		1.0 bc
0.7–1.2		1.0 bc
0.7–1.2		0.7 ab
0.5–0.8		2.2 e
1.9–2.5		0.8 bc
0.6–1.1		1.1 c
0.9–1.2		0.7 bc
0.6–0.9		0.07
C18:1 n−9c + C18:1 n−9t
[CI]		18.6 c
 
17.2–19.9		16.2 bc
 
15.4–17.0		26.8 d
 
23.0–30.5		18.4 c
 
16.1–20.9		31.5 e
 
28.3–34.8		23.7 d
 
20.6–26.8		18.5 c
 
15.5–21.6		11.1 a
 
9.0–13.1		16.8 bc
 
15.5–18.2		13.7 ab
 
13.7–14.7		15.4 abc
 
14.2–16.6		11.3 a
 
9.8–12.8		0.79
C20:1 n−9
[CI]		2.4 d
1.7–3.1		0.4 ab
0.2–0.5		0.8 bc
0.4–1.0		0.2 a
0.2–0.3		0.7 abc
0.5–0.9		0.3 ab
0.2–0.5		0.8 abc
0.5–1.0		0.4 ab
0.2–0.5		0.9 c
0.7–1.1		0.3 ab
0.3–0.4		0.6 abc
0.5–0.8		0.4 ab
0.3–0.5		0.08
MUFA
[CI]		27.8 ef
26.8–28.8		26.7 de
19.7–33.6		33.8 fg
29.3–38.3		21.7 cde
17.8–25.5		36.8 g
32.9–40–7		27.8 ef
24.1–31.4		20.6 bcd
17.7–23.4		13.4 a
11.2–15.7		20.2 abcd
18.4–21.9		15.9 abc
14.7–17.2		17.3 abc
15.7–18.8		13.8 ab
12.5–15.1		1.00
C18:2 n−6c + C18:2 n−6t
[CI]		7.4 bc
 
5.9–8.9		14.9 efg
 
13.4–16.3		2.4 a
 
2.1–2.8		9.3 cd
 
7.9–10.6		3.2 ab
 
2.3–4.1		11.5 cde
 
9.3–13.8		11.8 ed
 
7.7–15.8		16.7 fg
 
14.8–18.5		14.0 ef
 
12.9–15.1		18.6 g
 
15.8–21.3		11.8 ed
 
9.5–14.0		24.4 h
 
21.7–27.1		0.80
C18:3 n−3
[CI]		0.4 a
0.3–0.4		0.7 ab
0.6–0.7		0.4 a
0.3–0.6		0.8 ab
0.6–1.1		0.5 ab
0.3–0.8		1.9 c
1.5–2.2		1.1 b
0.8–1.4		2.7 d
2.1–3.2		2.3 cd
1.9–2.6		3.5 e
3.3–3.8		1.9 c
1.5–2.2		2.7 d
2.5–3.0		0.14
C20:2 n−6
[CI]		0.4 a
0.3–0.5		3.2 d
2.4–4.1		0.3 a
0.2–0.5		2.6 d
2.6–3.0		0.7 ab
0.5–1.0		1.5 bc
1.3–1.7		1.1 abc
0.8–1.4		2.8 d
2.4–3.3		1.3 bc
1.1–1.5		3.2 d
2.9–3.5		1.8 c
1.4–2.2		3.0 d
2.7–3.4		0.14
C20:3 n−3
[CI]		0.9 a
0.6–1.1		1.8 b
1.6–2.1		0.9 a
0.7–1.1		2.2 b
1.9–2.6		2.1 b
1.5–2.7		3.1 c
2.7–3.4		6.0 d
5.7–6.2		6.2 d
6.1–6.4		3.2 c
3.0–3.4		7.1 e
6.8–7.5		3.4 c
3.2–3.7		7.2 e
6.9–7.5		0.29
C20:4 n−6
[CI]		5.9 a
4.7–7.1		12.8 cd
10.8–14.8		5.0 a
4.1–5.9		14.1 cde
11.6–16.6		6.1 a
5.7–6.5		11.0 bc
9.2–12.8		6.9 a
5.7–8.1		13.8 cde
11.8–15.9		7.8 ab
5.5–10.2		15.2 de
13.2–17.2		8.0 ab
6.1–10.0		16.9 e
13.8–20.0		0.55
C20:5 n−3
[CI]		0.3 a
0.2–0.4		0.5 abc
0.4–0.6		0.3 a
0.1–0.4		0.7 bc
0.5–0.8		0.4 abc
0.3–0.6		0.7 bc
0.6–0.7		0.4 ab
0.2-–0.6		0.7 c
0.6–0.9		0.4 abc
0.2–0.6		0.6 bc
0.5–0.8		0.5 abc
0.4–0.7		0.7 c
0.6–0.9		0.02
C22:2 n−6
[CI]		0.7 a
0.4–0.9		2.4 e
2.0–2.8		0.5 a
0.4–0.7		1.9 cde
1.6–2.2		0.8 ab
0.5–1.2		2.0 cde
1.6–2.4		1.0 ab
0.8–1.2		2.1 de
1.7–2.6		1.4 bc
1.1–1.7		1.9 cde
1.6–2.2		1.5 bcd
1.2–1.8		2.2 e
1.8–2.7		0.09
PUFA
[CI]		30.0 abc
24.4–35.7		36.3 abc
14.4–58.3		14.1 a
60.1–65.7		31.5 abc
12.1–51.0		18.1 ab
9.2–27.1		35.4 abc
18.7–52.1		46.2 abc
31.2–61.2		56.7 c
32.4–80.1		44.4 abc
25.2–53.5		55.4 c
37.1–73.6		51.6 bc
36.6–66.7		57.8 c
33.4–82.2		2.45
PI
[CI]		72.8 b
71.3–74.2		76.5 bc
75.1–78.0		62.9 a
93.1–99.7		73.8 b
71.8–75.7		64.9 a
62.5–67.3		75.9 bc
73.8–77.1		80.7 cd
77.9–83.5		92.2 e
90.0–94.6		79.0 cd
76.1–81.8		89.8 e
86.8–92.7		83.0 d
81.0–85.0		94.3 e
91.3–97.3		1.26
UI
[CI]		108.8 b
105.9–111.7		119.9 c
116.8–123.0		96.4 a
93.1–99.7		111.7 b
108.4–115.0		99.7 a
94.9–104.4		120.7 c
116.6–124.7		128.4 d
126.0–130.9		139.7 f
126.9–142.6		125.8 cd
123.5–128.1		135.2 ef
132–7–137.7		130.7 de
128.6–132.8		139.1 f
137.5–140.7		1.85
SOD
[CI]		13.3 a
12.4–14.1		19.6 c
17.9–21.2		13.8 a
13.014.7		18.8 c
17.2–20.3		15.5 ab
14.3–16.3		22.9 d
21.3–24.6		18.9 c
18.7–19.1		22.6 d
21.5–23.8		17.9 bc
17.1–18.8		18.4 c
16.6–202		19.8 c
18.5–21.2		23.4 d
22.2–24.6		0.43
CAT
[CI]		16.9 a
14.2–19.5		56.3 f
52.4–60.2		13.1 a
11.7–14.5		34.2 e
31.0–37.4		24.7 bc
23.2–26.1		31.7 de
30.1–33.4		29.3 cde
24.6–34.1		31.2 de
28.0–34.4		23.4 b
22.3–24.6		34.9 e
32.1–38.8		26.6 bcd
24.0–29.3		31.8 de
29.4–34.2		1.37
TBARS
[CI]		1.6 e
1.6–1.7		0.8 bc
0.7–0.8		1.7 e
1.6–1.9		0.8 bc
0.8–0.9		1.0 cd
0.8–1.1		0.6 ab
0.5–0.7		1.1 d
0.8–1.5		0.5 a
0.4–0.5		1.0 cd
0.8–1.7		0.8 bc
0.7–0.8		0.8 bc
0.8–0.8		0.5 a
0.4–0.5		0.05
InteractionsWR************
S************
WRxS************
Groups: EI10HFB—WR deposit > 10 years, buckwheat field; EWFB—without WR deposit, buckwheat field; EI10HWI—WR deposit > 10 years, wasteland I; EWWI—without WR deposit, wasteland I; EI2FO—WR deposit = 2 years, oat field; EWFO—without WR deposit, oat field; EI1HMI—WR deposit > 1 year, meadow I; EWMI—without WR deposit, meadow I; EI1LWII—WR deposit < 1 year, wasteland II; EWWII—without WR deposit, wasteland II; EI1LMII—WR deposit < 1 year, meadow II; EWMII—without WR deposit, meadow II. n = 60. Parameters: biomarker FAs [%]: C12:0—lauric acid; C14:0—myristic acid; C16:0—palmitic acid; C18:0—stearic acid; C20:0—arachidic acid, eicosanoic acid; C21:0—heneicosanoic acid; C24:0—lignoceric acid, tetracosanoic acid; C16:1 n−7—palmitoleic acid; C18:1 n−9c + C18:1 n−9t—oleic acid + elaidic acid; C20:1 n−9—cis-11-eicosenic acid; C18:2 n−6c + C18:2 n−6t—linoleic acid + linolelaidic acid; C18:3 n−3—α-linolenic acid; C20:2 n−6—cis-11-14-eicosadienic acid; C20:3 n−3—eicosatrienic acid; C20:4 n−6—arachidonic acid; C20:5 n−3—cis-5,8,11,14,17-eicosapentaenic acid, EPA; C22:2 n−6—cis-13-16-docosadienic acid. SFA [%]—saturated fatty acids, MUFA [%]—monounsaturated fatty acids; PUFA [%]—polyunsaturated fatty acids. PI—peroxidation index; UI—unsaturation index. SOD [Unit/mg protein]—superoxide dismutase; CAT [µmol H2O2/mg protein/min]—catalase; TBARS [nM of MDA/mg of tissue]—thiobarbituric acid reactive substances. CI—95% confidence interval (lower–upper); SEM—standard error of mean; WR—waste rock; S—sampling sites; WRxS—interaction of waste rock with the sampling site; a–h—values in rows with different letters differ significantly at the level p ≤ 0.01; * significant at p ≤ 0.01.
Table 7. Pearson’s correlation coefficient (r) between metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu) and analyzed biomarker FAs, peroxidation (PI) and unsaturation (UI) indices, enzymatic (SOD, CAT) and non-enzymatic (TBARS) biomarkers of oxidative stress in earthworms obtained from sites with waste rock deposits.
Table 7. Pearson’s correlation coefficient (r) between metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu) and analyzed biomarker FAs, peroxidation (PI) and unsaturation (UI) indices, enzymatic (SOD, CAT) and non-enzymatic (TBARS) biomarkers of oxidative stress in earthworms obtained from sites with waste rock deposits.
PbCdCrBaNiZnCu
C12:00.3890 *0.0663−0.00070.26540.1775−0.01930.1773
moderatenegligiblenegligibleweakweaknegligibleweak
C14:00.5423 *0.6091 *0.0577−0.3199−0.21220.3808 *0.1788
strongstrongnegligiblemoderateweakmoderateweak
C16:00.6118 *0.6554 *−0.1539−0.4808 *−0.4707 *0.5083 *0.0297
strongstrongweakmoderatemoderatestrongnegligible
C18:00.6005 *0.6693 *0.2994−0.1565−0.05310.7102 *0.4106 *
strongstrongweakweaknegligiblevery strongmoderate
C20:00.4632 *0.6007 *0.0943−0.3404 *−0.3544 *0.5647 *0.0478
moderatestrongnegligiblemoderatemoderatestrongnegligible
C21:00.6298 *0.4764 *0.6133 *0.3661 *0.3758 *0.5082 *0.6990 *
strongmoderatestrongmoderatemoderatestrongstrong
C24:00.7112 *0.6797 *0.2858−0.1244−0.13790.6503 *0.4719 *
very strongstrongweakweakweakstrongmoderate
SFA0.6941 *0.8242 *0.0105−0.4497 *−0.3921 *0.6662 *0.1997
strongvery strongnegligiblemoderatemoderatestrongweak
C16:1 n−70.5759 *0.28400.03550.0467−0.10150.16590.1615
strongweaknegligiblenegligibleweakweakweak
C18:1 n−9c + C18:1 n−9t0.4989 *0.5261 *−0.0349−0.4112 *−0.4117 *0.4000 *−0.0488
moderatestrongnegligiblemoderatemoderatemoderatenegligible
C20:1 n−90.4171 *0.15120.3584 *0.3497 *0.3384 *0.15530.4456 *
moderateweakmoderatemoderatemoderateweakmoderate
MUFA0.5381 *0.5761 *−0.0760−0.4405 *−0.4311 *0.3948 *−0.0090
strongstrongnegligiblemoderatemoderatemoderatenegligible
C18:2 n−6c + C18:2 n−6t−0.6062 *−0.6551 *−0.17630.26520.2318−0.6035 *−0.2468
strongstrongweakweakweakstrongweak
C18:3 n−3−0.3961 *−0.5514 *−0.23660.27180.0695−0.6683 *−0.2536
moderatestrongweakweaknegligiblestrongweak
C20:2 n−6−0.5832 *−0.4221 *−0.4061 *−0.1546−0.1394−0.4235 *−0.4340 *
strongmoderatemoderateweakweakmoderatemoderate
C20:3 n−3−0.5459 *−0.5682 *0.13590.4329 *0.3069−0.4344 *−0.0928
strongstrongweakmoderatemoderatemoderatenegligible
C20:4 n−6−0.5138 *−0.3749 *−0.4203 *−0.1919−0.2052−0.3982 *−0.4175 *
strongmoderatemoderateweakweakmoderatemoderate
C20:5 n−3−0.5936 *−0.4037 *−0.3711 *−0.1440−0.1846−0.4512 *−0.4641 *
strongmoderatemoderateweakweakmoderatemoderate
C22:2 n−6−0.6540 *−0.4929 *−0.4704 *−0.2271−0.1448−0.5314 *−0.5315 *
strongmoderate moderate weakweakstrongstrong
PUFA−0.3862 *−0.6185 *0.02570.3671 *0.3318 *−0.4514 *−0.0698
moderate strongnegligiblemoderate moderate moderate negligible
PI−0.6229 *−0.6781 *−0.00130.3990 *0.3757 *−0.5845 *−0.1122
strongstrongnegligiblemoderate moderate strongweak
UI−0.6701 *−0.7190 *0.02490.4405 *0.4342 *−0.6093 *−0.1342
strongvery strongnegligiblemoderate moderate strongweak
SOD−0.7633 *−0.5480 *−0.2233−0.06120.1156−0.5072 *−0.3934 *
very strongstrongweaknegligibleweakstrongmoderate
CAT−0.5958 *−0.4376 *−0.3692 *−0.1992−0.2099−0.3471 *−0.5437 *
strongmoderate moderate weakweakmoderate strong
TBARS0.7206 *0.6463 *0.4280 *0.15290.11070.6502 *0.5912 *
very strongstrongmoderate weakweakstrongstrong
C12:0—lauric acid; C14:0—myristic acid; C16:0—palmitic acid; C18:0—stearic acid; C20:0—arachidic acid, eicosanoic acid; C21:0—heneicosanoic acid; C24:0—lignoceric acid, tetracosanoic acid; C16:1 n−7—palmitoleic acid; C18:1 n−9c + C18:1 n−9t—oleic acid + elaidic acid; C20:1 n−9—cis-11-eicosenic acid; C18:2 n−6c + C18:2 n−6t—linoleic acid + linolelaidic acid; C18:3 n−3—α-linolenic acid; C20:2 n−6—cis-11-14-eicosadienic acid; C20:3 n−3—eicosatrienic acid; C20:4 n−6—arachidonic acid; C20:5 n−3—cis-5,8,11,14,17-eicosapentaenic acid, EPA; C22:2 n−6—cis-13-16-docosadienic acid; SFA—saturated fatty acids, MUFA—monounsaturated fatty acids; PUFA—polyunsaturated fatty acids; PI—peroxidation index; UI—unsaturation index; SOD—superoxide dismutase; CAT—catalase; TBARS—thiobarbituric acid reactive substances; n = 30; * significant at p ≤ 0.01.
Table 8. Pearson’s correlation coefficient (r) between metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu) and analyzed biomarker FAs, peroxidation (PI) and unsaturation (UI) indices, enzymatic (SOD, CAT) and non-enzymatic (TBARS) biomarkers of oxidative stress in earthworms obtained from sites without waste rock deposits.
Table 8. Pearson’s correlation coefficient (r) between metals (Pb, Cd, Cr, Ba, Ni, Zn, Cu) and analyzed biomarker FAs, peroxidation (PI) and unsaturation (UI) indices, enzymatic (SOD, CAT) and non-enzymatic (TBARS) biomarkers of oxidative stress in earthworms obtained from sites without waste rock deposits.
PbCdCrBaNiZnCu
C12:00.7165 *0.6165 *−0.1448−0.2304−0.5754 *0.6423 *−0.0737
very strongstrongweakweakstrongstrongnegligible
C14:0−0.18720.1917−0.3305−0.4120−0.1974−0.1822−0.3154
weakweakmoderatemoderateweakweakmoderate
C16:00.37200.6245 *−0.5544 *−0.8450 *−0.7225 *0.5674 *−0.5100 *
moderatestrongstrongvery strongvery strongstrongstrong
C18:00.30830.6316 *−0.2053−0.7266 *−0.38160.7325 *−0.1656
moderatestrongweakvery strongmoderatevery strongweak
C20:00.35830.5446 *−0.5497 *−0.7228 *−0.7421 *0.3933−0.4963 *
moderatestrongstrongvery strongvery strongmoderatemoderate
C21:0−0.1464−0.5509 *0.26910.7946 *0.2911−0.6538 *0.2014
weakstrongweakvery strongweakstrongweak
C24:00.44100.5652 *−0.0123−0.4781 *−0.4734 *0.7543 *−0.0628
moderatestrongnegligiblemoderatemoderatevery strongnegligible
SFA0.43760.8136 *−0.2776−0.7424 *−0.5176 *0.7634 *−0.2297
moderatevery strongweakvery strongstrongvery strongweak
C16:1 n−70.31650.19750.02620.0405−0.33850.20540.0266
moderateweaknegligiblenegligiblemoderateweaknegligible
C18:1 n−9c + C18:1 n−9t0.21990.3881−0.6156 *−0.6950 *−0.7230 *0.1711−0.6619 *
weakmoderatestrongstrongvery strongweakstrong
C20:1 n−9−0.3539−0.38520.13330.08030.2376−0.38600.0748
moderatemoderateweaknegligibleweakmoderatenegligible
MUFA0.09930.4147−0.6381 *−0.7510 *−0.6142 *0.1113−0.6124 *
negligiblemoderatestrongvery strongstrongweakstrong
C18:2 n−6c + C18:2 n−6t−0.4229−0.6337 *0.28620.6775 *0.6158 *−0.5369 *0.3185
moderatestrongweakstrongstrongstrongmoderate
C18:3 n−3−0.1199−0.5308 *0.28540.8425 *0.2710−0.6458 *0.2193
weakstrongweakvery strongweakstrongweak
C20:2 n−60.0262−0.07830.27980.35090.35310.05240.3344
negligiblenegligibleweakmoderatemoderatenegligiblemoderate
C20:3 n−3−0.1780−0.5483 *0.44540.8820 *0.5247 *−0.5251 *0.4183
weakstrongmoderatevery strongstrongstrongmoderate
C20:4 n−60.1242−0.15930.28200.45630.34950.03410.3388
weakweakweakmoderatemoderatenegligiblemoderate
C20:5 n−3−0.2069−0.01390.27350.31470.3039−0.03510.1591
weaknegligibleweakmoderatemoderatenegligibleweak
C22:2 n−6−0.4478−0.18440.0657−0.14060.2942−0.08900.0248
moderateweaknegligibleweakweaknegligiblenegligible
PUFA−0.1535−0.6050 *0.32740.4808 *0.3697−0.32840.2210
weakstrongmoderatemoderatemoderatemoderateweak
PI−0.3414−0.5888 *0.5556 *0.7966 *0.6996 *−0.5128 *0.5202 *
moderatestrongstrongvery strongstrongstrongstrong
UI−0.4632 *−0.6830 *0.5153 *0.7873 *0.7123 *−0.6167 *0.4642 *
moderatestrongstrongvery strongvery strongstrongmoderate
SOD−0.7414 *−0.34760.29640.00580.5492 *−0.35160.2401
very strongmoderateweaknegligiblestrongmoderateweak
CAT−0.0609−0.0119−0.3603−0.3239−0.13710.0660−0.2586
negligiblenegligiblemoderatemoderateweaknegligibleweak
TBARS0.7657 *0.5712 *−0.5169 *−0.2889−0.7934 *0.4795 *−0.4378
very strongstrongstrongweakvery strongmoderatemoderate
C12:0—lauric acid; C14:0—myristic acid; C16:0—palmitic acid; C18:0—stearic acid; C20:0—arachidic acid, eicosanoic acid; C21:0—heneicosanoic acid; C24:0—lignoceric acid, tetracosanoic acid; C16:1 n−7—palmitoleic acid; C18:1 n−9c + C18:1 n−9t—oleic acid + elaidic acid; C20:1 n−9—cis-11-eicosenic acid; C18:2 n−6c + C18:2 n−6t—linoleic acid + linolelaidic acid; C18:3 n−3—α-linolenic acid; C20:2 n−6—cis-11-14-eicosadienic acid; C20:3 n−3—eicosatrienic acid; C20:4 n−6—arachidonic acid; C20:5 n−3—cis-5,8,11,14,17-eicosapentaenic acid, EPA; C22:2 n−6—cis-13-16-docosadienic acid; SFA—saturated fatty acids, MUFA—monounsaturated fatty acids; PUFA—polyunsaturated fatty acids; PI—peroxidation index; UI—unsaturation index; SOD—superoxide dismutase; CAT—catalase; TBARS—thiobarbituric acid reactive substances; n = 30; * significant at p ≤ 0.01.
Table 9. The full correlation matrix between Pb concentration and the other analyzed variables.
Table 9. The full correlation matrix between Pb concentration and the other analyzed variables.
Variable 1Variable 2rpFDR (BH) ThresholdsSignificant
PbC12:0−0.76330.0000 *0.0003**
PbC14:00.72060.0000 *0.0006**
PbC16:00.71120.0000 *0.0010**
PbC18:00.69410.0000 *0.0013**
PbC20:00.67270.0000 *0.0016**
PbC21:0−0.67010.0000 *0.0019**
PbC24:0−0.65400.0000 *0.0023**
PbSFA0.62980.0000 *0.0026**
PbC16:1 n−7−0.62290.0000 *0.0029**
PbC18:1 n−9c + C18:1 n−9t0.61180.0000 *0.0032**
PbC20:1 n−9−0.60620.0000 *0.0035**
PbMUFA0.60050.0000 *0.0039**
PbC18:2 n−6c + C18:2 n−6t−0.59580.0000 *0.0042**
PbC18:3 n−3−0.59360.0000 *0.0045**
PbC20:2 n−6−0.58320.0000 *0.0048**
PbC20:3 n−30.57590.0000 *0.0052**
PbC20:4 n−6−0.54590.0000 *0.0055**
PbC20:5 n−30.54230.0000 *0.0058**
PbC22:2 n−60.53810.0000 *0.0061**
PbPUFA−0.51380.0000 *0.0065**
PbPI0.49890.0000 *0.0068**
PbUI0.47680.0001 *0.0071**
PbSOD0.46320.0002 *0.0074**
PbCAT0.41710.0009 *0.0077**
PbTBARS0.40520.0013 *0.0081**
PbCD−0.39610.0017 *0.0084**
PbCr0.38900.0021 *0.0087**
PbBa−0.38620.0023 *0.0090**
PbNi−0.19450.13630.0094-
PbZn−0.07720.55790.0097-
PbCu0.07710.55820.0100-
* Significance confirmed by Pearson’s correlation analysis; ** Significance confirmed after Benjamini–Hochberg FDR correction; n = 60; significant at p ≤ 0.01.
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Garbacz, A.; Kowalczyk-Pecka, D.; Kursa, W. Fatty Acids in Lumbricidae as Biomarkers of In Situ Metals Exposure. Sustainability 2025, 17, 8076. https://doi.org/10.3390/su17178076

AMA Style

Garbacz A, Kowalczyk-Pecka D, Kursa W. Fatty Acids in Lumbricidae as Biomarkers of In Situ Metals Exposure. Sustainability. 2025; 17(17):8076. https://doi.org/10.3390/su17178076

Chicago/Turabian Style

Garbacz, Aleksandra, Danuta Kowalczyk-Pecka, and Weronika Kursa. 2025. "Fatty Acids in Lumbricidae as Biomarkers of In Situ Metals Exposure" Sustainability 17, no. 17: 8076. https://doi.org/10.3390/su17178076

APA Style

Garbacz, A., Kowalczyk-Pecka, D., & Kursa, W. (2025). Fatty Acids in Lumbricidae as Biomarkers of In Situ Metals Exposure. Sustainability, 17(17), 8076. https://doi.org/10.3390/su17178076

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