Effect of Lead on the Physiological Parameters and Elemental Composition of Pinus sylvestris L. and Picea abies (L.) H. Karst Seedlings

Abstract

Lead (Pb) pollution poses a long-term threat to forest ecosystems, particularly in mountainous areas affected by atmospheric deposition. This study examined the physiological and biochemical responses of juvenile Pinus sylvestris L. and Picea abies (L.) H. Karst seedlings to low concentrations of lead nitrate during early development. Treatments simulated environmentally relevant Pb exposure and focused on pigment composition, oxidative stress markers, soluble protein and proline levels, and elemental content. Both species exhibited hormetic stimulation of photosynthetic pigments at lower Pb concentrations. In P. sylvestris, this effect declined at the highest dose, whereas P. abies maintained pigment levels, suggesting stronger regulatory control. Pb exposure reduced soluble proteins and induced species-specific alterations in MDA and proline levels. Correlation analysis revealed a well-integrated stress response in P. abies, while P. sylvestris showed a more fragmented pattern. Elemental analysis confirmed Pb accumulation primarily in roots, with higher levels in P. sylvestris. Both species experienced reduced root Mg, K, and Mn, indicating ionic imbalance due to Pb²⁺ interference. Zn content increased in P. sylvestris but decreased in P. abies, possibly reflecting differences in uptake regulation. These species-specific responses support the hypothesis that P. abies activates more effective defense mechanisms against Pb toxicity, while P. sylvestris exhibits a stronger physiological stress response.

1. Introduction

The advancing level of technology in most areas of industry, mining, and manufacturing has not eliminated the long-term issue of environmental contamination by heavy metals. Even today, many countries experience significant contamination from heavy metals released through fossil fuel combustion, with lead being one of the key pollutants entering the environment through this process. Contamination with lead is caused by emissions from industrial processes, exhaust gases, mining, or the burning of fossil fuels [1,2,3]. The problem is not only the initial contamination with lead but also the further fate of this element [4,5]. Lead is characterized by low mobility, and as a result, its particles often remain on the soil surface or in water sediments [6,7,8]. This can lead to the gradual accumulation of this element in the environment [9,10]. Many studies have confirmed increased deposition of lead in areas affected by prevailing wind flow in the downwind direction from the original source of pollution [11,12,13]. High concentrations of lead are often found in mountainous areas, which act as a natural barrier to long-distance air flows [14,15,16]. This causes, on the windward side, a long-term contamination effect of the natural environment and forest stands [14,17,18]. Plants, including trees such as pine (Pinus sylvestris L.) and spruce (Picea abies (L.) H. Karst), absorb lead through their roots from the soil surface [19,20,21]. The presence of lead is toxic to plants and can cause many changes, like the disruption of nutrient uptake and water transport [22,23]. Lead also damages photosynthesis by inhibiting chlorophyll synthesis, destroying chloroplasts [24,25], and affecting the production of healthy pollen grains [26,27]. Therefore, the impact of lead in forest stands can lead to reduced tree growth, lower biomass accumulation, and diminished forest productivity [28,29]. The condition of forests is also influenced by other effects of the presence of lead, such as changes in soil microbial diversity [30,31]. Ecosystem contamination is a complex process influenced by various factors, such as site altitude, soil characteristics, organic matter content, forest litter [32,33,34] pH, temperature, and precipitation [35,36]. These factors affect the presence and bioavailability of lead (Pb) in forest ecosystems, as well as its direct impact on individual trees [37,38,39]. At lower concentrations, signs of contamination may not always be evident, as many species can adapt to prolonged exposure to these contaminants [38,40,41]. This study focuses on the contamination of juvenile stages of forest tree species from the Pinaceae family. Pine and spruce are key species in European woodlands, making up a significant proportion of forest stands [42,43]. Here, we simulated Pb contamination in forest stands, which could occur through long-term exposure to polluted precipitation [44]. The concentrations used in this study exceed the permissible limit for lead in surface waters in Europe [45], as well as the average Pb content typically found in precipitation across Europe [46,47]. However, long-term exposure to low concentrations of Pb can have a cumulative effect, resulting in increased Pb levels in topsoil and the ecosystem [48,49]. The concentrations used were thus chosen to reflect potential impacts on physiological processes in plants without causing immediate toxic effects. Here, we aimed to determine the basic impact of Pb on the physiological processes of juvenile conifer individuals germinating from seeds during the first two months of growth in Pb-contaminated forest stands.

The main hypothesis of this study is that juveniles of the two tested coniferous species express different sensitivity to variously lead-loaded sites. The results can be further used in the selection of reforestation practices at lead-loaded sites. The choice of not only plant species but also plant developmental stage can be made based on the results obtained, i.e., seeds, juveniles, or young trees.

2. Materials and Methods

2.1. Growth Conditions and Pb Treatments

The experiment was performed using seeds of Pinus sylvestris and Picea abies (Forests of the Slovak Republic, state enterprise, Semenoles, Slovakia, 2023). Only visually healthy seeds of average size that were free of abnormalities in size, shape, and color were selected for the study. In total, 1920 seeds were used—80 seeds per group, with 24 groups in total, including replicates. The seeds were placed in uncovered plastic containers (20 × 15 × 10 cm), with each group assigned to one container. The containers were filled with a perlite substrate (Perlite substrate, Forestina s.r.o., Mnichov, Czech Republic) and maintained under controlled conditions with a 16 h light/8 h dark photoperiod, a temperature of 23 ± 2 °C, and a relative humidity of 60 ± 5%. The samples were watered exclusively with distilled water, with no additional nutrients or treatments. For the first three weeks after sowing, the seeds were left untreated with Pb. After this period, 0.5 L of metal solution was applied five times at seven-day intervals (except in the control groups). The treatments included lead nitrate (Pb(NO₃)₂) at concentrations of 0.5 mg/L, 1 mg/L, and 2 mg/L. These solutions were applied directly to the substrate during watering for both species. Following the final treatment, the plants remained in the containers for an additional seven days before the experiment was terminated. The total duration of the experiment was nine weeks. After removal from the substrate, the plants were immediately rinsed with water and frozen in liquid nitrogen to preserve tissue integrity. The aboveground and below-ground parts were then separated and stored at −80 °C until further analysis.

2.2. Pigments

Before all analyses, plant samples from each treatment group (averaging 50 individuals per group) were homogenized in a frozen state to ensure uniformity for subsequent analyses. For pigment analysis, 25 mg of plant tissue (FW) was incubated in 15 mL of dimethyl sulfoxide (DMSO) at 65 °C for 60 min. After incubation, absorbance was measured using a multimode microplate spectrophotometer (Synergy HT, BioTek, Hudson, NY, USA) at wavelengths of 665, 649, 480, 435, and 415 nm for chlorophylls and carotenoids and 663, 647, and 537 nm for anthocyanins. The concentrations of chlorophylls a and b, total chlorophyll (a + b), and total carotenoids were calculated according to Wellburn’s method [50]. Anthocyanin concentration (µmol/mL) was determined using the formula: 0.08173 × A537 − 0.00697 × A647 − 0.00228 × A663 [51]. Pigment analyses were performed only on the aboveground photosynthetic tissues of the plants, with each sample analyzed in triplicate.

2.3. MDA Analysis

Malondialdehyde (MDA) content was evaluated using the method of Heath and Packer [52]. A total of 100 mg (FW) of homogenized plant tissue was ground in a pestle and mortar with 1.0 mL of 0.1% trichloroacetic acid (TCA) extract and then centrifuged at ±4 °C. After removing the supernatant, the samples were incubated with a mixture of 20% TCA and 0.5% thiobarbituric acid (TBA) at 90 °C. Following immediate cooling on ice, the samples were analyzed using the same spectrometer (Synergy HT, BioTek) as used in pigment analysis at wavelengths of 532 and 600 nm. MDA concentration (µg/mg FW) was calculated using the following formula: [(A₅₃₂ − A₆₀₀)/155] × 1000 × Volextract/Volaliquot × 1/FW. MDA analyses were performed only on the aboveground photosynthetic tissues of the plants, with each sample analyzed in triplicate.

2.4. Soluble Protein Quantification

For soluble protein quantification, the protocol of Bradford [53] was used. A total of 25 mg (FW) of homogenized tissue was ground in a pestle and mortar with 50 mM phosphate buffer (pH 6.5) and centrifuged at 15,000× g at 4 °C for 20 min. Then, the supernatant was mixed with Bradford solution and measured at an absorbance of 595 nm (Synergy HT, BioTek). Bovine serum albumin was used as the calibration standard. Soluble protein quantification analyses were performed only on the aboveground photosynthetic tissues of the plants, with each sample analyzed in triplicate.

2.5. Proline Analysis

Proline content was analyzed based on the protocol of Ábrahám et al. [54]. A total of 50 mg fresh weight (FW) of tissue per sample was ground in a mortar and pestle with 3% sulfosalicylic acid (SSA). Samples were centrifuged for 5 min at room temperature, and the supernatants were then incubated in a mixture of 3% SSA, glacial acetic acid, and acidic ninhydrin at 96 °C for 60 min. Subsequently, the samples were extracted with toluene, and absorbance was measured at 520 nm using a spectrometer (Synergy HT, BioTek). Proline concentration was determined using a standard curve and calculated based on fresh weight. Proline analysis was performed only on the aboveground tissues, and each sample was analyzed in triplicate.

2.6. AAS Determination of Elements

A total of 100 mg of dry plant samples was weighed into PTFE digestion vessels. To each sample, 8 mL of HNO₃ and 2 mL of H₂O₂ (trace purity, Sigma-Aldrich Chemie GmbH, Steinheim, Germany) were added. The digestion was performed using a microwave digestion system, ETHOS-One (Milestone Srl., Sarisole, Italy), with the following parameters: first ramp to 200 °C over 20 min, hold at 200 °C for 20 min, followed by a 20 min cooling phase. After mineralization, the digested samples were filtered using quantitative Munktell filter paper No. 390 (Munktell & Filtrak, Bärenstein, Germany) into 50 mL volumetric flasks and filled to the final volume with double deionized water (ddH₂O, 18.2 MΩ·cm⁻¹ at 25 °C), prepared using the Simplicity 185 purification system (Millipore SAS, Molsheim, France). The resulting solutions were stored in polyethylene tubes until analysis by ICP-OES. Elemental analysis was carried out using an Agilent 720 ICP-OES spectrometer (Agilent Technologies Inc., Santa Clara, CA, USA) with the axial plasma configuration and an SPS-3 auto-sampler (Agilent Technologies GmbH, Göttingen, Germany). The operating conditions were as follows: RF power of 1.75 kW, plasma gas flow rate of 16.0 L·min⁻¹, auxiliary gas flow of 1.50 L·min⁻¹, nebulizer gas flow of 0.85 L·min⁻¹, and CCD detector temperature set at −35 °C. Signal acquisition time was 3 × 3 s for each of the three replicates. Calibration of the ICP-OES method was conducted using a TraceCert ICP 5 mixed standard (Sigma-Aldrich GmbH, Steinheim, Germany), diluted to three concentration levels: Level I—0.0475 mg·kg⁻¹, Level II—0.0950 mg·kg⁻¹, and Level III—0.190 mg·kg⁻¹. Argon and carbon were used as internal standards. ERM^®-CE278k (mussel tissue; IRMM, Geel, Belgium) and procedural blanks were included for quality control. The recovery values, limits of detection (LOD), limits of quantification (LOQ), determination wavelengths, and calibration linearity are presented in the corresponding table in the Results section. For non-certified elements, recoveries were determined using the standard addition method. Elemental concentrations were determined separately for roots and aboveground parts, with each sample analyzed in triplicate.

2.7. Statistical Analysis

Complete statistical analysis was conducted using the R programming language (v. 4.4.1) [55]. For each parameter, a nonparametric factorial ANOVA was performed using the aligned rank transform (ART) procedure [56,57] implemented via the “ARTool” R package [58]. The ART method was applied because it enables analysis of factorial designs while accommodating non-normal data distributions and interaction effects. Factorial models were constructed using the “art” function, followed by an evaluation of the main effects and interactions with the “anova” function. Subsequently, post hoc contrast tests were carried out using the “art.con” function from the same package. In addition, Spearman correlation was performed to assess the relationships between parameters, along with complete-linkage hierarchical clustering using the “pheatmap” R package [59].

3. Results

In this study, the effects of low doses of lead on juvenile individuals of Pinus sylvestris and Picea abies during the first weeks after germination were shown. The physiological and biochemical responses of these species to the treatment, as well as the level of lead accumulation in plant tissues and its influence on the content of selected micro- and macroelements, were documented. In pigment content analysis, within the control groups, there were no significant differences between the species for any of the pigment parameters (Figure 1). In both species, chlorophyll a, chlorophyll b, and total chlorophyll concentrations (Figure 1A, Figure 1B, and Figure 1C, respectively) did not differ significantly between the control and the lowest applied lead nitrate concentration (0.5 mg/L). However, significantly higher values were observed in cases of higher applied lead nitrate concentrations (1 and 2 mg/L) compared to the control group (p < 0.05), suggesting a stimulatory effect of lead nitrate on chlorophyll content in both species. Lead nitrate treatments had a slightly positive effect on the chlorophyll a/b ratio (Figure 1D) in P. sylvestris (p < 0.05), while in P. abies, only the highest applied concentration (2 mg/L) significantly increased the ratio. Despite these differences, the chlorophyll a/b ratio remained close to 2:1 across all treatments. All applied concentrations significantly increased anthocyanin content in both species (p < 0.05) (Figure 1F). Additionally, a similar trend was observed for total carotenoids (Figure 1E), with the exception of P. abies treated with the lowest lead nitrate concentration (0.5 mg/L). Factorial ANOVA revealed that the main effects of concentration (C) and the interaction between species and concentration (S × C) were significant for all pigment parameters, indicating that pigment responses varied depending on both treatment intensity and species identity. Additionally, the main effect of species (S) was significant for both the chlorophyll a/b ratio and anthocyanin concentration (p < 0.05 and p < 0.001, respectively) (Figure 1).

The highest total protein concentration in both species was recorded in the control group, with no significant difference observed between the species (Figure 2A). Upon lead nitrate treatment, total protein levels significantly decreased in both species compared to their respective controls (p < 0.05), suggesting a general suppression of protein synthesis and/or degradation under treatment conditions. Malondialdehyde (MDA) concentrations (Figure 2B) did not differ significantly between species under control conditions. Under lead nitrate exposure, P. sylvestris exhibited significantly lower MDA levels compared to the control group (p < 0.05). In P. abies, MDA concentrations were significantly lower than the control (p < 0.05) at lower applied concentrations (0.5 and 1 mg/L), but at the highest applied concentration (2 mg/L), MDA levels returned to values comparable to the control. Proline concentrations (Figure 2C) differed significantly between the species under control conditions (p < 0.05), with much lower baseline levels documented in P. sylvestris. In P. abies, upon treatments, proline levels were significantly lower compared to the control group (Figure 2C), while they grew with the lead nitrate concentration. In P. sylvestris, a significant increase in proline concentration was observed only at the highest treatment level. Similar to P. abies, the proline concentration significantly increased with treatment concentration (p < 0.05). The main effects of species (S), concentration (C), and their interaction (S × C) were statistically significant for all three parameters (Figure 2) (p < 0.001), indicating that each species responded differently across the range of concentrations, reflecting distinct response patterns.

More detailed insight into the relationships among variables is offered by the correlation heatmaps (Figure 3 and Figure 4). The variables are distinctly grouped into two clusters, i.e., biochemical and pigment parameters in both species. Parameters within each cluster show strong positive correlations, particularly in P. abies (Figure 3). When comparing inter-cluster correlations in P. abies, proline and MDA exhibit weak negative correlations with pigment parameters (ρ = −0.2), while proteins show a moderate negative correlation (ρ = −0.4). Notably, anthocyanins diverged from this pattern, exhibiting a strong negative correlation with proteins (ρ = −0.8) and moderate correlations with MDA and proline (ρ = −0.4). Inter-cluster analysis revealed divergent relationships between stress markers and pigments in P. sylvestris (Figure 4). While MDA and proteins consistently correlated negatively with pigments (ρ = −0.2 to −0.4), proline showed a strong negative association with carotenoids (ρ = −0.6) but no linkage to chlorophylls. Notably, anthocyanins uniquely exhibited a positive correlation with proline (ρ = 0.4), contrasting with their negative associations with MDA and proteins (ρ = −0.4).

A final perspective on the processes induced by lead treatment was complemented by the elemental analysis (

Table 1. Element concentrations in shoots and roots of Picea abies and Pinus sylvestris seedlings exposed to lead nitrate treatments (mg/L). Values are expressed as mean concentrations (mg/kg) ± relative standard deviation (RSD, %). For measurements below the limit of detection (LOD), the LOD value is reported and expressed in mg/kg.

Species	Tissue	Pb(NO3)2	Pb	Cu	Fe	K	Mg	Mn	Na	Zn
Picea abies	Roots	0	<LOD = 3.49	38.79 ± 0.57	234.55 ± 0.67	14,523.44 ± 0.71	5052.59 ± 0.85	58.86 ± 0.73	4004.57 ± 0.06	136.96 ± 0.26
		0.5	8.37 ± 2.39	15.93 ± 0.59	374.60 ± 1.05	6282.36 ± 1.39	4904.22 ±1.22	35.48 ± 0.94	4277.96 ± 0.34	45.76 ± 0.86
		1	28.16 ± 2.39	20.36 ± 1.29	570.59 ± 2.28	7069.70 ± 1.52	4134.04 ± 1.30	37.46 ± 0.63	4401.02 ± 0.38	61.48 ± 0.36
		2	69.83 ± 1.16	18.94 ± 2.11	322.29 ± 2.07	6962.75 ± 0.77	4599.52 ± 0.98	23.12 ± 0.67	4107.79 ± 0.65	88.47 ± 0.97
	Shoots	0	<LOD = 2.30	20.90 ± 1.00	161.18 ± 5.06	10,830.89 ± 2.70	4561.15 ± 3.00	654.21 ± 0.32	1541.12 ± 0.40	114.00 ± 0.22
		0.5	<LOD = 2.93	6.94 ± 4.75	60.51 ± 6.49	5926.68 ± 2.66	4959.92 ± 2.21	229.73 ± 1.28	2944.83 ± 0.40	81.84 ± 0.08
		1	<LOD = 2.98	8.55 ± 1.56	107.00 ± 3.71	6459.11 ± 3.40	4368.03 ± 3.45	280.80 ± 0.40	3029.08 ± 0.23	82.92 ± 0.26
		2	<LOD = 3.14	7.81 ± 2.08	63.61 ± 1.02	5882.56 ± 1.54	4963.27 ± 2.02	245.15 ± 0.63	4020.92 ± 0.61	60.52 ± 0.03
Pinus sylvestris	Roots	0	<LOD = 2.56	39.22 ± 0.91	163.91 ± 4.10	11,049.32 ± 1.89	4859.56 ± 2.48	43.58 ± 0.85	4184.89 ± 0.17	99.40 ± 0.20
		0.5	21.39 ± 2.01	19.58 ± 1.44	382.99 ± 5.09	8102.72 ± 3.36	3794.21 ± 3.49	14.85 ± 0.51	5609.98 ± 0.11	85.28 ± 1.06
		1	47.73 ± 3.94	21.26 ± 1.38	431.07 ± 0.92	8995.49 ± 1.64	4243.87 ± 1.27	20.06 ± 0.62	7941.17 ± 0.70	109.86 ± 0.62
		2	153.33 ± 1.15	19.21 ± 3.55	211.28 ± 2.80	5586.62 ± 1.88	5377.81 ± 0.79	12.70 ± 1.48	10,104.37 ± 0.39	195.59 ± 0.59
	Shoots	0	<LOD = 3.35	15.45 ± 0.37	215.28 ± 1.28	792.46 ± 0.81	6942.64 ± 0.59	40.57 ± 0.42	3482.70 ± 0.23	149.10 ± 0.02
		0.5	<LOD = 3.49	3.41 ± 4.53	30.58 ± 8.26	8094.84 ± 2.12	4456.62 ± 2.10	80.20 ± 0.87	2900.29 ± 0.08	76.50 ± 0.50
		1	<LOD = 3.78	5.38 ± 7.23	39.11 ± 10.58	8690.26 ± 1.93	5102.89 ± 2.50	135.50 ± 0.48	4529.69 ± 0.30	97.63 ± 0.33
		2	<LOD = 3.75	6.38 ± 1.91	63.50 ± 5.90	5342.98 ± 3.18	5434.18 ± 3.61	181.88 ± 0.34	4573.15 ± 0.33	95.07 ± 0.57

). In the control groups, measured lead concentrations in both root and shoot tissues were below the limit of detection (LOD). In contrast, lead concentrations exceeding the LOD were detected in root tissues of both species following lead nitrate treatments, with generally higher values observed in P. sylvestris compared to P. abies (Table 1). In P. abies, the iron content in the roots decreased from 234.5 to 132.9 mg/kg after treatment, while in P. sylvestris, its levels slightly increased following exposure. A pronounced decrease was also observed in manganese—in P. abies, root concentrations dropped from 85.8 to 37.4 mg/kg, whereas in P. sylvestris, the values were generally lower, and changes were more evident at the highest Pb dose. Magnesium in the roots of P. abies declined from 505.2 to 413.4 mg/kg, while in P. sylvestris, the pattern was less pronounced. Potassium in P. abies showed a marked decrease after treatment, particularly in the roots (from 14,573 to 7089 mg/kg), while in P. sylvestris, the changes were less consistent. Copper and zinc contents did not follow a clear trend, although a decrease in Zn was observed in the roots of P. abies after treatment, while in P. sylvestris, Zn levels slightly increased at the intermediate Pb concentration. Sodium remained relatively stable in both species, with no notable deviations from the control.

4. Discussion

Both tested species showed stimulation in the production of chlorophyll a and b, anthocyanins, and carotenoids in correlation with the increasing intensity of lead treatment. This finding is particularly interesting, as numerous studies have confirmed that lead toxicity inhibits photosynthesis [7,60]. We assume that this stimulatory effect resulted from the selected concentration, which remained below the level of acute toxicity. This threshold, along with overall sensitivity and stress response to lead exposure, is species-specific [61,62], probably also varying in different developmental stages, genotypes, and ecotypes of tested species. Most detailed scientific studies have focused on crop plants or utilized model species [9,63]. Therefore, the specific effects of lead exposure—and particularly the threshold of acute toxicity—remain understudied in many forest tree species to this day [64].

The fact that low doses of lead may enhance photosynthetic parameters via the activation of hormetic stimulation mechanisms has been confirmed in juvenile maize—Zea mays L. [65], as well as in Vigna radiata (L.) R. Wilczek [66] and Vicia faba L. [67]. The stimulatory effect on pigment production in P. sylvestris begins to decline at the highest applied concentration, where pigment levels start to show a downward trend. We assume that this effect would intensify with continued exposure to higher concentrations and would likely become apparent in Picea abies as well. These differences also point to the distinct sensitivity of these species. The sensitivity of pine to lead was thoroughly studied by Belousov et al. [68], who confirmed the first toxic responses at the level of cytogenetic parameters at 5 μM (approximately equivalent to our treatment at 2 mg/L). The response of respiratory stress markers became fully apparent only at 500 μM [69]. Other evaluated markers also suggest rather different physiological responses in these conifers. While P. abies showed a gradual increase in MDA levels with increasing treatment concentration, this response was weaker in P. sylvestris. In contrast, proline accumulation was more pronounced in P. sylvestris. We assume that, under the highest treatment concentration, lead-detoxification within pine cells was insufficient. This interpretation is supported by the findings of Staszak et al. [70], in which germinating P. sylvestris seeds exposed to lead exhibited a significant reduction in reduced glutathione (GSH), along with an increase in its oxidized form (GSSG), indicating a rapid depletion of the non-enzymatic antioxidant system and a shift toward compensatory mechanisms. Reduced GSH capacity may trigger enhanced synthesis of alternative stress-related molecules such as proline.

These observations are further supported by correlation heatmaps (Figure 3 and Figure 4), in which P. abies, the evaluated parameters formed two coherent clusters—pigment and biochemical—with strong internal correlations, suggesting a well-coordinated stress response, while P. sylvestris showed fragmented responses, with weak coordination between proline and pigments. A similar trend was reported in a study by Khan et al. [71], where the sensitive rice cultivar exhibited weakened activation of antioxidant mechanisms, reduced pigment stability, and a less coordinated stress response. Wiszniewska et al. [72] emphasize that a coordinated stress response is crucial for resistance to toxicity, which is well expressed in adapted plants after prolonged exposure.

Furthermore, our elemental analysis (Table 1) shows that lead accumulation in the roots of pine was nearly twice as high as in spruce. This trend has already been observed in the study by Maddah and Moraghebi [73], and overall, P. sylvestris is often considered a suitable species for biomonitoring or for managing contaminated sites [19,74,75]. Therefore, increased proline levels do not correlate with more efficient lead exclusion or uptake regulation by the root system, but rather reflect a passive stress response, as also suggested by Hayat et al. [76]. In contrast, P. abies likely employs more effective defense mechanisms that limit both the uptake and toxicity of lead. These may include the remodeling of cell wall polysaccharides, which increases the wall’s capacity to bind lead and decreases its permeability—a mechanism that, together with the sequestration of toxic metals into vacuoles, has been confirmed in many plant species [77].

When focusing on other elements that play specific roles in plant metabolism, we observe trends similar to those reported in an earlier study by Godbold and Kettner [78], conducted on Picea abies. That study documented an increase in iron (Fe) concentrations in root tips at lower Pb concentrations, followed by a decrease as Pb treatment levels increased. This effect of lead on enhanced iron uptake was further detailed in the study by Varga et al. [79]. At the same time, the recorded decrease in Mg and K concentrations in the roots of both species suggests a disruption in ion homeostasis caused by competition between lead and essential cations Mg²⁺ and K⁺ [80]. A study by Shen et al. [81], conducted on Torreya grandis Fortune ex Lindl. (Taxaceae), also emphasized the critical role of Mg in these processes. Lamhamdi et al. [82] further reported a reduction in the content of most mineral ions in spinach and wheat even at low lead doses, which is consistent with our observations.

The only exception is the increasing concentration of zinc in the roots in response to higher Pb concentrations. Several studies have reported an antagonistic relationship between lead and zinc contents [83,84]. However, a study by Musielińska et al. [85], conducted on 60 plant species, also highlighted the high species-specific variability in these metabolic interactions. Another important aspect is that Zn plays a protective role against heavy metal toxicity by activating antioxidant enzymes, stabilizing cellular membranes, and regulating the expression of metal transporter genes [86]. The observed increase in Zn with rising Pb concentrations may thus represent a compensatory response to ionic stress. Since both Pb²⁺ and Zn²⁺ utilize similar transport mechanisms (e.g., transporters from the ZIP or HMA families) [87], it is likely that plants increase Zn uptake in an effort to maintain homeostasis and compensate for functions disrupted by lead toxicity.

Overall, after evaluating all variables, we conclude that Pinus sylvestris exhibits a more pronounced stress response with visible signs of toxicity at the highest tested lead-treatment concentration, while Picea abies appears to activate more effective regulatory mechanisms and a more coordinated metabolic response. At lower treatment concentrations, a hormetic effect was observed, manifested as a temporary stimulation of photosynthetic pigment production.

However, studies on synergistic/antagonistic effects of numerous environmental variables would be appreciated. Also, further investigations on molecular and microscopic levels could provide new insights and confirm the results achieved here. The mechanisms of lead stress response in the studied species would elucidate the results achieved here.

5. Conclusions

This study highlights species-specific responses to low-level lead exposure during the early developmental stages of conifers. Picea abies demonstrated greater physiological stability and more coordinated stress responses compared to Pinus sylvestris, suggesting a higher inherent tolerance to lead. Although P. sylvestris exhibits a less coordinated physiological response, it accumulates significantly more lead in its tissues, which—provided the plant maintains viability—may prove advantageous for phytoremediation efforts. These differences in metal uptake, pigment metabolism, and osmotic adjustment may not only influence forest regeneration at contaminated sites but also be useful in ecological engineering and metal-loaded site recovery by seeds or seedlings. Understanding such variability among species is critical for assessing ecological risks and guiding reforestation strategies in polluted environments.