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Article

Eucalyptus-Biochar Application for Mitigating the Combined Effects of Metal Toxicity and Osmotic-Induced Drought in Casuarina glauca Seedlings

by
Oumaima Ayadi
1,2,3,
Khawla Tlili
1,4,
Sylvain Bourgerie
3,* and
Zoubeir Bejaoui
1,2
1
Faculty of Sciences of Bizerte, University of Carthage, Bizerte 7021, Tunisia
2
Laboratory of Forest Ecology (LR11INRGREF03), National Institute of Research in Rural Engineering, Water and Forests (INRGREF), Ariana 2080, Tunisia
3
University of Orleans, Laboratory Physiology, Ecology and Environment (P2E), UR 1207—USC INRAE 1328, rue de Chartres, BP 6759, 45067 Orléans Cedex 2, France
4
Faculty of Sciences of Tunisia, University of Tunis, Elmanar, LEBPAO, Tunis 1068, Tunisia
*
Author to whom correspondence should be addressed.
Land 2025, 14(7), 1423; https://doi.org/10.3390/land14071423
Submission received: 30 May 2025 / Revised: 1 July 2025 / Accepted: 5 July 2025 / Published: 7 July 2025
(This article belongs to the Special Issue Challenges and Solutions for Sustainable Land: Soil Quality and Contamination)
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Abstract

Land degradation from trace metal pollution in North Africa severely compromises soil fertility. This study investigates the synergistic remediation potential of Eucalyptus biochar (EuB) and Casuarina glauca in iron mine soil contaminated with Fe, Zn, Mn, Pb, Cd, and As. Seedlings were grown for six months in: non-mining soil (NMS), contaminated soil (CS), and CS amended with 5% EuB (CS + EuB). Comprehensive ecophysiological assessments evaluated growth, water relations, gas exchange, chlorophyll fluorescence, oxidative stress, and metal accumulation. EuB significantly enhanced C. glauca tolerance to multi-trace metal stress. Compared to CS, CS + EuB increased total dry biomass by 14% and net photosynthetic rate by 22%, while improving predawn water potential (from −1.8 to −1.3 MPa) and water-use efficiency (18%). Oxidative damage was mitigated. EuB reduced soluble Fe by 71% but increased Zn, Mn, Pb, and Cd mobility. C. glauca exhibited hyperaccumulation of Fe, Zn, As, Pb, and Cd across treatments, with pronounced Fe accumulation under CS + EuB. EuB enhanced nodule development and amplified trace metals sequestration within nodules (Zn: +1.4×, Mn: +2.4×, Pb: +1.5×, Cd: +2.0×). The EuB-C. glauca synergy enhances stress resilience, optimizes rhizosphere trace metals bioavailability, and leverages nodule-mediated accumulation, establishing a sustainable platform for restoring contaminated lands.

1. Introduction

Globally, over 10% of agricultural soils in mining regions exhibit trace-metal concentrations exceeding recommended safety thresholds annually [1]. Excessive levels of these contaminants threaten ecosystem resilience and global food security [2], while also posing a significant health hazard [3]. Furthermore, they severely impact soil fertility by altering the soil’s biological, chemical, and physical properties [4]. North Africa experiences the most severe land degradation and desertification globally, driven primarily by accumulating harmful trace metals in the soil [5]. The environmental risks linked to soil pollution by trace metals (TM) are particularly acute in the North of Tunisia [6], where both active and legacy mining operations have been abandoned in the absence of any environmental safeguards [7,8]. These mine sites represent a significant source of contamination for surrounding agricultural soils [9]. For example, Nouairi et al. [10] showed high levels of Pb and Zn, in agricultural soils exposed to mining waste reaching 28,040 mg·kg−1 and 94,420 mg·kg−1, respectively. Similarly, Mabrouk et al. [11] have detected Ni levels of 101 mg·kg−1, while Achour et al. [12] have revealed contamination of Cd (64 mg·kg−1), As (669 mg·kg−1), and Sb (145 mg·kg−1). In Tunisia’s Mediterranean climate, mining sites face rehabilitation challenges due to the complex interplay between soil contamination and edaphic drought, complicating effective land rehabilitation efforts. Under such conditions, drought suppresses microbial activity [13], thereby diminishing soil fertility and constraining plant growth [14,15], both of which are critical for effective phytoremediation. Several researches have extensively explored phytoremediation under optimal growing conditions, yet the synergistic impacts of edaphic drought and trace metal-contaminated soils remain less studied.
Trace metals can infiltrate water sources through wind dispersal and runoff, leading to the contamination of both surface water and groundwater [16]. Given their persistent nature and toxicity even at low concentrations [17], addressing TM contamination necessitates sustainable remediation strategies to restore environmental balance [18]. The excessive accumulation of TM in soils exerts phytotoxic effects once absorbed by plants, leading to reduced biomass production and impaired water uptake [19]. This metal-induced stress triggers the overgeneration of reactive oxygen species (ROS), resulting in oxidative damage and physiological and biochemical disruptions [20]. This perturbation compromises enzymatic processes, destabilizes membranes, impairs photosynthetic activity, and damages cellular structures [21]. Plants have evolved intrinsic defense mechanisms to mitigate TM-induced stress, including stress-responsive gene activation [22], antioxidant enzyme regulation [23], and enhanced proline synthesis [24]. However, in highly polluted environments, these natural defenses are often insufficient, necessitating external interventions to enhance plant resilience and metal immobilization [19].
Rehabilitating degraded mine lands using appropriate tree species with soil wood amendments can efficiently be applied as a promising strategy for establishing a green cover. Actinorhizal trees, such as Casuarina glauca, are particularly promising due to their ability to establish symbiotic relationships with nitrogen-fixing bacteria, which significantly enhance soil fertility [25,26,27]. C. glauca, a model actinorhizal species, has shown promising adaptability to degraded soils beyond its native range [28]. It offers considerable potential for enhancing drought tolerance and rehabilitating soils contaminated with trace metals [27,29]. Effective phytoremediation requires plant species possessing extensive root systems, rapid growth rates, high tolerance to a multitude of abiotic stresses, and the capacity to uptake, translocate, and sequester trace metals [30,31]. Nonetheless, its capacity to remediate sites exposed simultaneously to TM contamination and drought-induced osmotic stress remains insufficiently explored. Numerous studies have highlighted the synergistic benefits of integrating phytoremediation with biochar amendment to remediate TM contaminated soils under drought conditions [32,33]. Biochar, generated via the pyrolysis of plant biomass, represents a cost-effective soil amendment that enhances water-retention capacity, thereby mitigating plant water stress during periods of drought [34,35]. Its highly porous architecture facilitates the adsorption and gradual release of water and nutrients to the rhizosphere [36], promoting improved plant growth and drought resilience. Moreover, biochar incorporation has been shown to elevate soil organic matter levels and stimulate microbial activity, further supporting soil health and remediation efficacy [37,38]. Biochar’s high cation exchange capacity, and alkaline pH make it a powerful adsorbent, reducing metal mobility and toxicity in contaminated soils [39]. Biochar cam improve soil stability and structure, helping to prevent erosion [40]. It also creates pores in the soil, improving aeration, drainage and root penetration [41]. However, the efficacy of biochar in TM stabilization depends on its feedstock composition, with woody biomass-derived biochars demonstrating superior adsorption properties [42]. Eucalyptus-derived biochar has shown promise in TM remediation due to its high cellulose content, which enhances adsorption capacity [43,44]. The biochar employed here exhibits a neutral to mildly alkaline pH, pronounced porosity, and minimal ash content [45,46]. These physicochemical attributes improve soil aggregation and water-holding capacity, thereby enhancing nutrient bioavailability and uptake by plants [47]. Moreover, biochar application markedly decreases the bioavailability and plant assimilation of TM, effectively limiting their entry into the food chain [43,48]. Given these properties, incorporating Eucalyptus biochar into contaminated soils could offer a viable strategy to improve the phytoremediation efficacy of C. glauca, promote plant growth, and mitigate secondary contamination risks through the stabilization of eroded soils.
This study targets six trace metals (Fe, Zn, Mn, Pb, Cd, As) prevalent at the Tamra iron mine site due to ore weathering and tailing dispersal [7]. Iron (Fe) constitutes the main trace metal in the ore mined. Zinc (Zn) and manganese (Mn) represent common geochemical co-occurring metals in iron formations, while lead (Pb), cadmium (Cd), and arsenic (As) are secondary contaminants [7]. These latter elements are prioritized by the U.S. Environmental Protection Agency (EPA) due to their high toxicity, environmental mobility, and bioaccumulation potential [2,4,12,19]. Collectively, they provide a representative model to evaluate remediation strategies for restoring soil health and ecosystem function in degraded mining landscapes. In this study, we assess the effectiveness of Eucalyptus-derived biochar in enhancing the physiological and biochemical resilience of C. glauca subjected concurrently to TM contamination and drought-induced osmotic stress in mining-impacted soils. By elucidating the underlying mechanisms of biochar-assisted phytoremediation, we provide critical insights for the sustainable reclamation of heavily polluted mining sites and facilitate the broader implementation of this integrated environmental-restoration strategy.

2. Materials and Methods

2.1. Soils, Plant Material, Experimental Design, and Growth Conditions

The study area is the iron mining site of “Tamra” located 130 km N-W of the Tunisian capital (37°03′12.8″ N, 9°06′03.04″ E). The region is characterized by a humid climate [49]. Contaminated soil (CS) samples were collected from the Tamra mine land. Several points were randomly sampled across the site and mixed to obtain a composite soil sample. Non-mining soil (NMS) was collected from a non-mining area (37°02′54″ N, 8°58′48″ E), located 11 Km of the mine. The soil was collected from a depth of 20 cm after removing the upper layer. It then was dried at room temperature and passed through a 2-mm mesh sieve. A portion of the contaminated soil was amended with 5% biochar (CS + EuB) (w/w). The biochar used was obtained by pyrolysis of Eucalyptus bark biomass and sieved to 2 mm. Trace metals concentrations were determined by Inductively Coupled Plasma- Atomic Emission Spectroscopy (ICP-AES, Table 1). The other physicochemical characteristics of the non-mining soil (NMS), the contaminated soil of Tamra (CS) and the contaminated soil with biochar (CS + EuB) are presented in Table 1.
The physicochemical characteristics of the biochar were determined by standard methods [50]. It is characterized by alkaline pH (8.9), Electrical Conductivity (EC) of 46.5 μS/cm, specific area of 20.9 m2·g−1, and elemental composition of carbon, hydrogen, nitrogen are 67.6%, 2.4% and 0.6%, respectively.
The experiment was conducted at the National Institute of Research in Rural Engineering, Water, and Forests (INRGREF) in Tunis (Tunisia).
Casuarina glauca Sieb. ex-Spreng seedlings were produced from seeds at the forest nursery (El Agba) in north-west Tunisia. The seedlings were selected on the basis of their morphological homogeneity, with a height of around 80 cm and a root collar diameter of around 5 mm. The selected seedlings were transplanted into pots (25 cm × 26 cm × 22 cm) that were filled with non-mining (NMS), the contaminated (CS) and the contaminated with biochar (CS + EuB) soil at the rate of 10 kg of soil/pot (one seedling/pot). The pots containing the seedlings of the three treatments were grown for 6 months and they were arranged in a randomized complete block design (RCBD) with five blocks, each containing four seedlings per treatment. Five replicates of different treatments were randomly placed in each block. For each pot, soil moisture was maintained at 80% field capacity throughout the experiment to avoid leaching of mineral and trace metals using Time Domain Reflectometry (Trase system I, soil moisture equipment Corp., Goleta, CA, USA).

2.2. Determination of Photosynthetic Gas Exchange, Water Use Efficiency, Chlorophyll Fluorescence and Total Dry Mass

Photosynthetic gas exchange variables were measured for five seedlings/treatment. Measurements were carried out at the end of six months, between 09:30 and 11:30 solar time to ensure maximum photosynthetic assimilation [51]. Net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (gsw), and intercellular CO2 concentration (Ci) were measured using an infrared analyzer (LCpro+, ADC bio Scientific Ltd., Hoddesdon, UK) with a cylindrical coniferous cuvette at an active photosynthetic photon flux density of 984 ± 56 µmol·m−2·s−1, a CO2 concentration of 350 µmol·mol−1, and a leaf temperature of 29 ± 4 °C [52]. Measurements were performed on healthy, fully developed needles from the apical region of each treatment group. Each value represents the mean of 12 replicates. All gas exchange parameters were measured at the same levels. Water use efficiency (WUE) was calculated as the ratio of net photosynthesis to transpiration [53].
Chlorophyll fluorescence was measured on the same seedlings used for gas exchange measurements using a fluorometer (LCpro-SD, ADC Bioscientific Ltd., Hertfordshire, UK). Measurements of minimum (F0) and maximum (Fm) chlorophyll were carried out on attached needles after 30 min of dark adaptation [54]. Chlorophyll fluorescence (Fv/Fm) was calculated as follows:
Fv/Fm = (Fm − F0)/Fm
After six months of growth, C. glauca seedlings were harvested and washed rinsed with distilled water to remove soil and biochar particles. Shoots and roots were separated and then dried at 40 °C for 72 h to determine total dry mass (TDM) [55], then preserved for trace metal analysis. For the root part, nodules were collected, dried in the same conditions for the determination of morphological aspect and TM.

2.3. Determination of Chlorophylls and Carotenoids Contents

Chlorophyll content was determined after six months according to the method described by [56,57]. Fresh needles (100 mg) were homogenized in 10 mL of 85% acetone. The filtered solutions were incubated in the dark to avoid photooxidation at 4 °C. After 48 h, the chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (Tchl) and carotenoids (Car) contents were measured using a spectrometer (Perkin Elmer/UV/VIS model, lambda 25), which were calculated as follows:
Chl a (mg·g−1 FW) = 9.784 × A662 − 0.99 × A644
Chl b (mg·g−1 FW) = 21.42 × A644 − 4.65 × A662
Tchl (mg·g−1 FW) = Chl a + Chl b
Car (mg·g−1 FW) = (1000 × A470 − 1.90 Chl a − 63.14 Chl b)/214
where A662, A644 and A470 are the absorbance measured at 662, 644 and 470 nm, respectively.

2.4. Determination of Water Status

Relative water content (RWC) was determined as in [58]. After recording fresh weight (FW), needles were immersed in distilled water at 4 °C and in the dark for 48 h, blotted dry and then weighed to get the turgid weight (TW). Needles were then dried in an oven at 80 °C for 48 h to determine the dry weight (DW). RWC was calculated according to [59] as follows (6):
RWC (%) = [(FW − DW)/(TW − DW)] × 100
Predawn water potential (Ψpd) was measured via the scholander pressure chamber technique (model 600, PMS Instrument Company, Albany, OR, USA) on young, fully developed C. glauca needles. The freshly harvested needle was inserted into a gas-tight stopper, with the served end protruding a few mm from stopper. When sealed in the chamber pressure was applied and controlled until sap was expressed from the surface of the cut stem.

2.5. Determination of Plant Biochemical Responses

Hydrogen peroxide (H2O2) concentration was determined according to the method described by [60] using 5 seedlings for each treatment. Fresh needles (0.3 g) were cold homogenized in 2 mL of 0.1% trichloroacetic acid (TCA) solution (w/v). The homogenate was then centrifuged at 7500× g at 4 °C for 15 min. 0.5 mL of the supernatant was added to 0.5 mL of 100 mmol·L−1 phosphate buffer (pH = 7) and 1 mL of potassium iodide (1 M). The absorbance was measured at 390 nm via the UV spectrophotometer (UV 1200 Model, Tomos Life Science Group Pte, Ltd., Shanghai, China), then H2O2 concentration was calculated as follows:
[H2O2] (µg g−1 FW) = (A390 × volume of supernatant, mL)/[(sample fresh weight, g)/(volume of TCA, mL)]
Malondialdehyde (MDA) concentration, a marker of lipid peroxidation, was measured according to the method described by [61]. One gram of fresh leaf was milled in the presence of 10 mL of extraction buffer consisting of 0.5% thiobarbituric acid (TBA), 10% trichloroacetic acid (TCA) and 0.2 mM EDTA. The mixture was incubated in water bath at 95 °C for 25 min then centrifuged at 1000 rpm for 10 min. The absorbance of the supernatant was determined at 532 nm and 600 nm against a blank using a same UV spectrophotometer. MDA concentration was calculated as follows [62], with an extinction coefficient of 155.000 nmol·cm−1:
MDA (nmol·L−1 FW) = [(A532 − A600)/155000] × 106
where A532, and A600 are absorbance values measured at 532 nm and 600 nm, respectively.
The determination of enzymatic activities for catalase and guaiacol peroxidase was performed after six months using five seedlings for each treatment.
Catalase (CAT) activity was determined by monitoring H2O2 decomposition at 240 nm (ε = 39.4 mM−1 cm−1) according to the method described by [63]. Each unit of enzyme activity was defined as the amount of enzyme required by to break down 1 µmol substrate per min at 25 °C. Guaiacol peroxidase (GPOX) activity was measured according to the method described by [64]. The reaction mixture consisted of 50 mM of phosphate buffer (pH = 7), 9 mM of guaiacol solution and 19 mM of H2O2 [65]. The reaction starts upon addition of the enzyme extract to the prepared solution. The kinetics of tetraguaiacol formation from guaiacol was measured at 470 nm for 1 min and its extinction coefficient (ε = 26.6 mM−1 cm−1) was used for the calculation of GPOX activity. One unit was determined by the amount of enzyme required to produce 1 µmol guaiacol per min at 25 °C. Proline (Pro) content was measured according to the method described by [66]. One hundred milligrams of fresh leaf were milled in 5 mL of 40% methanol (v/v) and the mixture was incubated in water bath at 80 °C for 1 h. After cooling, 1 mL of the mixture was added to 1 mL of acetic acid, 25 mg of ninhydrin and 1 mL of a solution composed of 30 mL orthophosphoric acid 300 mL acetic acid, and 120 mL distilled water. This mixture was incubated in water bath (100 °C) for 30 min. After cooling, 5 mL of toluene were added to the samples. The absorbance of sample was determined at 520 nm using a UV spectrophotometer (UV 1200 Model, Tomos Life Science Group Pte, Ltd., Shanghai, China). The concentration of proline was calculated using the standard curve.
Electrolyte leakage (EL), reflecting membrane integrity was measured according to the method described by [67]. Needles were cut into 1 cm long fragments. These fragments were washed twice with distilled water and then were placed in sterile tubes containing 15 mL of distilled water in the dark at 40 °C for 1 h. The conductivity (µS·cm−1) was measured before (C1) and after (C2) heat treatment (100 °C for 1 h) using a conductivity meter (Cellox 325, Multiline P3 PH/LF, WTW Gmbh, Weilheim, Germany). EL was calculated as follows:
EL (%) = (C1/C2) × 100

2.6. Trace Metals Concentrations in Casuarina Glauca Organs and Phytoremediation Indices

Shoots, roots, and nodules of three seedlings from each treatment (previously separated and dried at 40 °C for 72 h) were ground to a fine powder. Two hundred milligrams of the sample were digested in 9 mL of acid mixture (1:3 v/v ratio of HNO3, 65%, and HCl, 37%) using a microwave digestion system (Multiwave 3000; Anton Paar GmbH, Ostfildern, Germany). The process included a 15-min heating phase at 180 °C, holding for 15-min and cooling for other 15-min. The digestion products were diluted and filtered through a 45 µm nitrocellulose filter [68]. Trace metals concentrations (Fe, Zn, Mn, Pb, Cd, and As) were determined by ICP-AES (ULTIMA 2, HORIBA, Labcompare, San Francisco, CL, USA) following instrument calibration. Trace metal composition was expressed as content (concentration × dry biomass) per seedling to accurately reflect uptake and accumulation [19]. Additionally, TM fractions (Fe, Zn, Mn, Pb, Cd, and As) were determined using a sequential extraction procedure based on the BCR (European Community Bureau of Reference) method described by [69]. The final bioavailable concentration (FBC) was defined as the concentration of TM in the exchangeable fraction of the BCR sequential extraction procedure.
Bioconcentration factor (BCF) and translocation factor (TF) were used to assess Fe, Zn, Mn, Pb, Cd, and As uptake and distribution in C. glauca seedlings. These metrics reflect the plant’s efficiency in accumulating and translocating trace metals [70]. Trace metals concentration in soil corresponds to the bioavailable fraction determined by sequential extraction [71]. BCF and TF were calculated as follows:
BCF = Trace metals concentration in plant/Trace metals concentration in soil
TF = Trace metals concentration in shoots/Trace metals concentration in roots

2.7. Statistical Analysis

All data were subjected to one-way ANOVA using Statistic software version 8.0 (Analytical Software, McKinney, TX, USA). Mean separations among treatments were performed with Fisher’s protected Least Significant Difference (LSD) test at p < 0.05. Values are presented as the means ± standard error (SE). Principal component analysis (PCA) was conducted using Statistic Kingdom to explore relationships between concentrations of TM in soils and measured plant parameters.

3. Results

3.1. Total Dry Mass, Gas Exchanges, Chlorophyll Fluorescence and Chlorophyll Content

Under contaminated soil conditions, C. glauca seedlings showed a significant decrease 27% in TDM compared to NMS (p < 0.0001; Figure 1a). However, the addition of EuB to contaminated soil (CS + EuB) reduced the severity of this reduction. Seedlings cultivated in CS + EuB showed a 14% improvement in TDM compared to the CS treatment (Figure 1a).
After six months, gas exchanges parameters were significantly affected by contaminated soil conditions. CS seedlings had significantly lower transpiration rate (44%), assimilation rate (59%), stomatal conductance (47%), and chlorophyll fluorescence (7.2%) compared to the NMS seedlings (Figure 1b,c,e,f), whereas, Ci significantly increased by 15% under CS compared to NMS seedlings (Figure 1d). The EuB mitigated CS-induced stress, resulting in less pronounced reductions in Tr (23%), Pn (37%), gsw (25%), and Fv/Fm (4.3%), compared to NMS seedlings.
Seedlings grown under CS revealed a significant effect (p < 0.05) of the trace metals on Chl a, Chl b, Tchl and Car compared to those of NMS seedlings, reaching 58%, 73%, 63% and 60%, respectively (Figure 2). However, the addition of EuB significantly improved chlorophyll content levels, for Chl a, Chl b, Tchl and Car reached 52%, 54%, 52%, and 53%, respectively, with respect to the CS treatment (Figure 2).

3.2. Water Status, Biochemical Compounds and Electrolyte Leakage

After six months of growth, C. glauca seedlings grown in CS exhibited a significant reduction in RWC compared to those in NMS (p = 0.0026, Figure 3a). The addition of Eucalyptus biochar mitigated the effect of TM, where RWC in CS + EuB seedlings was higher than under CS, though still lower than in NMS treatment.
Predawn water potential (Figure 3b), reflecting intense water stress caused by trace metals. Ψpd showed a significant reduction (p < 0.0001) under CS treatment compared to NMS. Under contaminated conditions, Eu-biochar increased Ψpd of C. glauca seedlings compared to CS seedlings and similar improvements were observed relative to NMS seedlings.
Under contaminated conditions, WUE was significantly (p < 0.0001), reduced (Figure 3c). WUE values were significantly lower under the CS treatment compared to other treatments. The CS + EuB treatment improved WUE relative to CS, although values remained below those observed in the NMS treatment, indicating a partial recovery.
Seedlings grown under CS exhibited a significant increase in hydrogen peroxide (H2O2) concentration compared to those under NMS (p < 0.0001), reaching levels 1.8-fold higher (Figure 4a). However, EuB addition significantly mitigated the effects of trace metal exposure, reducing significantly H2O2 accumulation compared to the CS treatment (Figure 4a). MDA levels were significantly elevated in CS compared to non-mining soil (p < 0.0001). However, CS amended with EuB revealed a significant reduction in MDA by 44% relative to CS (Figure 4c). Contaminated soil triggered a significant (p < 0.05) overproduction of CAT and GPOX, compared to NMS (Figure 4b,d). The addition of EuB significantly reduced enzyme overproduction relative to CS. Under trace metal stress, EL increased by 3.2-fold in CS compared to non-mining soil (p < 0.05). But the incorporation of EuB significantly ameliorated this effect, reducing EL by 37% relative to CS (Figure 4e).
Proline accumulation induced by TM exposure surged 4-fold in CS compared to NMS (Figure 4f). CS + EuB significantly mitigated this response, reducing proline levels by 50% relative to CS (statistical groupings: a, b, c). This attenuation underscores biochar’s capacity to restore cellular homeostasis, likely through metal immobilization, ROS neutralization, or enhanced osmoregulatory efficiency, thereby alleviating stress-driven metabolic demands in plants.

3.3. Accumulation and Phytoremediation Potentiality of Trace Metals

After 6 months of growth, under CS C. glauca seedlings exhibited significant accumulation of Fe, Zn, Mn, Pb, Cd, and As in roots and Zn, Mn and Pb in shoots (Figure 5). The overall accumulation pattern in C. glauca followed the order: Fe > Mn > Zn > Pb > As > Cd. Biochar amendment (CS + EuB) induced metal-specific responses: root Mn decreased significantly, while Cd increased sharply, with Fe, Zn, Pb, and As (Figure 5a,b,e,f) remaining stable. Shoot metal accumulation patterns varied significantly by element (Figure 5). Zn alone exhibited treatment-dependent variation, exceeding 3000 µg·g−1 across all conditions (Figure 5b). Fe, Cd, and As maintained consistently high concentrations (>10,000 µg·g−1, >100 µg·g−1, and >1000 µg·g−1 respectively) without significant treatment effects (Figure 5a,d,f). Conversely, Mn and Pb showed significantly higher accumulation in CS and CS + EuB versus NMS (p < 0.05; Figure 5c,e), with Pb > 1000 µg·g−1 in all treatments and Mn > 10,000 µg·g−1 exclusively in contaminated soils. C. glauca demonstrated exceptional rhizofiltration potential through dominant root retention of trace metals. EuB amendment further modulated metal partitioning by: (1) reducing Mn uptake by 18% versus CS (Figure 5c), (2) enhancing Cd bioavailability (reflected in 32% higher shoot accumulation; Figure 5d), and (3) limiting Zn translocation to shoots despite elevated root concentrations.
Eucalyptus biochar distinctly enhances Frankia nodule development (Figure 6). The accumulation profile within nodules revealed a clear preference for sequestration in the order Fe > Mn > Pb > Zn > As > Cd (Table 2). In particular, EuB treatment significantly amplified Zn, Mn, Pb, and Cd concentrations in nodules by 1.4-, 2.4-, 1.5- and 2.0-fold, respectively, relative to nodules formed in contaminated soil. In contrast, As and Fe levels remained essentially unchanged compared to Frankia nodule under contaminated soil.
Translocation factor values for all TM remained TF < 1 across treatments (Table 2). Eu-Biochar (CS + EuB) significantly modulated TF values with an increase for Fe, Mn, and for As compared to CS, underscoring biochar’s metal-specific influence on root to shoot transfer. Bioconcentration factor values revealed distinct TM sequestration patterns in roots (Table 2). Under contaminated soil conditions, the Fe BCF exceeded 10 in both CS and CS + EuB treatments. Biochar-amended treatment exhibits a 3.4-fold increase in Fe uptake relative to CS. While Zn, Mn, and As all showed significant accumulation in CS (BCF > 1), their uptake was significantly lowered by EuB amendment. In contrast, Cd accumulation only reached quantifiable levels in the CS + EuB treatment (BCF > 1), indicating that biochar enhanced Cd sequestration by C. glauca seedlings. Pb remained below threshold levels in all treatments (BCF < 1), confirming that its immobilization was unaffected by the addition of EuB.
Final bioavailable concentration (FBC)revealed profound treatment-specific shifts in trace metal solubility (Table 2). CS + EuB treatment induced hyper-solubility for Zn, Mn, and Pb. Conversely, Fe bioavailability reduced by 71% in CS + EuB compared to CS treatment. These opposing trends underscore biochar’s metal-specific solubilization effects: dramatically enhancing Zn/Mn/Pb mobility while immobilizing Fe.
Principal component analysis (PCA) revealed distinct patterns linking soil TM bioavailability and C. glauca physiological responses across treatments NMS, CS and CS + EuB (Figure 7). The first principal component (PC1), which explained 81% of the total variance, showed a strong association between the bioavailable concentrations of Fe, Zn, Mn, Cd, Pb, and As in soil and key stress indicators such as Pro, EL, MDA, H2O2, antioxidant enzyme activities, Ci, and the accumulation of Mn, Pb, As, Fe, and Zn in roots and shoots. Conversely, PC1 was negatively correlated with Ψpd, photosynthetic pigments, photosynthetic efficiency, gas exchange parameters, TDM, RWC, and WUE. The second component (PC2), accounting for the remaining 19% of the variance, primarily distinguished tissue-specific accumulation patterns of Cd, Fe and As between shoots and roots.
Collectively, these results demonstrate that elevated TM bioavailability in soil induces pronounced physiological stress—marked by oxidative damage, activation of antioxidant defenses and severe impairment of photosynthesis, water relations and growth. The contaminated soil clustered distinctly from the non-contaminated soil, whereas the CS + EuB treatment occupied an intermediate position, indicating that biochar amendment substantially mitigates trace-metal-induced stress.

4. Discussion

This study investigates soil contamination in mining areas and evaluates the potential of Eucalyptus-derived biochar (EuB) to mitigate TM stress (Fe, Zn, Pb, Mn, Cd, As) in C. glauca seedlings by reducing metal bioavailability in soil.
Contaminated soils significantly impair photosynthesis activity (Figure 1c), as evidenced by reduced chlorophyll content (Figure 2c), consistent with known mechanisms of chlorophyll degradation under metal stress [72]. A decrease in Chl a and Chl b can impair Rubisco activity which in turn decreases the amount of CO2 fixation [73]. The Fv/Fm decrease (Figure 1f) further indicates photosystem II instability [74]. A higher intercellular CO2 concentration (Figure 1d) suggest compromised CO2 utilization, potentially reducing photosynthetic efficiency via feedback inhibition [52] and limiting the accumulation of organic matter [75], ultimately hindering seedling growth under contaminated soil (Figure 1a). However, EuB addition significantly improved photosynthetic performance in contaminated soils (Figure 1b), as evidenced by increases in chlorophyll content and Fv/Fm efficiency. These improvements are likely due to biochar’s ability to restore soil moisture [14,76] and to enhance nutrient availability and soil fertility under severe pollution conditions [14,77]. Thus, EuB had positive effects on C. glauca seedling growth (Figure 1a) by increasing mineral nutrients availability in the soil and stimulating production of photosynthetic pigments [43,78].
Under contaminated conditions, C. glauca showed signs of water stress, indicated by decreased RWC (Figure 3a), Ψpd (Figure 3b) and WUE (Figure 3c) likely mediated by abscisic acid (ABA) accumulation [79]. This triggered stomatal closure, reducing transpiration rates (Figure 1e) and impairing water transport to needles. High concentrations of TM, result in increased osmotic stress [52,80], limiting root water uptake and imposing induced drought stress [81] as confirmed by lowered Ψpd under CS conditions (Figure 3b) which leads to a decrease in gsw (Figure 1e) as indicators of water stress and leads to reduced gas exchange (Pn and Tr). Biochar application under contaminated conditions (CS + EuB) improved stomatal conductance (Figure 1e), alleviated water stress in C. glauca by stabilizing Ψpd (Figure 3b), and restored RWC and WUE (Figure 3a,c) through enhanced soil water retention [35]. In contaminated soils, WUE thus emerges as a useful bioindicator for assessing plant resilience under osmotic-induced drought. Additionally, trace metals induced oxidative stress, evidenced by elevated H2O2, lipid peroxidation (increased MDA) and electrolyte leakage (Figure 4a,c,e) [52,82].
In fact, a strong association between Pro, H2O2, CAT, and GPOX, confirming coordinated stress responses (Figure 7). The antioxidant defense system involves CAT and GPOX and Pro accumulation were significantly higher in CS seedlings (Figure 4b,d,f). These enzymatic antioxidants help plants to cope with H2O2-induced cellular damage [52,83] to protect cell membranes. In contaminated soils, biochar amendment significantly alleviated toxicity, expressed by reduced H2O2 accumulation and MDA content, thereby decreasing electrolyte leakage and improving membrane stability (Figure 4c,e). Biochar also lessened CAT, GPOX, and Pro overproduction, indicating lower oxidative stress intensity (Figure 4b,d,f). Plants combat oxidative stress using multi-enzymatic defense system [19]. ACP further associated reduced electrolyte leakage with biochar’s mitigation of soil TM bioavailability and plant uptake (Figure 7), demonstrating its role in enhancing stress resilience.
Trace metals (Fe, Zn, Mn, Pb, Cd, and As) accumulation was significantly (p < 0.05) higher in roots than shoots (TF < 1) highlighting roots as primary sinks for trace metals (Figure 5, Table 2). Notably, the higher Cd concentration in roots under NMS may be due to its lower specific surface area (1 ± 0.057 m2·g−1, Table 1), which offers fewer adsorption sites for Cd, thereby increasing its mobility and bioavailability for plant uptake [84]. Under CS + EuB treatment Cd concentrations in roots increased, while Mn decreased (Figure 5c,d), suggesting competitive inhibition, phenomenon corroborated by biochar-induced Mn mobility shifts via reductive dissolution of Mn4+ to Mn2+ as suggested by Graber et al. [85] and Lu et al. [86]. Eucalyptus biochar amendment also enhanced translocation of As, Mn, and Fe (Table 2), attributable to pH-mediated speciation of As (III) to As (V) [87] and stimulation of siderophore producing bacteria facilitating Fe3+ solubilization [88]. In contrast, Cd and Pb translocation diminished, due to biochar’s inhibition of symplastic xylem transport and subsequent nodular sequestration [89], supporting a phytostabilization mechanism, wherein trace metals are immobilized in non-translocatable tissues [90]. Significantly, shoot metal concentrations remained stable except for Zn (p < 0.05), underscoring biochar’s role in restricting upward mobility while modulating root-zone metal dynamics.
Biochar significantly enhanced overall TM bioavailability (excluding Fe; Table 2), likely through ion exchange processes where soil metals displaced surface ions on biochar [91]. Elevated TM concentrations in Frankia nodules (Table 2) confirmed their role as transient sinks, aligning with this mechanism. Bioconcentration factor analysis revealed significant root accumulation of Fe in C. glauca under the CS + EuB treatment (BCF > 100; TF < 1), alongside moderate Cd uptake. This pattern is attributed to Fe sequestration within Frankia root nodules and concomitant inhibition of translocation to shoots. Furthermore, Eucalyptus biochar amendment reduced As accumulation while suppressing BCF values for Mn and Zn (BCF < 1; TF < 1), indicating selective immobilization of these metals. Notably, C. glauca exhibited a high capacity for hyperaccumulating Fe, Zn, As, Pb, and Cd in shoots across all treatments (Figure 5a,b,d–f) with concentrations substantially exceeding established hyperaccumulation thresholds (Zn > 3000 µg/g, As > 1000 µg/g, Pb > 1000 µg/g, and Cd > 100 µg/g [92,93]. The highest concentrations were observed for Fe, reaching 85,760 µg/g in CS + EuB treatment (Figure 5a). These findings underscore the significant promise of the C. glauca–Frankia symbiosis combined with Eucalyptus biochar as a targeted strategy for rehabilitating contaminated mine soils, and provide a foundation for optimizing this synergistic phytotechnology.

5. Conclusions

This study has demonstrated that, under contaminated soils, the application of Eucalyptus-derived biochar simultaneously alleviates physiological stress in C. glauca seedlings leading to notable improvements in biomass (+14%), photosynthesis efficiency (+37%), and WUE, while simultaneously suppressing oxidative damage. C. glauca showed strong hyperaccumulation of Fe, Zn, As, Pb, and Cd in all treatments, with a particularity for Fe under CS + EuB.
Eucalyptus biochar transforms C. glauca’s root-Frankia nodule system as a dynamic metal sink, characterized by Fe accumulation (BCF > 100) -driven by nitrogenase activity, significant Fe immobilization in soil (−71% bioavailability), and amplifying sequestration of Cd (2.0×), Mn (2.4×), and Pb (1.5×) within nodules. ACP analysis confirms that EuB decouples ion trace metal bioavailability from physiological toxicity, guiding plants toward an intermediate state of resilience.
This integrated response—combining trace metals immobilization (Fe, As and Pb), stress mitigation, and symbiotic bioaccumulation (Cd, Mn and Zn)—positions the EuB-C. glauca system as a promising, scalable model for sustainable rehabilitation of degraded lands. By transforming forestry waste into a valuable resource for ecological restoration, this approach aligns circular bioeconomy goals while addressing critical soil security challenges.
This study demonstrates the remediation potential of Eucalyptus-derived biochar under controlled conditions. Critical limitations regarding long-term stability, cost-effectiveness, and field scalability must be resolved prior to practical deployment. To address these constraints, a field trial was initiated in March 2025 at a contaminated mine site, directly evaluating long-term efficacy, operational feasibility, and real-world performance.

Author Contributions

Conceptualization, O.A. and Z.B.; methodology, O.A. and Z.B.; software, O.A.; validation, O.A., Z.B., K.T. and S.B.; formal analysis, O.A.; investigation, O.A., Z.B., K.T. and S.B.; resources, O.A., Z.B., K.T. and S.B.; data curation, O.A., Z.B., K.T. and S.B.; writing—original draft preparation, O.A. and Z.B.; writing—review and editing, O.A., Z.B., K.T. and S.B.; visualization, O.A., Z.B., K.T. and S.B.; supervision, Z.B., K.T. and S.B.; project administration, O.A., Z.B., K.T. and S.B.; funding acquisition, Z.B., K.T. and S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Higher Education and Scientific Research, Tunisia, University of Carthage (Faculty of Sciences of Bizerte and National Institute of Research in Rural Engineering, Water and Forests, INRGREF, Tunisia) and the University of Orleans (Laboratory P2E INRAE USC1328, Orleans, France).

Data Availability Statement

All data used in this study are available from the corresponding author upon request: sylvain.bourgerie@univ-orleans.fr.

Acknowledgments

The authors are thankful to Mejda Abassi from INRGREF, Tunisia, for technical assistance and advice. We thank also the technicians and nurserymen of INRGREF for their help during the collection of soil samples and implementation of the experimental protocol. We are thankful to Khalil Khamassi from the Field crop laboratory at the National Institute of Agricultural Research of Tunisia, for his precious help on the statistical analyses. We acknowledge Fethi Chattouti from the Tamra iron mine, for facilitating access to the study site and for his help in collecting the soil samples. We would also like to express our sincere gratitude to Yassine Chafik from Laboratory P2E INRAE USC1328, and Domenico Morabito from University of Orleans their assistance in the analysis of the samples using ICP-AES.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
NMSNon-mining soil
CSContaminated soil
CS + EuBContaminated soil with biochar
EuBEucalyptus biochar
TMTrace metals
TDMTotal dry mass
Fv/FmChlorophyll fluorescence
PnNet photosynthetic rate
TrTranspiration rate
gswStomatal conductance
CiIntercellular CO2 concentration
ELElectrolyte Leakage
chl aChlorophyll a
chl bChlorophyll b
TchlTotal chlorophyll
CarCarotenoids content
ProProline
ΨpdPredawn water potential
WUEWater use efficiency
RWCRelative water content
MDAMalondialdehyde
H2O2Hydrogen peroxide concentration
CATCatalase activity
GPOXGuaiacol peroxidase activity

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Figure 1. (a) Total dry mass (TDM); (b) transpiration rate (Tr); (c) net photosynthetic rate (Pn); (d) intercellular CO2 concentration (Ci); (e) stomatal conductance (gsw); (f) chlorophyll fluorescence (Fv/Fm) in C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Figure 1. (a) Total dry mass (TDM); (b) transpiration rate (Tr); (c) net photosynthetic rate (Pn); (d) intercellular CO2 concentration (Ci); (e) stomatal conductance (gsw); (f) chlorophyll fluorescence (Fv/Fm) in C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
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Figure 2. (a) Chlorophyll a (Chl a); (b) chlorophyll b (Chl b); (c) total chlorophyll (Tchl); (d) carotenoids (Car) content in C. glauca needles after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Figure 2. (a) Chlorophyll a (Chl a); (b) chlorophyll b (Chl b); (c) total chlorophyll (Tchl); (d) carotenoids (Car) content in C. glauca needles after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
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Figure 3. (a) Relative water content (RWC) (b) Predawn water potential (Ψpd); (c) Water use efficiency (WUE) of C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Figure 3. (a) Relative water content (RWC) (b) Predawn water potential (Ψpd); (c) Water use efficiency (WUE) of C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Land 14 01423 g003aLand 14 01423 g003b
Land 14 01423 g004aLand 14 01423 g004b
Figure 4. (a) Hydrogen peroxide (H2O2) concentration; (b) Catalase (CAT) activity; (c) Malondialdehyde (MDA) concentration; (d) guaiacol peroxidase (GPOX) activity; (e) electrolyte leakage (EL); (f) Proline concentration in C. glauca after six months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Figure 4. (a) Hydrogen peroxide (H2O2) concentration; (b) Catalase (CAT) activity; (c) Malondialdehyde (MDA) concentration; (d) guaiacol peroxidase (GPOX) activity; (e) electrolyte leakage (EL); (f) Proline concentration in C. glauca after six months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB). Each value represents the mean ± standard error (n = 5). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Land 14 01423 g004aLand 14 01423 g004b
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Figure 5. Variation in trace metals concentrations: (a) iron (Fe); (b) zinc (Zn); (c) manganese (Mn); (d) cadmium (Cd); (e) arsenic (As); (f) lead (Pb) in shoots and rootsof C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB): orange: shoots, green: roots. Each value represents the mean ± standard error (n = 3). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
Figure 5. Variation in trace metals concentrations: (a) iron (Fe); (b) zinc (Zn); (c) manganese (Mn); (d) cadmium (Cd); (e) arsenic (As); (f) lead (Pb) in shoots and rootsof C. glauca after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB): orange: shoots, green: roots. Each value represents the mean ± standard error (n = 3). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
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Figure 6. Frankia nodules in C. glauca roots after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB).
Figure 6. Frankia nodules in C. glauca roots after 6 months of growing in non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB).
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Figure 7. Principal component analysis (PCA): (a) variable factor map; (b) distribution of treatments in the PC1 × PC2 factorial plane: non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB), Iron (Fe), Zinc (Zn), Lead (Pb), Manganese (Mn), Cadmium (Cd), Arsenic (As), Total dry mass (TDM), chlorophyll fluorescence (Fv/Fm), net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (gsw), intercellular CO2 concentration (Ci), Electrolyte Leakage (EL), Chlorophyll a (chl a), chlorophyll b (chl b), total chlorophyll (Tchl), carotenoids (car) content, predawn water potential (Ψpd), Water use efficiency (WUE), Relative water content (RWC), proline (Pro), malondialdehyde (MDA), hydrogen peroxide (H2O2) concentration, catalase (CAT), guaiacol peroxidase (GPOX) activities, R: roots, and AP: shoots.
Figure 7. Principal component analysis (PCA): (a) variable factor map; (b) distribution of treatments in the PC1 × PC2 factorial plane: non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB), Iron (Fe), Zinc (Zn), Lead (Pb), Manganese (Mn), Cadmium (Cd), Arsenic (As), Total dry mass (TDM), chlorophyll fluorescence (Fv/Fm), net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (gsw), intercellular CO2 concentration (Ci), Electrolyte Leakage (EL), Chlorophyll a (chl a), chlorophyll b (chl b), total chlorophyll (Tchl), carotenoids (car) content, predawn water potential (Ψpd), Water use efficiency (WUE), Relative water content (RWC), proline (Pro), malondialdehyde (MDA), hydrogen peroxide (H2O2) concentration, catalase (CAT), guaiacol peroxidase (GPOX) activities, R: roots, and AP: shoots.
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Table 1. Physicochemical characterizations of soils.
Table 1. Physicochemical characterizations of soils.
ParameterNMSCS + EuBCS
pH (H2O)7.81 ± 0.01 b8.25 ± 0.005 a7.41 ± 0.012 c
EC (µS·cm−1)53.50 ± 0.389 c133.80 ± 0.060 a70.80 ± 0.120 b
P (%)30.96 ± 0.016 c36.51 ± 1.723 b40.33 ± 0.007 a
K (cm·h−1)0.84 ± 0.008 a0.34 ± 0.018 c0.39 ± 0.004 b
Ss (m2·g−1)1 ± 0.057 c20.36 ± 0.023 a18.13 ± 0.069 b
Particle size distribution (%)Sand22.40nd65.45
Silt21.06nd14.80
Clay52.67nd19.45
Pseudototal concentration (mg/kg; DW)Fe7605.14 ± 328.12 b164,242.66 ± 4776.18 a173,010.44 ± 1648.42 a
Zn48.75 ± 4.81 b4037.46 ± 47.97 a4028.82 ± 72.47 a
Mn221.39 ± 22.87 d17,848.09 ± 521.02 b14,742.55 ± 384.35 c
Pb55.30 ± 3.27 b4480.19 ± 307.08 a4402.05 ± 89.66 a
Cd5.04 ± 0.09 b8.84 ± 0.06 a8.41 ± 0.23 a
As60.86 ± 1.84 b476 ± 2.96 a447.50 ± 14.98 a
Non-mining soil (NMS), contaminated soil with biochar (CS + EuB) and contaminated soil (CS): Hydrogen potential of water (pH (H2O)), electrical conductivity (EC), Porosity (P), permeability (K), specific surface (Ss), organic matter (OM), Iron (Fe), Zinc (Zn), Manganese (Mn), Lead (Pb), Cadmium (Cd), and Arsenic (As), not determined (nd). Results are expressed as the mean value ± standard error (n = 3). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (least significant difference) tests.
Table 2. Translocation factor (TF), bioconcentration factor (BCF), final bioavailable concentration (FBC), and concentrations in Frankia nodules (CFN) of trace metals after 6 months exposure to non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB).
Table 2. Translocation factor (TF), bioconcentration factor (BCF), final bioavailable concentration (FBC), and concentrations in Frankia nodules (CFN) of trace metals after 6 months exposure to non-mining soil (NMS), contaminated soil (CS), and contaminated soil with biochar (CS + EuB).
TreatmentsFeZnMnPbCdAs
TF
NMS0.328 ± 0.073 a0.615 ± 0.010 a0.602 ± 0.140 a0.482 ± 0.007 a0.506 ± 0.017 a0.967 ± 0.046 a
CS0.025 ± 0.002 c0.137 ± 0.014 b0.083 ± 0.006 c0.034 ± 0.007 b0.593 ± 0.046 a0.195 ± 0.015 c
CS + EuB0.056 ± 0.021 b0.108 ± 0.023 b0.177 ± 0.033 b0.029 ± 0.001 c0.397 ± 0.009 b0.334 ± 0.044 b
BCF
NMS4.421 ± 0.552 c0.760 ± 0.036 b0.152 ± 0.038 c0.259 ± 0.010 b_1.805 ± 0.045 c
CS30.164 ± 2.147 b2.339 ± 0.151 a1.562 ± 0.130 a0.571 ± 0.046 a_5.267 ± 0.201 a
CS + EuB102.057 ± 0.574 a0.248 ± 0.001 c0.398 ± 0.013 b0.555 ± 0.018 a7.395 ± 0.150 a4.026 ± 0.119 b
FBC (mg·kg−1)
NMS24.560 ± 0.672 b10.618 ± 0.309 c67.564 ± 0.409 c13.677 ± 0.458 c˂QL36.046 ± 0.330 c
CS55.195 ± 0.918 a24.816 ± 0.136 b108.848 ± 0.040 b92.603 ± 0.585 b˂QL37.286 ± 0.032 b
CS + EuB15.844 ± 0.053 c249.922 ± 0.765 a245.230 ± 1.639 a161.233 ± 0.681 a0.078 ± 0.001 a37.899 ± 0.201 a
CFN (mg·g−1)
NMS2.759 ± 0.159 b0.058 ± 0.007 c0.046 ± 0.003 c0.027 ± 0.005 c-0.068 ± 0.008 b
CS116.638 ± 3.261 a1.657 ± 0.061 b4.898 ± 0.170 b1.834 ± 0.047 b0.001 ± 0.0001 b0.530 ± 0.010 a
CS + EuB119.498 ± 5.680 a2.447 ± 0.123 a12.164 ± 0.317 a2.798 ± 0.103 a0.002 ± 0.00009 a0.543 ± 0.057 a
QL: quantification limit. Results are expressed as the mean value (±SE, n = 3). Means followed by different letters indicate statistical differences at p ≤ 0.05, according to Fisher’s LSD (Least Significant Difference) tests.
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Ayadi, O.; Tlili, K.; Bourgerie, S.; Bejaoui, Z. Eucalyptus-Biochar Application for Mitigating the Combined Effects of Metal Toxicity and Osmotic-Induced Drought in Casuarina glauca Seedlings. Land 2025, 14, 1423. https://doi.org/10.3390/land14071423

AMA Style

Ayadi O, Tlili K, Bourgerie S, Bejaoui Z. Eucalyptus-Biochar Application for Mitigating the Combined Effects of Metal Toxicity and Osmotic-Induced Drought in Casuarina glauca Seedlings. Land. 2025; 14(7):1423. https://doi.org/10.3390/land14071423

Chicago/Turabian Style

Ayadi, Oumaima, Khawla Tlili, Sylvain Bourgerie, and Zoubeir Bejaoui. 2025. "Eucalyptus-Biochar Application for Mitigating the Combined Effects of Metal Toxicity and Osmotic-Induced Drought in Casuarina glauca Seedlings" Land 14, no. 7: 1423. https://doi.org/10.3390/land14071423

APA Style

Ayadi, O., Tlili, K., Bourgerie, S., & Bejaoui, Z. (2025). Eucalyptus-Biochar Application for Mitigating the Combined Effects of Metal Toxicity and Osmotic-Induced Drought in Casuarina glauca Seedlings. Land, 14(7), 1423. https://doi.org/10.3390/land14071423

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