The potential of four legume trees for mercury phytoremediation and the role of arbuscular mycorrhizal fungi

The potential of four legume trees for mercury phytoremediation and the role of arbuscular mycorrhizal fungi | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The potential of four legume trees for mercury phytoremediation and the role of arbuscular mycorrhizal fungi Nadine Sommer, Yaqin Guo, Frank Rasche, Michael Helmut Hagemann, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5336359/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Artisanal and small-scale gold mining (ASGM) in low- and middle-income countries often lack adequate safety measures, leading to significant health risks and environmental mercury pollution. Phytoremediation, a plant-based method that utilizes plants to accumulate soil-borne contaminants such as heavy metals, has been verified to restore land for ecosystem services or even future farming. Therefore, this study evaluates the potential of four legume species typically found in Ghana, the world's second largest gold exporter - Acacia mangium , Gliricidia sepium , Leucaena leucocephala and Senna siamea - for the removal of mercury from contaminated soils, as well as potential trade-offs related to eco-physiological processes. It was further investigated whether arbuscular mycorrhizal fungi (AMF) inoculation could enhance mercury removal capacity. Predominantly, A. mangium consistently exhibited the highest mercury uptake and did not show signs of mercury toxicity. G. sepium showed moderate mercury uptake but suffered considerable physiological damage. L. leucocephala was resistant to mercury but accumulated only small amounts. S. siamea exhibited moderate mercury accumulation without physiological impairment. AMF inoculation did not significantly increase mercury uptake but appeared to mitigate physiological stress under mercury exposure. These results indicate that reforestation of abandoned gold mines with A. mangium may be a suitable starting point for phytoremediation of mercury and inoculation with AMF can provide additional protection against mercury toxicity. Bioaccumulation gold mining heavy metal photosynthesis pollution control soil rehabilitation Figures Figure 1 Figure 2 Figure 3 Introduction Artisanal and small-scale gold mining (ASGM) is the largest anthropogenic source of mercury pollution, which is caused by the amalgamation process used in gold extraction (Donkor et al. 2009 ; Boateng 2014 ). It was estimated that these mining activities emitted 838 tons of mercury to air in 2015, accounting for 38% of global anthropogenic mercury emissions (UNEP 2019 ). Mercury amalgamation is the preferred method of almost all ASGM activities because it is simple and inexpensive (Donkor et al. 2009 , Boateng et al. 2014 ). In addition to mercury contamination, gold mining drastically degrades soil health by removing the topsoil, which is rich in nutrients and organic matter (Aryee et al. 2003 ). Furthermore, the removal of vegetation has the effect of disrupting the flow of ecosystem services and matter fluxes, as well as increasing the risk of soil erosion (Schueler et al. 2011 ). What remains are “lunar” landscapes with rubbish dumps, abandoned excavations and vast, barren stretches of land (Aryee et al. 2003 ). In Ghana, where gold mining is a predominant economic activity, the repercussions are particularly pronounced. In 2022, gold accounted for 48% of total exports in Ghana (OEC 2024 ). But mining, with its environmental impact, directly competes with agriculture, which was the largest employment sector for the Ghanaian people at 35.3% in 2022 (FAO 2024 ). The loss of farmland due to mining-related changes often forces farmers to move to new locations. As a result, farmers clear forests to create new farmland, indicating spillover effects of mining on neighboring areas (Schueler et al. 2011 ). Contaminated soils can be remediated using chemical, physical or biological techniques. Chemical and physical treatments may irreversibly alter soil properties, destroy biodiversity, and are costly (Padmavathiamma and Li 2007 ). Since contaminated areas are extensive and funding is limited, a cost-effective biological soil remediation technique is needed to remove mercury without compromising soil fertility (Mertens et al. 2004 ). Phytoremediation, a process that uses plants to remove, transfer, stabilize or degrade contaminants in soil, is environmentally friendly and cost-effective (Hughes et al. 1997 ; Padmavathiamma and Li 2007 ). Such phytoremediation techniques include phytoextraction, phytostabilization, phytovolatilization, phytofiltration, and phytodegradation (Alkorta et al. 2004 ). Phytoextraction (also known as phytoaccumulation) is the uptake of contaminants from soil by plant roots and their translocation and accumulation in the aboveground biomass (Yoon et al. 2006 ). Translocation of metal ions into shoots is a crucial biochemical process and desirable for effective phytoextraction, as harvesting root biomass is difficult. Phytovolatilization describes a process whereby heavy metals are absorbed and transpired by plants (Yoon et al. 2006 ). Suitable plants for the phytoextraction of mercury should be tolerant to high mercury concentrations and should accumulate high concentrations of mercury in their harvestable above-ground tissues. Moreover, they should have a rapid growth rate with particularly high production of above-ground biomass, develop a well-branched root system, be adapted to the prevailing environmental and climatic conditions and should be easy to cultivate and harvest (Garbisu and Alkorta 2001 ; Ali et al. 2013 ). Plants adapted to thrive in heavy metal-rich soils, known as ´metallophytes´, are categorized into metal excluders, metal indicators, and metal accumulators (Ali et al. 2013 ; Baker 1981 ). Metal excluders store heavy metals in their roots but restrict their transport to aerial parts, maintaining low metal concentrations in their shoots (Baker 1981 ). Metal indicators accumulate heavy metals in their aerial parts and generally reflect heavy metal concentrations in the substrate (Sheoran et al. 2011 ). Metal accumulators are preferred for phytoremediation since they gather high concentrations of metals in their above-ground biomass. This leads to efficient removal of contaminants from the environment (Baker 1981 ). The efficacy of metal accumulator plants can be assessed by the bioaccumulation factor (BAF) calculated as the heavy metal concentrations in plant shoots divided by the heavy metal concentrations in corresponding soils (Liu et al. 2020 ). Further, a high translocation factor (TF) calculated as heavy metal concentrations in plant shoots divided by the heavy metal concentrations in plant roots, is another key parameter (Xun et al. 2017 ). Ideal metal accumulators do not show high reduction in plant biomass when plants are grown in soils contaminated with heavy metals. This can be evaluated by the tolerance index (TI) calculated as the biomass of treated plants divided by the biomass of control plants (Diwan et al. 2010 ). Although over the past 20 years many scientists from different countries have investigated more than 200 plant species for their ability to accumulate and translocate mercury, no accumulator has been identified yet (Liu et al. 2020 ). Generally, mercury is toxic for plants, it inhibits photosynthesis, nutrient uptake, nutrient transportaffecting plant growth and biomass production (Lenti et al. 2002 ; Mei et al. 2021). To counteract those negative effects, plants may be inoculated with plant strengthening agents such as arbuscular mycorrhizal fungi AMF (Ferrol et al. 2016 ; Pirsarandib et al. 2022 ). Several studies have reported that certain AMF species, like Glomus mosseae , enhance the transport of heavy metals into the aboveground plant biomass (Weissenhorn et al. 1995 ; Singh et al. 2019). However, other studies have shown that some AMF species, like Funneliformis mosseae , inhibit the translocation of heavy metals to the aboveground biomass (Shabani et al. 2016 ; Chamba et al. 2017 ; Salazar et al. 2018 ). This was explained by the observation that some heavy metals are bound to fungal hyphae, arbuscules, vesicles or vacuoles, which inhibits the transport of heavy metals to the plant tissue (Garg and Singh 2018; Motaharpoor et al. 2019 ). The use of nitrogen-fixing legumes in the remediation of mercury-contaminated soils has the added benefit of increasing the biomass of subsequent plant species and thus the biomass production of the whole plant community (Frérot et al. 2006 ). The four legume tree species, Acacia mangium Willd, Gliricidia sepium Jacq, Senna siamea Lam (synonym Cassia siamea ) and Leucaena leucocephala Lam, were selected for their rapid growth and ability to establish and survive on degraded land in Ghana (Tetteh et al. 2015 ; Festin et al. 2019 ; Kusumaningtyas et al. 2021 ). In addition, A. mangium , G. sepium , and L. leucocephala are nitrogen-fixing tree species, making them ideal for reforestation of degraded sites (Macedo et al. 2008 ; Tetteh et al. 2015 ). While the majority of studies focus on the phytoextraction of heavy metals by grasses and herbs, this work is dedicated to tropical trees, which could potentially produce a higher biomass and consequently remove a larger amount of mercury (Liu et al. 2020 ). This study aims to investigate the phytoremediation potential of four tree species from Ghana in mercury-contaminated soils within gold mining areas. The optimal candidate should accumulate a high concentration of mercury in the above-ground biomass while remaining unharmed (Alkorta et al. 2004 ). Specifically, the objectives are: (1) to assess the capacity of these species to accumulate mercury in their biomass, particularly in above-ground tissues, under varying levels of soil contamination; (2) to evaluate the physiological responses of these species to mercury exposure, including growth rates and photosynthesis; and (3) to explore the influence of AMF on the effectiveness of mercury uptake and resistance to mercury toxicity. Through this research, we identify and characterize species optimal for reforestation and ecological restoration of areas degraded by mercury pollution. Materials and Methods Plant cultivation To prepare the seedlings, the dormancy of the seeds of A. mangium (Am), L. leucocephala (Ll) and S. siamea (Ss) was broken by scarification of the seed coat, acid, or hot water treatment. G. sepium (Gs) did not require a pretreatment to break seed dormancy. After pretreatment, seeds were soaked in water for 24 h. Seeds were placed in germination trays and exposed to a 12/12 h light/dark cycle at temperatures of 25/20°C in a climate chamber for 11 days. Subsequently, seedlings were transplanted into planting trays and placed in a greenhouse. A mixture of sand and vermiculite (5:3 by volume) was used as substrate. Prior to use, sand and vermiculite were autoclaved at 120°C for 15 minutes and then completely dried at 80°C. Greenhouse conditions were maintained at 26°C with an average relative humidity of 56%. To provide artificial illumination, high-pressure sodium lamps were utilized (SONT Agro 400W; Philips, Amsterdam, Netherlands) with a photoperiod of 12 hours (PAR, 210–270 µmol m − 2 s − 1 ). Arbuscular mycorrhizal fungi (AMF) The AMF strain Rhizophagus irregularis Błaszk., Wubet, Renker & Buscot, 2009 QS81 was supplied by INOQ GmbH (Schnega, Germany). The inoculum of R. irregularis was prepared from arbuscular mycorrhizal root fragments of Trifolium pratense grown in sand: vermiculite (35:65 by volume). The inoculum contained 100 million propagules per kg of powder (as vesicles and spores according to INOQ GmbH). Experimental design Two consecutive greenhouse experiments were carried out. The greenhouse conditions were as described above. In the first experiment, the effect of a lower (12.5 mg kg − 1 ) and a higher (25.0 mg kg − 1 ) mercury concentration in the substrate on the tree species was investigated. This experiment is referred to as the ‘mercury concentration experiment’. Based on the results of the ‘mercury concentration experiment’ experiment, the higher mercury concentration was chosen for the second experiment, in which AMF was grown with only one mercury concentration. This experiment is referred to as the "mercury-AMF experiment". Mercury-concentration experiment : Seedlings were transplanted into their final pots 11 weeks after germination pretreatment. To prevent mercury leaching from drainage water, 1 L plastic buckets without holes in the bottom were used. The substrate was a mixture of sand and vermiculite (19:1 by weight) with the addition of 1 g kg − 1 controlled-release fertilizer (Osmocote® Exact Mini 3-4M, NPK 15:3.9:9.1 + 1.2 Mg + trace elements, ICL, Netherlands). Prior to use, sand and vermiculite were autoclaved at 120°C for 15 minutes and then completely dried at 80°C. Of the species A. mangium , G. sepium , and S. siamea , 15 plants were included in the experiment. Due to poor germination rate 9 plants of the species L. leucocephala were included. Arrangement of pots was a randomized block design with five blocks. Each block had three plants of each species; L. leucocephala had only three blocks. Of these three plants, one served as a control, one was treated with 12.5 mg Hg kg − 1 (Hg 12.5) and one with 25.0 mg Hg kg − 1 (Hg 25.0). Mercury was applied in the form of a mercury chloride (HgCl 2 ) solution, with the solution volume adjusted to achieve a final mercury concentration in the substrate of either 12.5 mg kg − 1 or 25 mg kg − 1 14 weeks after germination. Eight weeks after mercury treatment, plants were harvested and separated into roots, stems, and leaves. Roots were shortly washed three times in deionized water. Plant samples were air dried at room temperature for dry weight determination. Mercury-AMF experiment : Six weeks after germination, plants were divided into control (x) and AMF-inoculated (AMF) groups and transplanted into 1.0 L pots with 750 g of substrate. The substrate was a mixture of sand and vermiculite (19:1 by weight) with the addition of 0.5 g kg − 1 controlled-release fertilizer (Osmocote® Exact Mini 3-4M, NPK 15:3.9:9.1 + 1.2 Mg + trace elements, ICL, Netherlands). For the AMF-treated plants, the substrate was mixed with 0.075 g AMF inoculum (a ratio of 0.1 g kg − 1 ). A total of 64 plants were arranged in a complete randomized block design with four blocks. A three factorial design was used, with the factors of mercury concentrations (0 and 25 mg Hg kg − 1 ) and AMF (presence or absence) studied across the four tree species. Twelve weeks after germination 5 mg Hg kg − 1 (3.75 mg pot − 1 ) was applied as a mercuric chloride (HgCl 2 ) solution every week for a period of 5 weeks to reach a final concentration of 25 mg Hg kg − 1 . Six weeks after the first mercury application, the plants were harvested as mentioned in the “mercury-concentration experiment” above. A subsample of the roots from the AMF-treated plants was stored at -80°C to determine AMF root colonization. For this, roots were cut into 1 cm lengths and cleared with 10% NaOH in a 70°C water bath for 45 min and then soaked in 1% HCl for 1 min at room temperature. Roots were stained with 2% Parker Quink blue ink (Yon et al. 2015 ) in a 70°C water bath for 30 min. The roots were rinsed with tap water and then stored in a lactoglycerol solution (lactic acid, glycerol, H 2 O in a ratio of 1:1:1). Thirty fragments from each plant were randomly selected, placed on a microscope slide, and examined under a light microscope for mycorrhizal colonization (Trouvelot et al. 1986 ). Mercury concentration Plant samples were ground and homogenized using a mill with zirconium oxide grinding balls (MM40, Retsch GmbH, Haan, Germany). Subsequently, 0.2 g of the homogenized material were moistened with 1 mL of deionized H 2 O and digested in 2.5 mL of 69% HNO 3 in a microwave-heated UltraCLAVE III digestion unit (MLS-MWS GmbH, Leutkirch, Germany). One mL of the microwave pressure digestion solution was added to 1 mL of dilution solution (2% cysteine, 7% isopropanol made up to 1000 mL with 1% HNO 3 ) and 0.1 mL of 50 ppb rhodium standard solution and then made up to 10 mL with ddH 2 O. The mercury concentration was analyzed using a NexION 300 × inductively coupled plasma mass spectrometer (PerkinElmer LAS GmbH, Rodgau, Germany). Gas exchange and biomass determination All plants were analyzed weekly for their stem height using a scale and defined as the height from the substrate surface to the top of the main shoot. The gas exchange (CO 2 and H 2 O) of the youngest fully developed leaf was determined weekly (GFS-3000, Heinz Walz GmbH; 3010-S standard measuring head with 3040-L LED light source, head area of 2.5 cm 2 ). The area of leaves that did not fill the measuring head was determined using ImageJ. The Tolerance Index (TI) was calculated in this work using the following equations (Diwan, Ahmad, and Iqbal 2010 ). TI values above 1 indicate a net increase in biomass and imply that the plants have developed heavy metal tolerance, while TI values below 1 indicate a net decrease in biomass and a stressed state of the plants. $$\:TI=\:\frac{Biomass\:of\:treated\:plants\:\left(g\:{plant}^{-1}\right)}{Biomass\:of\:control\:plants\:\left(g\:{plant}^{-1}\right)}$$ The Bioaccumulation Factor (BAF) was calculated using the following equation (Liu et al., 2020 ). The initial Hg concentration in the substrate (12.5 or 25.0 mg Hg kg − 1 ) was used to calculate the BAF. $$\:BAF=\:\frac{Hg\:concentration\:in\:plant\:shoot}{\:Hg\:concentration\:in\:substrate}$$ The Translocation Factor (TF), i.e . the ability of a plant to translocate metal ions from the roots to the shoots, was calculated as follows: $$\:TF=\frac{Hg\:concentration\:in\:plant\:shoot}{Hg\:concentration\:in\:plant\:root}$$ Statistical analysis Mercury concentration, assimilation rate, stem height, biomass, TI, BAF, TF, and AMF were analyzed using ANOVA with SAS software 9.4 (SAS Institute, Cary NC, USA) with proc mixed. Least squares means were calculated for comparison between control and treated plants. The significance level was set at p ≤ 0.05. Model assumptions such as normality, homoscedasticity, and independence were verified, when necessary log-transformation was applied, and post hoc comparisons were conducted using the least significant difference (LSD) test to ensure accurate interpretation of the differences. Results Mercury accumulation Our analysis of mercury accumulation across different plant components (roots, stems and leaves), shows that the highest concentrations consistently occurred in the root system, irrespective of the species studied (Fig. 1 ). Mercury accumulation in the trees followed the treatment with lowest concentrations at the 12.5 Hg treatment and highest at the 25 Hg treatment (Fig. 1 b). The 12.5 Hg treatment did not lead to high Hg accumulation in the leaves, stems, or roots, except for the stems of A. mangium , which showed high Hg accumulation (Fig. 1 b). The 25 Hg treatment showed accumulation in all tree species. In the leaves, highest Hg concentration was detected in G. sepium with 95.8 mg kg − 1 and in A. mangium with 77.0 mg Hg kg − 1 . Stems of A. mangium (445 mg Hg kg − 1 ) and G. sepium (360.3 mg Hg kg − 1 ) accumulated highest mercury concentrations. L. leucocephala accumulated the lowest mercury concentration in both leaves and stem. Mercury accumulation in the above-ground biomass has a clear pattern: Am > Gs > Ss > Ll (Fig. 1 b). Consideration of the increase factor of mercury accumulation shows that a doubling of mercury treatment leads to a multiple increase in mercury accumulation (Table 1 ). This phenomenon is particularly evident in the stems, with A. mangium exhibiting a 49-fold higher Hg accumulation in Hg 25.0 than in Hg 12.5. Table 1 Increase factor of mercury accumulation when comparing Hg 25.0 and Hg 12.5 in leaves, stems, and roots of A. mangium , G. sepium , L. leucocephala , and S. siamea . A. mangium G. sepium L. leucocephala S. siamea Leaves 4 7 2 3 Stem 49 33 5 20 Root 2 2 2 1 Plant physiological responses to mercury accumulation Table 2 displays the total dry weight, mean assimilation rate, and stem growth for each tree species. G. sepium showed significant and particularly pronounced reduction in assimilation rate, stem height, and total dry weight with increasing mercury treatment. A. mangium showed a significant decrease in assimilation rate and stem height, but total dry weight remained unchanged. L. leucocephala and S. siamea appeared resistant to mercury effects on assimilation, stem height, and dry weight, with stable assimilation rates higher mercury concentrations. Table 2 Total dry weight, mean assimilation rate per plant species and stem growth over the mercury treatment period (8 w). Significant differences of treatment effects indicated by different letters (LSD, p ≤ 0.05 ). Statistical analysis was performed individually for each tree species. Species Mercury-Treatment (mg Hg kg − 1 ) Mean Assimilation (µmol m 2 s 1 ) Stem Growth (cm) Total Dry Weight (g per plant) 0.0 11.1 (± 0.7) a 11.9 (± 1.7) a 3.31 (± 0.5) a A. mangium 12.5 8.9 (± 0.6) ab 11.6 (± 1.8) a 3.91 (± 0.3) a 25.0 7.9 (± 1.9) b 6.6 (± 2.1) b 3.19 (± 0.9) a 0.0 5.1 (± 0.1) a 9.3 (± 0.5) a 7.88 (± 0.2) a G. sepium 12.5 3.6 (± 0.8) ab 5.4 (± 1.4) ab 5.62 (± 0.9) b 25.0 1.5 (± 0.8) b 2.4 (± 1.7) b 4.54 (± 0.9) b 0.0 5.5 (± 0.5) a 26.4 (± 2.5) a 11.35 (± 0.2) a L. leucocephala 12.5 5.5 (± 1.0) a 24.4 (± 3.3) a 10.01 (± 0.6) a 25.0 6.4 (± 0.3) a 21.7 (± 3.4) a 9.46 (± 1.2) a 0.0 6.8 (± 1.0) a 6.6 (± 0.6) a 6.23 (± 0.6) a S. siamea 12.5 7.0 (± 0.6) a 5.9 (± 0.6) a 6.80 (± 0.2) a 25.0 7.6 (± 1.0) a 4.9 (± 0.4) a 6.77 (± 1.5) a Phytoremediation assessment indicators The tolerance index (TI), calculated based on dry weight, was determined for each plant species across different treatments (Table 3 ). A. mangium exhibited a trend in dry weight accumulation at Hg 12.5 and a slight decline at Hg 25 but without statistical significance. The resulting tolerance index exceeding 1 indicated resilience to the medium mercury treatment, while a value slightly below 1 suggested a stress response at high mercury treatment. Furthermore, the ‘TI mean’ for A. mangium was 1.07 and with this the highest value among the four tree species indicating highest mercury tolerance. The dry mass of S. siamea was relatively unaffected at Hg 25 or increased at Hg 12.5 compared to control (Table 2 ). Therefore, the resulting TI values were in the range of 1 for both mercury treatments suggesting no harming effect of mercury on S. siamea . G. sepium exhibited the most adverse reaction to the presence of mercury, as indicated by reduced total dry weight (Table 2 ) and high TF of 35.4 (Table 3 ). The ‘TI mean’ of L. leucocephala was 0.86, which indicated a medium resistance range compared to the other plant species (Table 3 ). None of the tree species had a mercury translocation factor (TF) greater than 1.0 (Table 3 ). For A. mangium and S. siamea , the differences in TF between treatments were highly significant (p < 0.001, data not shown) with highest TF values compared to the other tree species. The bioaccumulation factor (BAF) is a metric used to calculate the accumulation of mercury in above-ground biomass (shoot) relative to the concentration of mercury in the substrate (Table 3 ). Except for L. leucocephala, the BAF increased with increasing mercury treatment (Table 3 ). Notably, the highest values were observed for A. mangium and G. sepium (Table 3 ). Table 3 Translocation factor (TF), bioaccumulation factor (BAF) and tolerance index (TI) per plant species and mercury treatment. BAF mean and TI mean represent the mean value per species averaged over the levels of the mercury treatment. Significant differences of mercury treatment effects are indicated by different letters (LSD, p ≤ 0.05). Species Mercury-treatment (mg kg -1 ) Translocation factor (TF) Bioaccumulation factor (BAF) BAF mean Tolerance index (TI) TI mean 0.0 - - A. mangium 12.5 0.014 a 1.32 b 3.45 a 1.18 a 1.07 a 25.0 0.106 b 5.57 a 0.96 ac 0.0 - - G. sepium 12.5 0.043 a 0.97 b 4.12 a 0.71 bc 0.65 b 25.0 0.354 b 7.27 a 0.58 c 0.0 - - L. leucocephala 12.5 0.024 a 0.47 a 0.54 b 0.88 ac 0.86 ab 25.0 0.028 a 0.61 a 0.83 ac 0.0 - - S. siamea 12.5 0.027 a 0.97 a 3.39 a 1.09 ab 1.04 a 25.0 0.087 b 2.24 a 1.09 ab Mycorrhizal colonization A. mangium and G. sepium had a successful inoculation with a high frequency of mycorrhizae in the root system without significant differences between control and mercury treatment (Fig. 2 ). However, L. leucocephala showed a very low mycorrhizal colonization rate in the control while the mercury treated plants showed high inoculation capacity. The roots of S. siamea were too thick and heavily pigmented to be analyzed for mycorrhizal colonization under the light microscope according to the method of Trouvelot et al. ( 1986 ). Mercury accumulation depending on arbuscular mycorrhizal fungi The highest mercury concentrations in aboveground biomass were found in leaves with 202 mg kg − 1 and in stem with 203 mg kg − 1 of AMF-treated A. mangium (Fig. 2 ). However, inoculation with AMF showed no significant effect on mercury accumulation in any of the tree species. Mercury accumulation in G. sepium and L. leucocephala was low in all plant tissues and seemed to be further reduced by inoculation with AMF, although without significant differences. The trends of mercury accumulation in the ‘mercury-concentration experiment’ were confirmed in the ‘mercury-AMF experiment’. The highest mercury concentration was always detected in A. mangium , the lowest in L. leucocephala. Physiological responses to mercury and arbuscular mycorrhizal fungi The Mercury-AMF experiment aimed to assess different plant physiological parameters such as photosynthesis as indicated by the assimilation rate at week 6 (Table 4 ). The assimilation of A. mangium was significantly reduced by mercury and was increased by inoculation with AMF. The assimilation of G. sepium was also significantly reduced by mercury. However, G. sepium plants inoculated with arbuscular mycorrhizal fungi (AMF) exhibited a reduction in assimilation due to mercury treatment, though this decrease was not statistically significant. (Table 4 ). L. leucocephala had no significant change in assimilation by either mercury or AMF. In contrast, S. siamea had a significant reduction in assimilation in response to mercury, this was mitigated by AMF. However, neither mercury nor AMF showed a significant effect on the total dry weight of A. mangium (Table 4 ). The mercury treatment showed a significant negative effect on the total dry weight (DW) of G. sepium (Table 4 ), while the inoculation with AMF did not significantly change this reduction of dry weight. The total DW of L. leucocephala and S. siamea was not significantly affected by either mercury or AMF (Table 4 ). Regarding the tolerance towards mercury overall, there are no significant differences in TI-values when comparing all treatments and species (Table 4 ). The TI-values for A. mangium were below 1, irrespective of the AMF-inoculation. Species and treatments with TI above 1 were G. sepium inoculated with AMF, and S. siamea without AMF. The mercury accumulated calculated as BAF showed significant differences between the tree species (Table 4 ), but the AMF-inoculation did not show significant effects. The highest BAF was found in A. mangium , the lowest in L. leucocephala . Table 4 Effect of arbuscular mycorrhizal fungi inoculation (AMF = AMF-inoculated; x = control) on mercury tolerance. Assimilation and total plant dry weight was evaluated 6 w after mercury application; bioaccumulation factor (BAF) and tolerance index (TI). Differences of significance are denoted by varying letters (LSD, p ≤ 0.05 ). Statistical analysis was performed separately for each plant species for assimilation and total dry weight. TI and BAF compares all treatments with each other. Species Microorganism Mercury-Treatment (mg Hg kg -1 ) Assimilation (µmol m 2 s 1 ) Total dry weight (g) Tolerance Index (TI) Bioaccumulation factor (BAF) A. mangium x 0.0 15.1 (± 2.8) a 1.7 a 0.85 a x 25.0 8.4 (± 2.5) b 1.4 a 6.0 (± 1.0) a AMF 0.0 18.5 (± 2.8) a 1.4 a 0.68 a AMF 25.0 11.6 (± 3.1) ab 1.0 a 8.4 (± 1.7) a G. sepium x 0.0 4.7 (± 0.7) a 7.7 a 0.72 a x 25.0 1.4 (± 0.7) b 5.6 b 0.8 (± 0.1) c AMF 0.0 4.1 (± 0.8) ab 6.1 ab 1.15 a AMF 25.0 2.8 (± 0.7) ab 7.0 ab 0.6 (± 0.1) cd L. leucocephala x 0.0 8.2 (± 1.2) a 6.0 a 0.84 a x 25.0 9.5 (± 1.3) a 5.0 a 0.6 (± 0.2) cd AMF 0.0 9.5 (± 1.6) a 5.2 a 1.00 a AMF 25.0 7.3 (± 1.3) a 5.2 a 0.5 (± 0.1) d S. siamea x 0.0 6.4 (± 0.6) a 2.3 a 1.02 a x 25.0 3.0 (± 0.5) b 2.3 a 2.7 (± 0.8) b AMF 0.0 8.7 (± 1.7) a 2.8 a 0.91 a AMF 25.0 5.4 (± 1.3) ab 2.6 a 2.5 (± 1.2) bc Discussion Given the universality of the amalgamation process, similar levels of pollution, as reported by Tomiyasu et al. ( 2023 ) may be anticipated in abandoned mining sites in Ghana and other areas exposed to gold mining including amalgamation with mercury. Accordingly, our study investigated the potential of four local leguminous tree species to remediate mercury-contaminated soils. Generally, mercury accumulation in plant tissues has a complex pattern, with roots consistently showing the highest concentrations (Fig. 1 ), as shown in other studies (Liu et al. 2017; Moreno et al. 2005 ). However, the accumulation of mercury in aboveground biomass is particularly important for phytoremediation (Ali et al. 2013 ). Our data revealed that specifically under high mercury treatment, A. mangium accumulated highest concentrations in above-ground biomass, closely followed by G. sepium (Fig. 1 ). Therefore, these two species are considered as mercury accumulators. L. leucocephala shows comparatively low values in the aboveground biomass (Fig. 1 ) and may be classified as an excluder (Baker 1981 ). The increase in mercury accumulation in the aboveground biomass, especially at the high mercury concentration in soil is of particular interest. Although the mercury concentration in the substrate increased 2-fold (from Hg 12.5 to Hg 25), the concentration in the biomass of all four tree species increased up to 49-fold in stems of A. mangium and 7-fold in the leaves of G. sepium (Table 1 ). In the roots, however, 2-fold soil mercury increase led to a 2-fold increase in mercury accumulation - irrespective of the tree species (Table 1 ). This suggests a threshold above which mercury accumulation becomes more effective but also more harmful for above-ground plant tissue. According to Baker ( 1981 ) A. mangium and G. sepium showed the characteristics of metal accumulators. Physiological responses and suitability for phytoremediation The ideal candidate suitable for phytoextraction should not only accumulate high concentrations of mercury in the aboveground biomass, but also remain unharmed (Alkorta et al. 2004 ). The high mercury-accumulating species A. mangium showed a reduction in assimilation and stem height but no reduction in total dry weight (Table 1 ). It could be suggested that mercury did not harm the plant but led to a more stunted habitus. On the contrary, G. sepium was severely affected; not only did assimilation and stem height decrease with increasing mercury treatment (Table 1 ), moreover, four out of 10 mercury-treated plants did not survive during the experiment (data not shown). Therefore, G. sepium is regarded as a susceptible tree species that is unsuitable for the phytoremediation of mercury-contaminated soils. The physiology of L. leucocephala was not affected by mercury; however, it did not absorb a significant amount of mercury (Table 1 , Fig. 1 ). Thus, even though the plant can likely tolerate mercury contaminated soil, it would not qualify as an effective accumulator. Metal remediation plant indicators have been developed to assist the comparability of different plant species for their phytoremediation potential. It is the main ambition to locate so-called hyperaccumulators, plants that accumulate heavy metals in their high yielding above-ground tissues to levels far above those found in the soil (Memon and Schröder, 2009 ). Characteristics of hyperaccumulators are high concentration thresholds for heavy metals in plant shoots ( e.g. 10,000 mg kg − 1 for zinc (Zn), 1000 mg kg − 1 for nickel (Ni), and 100 mg kg − 1 for cadmium (Cd)) (Baker 1981 ; Baker and Brooks 1989 ). No threshold levels have yet been set for mercury. Further, the bioaccumulation calculated as bioaccumulation factor (BAF) as well as the translocation factor (TF) should be greater than 1 (Liu et al. 2020 ; Xun et al. 2017 ). Finally, the plants should be extremely tolerant to heavy metals, i.e . they should not show significant reduction in biomass as determined by the tolerance with a TI-value of > 1 (Diwan et al. 2010 ). Despite numerous studies conducted from various countries on over 200 plant species in the last two decades in search of a hyperaccumulator of mercury, none has been successfully identified so far (Liu et al. 2020 ). Only Erato polymnioides and a few other species were labeled as potential mercury hyperaccumulators (Chamba et al. 2017 ). However, these species are native to the rainforests of Bolivia, Colombia, Costa Rica, Ecuador, Panamá, and Peru—not to West Africa. Introducing non-native plant species can destabilize local ecosystems, as these species often lack natural predators or competitors, allowing them to spread rapidly and become invasive (Zizka et al. 2015 ). According to the definition, none of the four plant species meets all criteria. G. sepium accumulated high levels of mercury, resulting in comparatively high TF values, but suffered considerable damage and plant death due to its sensitivity to mercury, as evident from its low TI values and the reduction in assimilation (Table 2 , 3 ). L. leucocephala had the lowest mercury accumulation in the aboveground biomass (Fig. 1 ) and showed the lowest mercury translocation rates of all species (Table 3 ). However, L. leucocephala did not respond to the mercury treatment in any way. Neither the stem growth, dry weight, nor the assimilation was affected (Table 2 , 3 , 4 ), suggesting that it can be classified as an excluder plant. S. siamea fulfilled the majority of the set requirements and demonstrated a TI above 1 and a BAF above 2 in both experiments. However, in comparison to A. mangium , S. siamea exhibited a reduced accumulation of mercury in both experiments, as well as a lower BAF (Table 3 , 4 , Fig. 1 , 3 ). With regard to the accumulation of mercury, A. mangium is the species with the greatest potential for mercury phytoremediation, as it exhibits the highest concentration of mercury in plant tissues and the highest BAF in both experiments (Table 3 , 4 , Fig. 1 . 3). It proved to be resistant to mercury exposure, with a TI greater than 1 in the mercury-concentration-Experiment (Diwan, Ahmad, and Iqbal 2010 ). Further, its BAF in the 25 Hg treatment was higher than in the 12.5 Hg treatment, corresponding to its increased mercury accumulation (Fig. 1 , Table 3 ). Most importantly, A. mangium accumulated by far the highest concentration of mercury in above-ground tissue, even though not being a hyperaccumulator. A. mangium could therefore be a suitable candidate for the phytoremediation of mercury-contaminated soils in Ghana. The findings of our study align with those of previous research, which have shown that A. mangium has the capacity to remediate soils contaminated with heavy metals (Sampanpanish 2018 ; Rosli et al. 2021 ; Couic et al. 2021 ). The concept of diverse forests for phytoremediation is well acknowledged and a fast-growing topic in land restoration research, as reviewed by Gómez et al. ( 2019 ). The proposal here is not to exploit the forests directly for short-term gains, but to carefully manage and monitor contamination levels over several decades so that the acacia forest and other organisms can establish a stable ecosystem that facilitates the natural decontamination of anthropogenic pollution. Therefore, A. mangium could be accompanied by S. siamea , which has also achieved promising results, and L. leucocephala , which is not a mercury accumulator but is a robust and fast-growing mercury excluder developing well in mercury-contaminated soils. L. leucocephala is a commonly utilized tree in the maintenance of agroforestry systems (Shelton 1998 ). As such, L. leucocephala could potentially contribute to the biodiversity of a remediating forest. Furthermore, previous studies have shown that S. siamea , in combination with other plants, provides significant benefits for soil remediation by accumulating heavy metals, improving soil structure and promoting fertility, thus supporting sustainable plant growth in heavy metal-contaminated soils (Vanlauwe et al. 2005 ; Kusumaningtyas et al. 2021 ). Physiological responses to mercury and arbuscular mycorrhizal fungi Research indicated that heavy metals typically decrease the mycorrhizal colonization; however, in our case (Fig. 2 ) the opposite effect was observed, a finding in line with earlier work (Schneider et al. 2017 ; Garcia et al. 2020 ). In our study, it is not possible to predict a general trend as to whether mercury accumulation is generally increased or decreased by inoculation with AMF, as no significant difference was found (Fig. 3 ). Previous findings indicate that inoculation with AMF can lead to both a decrease or an increase in the uptake of mercury by plants (Debeljak et al. 2018 ; Li et al. 2023 ). Although inoculation with AMF was successful, it did not result in a significant difference in assimilation or total dry weight as in other studies (Frosi et al. 2016 ; Estrada-Luna and Davies 2003 ). Nevertheless, it seems that AMF exerts a ‘buffer effect’ on the sensitivity of plants to mercury, as the reduction in assimilation in less pronounced in the mercury accumulating species A. mangium , G. sepium and S. siamea (Table 4 ). Comparing the two experiments, A. mangium was able to achieve an even higher mercury accumulation in the mercury-AMF experiment than in the mercury-concentration experiment (Table 3 , 4 ). Thus, the inoculation with AMF seemed to increase the BAF of A. mangium , but the TI of A. mangium in the mercury-AMF experiment was below 1 both with and without AMF (Table 4 ). In contrast, the BAF of G. sepium in the mercury-AMF experiment was much lower than in the mercury-concentration experiment (Table 2 , 4 ). This was probably due to the reduced mercury accumulation, whereby the TI of G. sepium in mercury-AMF was higher than 1. In A. mangium and G. sepium , the age of the plant and the duration of mercury exposure appeared to influence the process of mercury accumulation. The influence of the duration of mercury exposure on accumulation has already been observed in other research projects (Xun et al. 2017 ; Millhollen et al. 2006 ). The mechanisms underlying the ageing effect of plants on mercury accumulation is a subject for future research. Conclusion Although it cannot be classified as a hyperaccumulator this study identified A. mangium as the most promising species for phytoremediation of mercury-contaminated soils in former gold mining areas. It accumulates the highest concentrations of mercury and shows only minor signs of mercury toxicity making it well suitable for planting on areas with former gold mining. Compared to A. mangium S. siamea exhibited lower (moderate) mercury accumulation without physiological impairment. L. leucocephala did not accumulate mercury, but also demonstrated no adverse physiological effects and could play an important role as a mercury excluder, thereby promoting biodiversity and ecosystem stability. G. sepium showed moderate mercury uptake but suffered considerable physiological damage. Although inoculation with AMF did not significantly increase mercury uptake, it appeared to mitigate physiological stress, supporting plant health rather than directly enhancing mercury removal. These findings support the strategic use of diverse plant species in ecological restoration to optimize mercury removal and promote a stable ecosystem. Further research is needed to identify other suitable plant species that meet all the criteria for mercury hyperaccumulation and can be effectively used in phytoremediation strategies. Declarations Corresponding author Correspondence to Nadine Sommer: [email protected] Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics Approval Not applicable. Consent to Participate Not applicable. Consent to Publish Not applicable. Funding This work was funded by the Federal Ministry of Education and Research, Germany, under Support Code 01LZ1709A-B. Author Contributions All authors contributed to the study conception and design. Material preparation, experiments and data collection were performed by Nadine Sommer and Yaqin Guo. Analysis was performed by Nadine Sommer. The first draft of the manuscript was written by Nadine Sommer, Michael Helmut Hagemann and Christian Zörb. Frank Rasche and Yaqin Guo reviewed and edited the manuscript. All authors commented on previous versions of the manuscript and approved the final manuscript. Acknowledgements The authors are grateful to INOQ GmbH for providing us AMF inoculum ( Rhizophagus irregularis ). We thank Florian Fleckenstein and Ghofrane May for technical help in the laboratory and greenhouse. We further thank Prof. Dr. Hans-Peter Piepho and Dr. Jens Hartung for their help with statistical analysis. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Ali H, Khan E, Sajad MA (2013) Phytoremediation of heavy metals-concepts and applications. Chemosphere 91(7):869–881. https://doi.org/10.1016/j.chemosphere.2013.01.075 Alkorta I, Hernandez-Allica J, Becerril JM, Amezaga I, Albizu I, Garbisu C (2004) Recent findings on the phytoremediation of soils contaminated with environmentally toxic heavy metals and metalloids such as zinc, cadmium, lead, and arsenic. 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Candollea 70:9–20. https://doi.org/10.15553/c2015v701a Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major Revision 02 Aug, 2025 Reviewers agreed at journal 15 Jan, 2025 Reviewers invited by journal 23 Nov, 2024 Editor invited by journal 05 Nov, 2024 Editor assigned by journal 03 Nov, 2024 First submitted to journal 02 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5336359","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381799542,"identity":"407f244c-af53-40e2-8eb6-82e937438926","order_by":0,"name":"Nadine Sommer","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0005-7158-5012","institution":"University of Hohenheim: Universitat Hohenheim","correspondingAuthor":true,"prefix":"","firstName":"Nadine","middleName":"","lastName":"Sommer","suffix":""},{"id":381799543,"identity":"cf1aa23b-98c1-444e-ad5d-cc94e8c3dd42","order_by":1,"name":"Yaqin Guo","email":"","orcid":"","institution":"University of Hohenheim: Universitat Hohenheim","correspondingAuthor":false,"prefix":"","firstName":"Yaqin","middleName":"","lastName":"Guo","suffix":""},{"id":381799544,"identity":"a1d600f9-aa7d-45fe-878d-bcb19aa3d6fd","order_by":2,"name":"Frank Rasche","email":"","orcid":"","institution":"University of Hohenheim: Universitat Hohenheim","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Rasche","suffix":""},{"id":381799545,"identity":"9843f370-ec55-499f-8f13-c1c3fb215412","order_by":3,"name":"Michael Helmut Hagemann","email":"","orcid":"","institution":"University of Hohenheim: Universitat Hohenheim","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Helmut","lastName":"Hagemann","suffix":""},{"id":381799546,"identity":"3ac1b08a-765b-49ca-a61e-8a79f02f7ae4","order_by":4,"name":"Christian Zörb","email":"","orcid":"","institution":"University of Hohenheim: Universitat Hohenheim","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Zörb","suffix":""}],"badges":[],"createdAt":"2024-10-26 08:21:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5336359/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5336359/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73100107,"identity":"c0caa786-0fde-47f8-a03e-539007f886ea","added_by":"auto","created_at":"2025-01-06 17:34:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1103396,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Scheme of total mercury accumulation in leaves, stem, and root. (b) Data on the mercury accumulation per tissue for \u003cem\u003eA. mangium\u003c/em\u003e(Am, blue), \u003cem\u003eG. sepium\u003c/em\u003e (Gs, yellow), \u003cem\u003eL. leucocephala\u003c/em\u003e (Ll, purple) and \u003cem\u003eS. siamea\u003c/em\u003e (Ss, green). Significant differences in the effects of mercury\u003cem\u003e \u003c/em\u003etreatment are indicated by different letters (LSD, \u003cem\u003ep ≤ 0.05\u003c/em\u003e). Statistical analysis was performed individually for each box plot diagram. The box plots represent untransformed data, while the statistical analyses were performed on log-transformed data.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5336359/v1/2d1dcd04d191c0981d9455ec.png"},{"id":73100109,"identity":"ef602bf3-f899-4f35-853f-7813d36c0d79","added_by":"auto","created_at":"2025-01-06 17:34:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2809548,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of mycorrhizal colonization in the root system of plants treated with arbuscular mycorrhizal fungi (Am = \u003cem\u003eAcacia mangium\u003c/em\u003e, Gs = \u003cem\u003eGliricidia sepium\u003c/em\u003e, Ll = \u003cem\u003eLeucaena leucocephala\u003c/em\u003e, Ss = \u003cem\u003eSenna siamea\u003c/em\u003e) based on Trouvelot's (1986) method in relation to mercury exposure (Hg 0, control, Hg 25, 25 mg Hg kg\u003csup\u003e-1\u003c/sup\u003e). The roots of \u003cem\u003eS. siamea \u003c/em\u003ecould not be analyzed because they were too thick and heavily pigmented for analysis under the light microscope. Asterisks indicate a significant difference between Hg 0 and Hg 25 treatments (LSD,*** \u003cem\u003ep ≤ 0.001\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5336359/v1/731c274fa411c4b7147c757e.png"},{"id":73100951,"identity":"bc157ef4-bb3f-4511-bc85-98d7d424da17","added_by":"auto","created_at":"2025-01-06 17:42:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1182811,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Scheme of mercury accumulation in leaves, stem, and root depending on the presence or absence of arbuscular mycorrhizal fungi (AMF). (b) Mercury accumulation concentrations in the leaves, stems, and roots of plants (Am, \u003cem\u003eAcacia mangium\u003c/em\u003e; Gs, \u003cem\u003eGliricidia sepium\u003c/em\u003e; Ll, \u003cem\u003eLeucaena leucocephala\u003c/em\u003e; Ss, \u003cem\u003eSenna siamea\u003c/em\u003e) after inoculation with arbuscular mycorrhizal fungi (AMF, AMF-inoculated; x, control). The data presented pertain solely to plants subjected to mercury treatment (25 mg Hg kg\u003csup\u003e-1\u003c/sup\u003e). Variations of significance are denoted by distinct letters (LSD, \u003cem\u003ep ≤ 0.05\u003c/em\u003e). Box plots, non-transformed values; statistical assessments with log-transformation.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5336359/v1/b491bd0f820603d02b672af9.png"},{"id":73101895,"identity":"147191a3-5592-4c7e-81aa-9e111cfc847a","added_by":"auto","created_at":"2025-01-06 17:58:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4077647,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5336359/v1/9a4350d3-2a54-48fa-8b30-9f958c509a7b.pdf"}],"financialInterests":"","formattedTitle":"The potential of four legume trees for mercury phytoremediation and the role of arbuscular mycorrhizal fungi","fulltext":[{"header":"Introduction","content":"\u003cp\u003eArtisanal and small-scale gold mining (ASGM) is the largest anthropogenic source of mercury pollution, which is caused by the amalgamation process used in gold extraction (Donkor et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Boateng \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It was estimated that these mining activities emitted 838 tons of mercury to air in 2015, accounting for 38% of global anthropogenic mercury emissions (UNEP \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Mercury amalgamation is the preferred method of almost all ASGM activities because it is simple and inexpensive (Donkor et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Boateng et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In addition to mercury contamination, gold mining drastically degrades soil health by removing the topsoil, which is rich in nutrients and organic matter (Aryee et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Furthermore, the removal of vegetation has the effect of disrupting the flow of ecosystem services and matter fluxes, as well as increasing the risk of soil erosion (Schueler et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). What remains are \u0026ldquo;lunar\u0026rdquo; landscapes with rubbish dumps, abandoned excavations and vast, barren stretches of land (Aryee et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ghana, where gold mining is a predominant economic activity, the repercussions are particularly pronounced. In 2022, gold accounted for 48% of total exports in Ghana (OEC \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). But mining, with its environmental impact, directly competes with agriculture, which was the largest employment sector for the Ghanaian people at 35.3% in 2022 (FAO \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The loss of farmland due to mining-related changes often forces farmers to move to new locations. As a result, farmers clear forests to create new farmland, indicating spillover effects of mining on neighboring areas (Schueler et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContaminated soils can be remediated using chemical, physical or biological techniques. Chemical and physical treatments may irreversibly alter soil properties, destroy biodiversity, and are costly (Padmavathiamma and Li \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Since contaminated areas are extensive and funding is limited, a cost-effective biological soil remediation technique is needed to remove mercury without compromising soil fertility (Mertens et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Phytoremediation, a process that uses plants to remove, transfer, stabilize or degrade contaminants in soil, is environmentally friendly and cost-effective (Hughes et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Padmavathiamma and Li \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Such phytoremediation techniques include phytoextraction, phytostabilization, phytovolatilization, phytofiltration, and phytodegradation (Alkorta et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Phytoextraction (also known as phytoaccumulation) is the uptake of contaminants from soil by plant roots and their translocation and accumulation in the aboveground biomass (Yoon et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Translocation of metal ions into shoots is a crucial biochemical process and desirable for effective phytoextraction, as harvesting root biomass is difficult. Phytovolatilization describes a process whereby heavy metals are absorbed and transpired by plants (Yoon et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Suitable plants for the phytoextraction of mercury should be tolerant to high mercury concentrations and should accumulate high concentrations of mercury in their harvestable above-ground tissues. Moreover, they should have a rapid growth rate with particularly high production of above-ground biomass, develop a well-branched root system, be adapted to the prevailing environmental and climatic conditions and should be easy to cultivate and harvest (Garbisu and Alkorta \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Ali et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlants adapted to thrive in heavy metal-rich soils, known as \u0026acute;metallophytes\u0026acute;, are categorized into metal excluders, metal indicators, and metal accumulators (Ali et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Baker \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Metal excluders store heavy metals in their roots but restrict their transport to aerial parts, maintaining low metal concentrations in their shoots (Baker \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Metal indicators accumulate heavy metals in their aerial parts and generally reflect heavy metal concentrations in the substrate (Sheoran et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Metal accumulators are preferred for phytoremediation since they gather high concentrations of metals in their above-ground biomass. This leads to efficient removal of contaminants from the environment (Baker \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). The efficacy of metal accumulator plants can be assessed by the bioaccumulation factor (BAF) calculated as the heavy metal concentrations in plant shoots divided by the heavy metal concentrations in corresponding soils (Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Further, a high translocation factor (TF) calculated as heavy metal concentrations in plant shoots divided by the heavy metal concentrations in plant roots, is another key parameter (Xun et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Ideal metal accumulators do not show high reduction in plant biomass when plants are grown in soils contaminated with heavy metals. This can be evaluated by the tolerance index (TI) calculated as the biomass of treated plants divided by the biomass of control plants (Diwan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Although over the past 20 years many scientists from different countries have investigated more than 200 plant species for their ability to accumulate and translocate mercury, no accumulator has been identified yet (Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGenerally, mercury is toxic for plants, it inhibits photosynthesis, nutrient uptake, nutrient transportaffecting plant growth and biomass production (Lenti et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Mei et al. 2021). To counteract those negative effects, plants may be inoculated with plant strengthening agents such as arbuscular mycorrhizal fungi AMF (Ferrol et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pirsarandib et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Several studies have reported that certain AMF species, like \u003cem\u003eGlomus mosseae\u003c/em\u003e, enhance the transport of heavy metals into the aboveground plant biomass (Weissenhorn et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Singh et al. 2019). However, other studies have shown that some AMF species, like \u003cem\u003eFunneliformis mosseae\u003c/em\u003e, inhibit the translocation of heavy metals to the aboveground biomass (Shabani et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Chamba et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Salazar et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This was explained by the observation that some heavy metals are bound to fungal hyphae, arbuscules, vesicles or vacuoles, which inhibits the transport of heavy metals to the plant tissue (Garg and Singh 2018; Motaharpoor et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe use of nitrogen-fixing legumes in the remediation of mercury-contaminated soils has the added benefit of increasing the biomass of subsequent plant species and thus the biomass production of the whole plant community (Fr\u0026eacute;rot et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The four legume tree species, \u003cem\u003eAcacia mangium\u003c/em\u003e Willd, \u003cem\u003eGliricidia sepium\u003c/em\u003e Jacq, \u003cem\u003eSenna siamea\u003c/em\u003e Lam (synonym \u003cem\u003eCassia siamea\u003c/em\u003e) and \u003cem\u003eLeucaena leucocephala\u003c/em\u003e Lam, were selected for their rapid growth and ability to establish and survive on degraded land in Ghana (Tetteh et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Festin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kusumaningtyas et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition, \u003cem\u003eA. mangium\u003c/em\u003e, \u003cem\u003eG. sepium\u003c/em\u003e, and \u003cem\u003eL. leucocephala\u003c/em\u003e are nitrogen-fixing tree species, making them ideal for reforestation of degraded sites (Macedo et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Tetteh et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile the majority of studies focus on the phytoextraction of heavy metals by grasses and herbs, this work is dedicated to tropical trees, which could potentially produce a higher biomass and consequently remove a larger amount of mercury (Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study aims to investigate the phytoremediation potential of four tree species from Ghana in mercury-contaminated soils within gold mining areas. The optimal candidate should accumulate a high concentration of mercury in the above-ground biomass while remaining unharmed (Alkorta et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Specifically, the objectives are: (1) to assess the capacity of these species to accumulate mercury in their biomass, particularly in above-ground tissues, under varying levels of soil contamination; (2) to evaluate the physiological responses of these species to mercury exposure, including growth rates and photosynthesis; and (3) to explore the influence of AMF on the effectiveness of mercury uptake and resistance to mercury toxicity. Through this research, we identify and characterize species optimal for reforestation and ecological restoration of areas degraded by mercury pollution.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePlant cultivation\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTo prepare the seedlings, the dormancy of the seeds of \u003cem\u003eA. mangium\u003c/em\u003e (Am), \u003cem\u003eL. leucocephala\u003c/em\u003e (Ll) and \u003cem\u003eS. siamea\u003c/em\u003e (Ss) was broken by scarification of the seed coat, acid, or hot water treatment. \u003cem\u003eG. sepium\u003c/em\u003e (Gs) did not require a pretreatment to break seed dormancy. After pretreatment, seeds were soaked in water for 24 h. Seeds were placed in germination trays and exposed to a 12/12 h light/dark cycle at temperatures of 25/20\u0026deg;C in a climate chamber for 11 days. Subsequently, seedlings were transplanted into planting trays and placed in a greenhouse. A mixture of sand and vermiculite (5:3 by volume) was used as substrate. Prior to use, sand and vermiculite were autoclaved at 120\u0026deg;C for 15 minutes and then completely dried at 80\u0026deg;C. Greenhouse conditions were maintained at 26\u0026deg;C with an average relative humidity of 56%. To provide artificial illumination, high-pressure sodium lamps were utilized (SONT Agro 400W; Philips, Amsterdam, Netherlands) with a photoperiod of 12 hours (PAR, 210\u0026ndash;270 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eArbuscular mycorrhizal fungi (AMF)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe AMF strain \u003cem\u003eRhizophagus irregularis\u003c/em\u003e Błaszk., Wubet, Renker \u0026amp; Buscot, 2009 QS81 was supplied by INOQ GmbH (Schnega, Germany). The inoculum of \u003cem\u003eR. irregularis\u003c/em\u003e was prepared from arbuscular mycorrhizal root fragments of \u003cem\u003eTrifolium pratense\u003c/em\u003e grown in sand: vermiculite (35:65 by volume). The inoculum contained 100\u0026nbsp;million propagules per kg of powder (as vesicles and spores according to INOQ GmbH).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eExperimental design\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTwo consecutive greenhouse experiments were carried out. The greenhouse conditions were as described above. In the first experiment, the effect of a lower (12.5 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and a higher (25.0 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) mercury concentration in the substrate on the tree species was investigated. This experiment is referred to as the \u0026lsquo;mercury concentration experiment\u0026rsquo;. Based on the results of the \u0026lsquo;mercury concentration experiment\u0026rsquo; experiment, the higher mercury concentration was chosen for the second experiment, in which AMF was grown with only one mercury concentration. This experiment is referred to as the \"mercury-AMF experiment\".\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMercury-concentration experiment\u003c/span\u003e: Seedlings were transplanted into their final pots 11 weeks after germination pretreatment. To prevent mercury leaching from drainage water, 1 L plastic buckets without holes in the bottom were used. The substrate was a mixture of sand and vermiculite (19:1 by weight) with the addition of 1 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e controlled-release fertilizer (Osmocote\u0026reg; Exact Mini 3-4M, NPK 15:3.9:9.1\u0026thinsp;+\u0026thinsp;1.2 Mg\u0026thinsp;+\u0026thinsp;trace elements, ICL, Netherlands). Prior to use, sand and vermiculite were autoclaved at 120\u0026deg;C for 15 minutes and then completely dried at 80\u0026deg;C. Of the species \u003cem\u003eA. mangium\u003c/em\u003e, \u003cem\u003eG. sepium\u003c/em\u003e, and \u003cem\u003eS. siamea\u003c/em\u003e, 15 plants were included in the experiment. Due to poor germination rate 9 plants of the species \u003cem\u003eL. leucocephala\u003c/em\u003e were included. Arrangement of pots was a randomized block design with five blocks. Each block had three plants of each species; \u003cem\u003eL. leucocephala\u003c/em\u003e had only three blocks. Of these three plants, one served as a control, one was treated with 12.5 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Hg 12.5) and one with 25.0 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Hg 25.0). Mercury was applied in the form of a mercury chloride (HgCl\u003csub\u003e2\u003c/sub\u003e) solution, with the solution volume adjusted to achieve a final mercury concentration in the substrate of either 12.5 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e or 25 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e14 weeks after germination. Eight weeks after mercury treatment, plants were harvested and separated into roots, stems, and leaves. Roots were shortly washed three times in deionized water. Plant samples were air dried at room temperature for dry weight determination.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMercury-AMF experiment\u003c/span\u003e: Six weeks after germination, plants were divided into control (x) and AMF-inoculated (AMF) groups and transplanted into 1.0 L pots with 750 g of substrate. The substrate was a mixture of sand and vermiculite (19:1 by weight) with the addition of 0.5 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e controlled-release fertilizer (Osmocote\u0026reg; Exact Mini 3-4M, NPK 15:3.9:9.1\u0026thinsp;+\u0026thinsp;1.2 Mg\u0026thinsp;+\u0026thinsp;trace elements, ICL, Netherlands). For the AMF-treated plants, the substrate was mixed with 0.075 g AMF inoculum (a ratio of 0.1 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). A total of 64 plants were arranged in a complete randomized block design with four blocks. A three factorial design was used, with the factors of mercury concentrations (0 and 25 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and AMF (presence or absence) studied across the four tree species. Twelve weeks after germination 5 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (3.75 mg pot\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was applied as a mercuric chloride (HgCl\u003csub\u003e2\u003c/sub\u003e) solution every week for a period of 5 weeks to reach a final concentration of 25 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Six weeks after the first mercury application, the plants were harvested as mentioned in the \u0026ldquo;mercury-concentration experiment\u0026rdquo; above. A subsample of the roots from the AMF-treated plants was stored at -80\u0026deg;C to determine AMF root colonization. For this, roots were cut into 1 cm lengths and cleared with 10% NaOH in a 70\u0026deg;C water bath for 45 min and then soaked in 1% HCl for 1 min at room temperature. Roots were stained with 2% Parker Quink blue ink (Yon et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) in a 70\u0026deg;C water bath for 30 min. The roots were rinsed with tap water and then stored in a lactoglycerol solution (lactic acid, glycerol, H\u003csub\u003e2\u003c/sub\u003eO in a ratio of 1:1:1). Thirty fragments from each plant were randomly selected, placed on a microscope slide, and examined under a light microscope for mycorrhizal colonization (Trouvelot et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMercury concentration\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePlant samples were ground and homogenized using a mill with zirconium oxide grinding balls (MM40, Retsch GmbH, Haan, Germany). Subsequently, 0.2 g of the homogenized material were moistened with 1 mL of deionized H\u003csub\u003e2\u003c/sub\u003eO and digested in 2.5 mL of 69% HNO\u003csub\u003e3\u003c/sub\u003e in a microwave-heated UltraCLAVE III digestion unit (MLS-MWS GmbH, Leutkirch, Germany). One mL of the microwave pressure digestion solution was added to 1 mL of dilution solution (2% cysteine, 7% isopropanol made up to 1000 mL with 1% HNO\u003csub\u003e3\u003c/sub\u003e) and 0.1 mL of 50 ppb rhodium standard solution and then made up to 10 mL with ddH\u003csub\u003e2\u003c/sub\u003eO. The mercury concentration was analyzed using a NexION 300 \u0026times; inductively coupled plasma mass spectrometer (PerkinElmer LAS GmbH, Rodgau, Germany).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGas exchange and biomass determination\u003c/h2\u003e \u003cp\u003eAll plants were analyzed weekly for their stem height using a scale and defined as the height from the substrate surface to the top of the main shoot.\u003c/p\u003e \u003cp\u003eThe gas exchange (CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO) of the youngest fully developed leaf was determined weekly (GFS-3000, Heinz Walz GmbH; 3010-S standard measuring head with 3040-L LED light source, head area of 2.5 cm\u003csup\u003e2\u003c/sup\u003e). The area of leaves that did not fill the measuring head was determined using ImageJ.\u003c/p\u003e \u003cp\u003eThe Tolerance Index (TI) was calculated in this work using the following equations (Diwan, Ahmad, and Iqbal \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). TI values above 1 indicate a net increase in biomass and imply that the plants have developed heavy metal tolerance, while TI values below 1 indicate a net decrease in biomass and a stressed state of the plants.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:TI=\\:\\frac{Biomass\\:of\\:treated\\:plants\\:\\left(g\\:{plant}^{-1}\\right)}{Biomass\\:of\\:control\\:plants\\:\\left(g\\:{plant}^{-1}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe Bioaccumulation Factor (BAF) was calculated using the following equation (Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The initial Hg concentration in the substrate (12.5 or 25.0 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was used to calculate the BAF.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:BAF=\\:\\frac{Hg\\:concentration\\:in\\:plant\\:shoot}{\\:Hg\\:concentration\\:in\\:substrate}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe Translocation Factor (TF), \u003cem\u003ei.e\u003c/em\u003e. the ability of a plant to translocate metal ions from the roots to the shoots, was calculated as follows:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:TF=\\frac{Hg\\:concentration\\:in\\:plant\\:shoot}{Hg\\:concentration\\:in\\:plant\\:root}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMercury concentration, assimilation rate, stem height, biomass, TI, BAF, TF, and AMF were analyzed using ANOVA with SAS software 9.4 (SAS Institute, Cary NC, USA) with proc mixed. Least squares means were calculated for comparison between control and treated plants. The significance level was set at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. Model assumptions such as normality, homoscedasticity, and independence were verified, when necessary log-transformation was applied, and \u003cem\u003epost hoc\u003c/em\u003e comparisons were conducted using the least significant difference (LSD) test to ensure accurate interpretation of the differences.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMercury accumulation\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eOur analysis of mercury accumulation across different plant components (roots, stems and leaves), shows that the highest concentrations consistently occurred in the root system, irrespective of the species studied (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mercury accumulation in the trees followed the treatment with lowest concentrations at the 12.5 Hg treatment and highest at the 25 Hg treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The 12.5 Hg treatment did not lead to high Hg accumulation in the leaves, stems, or roots, except for the stems of \u003cem\u003eA. mangium\u003c/em\u003e, which showed high Hg accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The 25 Hg treatment showed accumulation in all tree species. In the leaves, highest Hg concentration was detected in \u003cem\u003eG. sepium\u003c/em\u003e with 95.8 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and in \u003cem\u003eA. mangium\u003c/em\u003e with 77.0 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Stems of \u003cem\u003eA. mangium\u003c/em\u003e (445 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and \u003cem\u003eG. sepium\u003c/em\u003e (360.3 mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) accumulated highest mercury concentrations. \u003cem\u003eL. leucocephala\u003c/em\u003e accumulated the lowest mercury concentration in both leaves and stem. Mercury accumulation in the above-ground biomass has a clear pattern: Am\u0026thinsp;\u0026gt;\u0026thinsp;Gs\u0026thinsp;\u0026gt;\u0026thinsp;Ss\u0026thinsp;\u0026gt;\u0026thinsp;Ll (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Consideration of the increase factor of mercury accumulation shows that a doubling of mercury treatment leads to a multiple increase in mercury accumulation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This phenomenon is particularly evident in the stems, with \u003cem\u003eA. mangium\u003c/em\u003e exhibiting a 49-fold higher Hg accumulation in Hg 25.0 than in Hg 12.5.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncrease factor of mercury accumulation when comparing Hg 25.0 and Hg 12.5 in leaves, stems, and roots of \u003cem\u003eA. mangium\u003c/em\u003e, \u003cem\u003eG. sepium\u003c/em\u003e, \u003cem\u003eL. leucocephala\u003c/em\u003e, and \u003cem\u003eS. siamea\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eA. mangium\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eG. sepium\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. siamea\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePlant physiological responses to mercury accumulation\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the total dry weight, mean assimilation rate, and stem growth for each tree species. \u003cem\u003eG. sepium\u003c/em\u003e showed significant and particularly pronounced reduction in assimilation rate, stem height, and total dry weight with increasing mercury treatment. \u003cem\u003eA. mangium\u003c/em\u003e showed a significant decrease in assimilation rate and stem height, but total dry weight remained unchanged. \u003cem\u003eL. leucocephala\u003c/em\u003e and \u003cem\u003eS. siamea\u003c/em\u003e appeared resistant to mercury effects on assimilation, stem height, and dry weight, with stable assimilation rates higher mercury concentrations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal dry weight, mean assimilation rate per plant species and stem growth over the mercury treatment period (8 w). Significant differences of treatment effects indicated by different letters (LSD, \u003cem\u003ep\u0026thinsp;\u0026le;\u0026thinsp;0.05\u003c/em\u003e). Statistical analysis was performed individually for each tree species.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMercury-Treatment\u003c/p\u003e \u003cp\u003e(mg Hg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMean Assimilation\u003c/p\u003e \u003cp\u003e(\u0026micro;mol m\u003csup\u003e2\u003c/sup\u003e s\u003csup\u003e1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eStem Growth \u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eTotal Dry Weight\u003c/p\u003e \u003cp\u003e(g per plant)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11.1 (\u0026plusmn;\u0026thinsp;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.9 (\u0026plusmn;\u0026thinsp;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.31 (\u0026plusmn;\u0026thinsp;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. mangium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8.9 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.6 (\u0026plusmn;\u0026thinsp;1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.91 (\u0026plusmn;\u0026thinsp;0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7.9 (\u0026plusmn;\u0026thinsp;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6 (\u0026plusmn;\u0026thinsp;2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.19 (\u0026plusmn;\u0026thinsp;0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5.1 (\u0026plusmn;\u0026thinsp;0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.3 (\u0026plusmn;\u0026thinsp;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.88 (\u0026plusmn;\u0026thinsp;0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eG. sepium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.6 (\u0026plusmn;\u0026thinsp;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4 (\u0026plusmn;\u0026thinsp;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.62 (\u0026plusmn;\u0026thinsp;0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.5 (\u0026plusmn;\u0026thinsp;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4 (\u0026plusmn;\u0026thinsp;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.54 (\u0026plusmn;\u0026thinsp;0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5.5 (\u0026plusmn;\u0026thinsp;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.4 (\u0026plusmn;\u0026thinsp;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.35 (\u0026plusmn;\u0026thinsp;0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5.5 (\u0026plusmn;\u0026thinsp;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.4 (\u0026plusmn;\u0026thinsp;3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.01 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6.4 (\u0026plusmn;\u0026thinsp;0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.7 (\u0026plusmn;\u0026thinsp;3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.46 (\u0026plusmn;\u0026thinsp;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6.8 (\u0026plusmn;\u0026thinsp;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.23 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. siamea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7.0 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.9 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.80 (\u0026plusmn;\u0026thinsp;0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7.6 (\u0026plusmn;\u0026thinsp;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9 (\u0026plusmn;\u0026thinsp;0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.77 (\u0026plusmn;\u0026thinsp;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePhytoremediation assessment indicators\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe tolerance index (TI), calculated based on dry weight, was determined for each plant species across different treatments (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). \u003cem\u003eA. mangium\u003c/em\u003e exhibited a trend in dry weight accumulation at Hg 12.5 and a slight decline at Hg 25 but without statistical significance. The resulting tolerance index exceeding 1 indicated resilience to the medium mercury treatment, while a value slightly below 1 suggested a stress response at high mercury treatment. Furthermore, the \u0026lsquo;TI mean\u0026rsquo; for \u003cem\u003eA. mangium\u003c/em\u003e was 1.07 and with this the highest value among the four tree species indicating highest mercury tolerance. The dry mass of \u003cem\u003eS. siamea\u003c/em\u003e was relatively unaffected at Hg 25 or increased at Hg 12.5 compared to control (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Therefore, the resulting TI values were in the range of 1 for both mercury treatments suggesting no harming effect of mercury on \u003cem\u003eS. siamea\u003c/em\u003e. \u003cem\u003eG. sepium\u003c/em\u003e exhibited the most adverse reaction to the presence of mercury, as indicated by reduced total dry weight (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and high TF of 35.4 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The \u0026lsquo;TI mean\u0026rsquo; of \u003cem\u003eL. leucocephala\u003c/em\u003e was 0.86, which indicated a medium resistance range compared to the other plant species (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNone of the tree species had a mercury translocation factor (TF) greater than 1.0 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For \u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eS. siamea\u003c/em\u003e, the differences in TF between treatments were highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, data not shown) with highest TF values compared to the other tree species.\u003c/p\u003e \u003cp\u003eThe bioaccumulation factor (BAF) is a metric used to calculate the accumulation of mercury in above-ground biomass (shoot) relative to the concentration of mercury in the substrate (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Except for L. leucocephala, the BAF increased with increasing mercury treatment (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Notably, the highest values were observed for \u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eG. sepium\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTranslocation factor (TF), bioaccumulation factor (BAF) and tolerance index (TI) per plant species and mercury treatment. BAF mean and TI mean represent the mean value per species averaged over the levels of the mercury treatment. Significant differences of mercury treatment effects are indicated by different letters (LSD, p\u0026thinsp;\u0026le;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMercury-treatment\u003c/p\u003e \u003cp\u003e(mg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTranslocation factor\u003c/p\u003e \u003cp\u003e(TF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBioaccumulation factor \u003c/p\u003e \u003cp\u003e(BAF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBAF \u003c/p\u003e \u003cp\u003emean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eTolerance index \u003c/p\u003e \u003cp\u003e(TI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eTI\u003c/p\u003e \u003cp\u003emean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. mangium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eG. sepium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. siamea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMycorrhizal colonization\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e\u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eG. sepium\u003c/em\u003e had a successful inoculation with a high frequency of mycorrhizae in the root system without significant differences between control and mercury treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, \u003cem\u003eL. leucocephala\u003c/em\u003e showed a very low mycorrhizal colonization rate in the control while the mercury treated plants showed high inoculation capacity. The roots of \u003cem\u003eS. siamea\u003c/em\u003e were too thick and heavily pigmented to be analyzed for mycorrhizal colonization under the light microscope according to the method of Trouvelot et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMercury accumulation depending on arbuscular mycorrhizal fungi\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe highest mercury concentrations in aboveground biomass were found in leaves with 202 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and in stem with 203 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of AMF-treated \u003cem\u003eA. mangium\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, inoculation with AMF showed no significant effect on mercury accumulation in any of the tree species. Mercury accumulation in \u003cem\u003eG. sepium\u003c/em\u003e and \u003cem\u003eL. leucocephala\u003c/em\u003e was low in all plant tissues and seemed to be further reduced by inoculation with AMF, although without significant differences. The trends of mercury accumulation in the \u0026lsquo;mercury-concentration experiment\u0026rsquo; were confirmed in the \u0026lsquo;mercury-AMF experiment\u0026rsquo;. The highest mercury concentration was always detected in \u003cem\u003eA. mangium\u003c/em\u003e, the lowest in \u003cem\u003eL. leucocephala.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePhysiological responses to mercury and arbuscular mycorrhizal fungi\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe Mercury-AMF experiment aimed to assess different plant physiological parameters such as photosynthesis as indicated by the assimilation rate at week 6 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The assimilation of \u003cem\u003eA. mangium\u003c/em\u003e was significantly reduced by mercury and was increased by inoculation with AMF. The assimilation of \u003cem\u003eG. sepium\u003c/em\u003e was also significantly reduced by mercury. However, \u003cem\u003eG. sepium\u003c/em\u003e plants inoculated with arbuscular mycorrhizal fungi (AMF) exhibited a reduction in assimilation due to mercury treatment, though this decrease was not statistically significant. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). \u003cem\u003eL. leucocephala\u003c/em\u003e had no significant change in assimilation by either mercury or AMF. In contrast, \u003cem\u003eS. siamea\u003c/em\u003e had a significant reduction in assimilation in response to mercury, this was mitigated by AMF. However, neither mercury nor AMF showed a significant effect on the total dry weight of \u003cem\u003eA. mangium\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mercury treatment showed a significant negative effect on the total dry weight (DW) of \u003cem\u003eG. sepium\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), while the inoculation with AMF did not significantly change this reduction of dry weight. The total DW of \u003cem\u003eL. leucocephala\u003c/em\u003e and \u003cem\u003eS. siamea\u003c/em\u003e was not significantly affected by either mercury or AMF (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Regarding the tolerance towards mercury overall, there are no significant differences in TI-values when comparing all treatments and species (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The TI-values for \u003cem\u003eA. mangium\u003c/em\u003e were below 1, irrespective of the AMF-inoculation. Species and treatments with TI above 1 were \u003cem\u003eG. sepium\u003c/em\u003e inoculated with AMF, and \u003cem\u003eS. siamea\u003c/em\u003e without AMF. The mercury accumulated calculated as BAF showed significant differences between the tree species (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), but the AMF-inoculation did not show significant effects. The highest BAF was found in \u003cem\u003eA. mangium\u003c/em\u003e, the lowest in \u003cem\u003eL. leucocephala\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of arbuscular mycorrhizal fungi inoculation (AMF\u0026thinsp;=\u0026thinsp;AMF-inoculated; x\u0026thinsp;=\u0026thinsp;control) on mercury tolerance. Assimilation and total plant dry weight was evaluated 6 w after mercury application; bioaccumulation factor (BAF) and tolerance index (TI). Differences of significance are denoted by varying letters (LSD, \u003cem\u003ep\u0026thinsp;\u0026le;\u0026thinsp;0.05\u003c/em\u003e). Statistical analysis was performed separately for each plant species for assimilation and total dry weight. TI and BAF compares all treatments with each other.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicroorganism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMercury-Treatment\u003c/p\u003e \u003cp\u003e(mg Hg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAssimilation\u003c/p\u003e \u003cp\u003e(\u0026micro;mol m\u003csup\u003e2\u003c/sup\u003e s\u003csup\u003e1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTotal dry weight\u003c/p\u003e \u003cp\u003e(g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eTolerance Index\u003c/p\u003e \u003cp\u003e(TI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eBioaccumulation factor\u003c/p\u003e \u003cp\u003e(BAF)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eA. mangium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.1 (\u0026plusmn;\u0026thinsp;2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.4 (\u0026plusmn;\u0026thinsp;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.0 (\u0026plusmn;\u0026thinsp;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.5 (\u0026plusmn;\u0026thinsp;2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.6 (\u0026plusmn;\u0026thinsp;3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.4 (\u0026plusmn;\u0026thinsp;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eG. sepium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7 (\u0026plusmn;\u0026thinsp;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4 (\u0026plusmn;\u0026thinsp;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.8 (\u0026plusmn;\u0026thinsp;0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1 (\u0026plusmn;\u0026thinsp;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8 (\u0026plusmn;\u0026thinsp;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6 (\u0026plusmn;\u0026thinsp;0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.2 (\u0026plusmn;\u0026thinsp;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5 (\u0026plusmn;\u0026thinsp;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6 (\u0026plusmn;\u0026thinsp;0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5 (\u0026plusmn;\u0026thinsp;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3 (\u0026plusmn;\u0026thinsp;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.5 (\u0026plusmn;\u0026thinsp;0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eS. siamea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.4 (\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 (\u0026plusmn;\u0026thinsp;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.7 (\u0026plusmn;\u0026thinsp;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7 (\u0026plusmn;\u0026thinsp;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4 (\u0026plusmn;\u0026thinsp;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.5 (\u0026plusmn;\u0026thinsp;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGiven the universality of the amalgamation process, similar levels of pollution, as reported by Tomiyasu et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) may be anticipated in abandoned mining sites in Ghana and other areas exposed to gold mining including amalgamation with mercury. Accordingly, our study investigated the potential of four local leguminous tree species to remediate mercury-contaminated soils. Generally, mercury accumulation in plant tissues has a complex pattern, with roots consistently showing the highest concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), as shown in other studies (Liu et al. 2017; Moreno et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, the accumulation of mercury in aboveground biomass is particularly important for phytoremediation (Ali et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Our data revealed that specifically under high mercury treatment, \u003cem\u003eA. mangium\u003c/em\u003e accumulated highest concentrations in above-ground biomass, closely followed by \u003cem\u003eG. sepium\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Therefore, these two species are considered as mercury accumulators. \u003cem\u003eL. leucocephala\u003c/em\u003e shows comparatively low values in the aboveground biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and may be classified as an excluder (Baker \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe increase in mercury accumulation in the aboveground biomass, especially at the high mercury concentration in soil is of particular interest. Although the mercury concentration in the substrate increased 2-fold (from Hg 12.5 to Hg 25), the concentration in the biomass of all four tree species increased up to 49-fold in stems of \u003cem\u003eA. mangium\u003c/em\u003e and 7-fold in the leaves of \u003cem\u003eG. sepium\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the roots, however, 2-fold soil mercury increase led to a 2-fold increase in mercury accumulation - irrespective of the tree species (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This suggests a threshold above which mercury accumulation becomes more effective but also more harmful for above-ground plant tissue. According to Baker (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e) \u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eG. sepium\u003c/em\u003e showed the characteristics of metal accumulators.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePhysiological responses and suitability for phytoremediation\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe ideal candidate suitable for phytoextraction should not only accumulate high concentrations of mercury in the aboveground biomass, but also remain unharmed (Alkorta et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The high mercury-accumulating species \u003cem\u003eA. mangium\u003c/em\u003e showed a reduction in assimilation and stem height but no reduction in total dry weight (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It could be suggested that mercury did not harm the plant but led to a more stunted habitus. On the contrary, \u003cem\u003eG. sepium\u003c/em\u003e was severely affected; not only did assimilation and stem height decrease with increasing mercury treatment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), moreover, four out of 10 mercury-treated plants did not survive during the experiment (data not shown). Therefore, \u003cem\u003eG. sepium\u003c/em\u003e is regarded as a susceptible tree species that is unsuitable for the phytoremediation of mercury-contaminated soils. The physiology of \u003cem\u003eL. leucocephala\u003c/em\u003e was not affected by mercury; however, it did not absorb a significant amount of mercury (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Thus, even though the plant can likely tolerate mercury contaminated soil, it would not qualify as an effective accumulator.\u003c/p\u003e \u003cp\u003eMetal remediation plant indicators have been developed to assist the comparability of different plant species for their phytoremediation potential. It is the main ambition to locate so-called hyperaccumulators, plants that accumulate heavy metals in their high yielding above-ground tissues to levels far above those found in the soil (Memon and Schr\u0026ouml;der, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Characteristics of hyperaccumulators are high concentration thresholds for heavy metals in plant shoots (\u003cem\u003ee.g.\u003c/em\u003e 10,000 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for zinc (Zn), 1000 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for nickel (Ni), and 100 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for cadmium (Cd)) (Baker \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Baker and Brooks \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). No threshold levels have yet been set for mercury. Further, the bioaccumulation calculated as bioaccumulation factor (BAF) as well as the translocation factor (TF) should be greater than 1 (Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xun et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Finally, the plants should be extremely tolerant to heavy metals, \u003cem\u003ei.e\u003c/em\u003e. they should not show significant reduction in biomass as determined by the tolerance with a TI-value of \u0026gt;\u0026thinsp;1 (Diwan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Despite numerous studies conducted from various countries on over 200 plant species in the last two decades in search of a hyperaccumulator of mercury, none has been successfully identified so far (Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Only \u003cem\u003eErato polymnioides\u003c/em\u003e and a few other species were labeled as potential mercury hyperaccumulators (Chamba et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, these species are native to the rainforests of Bolivia, Colombia, Costa Rica, Ecuador, Panam\u0026aacute;, and Peru\u0026mdash;not to West Africa. Introducing non-native plant species can destabilize local ecosystems, as these species often lack natural predators or competitors, allowing them to spread rapidly and become invasive (Zizka et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). According to the definition, none of the four plant species meets all criteria. \u003cem\u003eG. sepium\u003c/em\u003e accumulated high levels of mercury, resulting in comparatively high TF values, but suffered considerable damage and plant death due to its sensitivity to mercury, as evident from its low TI values and the reduction in assimilation (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). \u003cem\u003eL. leucocephala\u003c/em\u003e had the lowest mercury accumulation in the aboveground biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and showed the lowest mercury translocation rates of all species (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, \u003cem\u003eL. leucocephala\u003c/em\u003e did not respond to the mercury treatment in any way. Neither the stem growth, dry weight, nor the assimilation was affected (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), suggesting that it can be classified as an excluder plant. \u003cem\u003eS. siamea\u003c/em\u003e fulfilled the majority of the set requirements and demonstrated a TI above 1 and a BAF above 2 in both experiments. However, in comparison to \u003cem\u003eA. mangium\u003c/em\u003e, \u003cem\u003eS. siamea\u003c/em\u003e exhibited a reduced accumulation of mercury in both experiments, as well as a lower BAF (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). With regard to the accumulation of mercury, \u003cem\u003eA. mangium\u003c/em\u003e is the species with the greatest potential for mercury phytoremediation, as it exhibits the highest concentration of mercury in plant tissues and the highest BAF in both experiments (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. 3). It proved to be resistant to mercury exposure, with a TI greater than 1 in the mercury-concentration-Experiment (Diwan, Ahmad, and Iqbal \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Further, its BAF in the 25 Hg treatment was higher than in the 12.5 Hg treatment, corresponding to its increased mercury accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Most importantly, \u003cem\u003eA. mangium\u003c/em\u003e accumulated by far the highest concentration of mercury in above-ground tissue, even though not being a hyperaccumulator.\u003c/p\u003e \u003cp\u003e \u003cem\u003eA. mangium\u003c/em\u003e could therefore be a suitable candidate for the phytoremediation of mercury-contaminated soils in Ghana. The findings of our study align with those of previous research, which have shown that \u003cem\u003eA. mangium\u003c/em\u003e has the capacity to remediate soils contaminated with heavy metals (Sampanpanish \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rosli et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Couic et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The concept of diverse forests for phytoremediation is well acknowledged and a fast-growing topic in land restoration research, as reviewed by G\u0026oacute;mez et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The proposal here is not to exploit the forests directly for short-term gains, but to carefully manage and monitor contamination levels over several decades so that the acacia forest and other organisms can establish a stable ecosystem that facilitates the natural decontamination of anthropogenic pollution. Therefore, \u003cem\u003eA. mangium\u003c/em\u003e could be accompanied by \u003cem\u003eS. siamea\u003c/em\u003e, which has also achieved promising results, and \u003cem\u003eL. leucocephala\u003c/em\u003e, which is not a mercury accumulator but is a robust and fast-growing mercury excluder developing well in mercury-contaminated soils. \u003cem\u003eL. leucocephala\u003c/em\u003e is a commonly utilized tree in the maintenance of agroforestry systems (Shelton \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). As such, \u003cem\u003eL. leucocephala\u003c/em\u003e could potentially contribute to the biodiversity of a remediating forest. Furthermore, previous studies have shown that \u003cem\u003eS. siamea\u003c/em\u003e, in combination with other plants, provides significant benefits for soil remediation by accumulating heavy metals, improving soil structure and promoting fertility, thus supporting sustainable plant growth in heavy metal-contaminated soils (Vanlauwe et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Kusumaningtyas et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePhysiological responses to mercury and arbuscular mycorrhizal fungi\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eResearch indicated that heavy metals typically decrease the mycorrhizal colonization; however, in our case (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) the opposite effect was observed, a finding in line with earlier work (Schneider et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Garcia et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In our study, it is not possible to predict a general trend as to whether mercury accumulation is generally increased or decreased by inoculation with AMF, as no significant difference was found (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Previous findings indicate that inoculation with AMF can lead to both a decrease or an increase in the uptake of mercury by plants (Debeljak et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although inoculation with AMF was successful, it did not result in a significant difference in assimilation or total dry weight as in other studies (Frosi et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Estrada-Luna and Davies \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Nevertheless, it seems that AMF exerts a \u0026lsquo;buffer effect\u0026rsquo; on the sensitivity of plants to mercury, as the reduction in assimilation in less pronounced in the mercury accumulating species \u003cem\u003eA. mangium\u003c/em\u003e, \u003cem\u003eG. sepium\u003c/em\u003e and \u003cem\u003eS. siamea\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Comparing the two experiments, \u003cem\u003eA. mangium\u003c/em\u003e was able to achieve an even higher mercury accumulation in the mercury-AMF experiment than in the mercury-concentration experiment (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Thus, the inoculation with AMF seemed to increase the BAF of \u003cem\u003eA. mangium\u003c/em\u003e, but the TI of \u003cem\u003eA. mangium\u003c/em\u003e in the mercury-AMF experiment was below 1 both with and without AMF (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In contrast, the BAF of \u003cem\u003eG. sepium\u003c/em\u003e in the mercury-AMF experiment was much lower than in the mercury-concentration experiment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This was probably due to the reduced mercury accumulation, whereby the TI of \u003cem\u003eG. sepium\u003c/em\u003e in mercury-AMF was higher than 1. In \u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eG. sepium\u003c/em\u003e, the age of the plant and the duration of mercury exposure appeared to influence the process of mercury accumulation. The influence of the duration of mercury exposure on accumulation has already been observed in other research projects (Xun et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Millhollen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The mechanisms underlying the ageing effect of plants on mercury accumulation is a subject for future research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough it cannot be classified as a hyperaccumulator this study identified \u003cem\u003eA. mangium\u003c/em\u003e as the most promising species for phytoremediation of mercury-contaminated soils in former gold mining areas. It accumulates the highest concentrations of mercury and shows only minor signs of mercury toxicity making it well suitable for planting on areas with former gold mining. Compared to \u003cem\u003eA. mangium S. siamea\u003c/em\u003e exhibited lower (moderate) mercury accumulation without physiological impairment. \u003cem\u003eL. leucocephala\u003c/em\u003e did not accumulate mercury, but also demonstrated no adverse physiological effects and could play an important role as a mercury excluder, thereby promoting biodiversity and ecosystem stability. \u003cem\u003eG. sepium\u003c/em\u003e showed moderate mercury uptake but suffered considerable physiological damage. Although inoculation with AMF did not significantly increase mercury uptake, it appeared to mitigate physiological stress, supporting plant health rather than directly enhancing mercury removal. These findings support the strategic use of diverse plant species in ecological restoration to optimize mercury removal and promote a stable ecosystem. Further research is needed to identify other suitable plant species that meet all the criteria for mercury hyperaccumulation and can be effectively used in phytoremediation strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCorresponding author\u003c/h2\u003e \u003cp\u003eCorrespondence to Nadine Sommer: [email protected]\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics Approval\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Publish\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was funded by the Federal Ministry of Education and Research, Germany, under Support Code 01LZ1709A-B.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eAll authors contributed to the study conception and design. Material preparation, experiments and data collection were performed by Nadine Sommer and Yaqin Guo. Analysis was performed by Nadine Sommer. The first draft of the manuscript was written by Nadine Sommer, Michael Helmut Hagemann and Christian Z\u0026ouml;rb. Frank Rasche and Yaqin Guo reviewed and edited the manuscript. All authors commented on previous versions of the manuscript and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors are grateful to INOQ GmbH for providing us AMF inoculum (\u003cem\u003eRhizophagus irregularis\u003c/em\u003e). We thank Florian Fleckenstein and Ghofrane May for technical help in the laboratory and greenhouse. We further thank Prof. Dr. Hans-Peter Piepho and Dr. Jens Hartung for their help with statistical analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAli H, Khan E, Sajad MA (2013) Phytoremediation of heavy metals-concepts and applications. 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Candollea 70:9\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15553/c2015v701a\u003c/span\u003e\u003cspan address=\"10.15553/c2015v701a\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Bioaccumulation, gold mining, heavy metal, photosynthesis, pollution control, soil rehabilitation","lastPublishedDoi":"10.21203/rs.3.rs-5336359/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5336359/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eArtisanal and small-scale gold mining (ASGM) in low- and middle-income countries often lack adequate safety measures, leading to significant health risks and environmental mercury pollution. Phytoremediation, a plant-based method that utilizes plants to accumulate soil-borne contaminants such as heavy metals, has been verified to restore land for ecosystem services or even future farming. Therefore, this study evaluates the potential of four legume species typically found in Ghana, the world's second largest gold exporter - \u003cem\u003eAcacia mangium\u003c/em\u003e, \u003cem\u003eGliricidia sepium\u003c/em\u003e, \u003cem\u003eLeucaena leucocephala\u003c/em\u003e and \u003cem\u003eSenna siamea\u003c/em\u003e - for the removal of mercury from contaminated soils, as well as potential trade-offs related to eco-physiological processes. It was further investigated whether arbuscular mycorrhizal fungi (AMF) inoculation could enhance mercury removal capacity. Predominantly, \u003cem\u003eA. mangium\u003c/em\u003e consistently exhibited the highest mercury uptake and did not show signs of mercury toxicity. \u003cem\u003eG. sepium\u003c/em\u003e showed moderate mercury uptake but suffered considerable physiological damage. \u003cem\u003eL. leucocephala\u003c/em\u003e was resistant to mercury but accumulated only small amounts. \u003cem\u003eS. siamea\u003c/em\u003e exhibited moderate mercury accumulation without physiological impairment. AMF inoculation did not significantly increase mercury uptake but appeared to mitigate physiological stress under mercury exposure. These results indicate that reforestation of abandoned gold mines with \u003cem\u003eA. mangium\u003c/em\u003e may be a suitable starting point for phytoremediation of mercury and inoculation with AMF can provide additional protection against mercury toxicity.\u003c/p\u003e","manuscriptTitle":"The potential of four legume trees for mercury phytoremediation and the role of arbuscular mycorrhizal fungi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-06 17:34:00","doi":"10.21203/rs.3.rs-5336359/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2025-08-02T16:30:19+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-01-15T23:20:55+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-23T21:17:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2024-11-05T13:54:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-04T04:25:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2024-11-02T17:20:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"97bf5e8a-b8bf-42ed-98ce-1ef32c0b2905","owner":[],"postedDate":"January 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-20T07:52:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-06 17:34:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5336359","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5336359","identity":"rs-5336359","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}