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Pore-water chemistry explains zinc phytotoxicity in soil
Ecotoxicology and Environmental Safety 122 (2015) 252–259
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Pore-water chemistry explains zinc phytotoxicity in soil Mohammed Kader a,b,c,1, Dane T. Lamb a,b,c,n,1, Ray Correll a, Mallavarapu Megharaj a,b,c,1, Ravi Naidu a,b,c,1 a
Centre for Environmental Risk Assessment and Remediation, University of South Australia, Building X, Mawson Lakes, SA 5095, Australia Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of South Australia, Building X, Mawson Lakes, SA 5095, Australia c Global Centre for Environmental Remediation (GCER), Faculty of Science and Information Technology, The University of Newcaslte, Callaghan, NSW, 2308, Australia, Callaghan b
art ic l e i nf o
a b s t r a c t
Article history: Received 3 June 2015 Received in revised form 6 August 2015 Accepted 6 August 2015 Available online 20 September 2015
Zinc (Zn) is a widespread soil contaminant arising from a numerous anthropogenic sources. However, adequately predicting toxicity of Zn to ecological receptors remains difficult due to the complexity of soil characteristics. In this study, we examined solid–solution partitioning using pore-water data and toxicity of Zn to cucumber (Cucumis sativus L.) in spiked soils. Pore-water effective concentration (ECx, x ¼10%, 20% and 50% reduction) values were negatively related to pH, indicating lower Zn pore water concentration were needed to cause phytotoxicity at high pH soils. Total dissolved zinc (Znpw) and free zinc (Zn2 þ ) in soil-pore water successfully described 78% and 80.3% of the variation in relative growth (%) in the full dataset. When the complete data set was used (10 soils), the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Total added Zn, soil pore water pH (pHpw) and dissolve organic carbon (DOC) were the best predictors of Znpw and Zn2 þ in pore-water. The EC10 (total loading) values ranged from 179 to 5214 mg/kg, depending on soil type. Only pH measurements in soil were related to ECx total Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw were in general related to Zn ECx. Similarly, when a solution-only model was used to predict Zn in shoot, DOC was negatively related to Zn in shoot, indicating a reduction in uptake/ translocation of Zn from solution with increasing DOC. & 2015 Elsevier Inc. All rights reserved.
Keywords: Soil solution Soil toxicology Dissolved organic carbon Plants
1. Introduction Zinc (Zn) is an essential trace element for most organisms and is pervasive in the soil environment. Contamination of the soil environment with excessive Zn occurs from a variety of sources, including mining operations, transportation of Zn ore bodies, smelting and Zn plating industries (Lamb et al., 2009). In addition, high Zn levels have been found in soils below galvanised objects (Lock and Janssen, 2001). At metal(loid) contaminated sites, Zn is commonly found at proportionally high concentrations in comparison to other metal(loid)s, such as arsenic, cadmium, lead and copper. Although Zn is essential for numerous functions within organisms, an excess of Zn can result in toxicity. Zinc is required in exceedingly high concentrations in soil to cause Zn toxicity in n Corresponding author at: Global Centre for Environmental Remediation (GCER), Faculty of Science and Information Technology, The University of Newcaslte, Callaghan, NSW, 2308, Australia. E-mail address: [email protected] (D.T. Lamb). 1 Current address: Faculty of Science and Information Technology, The University of Newcastle, ATC Building, Callaghan, NSW 2308, Australia.
http://dx.doi.org/10.1016/j.ecoenv.2015.08.004 0147-6513/& 2015 Elsevier Inc. All rights reserved.
humans. Toxicity to ecological receptors is however a serious problem in Zn contaminated sites. Zinc is a relatively mobile trace element in aerobic soil environments in comparison to other transition series metals such as Cu and Pb (McBride et al., 1997). Preliminary assessment of Zn contaminated sites are first made with measurement of the total soil concentrations. It is commonly acknowledged within the literature that total soil Zn is not necessarily a good indicator of toxicity (McBride et al., 1997). Speciation of Zn in different solid-phases, either as slag or crystalline mineral phases, can alter expected relations with total Zn loading. Nevertheless, Zn loading has often been shown to be a necessary indicator of Zn in soil solution and toxicity to ecological receptors. Indeed, despite the recently updated guideline values for Zn in soil, trigger values are still expressed on total (w/w) basis (Heemsbergen et al., 2009). Studies on Zn toxicity to plants (McBride et al., 2009), invertebrates (Lock and Janssen, 2001) and microorganisms (Broos et al., 2007; Smolders et al., 2004) predominantly focus on total concentrations. Toxicity end points have been reported using dose–response studies in the laboratory (Warne et al., 2008b) and in short-term field studies (Heemsbergen et al., 2009; Warne et al.,
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Table 1 Properties of experimental soils used for the phytotoxicity experiment. FC (%) is field capacity of soil. Soil location
Soil code
pHw
pHpw
% Clay
CEC (cmol(þ )/kg)
% OC
FC %
Zn content (mg/kg)
Feox (g/kg)
Alox (g/kg)
Mnox (g/kg)
Brookland, QLD Dublin, SA Kersbrook, SA Mount Gambier, SA Millicent, SA Port Broughton, SA South Nanango, QLD Tarrington, Vic Wallaroo, SA Yenda, NSW
BK DU KB MG MI PB SN TA WR YE
7.01 7.76 5.05 6.29 7.42 8.72 5.2 5.31 8.08 8.09
6.76 7.98 5.74 6.86 8.09 8.20 6.20 6.06 8.23 7.95
20.0 7.50 20.0 16.3 10.0 6.70 36.0 10.0 17.5 62.1
20.9 7.36 7.26 24.1 29.1 5.79 5.33 11.7 19.3 24.2
2.99 5.49 1.48 8.37 3.86 1.76 3.49 4.98 3.54 1.14
28.8 15.7 25.6 37.1 28.4 17.9 31.6 26.9 26.9 31.2
23.1 13.5 14.5 51.9 34.4 18.3 25.7 23.1 35.9 39.9
3.49 0.64 1.72 12.49 0.43 0.28 2.68 3.12 0.47 1.47
1.11 0.74 2.13 12.60 2.27 0.50 1.87 3.01 1.38 1.23
0.632 0.133 0.045 0.302 0.0252 0.060 0.240 0.212 0.237 0.296
Table 2 Phytotoxicity threshold data expressed as total Zn loading (mg/kg) with confidence intervals (95%), R2 values for dose–response curves (Eq. 1) and EIL values calculated for High Conservation areas and Urban Residential and Open Space land uses. Soils
High conservation
Urban
EC50
EC20
BK DU KB MG MI PB SN TA WR YE
85 65 45 65 130 60 45 50 100 110
230 150 80 150 390 130 75 100 290 340
1334 (1175–1514) 1972 (1607–2421) 685 (546–859) 2483 (2198–2805) 2911 (2080–4083) 6353 (5272–7656) 335 (253–443) 1416 (1159–1730) 4 10,000a 1578 (1253–1982)
807 1361 357 1774 940 3839 226 948 8725 640
a
R2
EC10 (588–1020) (190–1976) (135–561) (1262–2204) (368–1763) (2060–5417) (65–351) (536–1320) (0–36,458) (331–1002)
601 1095 243 1457 485 2859 179 750 5214 377
(393–809) (54–1754) (60–437) (912–1913) (134–1079) (1189–4437) (30–307) (341–1126) (0–28,601) (152–672)
0.96 0.84 0.88 0.95 0.88 0.84 0.90 0.89 0.50 0.93
Highest treatment of 10,000 mg/kg Zn did not cause a 50% reduction from control. At 10,000 mg/kg Zn, a % reduction was observed.
2008a). Studies reporting empirical regression models have typically shown that total concentrations in soil, soil pH, organic matter and cation exchange capacity (CEC) are the key soil properties describing Zn toxicity to biota. Few of these studies have related solubility, bioavailability or bioaccessibility estimates to toxicity directly. In particular, few, if any, report soluble or porewater data in relation to ecotoxicity data sets (Beesley et al., 2010). Smolders et al. (2004) studied the effect of increasing Zn dose to microbial processes in soil. They measured water-extractable Zn but did not report concentrations as related to soil microbial processes. In this study, we studied Zn phytotoxicity to Cucumber (Cucumis sativus L.) in 10 contrasting soils in a dose–response experimental design. We extracted pore-water from soil from each treatment and measured soluble Zn in addition to other solution properties, including soil pH, dissolved carbon, chloride and sulphate.
2. Materials and methods 2.1. Soils and study design Ten soils were selected for study from across Australia, including South Australia, New South Wales, Queensland and Victoria. All samples were sampled from the top 0–0.2 m of each profile, air-dried and sieved through 4 mm sieves initially and later through 2-mm. With the exception of soil YE, which had minimal cultivation, no soils had a history of cultivation. Soil organic carbon was determined using a LECO TOC analyser (TruMac CNS). For soil with a pHwater 46, the TOC was determined with and without addition of HCl (TOCHCl). Thus for soils that were neutral to alkaline, soil organic carbon was determined by subtraction of TOCHCl from TC. Cation Exchange Capacity was determined by the modified compulsive exchange method (Gillman and Sumpter, 1986).
The ‘amorphous’ Fe, Al and Mn oxide content was determined with acid oxalate method (pH ¼3) (Rayment and Higginson, 1992) and clay content using the hydrometer method (Gee and Bauder, 1986). Soil properties are presented in Table 1. Soil pH in the two Ferrosols and Kursols (SN and TA) had the lowest soil pHw (water) (5.05 to 5.31), whilst pHw was 8.72 in soil PB. The pore-water pH (pHpw) differed (see below) in some cases to pHw by up to 0.8 pH units from estimates made on the same soil. Soil organic carbon ranged from 1.14 in Yenda (YE) soil to 8.37 in the Mount Gambier (MG) soil. Clay contents were in general below 20%, however the Vertosol (YE) had high clay content (62%). The CEC ranged from 5.79 (PB) to 29.1 (MI) cmol( þ)/kg. Oxalate extractable Fe content was highest in the Mount Gambier soil and moderately high in the two Ferrosols (TA, SN). 2.2. Toxicity study Soils (air-dried and sieved through 2-mm sieve) were weighed to plastic trays and spread to a thin layer ( 3 cm) and Zn solution sprayed. A spiking solution was prepared that contained the required amount of zinc sulphate to achieve the required soil concentrations. Soil concentrations ranged from 100 to 10,000 mg/kg Zn, although some soils were spiked in a more narrow range to low pH (100 to 5000 mg/kg). To construct dose–response curves, it is ideal to expose organisms at very high levels to achieve a curve ranging from 0% to 100% response. The soil was then sprayed with the spiking solution and mixed thoroughly using a stainless steel trowel. After mixing, the soil was again spread evenly over the tray and the procedure repeated. This continued until all spiking solution was dispensed. Treated soils were then placed in plastic containers and mixed with a mechanical mixer for 5–10 min. The water content of all soils was adjusted to 70% of the estimated field capacity. Soils were placed in 10 L plastic containers with loosely placed lids and incubated for 6 weeks.
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Fig. 1. Response of C. sativus growth to increasing dissolved Zn in porewater expressed as [Zn]pw (dissolved) and Zn2 þ (modelled free ion activity of Zn).
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Table 3 EC 20 and EC10 parameters for Znpw and Zn2 þ from Eq. (1) based on dry weights.
BK DU KB MI MG PB SN TA WR YE
2 Zn+ pw EC50 (lM)
2 Zn+ pw EC10 (lM)
2 Zn+ pw EC20 (lM)
Znpw EC50 (lM)
Znpw EC10 (lM)
Znpw EC20 (lM)
191.4 151.7 182.8 5.754 258.2 26.00 5.445 358.1 15.52 132.7
14.22 15.49 182.8 0.6561 59.43 4.797 0.928 137.4 1.55 2.371
37.15 35.98 52.48 1.462 102.1 8.954 1.483 195.4 7.943 10.47
837.5 1009 935.4 5.745 1038 354.8 34.91 1419 235.0 411.2
113.7 138.1 104.5 0.656 220.3 59.16 3.447 543.3 68.39 11.01
237.7 287.7 234.4 1.462 390.0 128.8 8.101 774.5 107.9 41.88
(80.73–453.9) (40.18–571.5) (116.7–285.8) (1.528–22.13) (168.3–397.2) (12.71–53.21) (1.040–28.51) (184.1–696.6) (6.808–35.31) (32.73–538.3)
(0.3707–81.66) (138,700–209.9) (1.528–79.43) (30.06–9.750) (6.998–152.8) (0.00001–21.63) (0.0018–12.88) (0.00002–434.5) (35.31 –533.3) (0.000–53.70)
(2.704–154.2) (6855–304.1) (7.568–127.4) (10–13.09) (22.65–217.3) (0.0020–30.13) (0.0189–17.87) (4.169–517.6) (35.31–106.7) (0.0015–125.9)
Triplicate samples (300 g of air-dried 2-mm sieved soil) were placed into plant pots lined with nylon mesh for each treatment. Soils were wet from the bottom with deionised water for 24 h and cucumber seeds (C. sativus L.) were sown (10 per pot). Soils were watered to maintain 80–100% of the measured field capacity by weight of each soil. After 28 days of growth, plants were harvested by cutting shoots 1 cm above the soils. Fresh weights, heights and dry weights were recorded. Plants were dried at 70 °C for 72 h and then crushed and digested in concentrated nitric acid after overnight cold digestion.
2.3. Pore-water extraction and modelling At the end of the experiment plant pots were allowed to dry in the greenhouse. Soils were wet to low moisture content (o15– 20% w/w) 3–5 days prior to pore water extraction (Lamb et al., 2013). Twenty-four hours before extraction, the soils were wet to approximately field capacity from the bottom by placing the pot in a tray of deionised and allowing moisture to move upwards. Water added to the bottom reservoir to soils (i.e. clay soils) if required. Pore-water was extracted using the double chamber method (Gillman and Sumpter, 1986; Lamb et al., 2009) To extract sufficient volume of pore-water, moist soil was weighed into the barrels of three 30 or 35 mL syringes with acid cleaned glass wool at the bottom to provide a coarse filter. The solutions from each tube were pooled to create a composite porewater sample. Solutions were then filtered (0.45 mm) for analysis. Composite pore-water samples were separated for measurement of metal concentrations (Na, Mg, Al, K, Ca, Mn, Fe, Cu, and Zn), anions (Cl , NO−3 , SO−4 2), dissolved organic carbon (DOC) and pHpw. Pore-water and plant digested samples were analysed for total metal concentrations by ICP-MS (Agilent 7500c) after appropriate dilutions and matrix considering standards. Quality control measures were taken in every steps of sample preparation and analysis. During pore-water extraction, control soils and blank (purified water) were carried out and even during analysis 50 mg/L standards and blanks were run in every 20 samples in sample sets. Pore-water analysis data were used as input data for modelling in the WHAM 7 model to measure Zn2 þ . All solutions were modelled at 22 °C. The inorganic carbon chemistry was all modelled by equilibrating each solution atmospheric CO2 at a partial pressure of 3.2 10 4 atm. WHAM allows for detailed input for DOC fractions of fulvic acid and humic acid, however we used the default parameters for fulvic acid, allowing 100% of measured DOC to be considered as fulvic acid. All Fe was assumed to be Fe(III) and allowed to precipitate – this was observed to have occurred in many solutions. No solid-phase partitioning was included in any models.
(566.2–1239) (324.3–3148) (516.4–1698) (1.528–21.63) (86.10– 12,330) (193.6–651.6) (16.07–76.03) (722.8–2786) (44.46–1239) (126.8–1337)
(22.08–293.1) (0–1327) (0–415.9) (0.97–30.06) (45.60–512.9) (0.009–89 106) (4.790–7590) (0.000–452.0) (142.6–827.9) (0.01–141.6)
(73.11–498.9) (0.000– 1824) (0.000–698.2) (1.00–13.09) (125.6–762.1) (0.005–1.2 108) (7.448– 111,400) (0.008–2072) (92.68–961.6) (0.3475–324.3)
2.4. Statistical analysis and modelling All statistical analysis was all performed using IBM SPSS (V21). Dose–response curves were fitted to all soils individually with a logistic function. The logistic model used was
Y=
a 1 + e k (x − c )
(1)
where a, k and c are constants that relate to intercept on the yvariable, k is a slope parameter and c is interpreted as the effective concentration causing a 50% reduction of variable y (EC50). In addition, in attempt to describe toxicity data for the full dataset of 10 soils, we modelled all data with a logistic curve. For this purpose, plant response was expressed as %Relative Growth (plant weight at each concentration/plant weight (control) (%RG) (a was set at 100). To explore relationships between soil properties and plant response, correlation analysis and step-wise multiple linear regression was utilised. Phytotoxicological parameters EC10, EC20 and EC50 were estimated for total Zn loading, pore-water concentration, and Zn2+ pw . All statistical parameters from dose–response and sorption curves are from SPSS. Parameter estimates from SPSS were used in Grapher 9 (Golden Software) to provide a depiction of the curve.
3. Results and discussion 3.1. Zinc partitioning and pore-water data Amongst trace metals, Zn is generally considered to be a mobile element in the soil environment. In our study, Zn sorption followed previously reported trends of soil properties. In general, increasing soil pH and clay content resulted in high sorption. Porewater Zn (Znpw) in control soils was in the range of 0.097 to 1.94 mM (mean7 SD¼ 0.537 0.55). Native pore-water Zn was very low with the highest Zn found in the most acidic soil at 1.94 mM. These values contrast with those of Krishnamurti and Naidu (2002) who reported dissolved Zn concentrations in saturation water extracts of 0.75–5.48 mM (mean7 SD¼ 2.800 71.369). Addition of Zn caused Zn in pore water to increase from approximately 1 mM to as high as 0.1 M in the 10,000 mg/kg Zn treatment. In most soils receiving 8000–10,000 mg/kg Zn there was a small reduction in pHpw which contributed to higher Zn solubility. Below such concentrations there was little effect on pHpw from ZnSO4 spiking. Concentrations in the toxicity range of most soils (100–4000 mg/kg Zn) showed no consistent trend towards acidification. In soil WRA, where severe phytotoxicity was not observed at any concentration, there was similarly no consistent pH decline; this was attributable to the high inorganic carbon content in this soil. In soil PB, at 8000 and 10,000 mg/kg Zn soil pHpw dropped by approximately 1 pH unit from 8.20 in the control.
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3.2. Zinc accumulation and phytotoxicity
Fig. 2. Relationship between Zn2 þ estimated EC10, EC20 and EC50 in porewater and pH measured in porewater (pHpw) and 10 mM CaCl2 (pHca).
Zinc solubility in the experimental soils was high with porewater concentrations at the highest treatments reaching over mM concentration range. The high Zn solubility in our soils resulted in significant uptake and translocation of Zn to cucumber shoots. The range of Zn concentration in cucumber shoots over the full spiking range was very high. At the highest Zn treatments, tissue concentrations was observed to reach in excess of 2000 mg/kg in some soils whereas Zn in shoots for uncontaminated soils was in the range (11.1–37.4 mg/kg). For the combined dataset (all soils), the logarithm of Zn concentration in shoot was found to be proportional to the added Zn. For spiked soils, this is the expected outcome. Total Zn concentrations in soils are a key factor in predicting concentration of Zn in soil, although other soil factors influence uptake. At each nominal loading, the variation between soils is considerable. Thus, the variation around the line-of-best fit is considerable (R2 ¼0.50) when all soils are plotted. In contrast, measured pore-water Zn was shown to have a stronger relationship with Zn concentration in shoot (R2 ¼0.78). Despite its high solubility, the total Zn loading required to cause a phytotoxic response was high. Dose–response curves fitted well with a R2 obtained from SPSS of 0.84–0.98 excluding soil WR (Table 2). In soil WR, the highest Zn loading did not cause serious reduction in dry matter production, and so fitted logistic functions showed a poor fit in this soil. This is also reflected in the high confidence interval range of the EC50 for that soil. The calculated EC50 values ranged from 335 mg/kg to 410,000 mg/kg Zn. In soil WR, the highest added dose of 10,000 mg/kg did not reduce cucumber growth by 50%. Soil WR is a calcaric soil with high pH, high carbonate content, CEC and organic carbon. As a result, Zn sorption in this soil was very high, reducing Zn solubility in soil pore-water. Pore-water data shows that Znpw and Zn2 þ were 115 and 9.52 mM at 10,000 mg/kg, respectively. This soil also possessed moderate clay and organic carbon contents. The highest measurable EC50 was in soil PB (6353 mg/kg) which was also alkaline. In our dataset, only two soils had estimated EC50 values below 1000 mg/kg (SN, KB). Both SN and KB soils had a low pHca of approximately 4.5. In contrast to EC50 values, EC10 and EC20 values were mostly below 1000 mg/kg. The EC20 values ranged from 226 (65–351) mg/kg to 8725 (0–36,458) mg/kg. The EC10 values ranged from 179 (SN) to 5214 (WR) mg/kg. The lowest ECx (x ¼10%, 20% or 50% reduction) values were in all cases from the acidic Ferrosol SN. The ECx data for Zn are similar in magnitude to those previously reported (Warne et al., 2008a, 2008b). Warne et al. (2008b) reported Zn phytotoxicity data for 14 Australian soils for Triticum aestivum L (wheat). In the latter study, EC10 values ranged from 110 to 3300 mg/kg as added Zn. Overall, the EC10 values for Warne et al. (2008a, 2008b) are lower than those reported in the present study. The difference between studies may be attributed to differences in ageing time because we incubated the soils for approximately 6 weeks prior to commencement of plant exposure, whereas Warne et al. (2008b) used freshly spiked soils by germinating plants 7 days after spiking. In addition, wheat may be more sensitive to Zn than cucumber. Unpublished work in solution culture from our laboratory showed that cucumber was more sensitive than wheat, ryegrass and sunflower, which was the principal criteria for selecting cucumber as the test species. In addition, soil pHca in our study was also overall higher than that of Warne et al. which would also increase the ECx data overall expressed on a total soil concentration (w/w) basis. Zinc toxicity to plants, invertebrates and microbial communities have been related to soil pH and CEC as semi-empirical transfer functions (Impellitteri et al., 2003; Saxe et al., 2001; Warne et al., 2008b). Cation Exchange Capacity has increasingly
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Table 4 Semi-empirical relationships between solution and biological end-points. Included are non-linear with RG % (relative growth) and multiple linear regression. Equation
Toxicity endpoint
Phase
2
RG
General Form
Regression equation
df
Adj. R2
96
0.596
p
100 1 + ek (SE)(EC50 (SE)− log Znadd 100 1 + e−2.761 (0.436)(3.218 (0.061)− log Znadd
3
RG
Solid
4
RG
Solution
100
96
0.784
96
0.803
82 82 82 89 89 88 88 88 74 74 73 73 73
0.659 0.844 0.881 0.453 0.712 0.96 0.96 0.989 0.822 0.843 0.594 0.840 0.858
5
RG
Solution
1 + e−1.184 (0.262)×(−3.350 (0.084)− log Znpw ) 100 + −1.489 (0.201)×(−4.102 (0.094)− log Zn2 pw) 1+e
6 7 8 9 10 11 12 13 14 15 16 17 18
Log Znpw Log Znpw Log Znpw pZn pZn pZn pZn pZn Shoot Zn Shoot Zn Shoot Zn Shoot Zn Shoot Zn
Solid Solid Solid Solid Solid Solution Solution Solution Solid Solid Solution Solution Solution
0.8.290(0.326) þ 1.473(0.117)log Znadded 4.041(0.483) þ1.340(0.080)log Znadded 0.572(0.058)pHpw 1.751(0.617) þ1.226(0.073) log Znadded 0.635(0.052) pHpw 0.878pDOC 9.1718 (0.498) 1.478 (0.178)Znadded 3.307þ 0.803(0.093)pH 1.320(0.130) Znadded 0.475(0.115) 1.111((0.025) log Znpw 1.641(0.116) 1.170(0.016) 0.800(0.065)pDOC 0.974(0.189) 1.119(0.019) 0.677(0.066)pDOC þ 0.099(0.023)pH 3.079(0.180) þ 0.671 log Znadded 0.361(0.035)pHpw 2.192(0.637) þ 0.726(0.044) log Znadded 0.364(0.032) pHpw 0.228(0.070)log Kpw 4.206(0.191) 0.346(0.033)pZn 4.021(0.029) þ0.555(0.029)log Znpw 0.253(0.071)log Kpw 3.526(0.255) þ 0.572(0.028)log Znpw 0.252(0.066)log Kpw þ 0.319(0.090)pDOC
been shown to relate to metal(loid) sorption, uptake and toxicity threshold values in soil. Although heavy metals such as Cu and Zn are well known to bind to soil by specific sorption mechanisms (that is, not by charge alone), CEC can be viewed as a parameter that relates properties of the soil associated with specific bonding sites. Negative charge in soil is related to changes in organic matter, Fe/Mn oxide content, clay mineralogy and pH. Therefore, as CEC encapsulates many soil properties that are correlated to metal solubility, it can be expected to relate to toxicity data. However, in our study, only soil pH measures were related to ECx Zn data. Clay content, CEC, and organic carbon were not consistently related to any toxicity Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw were in general related to Zn ECx data. For all pH estimates, the strongest relationship was found for EC50 data. Estimated EC10 and EC20 were related to pHw and pHpw but pHca was the best predictor of EC10, 20 and 50 data. The EC10 and EC20 are less reliably estimated as indicated by the confidence intervals in Table 2. At low concentrations there is more variation. However, the lack of a statistically significant relationship with soil parameters is likely due to the modest sample size (n¼ 10) and the large variation in our soil data set. 3.3. Aqueous chemodynamics of Zn and plant growth The dose response relationship to pore-water Zn and modelled Zn2 þ activity is shown in Fig. 1. The EC10, EC20 and EC50 data for each soil is shown in Table 3. The EC50 of Znpw in these soils varied between 411 and 1038 mM for soils BK, DU, KB, MG, TA, and YE. The alkaline soils PB and WR had much lower EC50 Znpw values of 235 to 354 mM. Soils of SN and MI had much lower EC50 values despite large differences in the solution chemistry of the two soils. The EC10 and EC20 calculations depend on the estimated EC50 in addition to parameter a and slope parameter k. The EC10 values ranged from 11.01 (YE) to 543.3 (TA) mM and EC20 values from 41.88 (YE) to 774.5 (TA) mM. Soil SN produced ECx pore-water values which were unexpectedly low based on soil pH and the trend from our dataset. The EC10, EC20 an EC50 were respectively 0.928, 1.48 and 5.45 mM. These values are similar but lower than those found in the alkaline soils of WR and PB but do not follow the overall trend of ECx with pH and ionic strength. The data for this soil is in approximate agreement with data reported for acidic oxisols and ferrosols for
o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001
agricultural plant species previously based on total Zn loading levels in soil (Warne et al., 2008a, 2008b). For example, the EC10 value for this soil was 179, which is consistent with Warne et al. (2008b) for acidic Fe oxide rich soils EC10 (o 500 mg/kg). However, there is limited soil pore-water Zn data relating to phytotoxicity parameters in the literature from which to compare. Thus we suspect that acidic cations such as Fe, Al or Mn may play a role on estimated toxicity data. Our data indicate that Mn may have influenced estimated Zn porewater for soil SN (data not shown). The native Mnpw and Mn2 þ in this soil were estimated to be 33.3 and 6.75 mM, respectively. Pore-water Mn and Mn2 þ increased with increasing Zn loading to maximum values of 355 and 58.2 mM, respectively. Furthermore, the ratio of [Mn]pw/[Zn]pw and Mn2 þ /Zn2 þ was greater than 1 until after Zn EC50 (total) value for this soil. The high native Mn that was present and the associated increase with Zn addition complicates the interpretation. Concentrations of Mn in pore-water of soil SN are in the low range that has been shown to cause phytotoxicity in agricultural plant species. Reichman et al. (2004) reported Zn EC50 values in nutrient culture at pH of 5 in Australian tree species in the range of 5.0–330 mM. Reported Mn toxicity thresholds are from approximately 1 mM upwards in dilute nutrient culture. However, most literature values suggest higher plant tolerance to Mn in nutrient culture (Kopittke et al., 2011; Reichman et al., 2004). An increase of dissolved Mnpw occurred with increasing Zn. The Mnpw and Mn2 þ solution values at which there was a 50% reduction in growth range from 0.32 (MI) to 62 mM (TA). In the alkaline soils WR and PB pore-water Mn was not high enough to estimate ECx data. The Mn2 þ values are often several times higher than soil SN, which had a Mn EC50 of 4.932 mM. This is almost equivalent to the Zn2 þ EC50 of 5.445 mM, the ratio of Zn2 þ /Mn2 þ was 1.1. Therefore, in soil SN it is particularly difficult to determine whether Zn2 þ was the cause of growth reductions or Mn2 þ . This contrasts with the Zn2 þ /Mn2 þ of the remaining soils (ratio¼5.8–80). The concentration at EC50 for Zn2 þ was substantially higher than Mn2 þ and likely to be the cause of growth reductions in the other soils. In addition, the high Zn2 þ /Mn2 þ ratio of the other soils may potentially provide a protective effect to Mn2 þ . This is the focus of current work in our laboratory. However, given the high Mn in pore-waters for the majority of our soils due to Zn-induced desorption, Mn may contribute in some way to the response of cucumber. Pore-water Zn2 þ phytotoxicity thresholds for the dataset as a
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culture studies (Reichman et al., 2001). 3.4. Semi-empirical relationships
Fig. 3. Relationship between relative growth (%) and pore-water Zn concentrations and pore-water Zn2 þ activity for all 10 soils together. Dashed line indicates fitted parameter (a). Solid line indicates parameter a¼ 100.
whole were related to pH when soil SN was excluded (Fig. 2). The estimated EC50 and EC10 values tended to decrease as the soil pHca and pHpw increased. It should be noted that pHw was also related to ECx, but R2 were lower than pHca and pHw. This is in some respects is expected, as pHCa and pHpw should reflect soil pH more closely than pHw (White, 2009). Similarly, EC10 followed by EC50 showed the strongest relationship to pHca and pHpw. Numerous parameters in pore-water change over the pH range in this study, most notably, the H þ activity, inorganic carbon concentration, carbonate speciation and dissolved organic matter concentrations and surface charge. The biotic ligand model broadly predicts that as H þ decreases, there is a decrease in competition at the biotic ligand site, resulting in enhanced uptake to the biological organ, in this case, the plant root (Antunes et al., 2006; Di Toro et al., 2001). The phenomenon is parallel with sorption of Zn to soil sites, with the well-known trend of increased sorption as pH is increased. The free ion activity model qualitatively predicts that toxicity should occur at relatively constant activity of a metal cation (McBride, 2001). In our study, the estimated Znpw and Zn2 þ activity varies between our 10 soils, with the variation in some cases being as large as that reported between plant species in nutrient
Zinc speciation in soil is determined by numerous soil factors. In an attempt to understand the key factors controlling solubility and toxicity, we used least squares regression analysis. For relative shoot growth, expressed as a percentage of control weight, we first fit RG (dry weight) against Zn concentration in soil. Zinc in soil was expressed as log10 total added Zn (mg/kg), pore-water (mM), concentrations or Zn2 þ activity (mM). When all 10 soils are collated, Zn levels in soil could significantly describe the relative growth (%) of cucumber using logistic regression in the same manner as the 2 was low individual soils. However, for total added Zn, the Radj (0.596) (Table 4), as there was significant spread in the dataset. Pore-water Zn and Zn2 þ , however, described the full dataset well (Table 4; Fig. 3), with dissolved Znpw and Zn2 þ described 78% and 80.3% of the variation in RG (%), respectively. When the whole data set is used, the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Previous studies have generally used multiple linear regression analysis to describe key soil factors that influence Zn toxicity. Smolders et al. (2004) studied Zn toxicity on soil invertebrates. The latter study reported that total Zn concentration in addition to soil pH and CEC were overall good predictors of Zn to invertebrate toxicity. The results of Smolders et al. support previous work (Impellitteri et al., 2003; Sauvé et al., 2000) who reported relations with soil pH and other factors such as CEC. Few have focussed extensively on pore-water chemistry across many treatments, and thus there are few papers predicting toxicity based on pore-water chemistry. Pore-water concentrations of Zn have thus been used infrequently as a predictor of toxicity. Beesley et al. (2010) studied pore-water chemistry in a multiple contaminated site (arsenic, cadmium and zinc) and related their data to extractability not directly to toxicity end-points. Indeed, to understand toxicity processes in mixed contaminant sites, interactions with pore-water are necessary, as total concentrations in soil reveal little detail. Knowledge of single contaminant toxicology and chemistry is essential before understanding mixed contaminated soils. This study has shown that pore-water Zn could predict phytotoxicity in several soils using logistic regression. Multiple regression analysis of Znpw and pZn ( log Zn2 þ activity) could be predicted by soil properties (Table 4). Total added Zn, soil pHpw and pDOC were the best predictors of Znpw and Zn2 þ in pore-water. Sauvé et al. (2000) reported that total Zn and pH (in a suspension) effectively described Zn Kd values in a range of soils. This to some extent agrees with the present work. Surprisingly, DOC concentration, whilst not correlated in simple linear correlation, was a significant variable when predicting both Zn in porewater and Zn concentrations in shoot. In general, Zn is commonly considered to not bind strongly with DOC in soil, and is often considered to be less important in controlling Zn in comparison to Cu, for example (Sauve et al., 1998). The fitting constant for pDOC was negative, indicating that lower DOC resulted in higher Zn in pore-water. The relatively high pore-water concentrations observed may explain this relationship, as DOC ranged from 52.4 to 549 mg/L in the control samples. However, when a solution-only model was used to predict Zn in shoot DOC was negatively related, indicating a reduction in uptake/translocation of Zn with increasing DOC. Interestingly, the measured pore-water potassium (K) was also a significant parameter describing Zn uptake to cucumber shoots. Potassium tended to stay relatively constant in pore-water, or, in some soils, increase with increasing Zn addition. This indicates that K may have a competing effect on Zn uptake or translocation in cucumber. Generally, divalent cations have been associated with reduced uptake of metals such as Ca and Mg
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(Cheng and Allen, 2001; Lock et al., 2007). In a study on Cu, uptake kinetics to roots of Bothriochloa macra was not reduced by Ca or K despite 3-fold higher concentration in solution (Lamb et al., 2012). Most studies on interactions with cations are based on nutrient culture and not soil pore-water. In our study, the relationship between Zn and K only occurred in 2 soils, but it may have influenced the overall relationship.
4. Conclusions Zinc contamination of soil poses a threat to ecological receptors. In this study we examined Zn phytotoxicity in a range of soils as function of total Zn loading and, moreover, Zn pore-water properties. In terms of Zn loading, the highest measurable EC50 was in soil PB, which was also alkaline, at 6353 mg/kg. In our dataset, only two soils had estimated EC50 values below 1000 mg/ kg (SN, KB). Both SN and KB soils had very low pHca of approximately 4.5. The EC10 values ranged from 179 (SN) to 5214 (WR) mg/kg. The soil that produced the lowest ECx values was in all cases SN soil, which is an acidic Ferrosol. In our study, only soil pH measures in soil was related to ECx Zn data, and CEC, clay content and organic carbon not consistently related to Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw was in general related to Zn ECx data. However, one Ferrosol was removed from the relationship, as Mn appeared to have added complexity to the toxicity parameter. Dissolved Znpw and Zn2 þ successfully described 78% and 80.3% of the variation in RG (%). When the whole data set is used, the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Total added Zn, soil pHpw and pDOC were the best predictors of Znpw and Zn2 þ in pore-water. When a solution-only model was used to predict Zn in shoot the DOC was negative, indicating a reduction in uptake/ translocation of Zn with increasing DOC.
Acknowledgements The authors thank Mr Rayhan Mahbub, Mr. Ramkrishna Nirola and Ms. Sedigheh Abbasi for their valuable assistance in soil sampling. This research was funded through Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE Pty Ltd).
References Antunes, P.M.C., Berkelaar, E.J., Boyle, D., Hale, B.A., Hendershot, W., Voigt, A., 2006. The biotic ligand model for plants and metals: technical challenges for field application. Environ. Toxicol. Chem. 25 (3), 875–882. Beesley, L., Moreno-Jimenez, E., Clemente, R., Lepp, N., Dickinson, N., 2010. Mobility of arsenic, cadmium and zinc in a multi-element contaminated soil profile assessed by in-situ soil pore water sampling, column leaching and sequential extraction. Environ. Pollut. 158 (1), 155–160. Broos, K., Warne, M.S.J., Heemsbergen, D.A., Stevens, D., Barnes, M.B., Correll, R.L., McLaughlin, M.J., 2007. Soil factors controlling the toxicity of copper and zinc to
259
microbial processes in Australian soils. Environ. Toxicol. Chem. 26 (4), 583–590. Cheng, T., Allen, H.E., 2001. Prediction of copper form solution by lettuce (Lactuca sativa Romance). Environ. Toxicol. Chem. 20, 2544–2551. Di Toro, D.M., Allen, H.E., Bergman, H.L., Meyer, J.S., Paquin, P.R., Santore, R.C., 2001. Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environ. Toxicol. Chem. 20 (10), 2383–2396. Gillman, G., Sumpter, E., 1986. Modification to the compulsive exchange method for measuring exchange characteristics of soils. Soil Res. 24 (1), 61–66. Heemsbergen, D.A., Warne, M.S.J., Broos, K., Bell, M., Nash, D., McLaughlin, M., Whatmuff, M., Barry, G., Pritchard, D., Penney, N., 2009. Application of phytotoxicity data to a new Australian soil quality guideline framework for biosolids. Sci. Total Environ. 407 (8), 2546–2556. Impellitteri, C.A., Saxe, J.K., Cochran, M., Janssen, G.M., Allen, H.E., 2003. Predicting the bioavailability of copper and zinc in soils: modeling the partitioning of potentially bioavailable copper and zinc from soil solid to soil solution. Environ. Toxicol. Chem. 22 (6), 1380–1386. Kopittke, P.M., Blamey, F.P.C., Wang, P., Menzies, N.W., 2011. Calculated activity of Mn2 þ at the outer surface of the root cell plasma membrane governs Mn nutrition of cowpea seedlings. J. Exp. Bot. 62 (11), 3993–4001. Krishnamurti, G.S.R., Naidu, R., 2002. Solid–solution speciation and phytoavailability of copper and zinc in soils. Environ. Sci. Technol. 36 (12), 2645–2651. Lamb, D., Ming, H., Megharaj, M., Naidu, R., 2009. Heavy metal (Cu, Zn, Cd and Pb) partitioning and bioaccessibility in uncontaminated and long-term contaminated soils. J. Hazard. Mater. 171 (1–3), 1150–1158. Lamb, D.T., Naidu, R., Ming, H., Megharaj, M., 2012. Copper phytotoxicity in native and agronomical plant species. Ecotoxicol. Environ. Safety 85 (0), 23–29. Lamb, D.T., Matanitobua, V.P., Palanisami, T., Megharaj, M., Naidu, R., 2013. Bioavailability of barium to plants and invertebrates in soils contaminated by barite. Environ. Sci. Technol. 47 (9), 4670–4676. Lock, K., Janssen, C.R., 2001. Modeling zinc toxicity for terrestrial invertebrates. Environ. Toxicol. Chem. 20 (9), 1901–1908. Lock, K., Criel, P., De Schamphelaere, K.A.C., Van Eeckhout, H., Janssen, C.R., 2007. Influence of calcium, magnesium, sodium, potassium and pH on copper toxicity to barley (Hordeum vulgare). Ecotoxicol. Environ. Safety 68, 299–304. McBride, M., Sauve, S., Hendershot, W., 1997. Solubility control of Cu, Zn, Cd and Pb in contaminated soils. Eur. J. Soil Sci. 48 (2), 337–346. McBride, M.B., 2001. Cupric ion activity in peat soil as a toxicity indicator for maize. J. Environ. Qual. 30 (1), 78–84. McBride, M.B., Pitiranggon, M., Kim, B., 2009. A comparison of tests for extractable copper and zinc in metal-spiked and field-contaminated soil. Soil Sci. 174 (8), 439–444. Rayment, G., Higginson, F., 1992. Australian Laboratory Handbook of Soil and Water Chemical Methods. Inkata Press Pty Ltd., Melbourne. Reichman, S.M., Asher, C.J., Mulligan, D.R., Menzies, N.W., 2001. Seedling responses of three Australian tree species to toxic concentrations of zinc in solution culture. Plant Soil 235 (2), 151–158. Reichman, S.M., Menzies, N.W., Asher, C.J., Mulligan, D.R., 2004. Seedling responses of four Australian tree species to toxic concentrations of manganese in solution culture. Plant Soil 258 (1–2), 341–350. Sauvé, S., Hendershot, W., Allen, H.E., 2000. Solid–solution partitioning of metals in contaminated soils: dependence on pH, total metal burden, and organic matter. Environ. Sci. Technol. 34 (7), 1125–1131. Sauve, S., McBride, M., Hendershot, W., 1998. Lead phosphate solubility in water and soil suspensions. Environ. Sci. Technol. 32 (3), 388–393. Saxe, J.K., Impellitteri, C.A., Peijnenburg, W.J.G.M., Allen, H.E., 2001. novel model describing trace metal concentrations in the earthworm, Eisenia andrei. Environ. Sci. Technol. 35 (22), 4522–4529. Smolders, E., Buekers, J., Oliver, I., McLaughlin, M.J., 2004. Soil properties affecting toxicity of zinc to soil microbial properties in laboratory-spiked and fieldcontaminated soils. Environ. Toxicol. Chem. 23 (11), 2633–2640. Warne, M.S.J., Heemsbergen, D., McLaughlin, M., Bell, M., Broos, K., Whatmuff, M., Barry, G., Nash, D., Pritchard, D., Penney, N., 2008a. Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models. Environ. Pollut. 156 (3), 707–714. Methods of soil analysis. Part 1. In: Gee, G.W., Bauder, J.W. (Eds.), Particle-size Analysis. Soil Science Society of America, Madison. Warne, M.S.J., Heemsbergen, D., Stevens, D., McLaughlin, M., Cozens, G., Whatmuff, M., Broos, K., Barry, G., Bell, M., Nash, D., Pritchard, D., Penney, N., 2008d. Modeling the toxicity of copper and zinc salts to wheat in 14 soils. Environ. Toxicol. Chem. 27 (4), 786–792. White, R.E., 2009. Principles and Practice of Soil Science: The Soil as a Natural Resource. John Wiley & Sons, Malden.
Contents lists available at ScienceDirect
Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
Pore-water chemistry explains zinc phytotoxicity in soil Mohammed Kader a,b,c,1, Dane T. Lamb a,b,c,n,1, Ray Correll a, Mallavarapu Megharaj a,b,c,1, Ravi Naidu a,b,c,1 a
Centre for Environmental Risk Assessment and Remediation, University of South Australia, Building X, Mawson Lakes, SA 5095, Australia Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of South Australia, Building X, Mawson Lakes, SA 5095, Australia c Global Centre for Environmental Remediation (GCER), Faculty of Science and Information Technology, The University of Newcaslte, Callaghan, NSW, 2308, Australia, Callaghan b
art ic l e i nf o
a b s t r a c t
Article history: Received 3 June 2015 Received in revised form 6 August 2015 Accepted 6 August 2015 Available online 20 September 2015
Zinc (Zn) is a widespread soil contaminant arising from a numerous anthropogenic sources. However, adequately predicting toxicity of Zn to ecological receptors remains difficult due to the complexity of soil characteristics. In this study, we examined solid–solution partitioning using pore-water data and toxicity of Zn to cucumber (Cucumis sativus L.) in spiked soils. Pore-water effective concentration (ECx, x ¼10%, 20% and 50% reduction) values were negatively related to pH, indicating lower Zn pore water concentration were needed to cause phytotoxicity at high pH soils. Total dissolved zinc (Znpw) and free zinc (Zn2 þ ) in soil-pore water successfully described 78% and 80.3% of the variation in relative growth (%) in the full dataset. When the complete data set was used (10 soils), the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Total added Zn, soil pore water pH (pHpw) and dissolve organic carbon (DOC) were the best predictors of Znpw and Zn2 þ in pore-water. The EC10 (total loading) values ranged from 179 to 5214 mg/kg, depending on soil type. Only pH measurements in soil were related to ECx total Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw were in general related to Zn ECx. Similarly, when a solution-only model was used to predict Zn in shoot, DOC was negatively related to Zn in shoot, indicating a reduction in uptake/ translocation of Zn from solution with increasing DOC. & 2015 Elsevier Inc. All rights reserved.
Keywords: Soil solution Soil toxicology Dissolved organic carbon Plants
1. Introduction Zinc (Zn) is an essential trace element for most organisms and is pervasive in the soil environment. Contamination of the soil environment with excessive Zn occurs from a variety of sources, including mining operations, transportation of Zn ore bodies, smelting and Zn plating industries (Lamb et al., 2009). In addition, high Zn levels have been found in soils below galvanised objects (Lock and Janssen, 2001). At metal(loid) contaminated sites, Zn is commonly found at proportionally high concentrations in comparison to other metal(loid)s, such as arsenic, cadmium, lead and copper. Although Zn is essential for numerous functions within organisms, an excess of Zn can result in toxicity. Zinc is required in exceedingly high concentrations in soil to cause Zn toxicity in n Corresponding author at: Global Centre for Environmental Remediation (GCER), Faculty of Science and Information Technology, The University of Newcaslte, Callaghan, NSW, 2308, Australia. E-mail address: [email protected] (D.T. Lamb). 1 Current address: Faculty of Science and Information Technology, The University of Newcastle, ATC Building, Callaghan, NSW 2308, Australia.
http://dx.doi.org/10.1016/j.ecoenv.2015.08.004 0147-6513/& 2015 Elsevier Inc. All rights reserved.
humans. Toxicity to ecological receptors is however a serious problem in Zn contaminated sites. Zinc is a relatively mobile trace element in aerobic soil environments in comparison to other transition series metals such as Cu and Pb (McBride et al., 1997). Preliminary assessment of Zn contaminated sites are first made with measurement of the total soil concentrations. It is commonly acknowledged within the literature that total soil Zn is not necessarily a good indicator of toxicity (McBride et al., 1997). Speciation of Zn in different solid-phases, either as slag or crystalline mineral phases, can alter expected relations with total Zn loading. Nevertheless, Zn loading has often been shown to be a necessary indicator of Zn in soil solution and toxicity to ecological receptors. Indeed, despite the recently updated guideline values for Zn in soil, trigger values are still expressed on total (w/w) basis (Heemsbergen et al., 2009). Studies on Zn toxicity to plants (McBride et al., 2009), invertebrates (Lock and Janssen, 2001) and microorganisms (Broos et al., 2007; Smolders et al., 2004) predominantly focus on total concentrations. Toxicity end points have been reported using dose–response studies in the laboratory (Warne et al., 2008b) and in short-term field studies (Heemsbergen et al., 2009; Warne et al.,
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Table 1 Properties of experimental soils used for the phytotoxicity experiment. FC (%) is field capacity of soil. Soil location
Soil code
pHw
pHpw
% Clay
CEC (cmol(þ )/kg)
% OC
FC %
Zn content (mg/kg)
Feox (g/kg)
Alox (g/kg)
Mnox (g/kg)
Brookland, QLD Dublin, SA Kersbrook, SA Mount Gambier, SA Millicent, SA Port Broughton, SA South Nanango, QLD Tarrington, Vic Wallaroo, SA Yenda, NSW
BK DU KB MG MI PB SN TA WR YE
7.01 7.76 5.05 6.29 7.42 8.72 5.2 5.31 8.08 8.09
6.76 7.98 5.74 6.86 8.09 8.20 6.20 6.06 8.23 7.95
20.0 7.50 20.0 16.3 10.0 6.70 36.0 10.0 17.5 62.1
20.9 7.36 7.26 24.1 29.1 5.79 5.33 11.7 19.3 24.2
2.99 5.49 1.48 8.37 3.86 1.76 3.49 4.98 3.54 1.14
28.8 15.7 25.6 37.1 28.4 17.9 31.6 26.9 26.9 31.2
23.1 13.5 14.5 51.9 34.4 18.3 25.7 23.1 35.9 39.9
3.49 0.64 1.72 12.49 0.43 0.28 2.68 3.12 0.47 1.47
1.11 0.74 2.13 12.60 2.27 0.50 1.87 3.01 1.38 1.23
0.632 0.133 0.045 0.302 0.0252 0.060 0.240 0.212 0.237 0.296
Table 2 Phytotoxicity threshold data expressed as total Zn loading (mg/kg) with confidence intervals (95%), R2 values for dose–response curves (Eq. 1) and EIL values calculated for High Conservation areas and Urban Residential and Open Space land uses. Soils
High conservation
Urban
EC50
EC20
BK DU KB MG MI PB SN TA WR YE
85 65 45 65 130 60 45 50 100 110
230 150 80 150 390 130 75 100 290 340
1334 (1175–1514) 1972 (1607–2421) 685 (546–859) 2483 (2198–2805) 2911 (2080–4083) 6353 (5272–7656) 335 (253–443) 1416 (1159–1730) 4 10,000a 1578 (1253–1982)
807 1361 357 1774 940 3839 226 948 8725 640
a
R2
EC10 (588–1020) (190–1976) (135–561) (1262–2204) (368–1763) (2060–5417) (65–351) (536–1320) (0–36,458) (331–1002)
601 1095 243 1457 485 2859 179 750 5214 377
(393–809) (54–1754) (60–437) (912–1913) (134–1079) (1189–4437) (30–307) (341–1126) (0–28,601) (152–672)
0.96 0.84 0.88 0.95 0.88 0.84 0.90 0.89 0.50 0.93
Highest treatment of 10,000 mg/kg Zn did not cause a 50% reduction from control. At 10,000 mg/kg Zn, a % reduction was observed.
2008a). Studies reporting empirical regression models have typically shown that total concentrations in soil, soil pH, organic matter and cation exchange capacity (CEC) are the key soil properties describing Zn toxicity to biota. Few of these studies have related solubility, bioavailability or bioaccessibility estimates to toxicity directly. In particular, few, if any, report soluble or porewater data in relation to ecotoxicity data sets (Beesley et al., 2010). Smolders et al. (2004) studied the effect of increasing Zn dose to microbial processes in soil. They measured water-extractable Zn but did not report concentrations as related to soil microbial processes. In this study, we studied Zn phytotoxicity to Cucumber (Cucumis sativus L.) in 10 contrasting soils in a dose–response experimental design. We extracted pore-water from soil from each treatment and measured soluble Zn in addition to other solution properties, including soil pH, dissolved carbon, chloride and sulphate.
2. Materials and methods 2.1. Soils and study design Ten soils were selected for study from across Australia, including South Australia, New South Wales, Queensland and Victoria. All samples were sampled from the top 0–0.2 m of each profile, air-dried and sieved through 4 mm sieves initially and later through 2-mm. With the exception of soil YE, which had minimal cultivation, no soils had a history of cultivation. Soil organic carbon was determined using a LECO TOC analyser (TruMac CNS). For soil with a pHwater 46, the TOC was determined with and without addition of HCl (TOCHCl). Thus for soils that were neutral to alkaline, soil organic carbon was determined by subtraction of TOCHCl from TC. Cation Exchange Capacity was determined by the modified compulsive exchange method (Gillman and Sumpter, 1986).
The ‘amorphous’ Fe, Al and Mn oxide content was determined with acid oxalate method (pH ¼3) (Rayment and Higginson, 1992) and clay content using the hydrometer method (Gee and Bauder, 1986). Soil properties are presented in Table 1. Soil pH in the two Ferrosols and Kursols (SN and TA) had the lowest soil pHw (water) (5.05 to 5.31), whilst pHw was 8.72 in soil PB. The pore-water pH (pHpw) differed (see below) in some cases to pHw by up to 0.8 pH units from estimates made on the same soil. Soil organic carbon ranged from 1.14 in Yenda (YE) soil to 8.37 in the Mount Gambier (MG) soil. Clay contents were in general below 20%, however the Vertosol (YE) had high clay content (62%). The CEC ranged from 5.79 (PB) to 29.1 (MI) cmol( þ)/kg. Oxalate extractable Fe content was highest in the Mount Gambier soil and moderately high in the two Ferrosols (TA, SN). 2.2. Toxicity study Soils (air-dried and sieved through 2-mm sieve) were weighed to plastic trays and spread to a thin layer ( 3 cm) and Zn solution sprayed. A spiking solution was prepared that contained the required amount of zinc sulphate to achieve the required soil concentrations. Soil concentrations ranged from 100 to 10,000 mg/kg Zn, although some soils were spiked in a more narrow range to low pH (100 to 5000 mg/kg). To construct dose–response curves, it is ideal to expose organisms at very high levels to achieve a curve ranging from 0% to 100% response. The soil was then sprayed with the spiking solution and mixed thoroughly using a stainless steel trowel. After mixing, the soil was again spread evenly over the tray and the procedure repeated. This continued until all spiking solution was dispensed. Treated soils were then placed in plastic containers and mixed with a mechanical mixer for 5–10 min. The water content of all soils was adjusted to 70% of the estimated field capacity. Soils were placed in 10 L plastic containers with loosely placed lids and incubated for 6 weeks.
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Fig. 1. Response of C. sativus growth to increasing dissolved Zn in porewater expressed as [Zn]pw (dissolved) and Zn2 þ (modelled free ion activity of Zn).
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Table 3 EC 20 and EC10 parameters for Znpw and Zn2 þ from Eq. (1) based on dry weights.
BK DU KB MI MG PB SN TA WR YE
2 Zn+ pw EC50 (lM)
2 Zn+ pw EC10 (lM)
2 Zn+ pw EC20 (lM)
Znpw EC50 (lM)
Znpw EC10 (lM)
Znpw EC20 (lM)
191.4 151.7 182.8 5.754 258.2 26.00 5.445 358.1 15.52 132.7
14.22 15.49 182.8 0.6561 59.43 4.797 0.928 137.4 1.55 2.371
37.15 35.98 52.48 1.462 102.1 8.954 1.483 195.4 7.943 10.47
837.5 1009 935.4 5.745 1038 354.8 34.91 1419 235.0 411.2
113.7 138.1 104.5 0.656 220.3 59.16 3.447 543.3 68.39 11.01
237.7 287.7 234.4 1.462 390.0 128.8 8.101 774.5 107.9 41.88
(80.73–453.9) (40.18–571.5) (116.7–285.8) (1.528–22.13) (168.3–397.2) (12.71–53.21) (1.040–28.51) (184.1–696.6) (6.808–35.31) (32.73–538.3)
(0.3707–81.66) (138,700–209.9) (1.528–79.43) (30.06–9.750) (6.998–152.8) (0.00001–21.63) (0.0018–12.88) (0.00002–434.5) (35.31 –533.3) (0.000–53.70)
(2.704–154.2) (6855–304.1) (7.568–127.4) (10–13.09) (22.65–217.3) (0.0020–30.13) (0.0189–17.87) (4.169–517.6) (35.31–106.7) (0.0015–125.9)
Triplicate samples (300 g of air-dried 2-mm sieved soil) were placed into plant pots lined with nylon mesh for each treatment. Soils were wet from the bottom with deionised water for 24 h and cucumber seeds (C. sativus L.) were sown (10 per pot). Soils were watered to maintain 80–100% of the measured field capacity by weight of each soil. After 28 days of growth, plants were harvested by cutting shoots 1 cm above the soils. Fresh weights, heights and dry weights were recorded. Plants were dried at 70 °C for 72 h and then crushed and digested in concentrated nitric acid after overnight cold digestion.
2.3. Pore-water extraction and modelling At the end of the experiment plant pots were allowed to dry in the greenhouse. Soils were wet to low moisture content (o15– 20% w/w) 3–5 days prior to pore water extraction (Lamb et al., 2013). Twenty-four hours before extraction, the soils were wet to approximately field capacity from the bottom by placing the pot in a tray of deionised and allowing moisture to move upwards. Water added to the bottom reservoir to soils (i.e. clay soils) if required. Pore-water was extracted using the double chamber method (Gillman and Sumpter, 1986; Lamb et al., 2009) To extract sufficient volume of pore-water, moist soil was weighed into the barrels of three 30 or 35 mL syringes with acid cleaned glass wool at the bottom to provide a coarse filter. The solutions from each tube were pooled to create a composite porewater sample. Solutions were then filtered (0.45 mm) for analysis. Composite pore-water samples were separated for measurement of metal concentrations (Na, Mg, Al, K, Ca, Mn, Fe, Cu, and Zn), anions (Cl , NO−3 , SO−4 2), dissolved organic carbon (DOC) and pHpw. Pore-water and plant digested samples were analysed for total metal concentrations by ICP-MS (Agilent 7500c) after appropriate dilutions and matrix considering standards. Quality control measures were taken in every steps of sample preparation and analysis. During pore-water extraction, control soils and blank (purified water) were carried out and even during analysis 50 mg/L standards and blanks were run in every 20 samples in sample sets. Pore-water analysis data were used as input data for modelling in the WHAM 7 model to measure Zn2 þ . All solutions were modelled at 22 °C. The inorganic carbon chemistry was all modelled by equilibrating each solution atmospheric CO2 at a partial pressure of 3.2 10 4 atm. WHAM allows for detailed input for DOC fractions of fulvic acid and humic acid, however we used the default parameters for fulvic acid, allowing 100% of measured DOC to be considered as fulvic acid. All Fe was assumed to be Fe(III) and allowed to precipitate – this was observed to have occurred in many solutions. No solid-phase partitioning was included in any models.
(566.2–1239) (324.3–3148) (516.4–1698) (1.528–21.63) (86.10– 12,330) (193.6–651.6) (16.07–76.03) (722.8–2786) (44.46–1239) (126.8–1337)
(22.08–293.1) (0–1327) (0–415.9) (0.97–30.06) (45.60–512.9) (0.009–89 106) (4.790–7590) (0.000–452.0) (142.6–827.9) (0.01–141.6)
(73.11–498.9) (0.000– 1824) (0.000–698.2) (1.00–13.09) (125.6–762.1) (0.005–1.2 108) (7.448– 111,400) (0.008–2072) (92.68–961.6) (0.3475–324.3)
2.4. Statistical analysis and modelling All statistical analysis was all performed using IBM SPSS (V21). Dose–response curves were fitted to all soils individually with a logistic function. The logistic model used was
Y=
a 1 + e k (x − c )
(1)
where a, k and c are constants that relate to intercept on the yvariable, k is a slope parameter and c is interpreted as the effective concentration causing a 50% reduction of variable y (EC50). In addition, in attempt to describe toxicity data for the full dataset of 10 soils, we modelled all data with a logistic curve. For this purpose, plant response was expressed as %Relative Growth (plant weight at each concentration/plant weight (control) (%RG) (a was set at 100). To explore relationships between soil properties and plant response, correlation analysis and step-wise multiple linear regression was utilised. Phytotoxicological parameters EC10, EC20 and EC50 were estimated for total Zn loading, pore-water concentration, and Zn2+ pw . All statistical parameters from dose–response and sorption curves are from SPSS. Parameter estimates from SPSS were used in Grapher 9 (Golden Software) to provide a depiction of the curve.
3. Results and discussion 3.1. Zinc partitioning and pore-water data Amongst trace metals, Zn is generally considered to be a mobile element in the soil environment. In our study, Zn sorption followed previously reported trends of soil properties. In general, increasing soil pH and clay content resulted in high sorption. Porewater Zn (Znpw) in control soils was in the range of 0.097 to 1.94 mM (mean7 SD¼ 0.537 0.55). Native pore-water Zn was very low with the highest Zn found in the most acidic soil at 1.94 mM. These values contrast with those of Krishnamurti and Naidu (2002) who reported dissolved Zn concentrations in saturation water extracts of 0.75–5.48 mM (mean7 SD¼ 2.800 71.369). Addition of Zn caused Zn in pore water to increase from approximately 1 mM to as high as 0.1 M in the 10,000 mg/kg Zn treatment. In most soils receiving 8000–10,000 mg/kg Zn there was a small reduction in pHpw which contributed to higher Zn solubility. Below such concentrations there was little effect on pHpw from ZnSO4 spiking. Concentrations in the toxicity range of most soils (100–4000 mg/kg Zn) showed no consistent trend towards acidification. In soil WRA, where severe phytotoxicity was not observed at any concentration, there was similarly no consistent pH decline; this was attributable to the high inorganic carbon content in this soil. In soil PB, at 8000 and 10,000 mg/kg Zn soil pHpw dropped by approximately 1 pH unit from 8.20 in the control.
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3.2. Zinc accumulation and phytotoxicity
Fig. 2. Relationship between Zn2 þ estimated EC10, EC20 and EC50 in porewater and pH measured in porewater (pHpw) and 10 mM CaCl2 (pHca).
Zinc solubility in the experimental soils was high with porewater concentrations at the highest treatments reaching over mM concentration range. The high Zn solubility in our soils resulted in significant uptake and translocation of Zn to cucumber shoots. The range of Zn concentration in cucumber shoots over the full spiking range was very high. At the highest Zn treatments, tissue concentrations was observed to reach in excess of 2000 mg/kg in some soils whereas Zn in shoots for uncontaminated soils was in the range (11.1–37.4 mg/kg). For the combined dataset (all soils), the logarithm of Zn concentration in shoot was found to be proportional to the added Zn. For spiked soils, this is the expected outcome. Total Zn concentrations in soils are a key factor in predicting concentration of Zn in soil, although other soil factors influence uptake. At each nominal loading, the variation between soils is considerable. Thus, the variation around the line-of-best fit is considerable (R2 ¼0.50) when all soils are plotted. In contrast, measured pore-water Zn was shown to have a stronger relationship with Zn concentration in shoot (R2 ¼0.78). Despite its high solubility, the total Zn loading required to cause a phytotoxic response was high. Dose–response curves fitted well with a R2 obtained from SPSS of 0.84–0.98 excluding soil WR (Table 2). In soil WR, the highest Zn loading did not cause serious reduction in dry matter production, and so fitted logistic functions showed a poor fit in this soil. This is also reflected in the high confidence interval range of the EC50 for that soil. The calculated EC50 values ranged from 335 mg/kg to 410,000 mg/kg Zn. In soil WR, the highest added dose of 10,000 mg/kg did not reduce cucumber growth by 50%. Soil WR is a calcaric soil with high pH, high carbonate content, CEC and organic carbon. As a result, Zn sorption in this soil was very high, reducing Zn solubility in soil pore-water. Pore-water data shows that Znpw and Zn2 þ were 115 and 9.52 mM at 10,000 mg/kg, respectively. This soil also possessed moderate clay and organic carbon contents. The highest measurable EC50 was in soil PB (6353 mg/kg) which was also alkaline. In our dataset, only two soils had estimated EC50 values below 1000 mg/kg (SN, KB). Both SN and KB soils had a low pHca of approximately 4.5. In contrast to EC50 values, EC10 and EC20 values were mostly below 1000 mg/kg. The EC20 values ranged from 226 (65–351) mg/kg to 8725 (0–36,458) mg/kg. The EC10 values ranged from 179 (SN) to 5214 (WR) mg/kg. The lowest ECx (x ¼10%, 20% or 50% reduction) values were in all cases from the acidic Ferrosol SN. The ECx data for Zn are similar in magnitude to those previously reported (Warne et al., 2008a, 2008b). Warne et al. (2008b) reported Zn phytotoxicity data for 14 Australian soils for Triticum aestivum L (wheat). In the latter study, EC10 values ranged from 110 to 3300 mg/kg as added Zn. Overall, the EC10 values for Warne et al. (2008a, 2008b) are lower than those reported in the present study. The difference between studies may be attributed to differences in ageing time because we incubated the soils for approximately 6 weeks prior to commencement of plant exposure, whereas Warne et al. (2008b) used freshly spiked soils by germinating plants 7 days after spiking. In addition, wheat may be more sensitive to Zn than cucumber. Unpublished work in solution culture from our laboratory showed that cucumber was more sensitive than wheat, ryegrass and sunflower, which was the principal criteria for selecting cucumber as the test species. In addition, soil pHca in our study was also overall higher than that of Warne et al. which would also increase the ECx data overall expressed on a total soil concentration (w/w) basis. Zinc toxicity to plants, invertebrates and microbial communities have been related to soil pH and CEC as semi-empirical transfer functions (Impellitteri et al., 2003; Saxe et al., 2001; Warne et al., 2008b). Cation Exchange Capacity has increasingly
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257
Table 4 Semi-empirical relationships between solution and biological end-points. Included are non-linear with RG % (relative growth) and multiple linear regression. Equation
Toxicity endpoint
Phase
2
RG
General Form
Regression equation
df
Adj. R2
96
0.596
p
100 1 + ek (SE)(EC50 (SE)− log Znadd 100 1 + e−2.761 (0.436)(3.218 (0.061)− log Znadd
3
RG
Solid
4
RG
Solution
100
96
0.784
96
0.803
82 82 82 89 89 88 88 88 74 74 73 73 73
0.659 0.844 0.881 0.453 0.712 0.96 0.96 0.989 0.822 0.843 0.594 0.840 0.858
5
RG
Solution
1 + e−1.184 (0.262)×(−3.350 (0.084)− log Znpw ) 100 + −1.489 (0.201)×(−4.102 (0.094)− log Zn2 pw) 1+e
6 7 8 9 10 11 12 13 14 15 16 17 18
Log Znpw Log Znpw Log Znpw pZn pZn pZn pZn pZn Shoot Zn Shoot Zn Shoot Zn Shoot Zn Shoot Zn
Solid Solid Solid Solid Solid Solution Solution Solution Solid Solid Solution Solution Solution
0.8.290(0.326) þ 1.473(0.117)log Znadded 4.041(0.483) þ1.340(0.080)log Znadded 0.572(0.058)pHpw 1.751(0.617) þ1.226(0.073) log Znadded 0.635(0.052) pHpw 0.878pDOC 9.1718 (0.498) 1.478 (0.178)Znadded 3.307þ 0.803(0.093)pH 1.320(0.130) Znadded 0.475(0.115) 1.111((0.025) log Znpw 1.641(0.116) 1.170(0.016) 0.800(0.065)pDOC 0.974(0.189) 1.119(0.019) 0.677(0.066)pDOC þ 0.099(0.023)pH 3.079(0.180) þ 0.671 log Znadded 0.361(0.035)pHpw 2.192(0.637) þ 0.726(0.044) log Znadded 0.364(0.032) pHpw 0.228(0.070)log Kpw 4.206(0.191) 0.346(0.033)pZn 4.021(0.029) þ0.555(0.029)log Znpw 0.253(0.071)log Kpw 3.526(0.255) þ 0.572(0.028)log Znpw 0.252(0.066)log Kpw þ 0.319(0.090)pDOC
been shown to relate to metal(loid) sorption, uptake and toxicity threshold values in soil. Although heavy metals such as Cu and Zn are well known to bind to soil by specific sorption mechanisms (that is, not by charge alone), CEC can be viewed as a parameter that relates properties of the soil associated with specific bonding sites. Negative charge in soil is related to changes in organic matter, Fe/Mn oxide content, clay mineralogy and pH. Therefore, as CEC encapsulates many soil properties that are correlated to metal solubility, it can be expected to relate to toxicity data. However, in our study, only soil pH measures were related to ECx Zn data. Clay content, CEC, and organic carbon were not consistently related to any toxicity Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw were in general related to Zn ECx data. For all pH estimates, the strongest relationship was found for EC50 data. Estimated EC10 and EC20 were related to pHw and pHpw but pHca was the best predictor of EC10, 20 and 50 data. The EC10 and EC20 are less reliably estimated as indicated by the confidence intervals in Table 2. At low concentrations there is more variation. However, the lack of a statistically significant relationship with soil parameters is likely due to the modest sample size (n¼ 10) and the large variation in our soil data set. 3.3. Aqueous chemodynamics of Zn and plant growth The dose response relationship to pore-water Zn and modelled Zn2 þ activity is shown in Fig. 1. The EC10, EC20 and EC50 data for each soil is shown in Table 3. The EC50 of Znpw in these soils varied between 411 and 1038 mM for soils BK, DU, KB, MG, TA, and YE. The alkaline soils PB and WR had much lower EC50 Znpw values of 235 to 354 mM. Soils of SN and MI had much lower EC50 values despite large differences in the solution chemistry of the two soils. The EC10 and EC20 calculations depend on the estimated EC50 in addition to parameter a and slope parameter k. The EC10 values ranged from 11.01 (YE) to 543.3 (TA) mM and EC20 values from 41.88 (YE) to 774.5 (TA) mM. Soil SN produced ECx pore-water values which were unexpectedly low based on soil pH and the trend from our dataset. The EC10, EC20 an EC50 were respectively 0.928, 1.48 and 5.45 mM. These values are similar but lower than those found in the alkaline soils of WR and PB but do not follow the overall trend of ECx with pH and ionic strength. The data for this soil is in approximate agreement with data reported for acidic oxisols and ferrosols for
o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 o 0.001
agricultural plant species previously based on total Zn loading levels in soil (Warne et al., 2008a, 2008b). For example, the EC10 value for this soil was 179, which is consistent with Warne et al. (2008b) for acidic Fe oxide rich soils EC10 (o 500 mg/kg). However, there is limited soil pore-water Zn data relating to phytotoxicity parameters in the literature from which to compare. Thus we suspect that acidic cations such as Fe, Al or Mn may play a role on estimated toxicity data. Our data indicate that Mn may have influenced estimated Zn porewater for soil SN (data not shown). The native Mnpw and Mn2 þ in this soil were estimated to be 33.3 and 6.75 mM, respectively. Pore-water Mn and Mn2 þ increased with increasing Zn loading to maximum values of 355 and 58.2 mM, respectively. Furthermore, the ratio of [Mn]pw/[Zn]pw and Mn2 þ /Zn2 þ was greater than 1 until after Zn EC50 (total) value for this soil. The high native Mn that was present and the associated increase with Zn addition complicates the interpretation. Concentrations of Mn in pore-water of soil SN are in the low range that has been shown to cause phytotoxicity in agricultural plant species. Reichman et al. (2004) reported Zn EC50 values in nutrient culture at pH of 5 in Australian tree species in the range of 5.0–330 mM. Reported Mn toxicity thresholds are from approximately 1 mM upwards in dilute nutrient culture. However, most literature values suggest higher plant tolerance to Mn in nutrient culture (Kopittke et al., 2011; Reichman et al., 2004). An increase of dissolved Mnpw occurred with increasing Zn. The Mnpw and Mn2 þ solution values at which there was a 50% reduction in growth range from 0.32 (MI) to 62 mM (TA). In the alkaline soils WR and PB pore-water Mn was not high enough to estimate ECx data. The Mn2 þ values are often several times higher than soil SN, which had a Mn EC50 of 4.932 mM. This is almost equivalent to the Zn2 þ EC50 of 5.445 mM, the ratio of Zn2 þ /Mn2 þ was 1.1. Therefore, in soil SN it is particularly difficult to determine whether Zn2 þ was the cause of growth reductions or Mn2 þ . This contrasts with the Zn2 þ /Mn2 þ of the remaining soils (ratio¼5.8–80). The concentration at EC50 for Zn2 þ was substantially higher than Mn2 þ and likely to be the cause of growth reductions in the other soils. In addition, the high Zn2 þ /Mn2 þ ratio of the other soils may potentially provide a protective effect to Mn2 þ . This is the focus of current work in our laboratory. However, given the high Mn in pore-waters for the majority of our soils due to Zn-induced desorption, Mn may contribute in some way to the response of cucumber. Pore-water Zn2 þ phytotoxicity thresholds for the dataset as a
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culture studies (Reichman et al., 2001). 3.4. Semi-empirical relationships
Fig. 3. Relationship between relative growth (%) and pore-water Zn concentrations and pore-water Zn2 þ activity for all 10 soils together. Dashed line indicates fitted parameter (a). Solid line indicates parameter a¼ 100.
whole were related to pH when soil SN was excluded (Fig. 2). The estimated EC50 and EC10 values tended to decrease as the soil pHca and pHpw increased. It should be noted that pHw was also related to ECx, but R2 were lower than pHca and pHw. This is in some respects is expected, as pHCa and pHpw should reflect soil pH more closely than pHw (White, 2009). Similarly, EC10 followed by EC50 showed the strongest relationship to pHca and pHpw. Numerous parameters in pore-water change over the pH range in this study, most notably, the H þ activity, inorganic carbon concentration, carbonate speciation and dissolved organic matter concentrations and surface charge. The biotic ligand model broadly predicts that as H þ decreases, there is a decrease in competition at the biotic ligand site, resulting in enhanced uptake to the biological organ, in this case, the plant root (Antunes et al., 2006; Di Toro et al., 2001). The phenomenon is parallel with sorption of Zn to soil sites, with the well-known trend of increased sorption as pH is increased. The free ion activity model qualitatively predicts that toxicity should occur at relatively constant activity of a metal cation (McBride, 2001). In our study, the estimated Znpw and Zn2 þ activity varies between our 10 soils, with the variation in some cases being as large as that reported between plant species in nutrient
Zinc speciation in soil is determined by numerous soil factors. In an attempt to understand the key factors controlling solubility and toxicity, we used least squares regression analysis. For relative shoot growth, expressed as a percentage of control weight, we first fit RG (dry weight) against Zn concentration in soil. Zinc in soil was expressed as log10 total added Zn (mg/kg), pore-water (mM), concentrations or Zn2 þ activity (mM). When all 10 soils are collated, Zn levels in soil could significantly describe the relative growth (%) of cucumber using logistic regression in the same manner as the 2 was low individual soils. However, for total added Zn, the Radj (0.596) (Table 4), as there was significant spread in the dataset. Pore-water Zn and Zn2 þ , however, described the full dataset well (Table 4; Fig. 3), with dissolved Znpw and Zn2 þ described 78% and 80.3% of the variation in RG (%), respectively. When the whole data set is used, the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Previous studies have generally used multiple linear regression analysis to describe key soil factors that influence Zn toxicity. Smolders et al. (2004) studied Zn toxicity on soil invertebrates. The latter study reported that total Zn concentration in addition to soil pH and CEC were overall good predictors of Zn to invertebrate toxicity. The results of Smolders et al. support previous work (Impellitteri et al., 2003; Sauvé et al., 2000) who reported relations with soil pH and other factors such as CEC. Few have focussed extensively on pore-water chemistry across many treatments, and thus there are few papers predicting toxicity based on pore-water chemistry. Pore-water concentrations of Zn have thus been used infrequently as a predictor of toxicity. Beesley et al. (2010) studied pore-water chemistry in a multiple contaminated site (arsenic, cadmium and zinc) and related their data to extractability not directly to toxicity end-points. Indeed, to understand toxicity processes in mixed contaminant sites, interactions with pore-water are necessary, as total concentrations in soil reveal little detail. Knowledge of single contaminant toxicology and chemistry is essential before understanding mixed contaminated soils. This study has shown that pore-water Zn could predict phytotoxicity in several soils using logistic regression. Multiple regression analysis of Znpw and pZn ( log Zn2 þ activity) could be predicted by soil properties (Table 4). Total added Zn, soil pHpw and pDOC were the best predictors of Znpw and Zn2 þ in pore-water. Sauvé et al. (2000) reported that total Zn and pH (in a suspension) effectively described Zn Kd values in a range of soils. This to some extent agrees with the present work. Surprisingly, DOC concentration, whilst not correlated in simple linear correlation, was a significant variable when predicting both Zn in porewater and Zn concentrations in shoot. In general, Zn is commonly considered to not bind strongly with DOC in soil, and is often considered to be less important in controlling Zn in comparison to Cu, for example (Sauve et al., 1998). The fitting constant for pDOC was negative, indicating that lower DOC resulted in higher Zn in pore-water. The relatively high pore-water concentrations observed may explain this relationship, as DOC ranged from 52.4 to 549 mg/L in the control samples. However, when a solution-only model was used to predict Zn in shoot DOC was negatively related, indicating a reduction in uptake/translocation of Zn with increasing DOC. Interestingly, the measured pore-water potassium (K) was also a significant parameter describing Zn uptake to cucumber shoots. Potassium tended to stay relatively constant in pore-water, or, in some soils, increase with increasing Zn addition. This indicates that K may have a competing effect on Zn uptake or translocation in cucumber. Generally, divalent cations have been associated with reduced uptake of metals such as Ca and Mg
M. Kader et al. / Ecotoxicology and Environmental Safety 122 (2015) 252–259
(Cheng and Allen, 2001; Lock et al., 2007). In a study on Cu, uptake kinetics to roots of Bothriochloa macra was not reduced by Ca or K despite 3-fold higher concentration in solution (Lamb et al., 2012). Most studies on interactions with cations are based on nutrient culture and not soil pore-water. In our study, the relationship between Zn and K only occurred in 2 soils, but it may have influenced the overall relationship.
4. Conclusions Zinc contamination of soil poses a threat to ecological receptors. In this study we examined Zn phytotoxicity in a range of soils as function of total Zn loading and, moreover, Zn pore-water properties. In terms of Zn loading, the highest measurable EC50 was in soil PB, which was also alkaline, at 6353 mg/kg. In our dataset, only two soils had estimated EC50 values below 1000 mg/ kg (SN, KB). Both SN and KB soils had very low pHca of approximately 4.5. The EC10 values ranged from 179 (SN) to 5214 (WR) mg/kg. The soil that produced the lowest ECx values was in all cases SN soil, which is an acidic Ferrosol. In our study, only soil pH measures in soil was related to ECx Zn data, and CEC, clay content and organic carbon not consistently related to Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw was in general related to Zn ECx data. However, one Ferrosol was removed from the relationship, as Mn appeared to have added complexity to the toxicity parameter. Dissolved Znpw and Zn2 þ successfully described 78% and 80.3% of the variation in RG (%). When the whole data set is used, the estimated EC50pw was 450 and 79.2 mM for Znpw and Zn2 þ , respectively. Total added Zn, soil pHpw and pDOC were the best predictors of Znpw and Zn2 þ in pore-water. When a solution-only model was used to predict Zn in shoot the DOC was negative, indicating a reduction in uptake/ translocation of Zn with increasing DOC.
Acknowledgements The authors thank Mr Rayhan Mahbub, Mr. Ramkrishna Nirola and Ms. Sedigheh Abbasi for their valuable assistance in soil sampling. This research was funded through Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE Pty Ltd).
References Antunes, P.M.C., Berkelaar, E.J., Boyle, D., Hale, B.A., Hendershot, W., Voigt, A., 2006. The biotic ligand model for plants and metals: technical challenges for field application. Environ. Toxicol. Chem. 25 (3), 875–882. Beesley, L., Moreno-Jimenez, E., Clemente, R., Lepp, N., Dickinson, N., 2010. Mobility of arsenic, cadmium and zinc in a multi-element contaminated soil profile assessed by in-situ soil pore water sampling, column leaching and sequential extraction. Environ. Pollut. 158 (1), 155–160. Broos, K., Warne, M.S.J., Heemsbergen, D.A., Stevens, D., Barnes, M.B., Correll, R.L., McLaughlin, M.J., 2007. Soil factors controlling the toxicity of copper and zinc to
259
microbial processes in Australian soils. Environ. Toxicol. Chem. 26 (4), 583–590. Cheng, T., Allen, H.E., 2001. Prediction of copper form solution by lettuce (Lactuca sativa Romance). Environ. Toxicol. Chem. 20, 2544–2551. Di Toro, D.M., Allen, H.E., Bergman, H.L., Meyer, J.S., Paquin, P.R., Santore, R.C., 2001. Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environ. Toxicol. Chem. 20 (10), 2383–2396. Gillman, G., Sumpter, E., 1986. Modification to the compulsive exchange method for measuring exchange characteristics of soils. Soil Res. 24 (1), 61–66. Heemsbergen, D.A., Warne, M.S.J., Broos, K., Bell, M., Nash, D., McLaughlin, M., Whatmuff, M., Barry, G., Pritchard, D., Penney, N., 2009. Application of phytotoxicity data to a new Australian soil quality guideline framework for biosolids. Sci. Total Environ. 407 (8), 2546–2556. Impellitteri, C.A., Saxe, J.K., Cochran, M., Janssen, G.M., Allen, H.E., 2003. Predicting the bioavailability of copper and zinc in soils: modeling the partitioning of potentially bioavailable copper and zinc from soil solid to soil solution. Environ. Toxicol. Chem. 22 (6), 1380–1386. Kopittke, P.M., Blamey, F.P.C., Wang, P., Menzies, N.W., 2011. Calculated activity of Mn2 þ at the outer surface of the root cell plasma membrane governs Mn nutrition of cowpea seedlings. J. Exp. Bot. 62 (11), 3993–4001. Krishnamurti, G.S.R., Naidu, R., 2002. Solid–solution speciation and phytoavailability of copper and zinc in soils. Environ. Sci. Technol. 36 (12), 2645–2651. Lamb, D., Ming, H., Megharaj, M., Naidu, R., 2009. Heavy metal (Cu, Zn, Cd and Pb) partitioning and bioaccessibility in uncontaminated and long-term contaminated soils. J. Hazard. Mater. 171 (1–3), 1150–1158. Lamb, D.T., Naidu, R., Ming, H., Megharaj, M., 2012. Copper phytotoxicity in native and agronomical plant species. Ecotoxicol. Environ. Safety 85 (0), 23–29. Lamb, D.T., Matanitobua, V.P., Palanisami, T., Megharaj, M., Naidu, R., 2013. Bioavailability of barium to plants and invertebrates in soils contaminated by barite. Environ. Sci. Technol. 47 (9), 4670–4676. Lock, K., Janssen, C.R., 2001. Modeling zinc toxicity for terrestrial invertebrates. Environ. Toxicol. Chem. 20 (9), 1901–1908. Lock, K., Criel, P., De Schamphelaere, K.A.C., Van Eeckhout, H., Janssen, C.R., 2007. Influence of calcium, magnesium, sodium, potassium and pH on copper toxicity to barley (Hordeum vulgare). Ecotoxicol. Environ. Safety 68, 299–304. McBride, M., Sauve, S., Hendershot, W., 1997. Solubility control of Cu, Zn, Cd and Pb in contaminated soils. Eur. J. Soil Sci. 48 (2), 337–346. McBride, M.B., 2001. Cupric ion activity in peat soil as a toxicity indicator for maize. J. Environ. Qual. 30 (1), 78–84. McBride, M.B., Pitiranggon, M., Kim, B., 2009. A comparison of tests for extractable copper and zinc in metal-spiked and field-contaminated soil. Soil Sci. 174 (8), 439–444. Rayment, G., Higginson, F., 1992. Australian Laboratory Handbook of Soil and Water Chemical Methods. Inkata Press Pty Ltd., Melbourne. Reichman, S.M., Asher, C.J., Mulligan, D.R., Menzies, N.W., 2001. Seedling responses of three Australian tree species to toxic concentrations of zinc in solution culture. Plant Soil 235 (2), 151–158. Reichman, S.M., Menzies, N.W., Asher, C.J., Mulligan, D.R., 2004. Seedling responses of four Australian tree species to toxic concentrations of manganese in solution culture. Plant Soil 258 (1–2), 341–350. Sauvé, S., Hendershot, W., Allen, H.E., 2000. Solid–solution partitioning of metals in contaminated soils: dependence on pH, total metal burden, and organic matter. Environ. Sci. Technol. 34 (7), 1125–1131. Sauve, S., McBride, M., Hendershot, W., 1998. Lead phosphate solubility in water and soil suspensions. Environ. Sci. Technol. 32 (3), 388–393. Saxe, J.K., Impellitteri, C.A., Peijnenburg, W.J.G.M., Allen, H.E., 2001. novel model describing trace metal concentrations in the earthworm, Eisenia andrei. Environ. Sci. Technol. 35 (22), 4522–4529. Smolders, E., Buekers, J., Oliver, I., McLaughlin, M.J., 2004. Soil properties affecting toxicity of zinc to soil microbial properties in laboratory-spiked and fieldcontaminated soils. Environ. Toxicol. Chem. 23 (11), 2633–2640. Warne, M.S.J., Heemsbergen, D., McLaughlin, M., Bell, M., Broos, K., Whatmuff, M., Barry, G., Nash, D., Pritchard, D., Penney, N., 2008a. Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models. Environ. Pollut. 156 (3), 707–714. Methods of soil analysis. Part 1. In: Gee, G.W., Bauder, J.W. (Eds.), Particle-size Analysis. Soil Science Society of America, Madison. Warne, M.S.J., Heemsbergen, D., Stevens, D., McLaughlin, M., Cozens, G., Whatmuff, M., Broos, K., Barry, G., Bell, M., Nash, D., Pritchard, D., Penney, N., 2008d. Modeling the toxicity of copper and zinc salts to wheat in 14 soils. Environ. Toxicol. Chem. 27 (4), 786–792. White, R.E., 2009. Principles and Practice of Soil Science: The Soil as a Natural Resource. John Wiley & Sons, Malden.