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Environ. Sci. Technol. 2007, 41, 2992-2997

Zinc Toxicity to Nitrification in Soil and Soilless Culture Can Be Predicted with the Same Biotic Ligand Model JELLE MERTENS,* FIEN DEGRYSE, DIRK SPRINGAEL, AND ERIK SMOLDERS Division of Soil and Water Management, K. U. Leuven, Kasteelpark Arenberg 20, B-3001 Heverlee, Belgium

The inhibitory effect of Zn on the nitrification process in ZnCl2 spiked soils (12 soils, pH range 4.8-7.5) was compared to toxic effects of Zn on the nitrification by Nitrosospira sp. in soilless solutions with varying pH (pH 6-8) and ionic composition. The nitrification was reduced by 20% at Zn solution concentrations (EC20) ranging between 7 and 1200 µM Zn in the soil pore water and between 5 and 150 µM Zn in the soilless solutions. Protective effects of H+, Ca2+, and Mg2+ against Zn2+ toxicity were observed in both systems. Zinc speciation was determined, and 60-90% of the Zn in the soils and 35-80% of the Zn in the soilless solutions was present as Zn2+. A biotic ligand model and a Freundlich-type model, incorporating the competition of Zn2+ ions with H+, Ca2+, and Mg2+ for binding on the biotic ligands, were used to model the results. The Zn2+ activities resulting in 20% reduction of the nitrification were well predicted using the same parameters for both (soil and soilless) systems, indicating that microorganisms in soil are exposed to zinc through the free zinc ion in soil pore water.

Introduction Toxic effects of trace metals such as zinc (Zn) or copper (Cu) to soil microbial processes occur close to background concentrations (e.g., ref 1), strengthening the need to derive toxic thresholds for metals in soil based on their effect on microbial processes. It is well-known that total metal concentrations at which soil microbial processes are inhibited vary largely among soils, suggesting that metal bioavailability is a critical factor. The toxic thresholds of trace metals correlate with soil properties such as the cation exchange capacity (2), but the mechanisms behind these trends are unclear. For most trace metals, it appears that the free metal ion determines metal bioavailability, which led to the “free ion activity model” (FIAM) for metal toxicity (3). In addition, free metal ion toxicity is also affected by the presence of other cations in solution (e.g., Ca2+, Mg2+, H+), that compete with the trace metal for binding on the “sites of toxic action” (4). The “biotic ligand model” or BLM (5) takes into account these interactions and has been successfully calibrated and validated to predict toxicity of metals to various freshwater organisms (6-8). The quantitative description and prediction of toxic effects in soil systems is much less advanced than in aquatic systems. Manipulation of metal speciation in * Corresponding author phone: +32 16 32 14; fax: +32 16 32 19 97; e-mail: [email protected]. 2992

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soilless cultures of soil microorganisms by adding organic or inorganic ligands has provided support of the FIAM for microorganisms in these model cultures (9, 10). The FIAM concept was also shown to be applicable for nitrification in copper-contaminated activated sludge (11) and for microbial processes in lead- and copper-contaminated soils (12). Recently, a selected number of terrestrial-BLMs (t-BLM) have been developed for cadmium toxicity to the springtail Folsomia candida (13) and Cu toxicity to the common earthworm Aporrectodea caliginosa (14, 15). All these studies are, however, based on regression analysis, i.e., the observation that the critical free ion activity in solution varies with the concentrations of competing ions. None of these studies has revealed a direct proof of the concept that assumes pore water exposure only, i.e., by validating that the same BLM holds for these organisms in the absence of the soil solid phase. Recently, Lock et al. (16) developed a BLM to predict the effect of Co on the survival of the potworm Enchytraeus albidus in nutrient solutions. The model was validated using a standard artificial and a standard field soil, and the soil (Co2+)LC50 (i.e., Co2+ activities causing 50% lethality) were predicted within a factor 2 suggesting the usefulness of the BLM to predict metal toxicity in soil. This concept might, however, not be applicable to soil microorganisms that are attached to soil particles in a microbial biofilm because the response of biofilms to metals can be different from that of free living cells in solution (17). The aim of this study was to compare toxic effects of Zn to nitrification in soils, with toxic effects of Zn to the nitrification by Nitrosospira sp. NpAV in solution. Nitrification was selected for its relatively large sensitivity to metal additions and the fact that the microbial diversity for this process is relatively small, compared to that responsible for other soil processes such as respiration (18, 19). Indeed, a drawback in predicting variability in toxicity among soils is the inherent variability of the microbial community among soils. The ionic composition of the soilless solutions was manipulated to mimic the different conditions of pH and ionic composition of soil solutions. It was assessed whether the effects of solution composition on Zn toxicity were similar in soils and soilless solutions, and whether these effects could be described with a quantitative model, such as the BLM.

Materials and Methods Toxicity Tests in Soil. The toxicity data in soil were obtained from the study of Smolders et al. (19). In that study, fifteen uncontaminated soils were sampled at different locations in Europe. All soils were spiked with increasing ZnCl2 concentrations, varying between 0 and 1800 mg Zn kg-1, and the potential nitrification rate (PNR) was calculated. The data were statistically analyzed using a log-logistic dose-response model, fitted with the Marquardt method (proc NLIN, SAS 9.1; Cary, NC). The Zn concentration in pore water causing 20% inhibition of the nitrification (ZnEC20) and its 95% confidence interval were derived from the appropriate parameters. More details about procedures can be found in the cited article. From that study, we selected the data of the 12 soils in which (i) PNR was detectable, (ii) a significant inhibitory effect of Zn on the PNR was observed, and (iii) pH and pore water properties (Ca, Mg, and Zn concentration in pore water) were measured (Table 1; soils n° 4-15 in ref 19). Culture Growth. Nitrosospira sp. NpAV, a chemolithotrophic ammonia oxidizing bacterium that was originally isolated from soil (20), was obtained from the Institut for Okologi, Sektion for Microbiologi, Frederiksberg. The culture was grown in 250 mL Erlenmeyers containing 100 10.1021/es061995+ CCC: $37.00

 2007 American Chemical Society Published on Web 03/08/2007

TABLE 1. Sampling Sites and Selected Properties of Soil Samples (19)a Ca (mM)

Mg (mM)

sample

pH (CaCl2)

OC (%)

DOC (mg L-1)

CTRL

EC20

CTRL

EC20

Zn (µM) CTRL

EC20

Zn2+ (µM)b EC20

PNR (mmol NO3-N kg-1 d-1)

1. Rhydtalog (United Kingdom) 2. Souli (Greece) 3. Ko¨ vlinge (Sweden) 4. De Meern (The Netherlands) 5. Aluminusa (Italy) 6. Zeveren (Belgium) 7. Woburn (United Kingdom) 8. Ter Munck (Belgium) 9. Rots (France) 10. Souli (Greece) 11. Marknesse (The Netherlands) 12. Guadelajara (Spain)

4.8 4.8 5.1 5.2 5.4 5.7 6.4 6.8 7.4 7.4 7.5 7.5

7.8 0.4 2.4 10.2 0.9 3.5 4.4 1.0 1.3 2.6 1.3 0.4

694 15 < 15 < 15 < 15 < 15 23 33 < 15 48 < 15 < 15

6.2 0.8 0.5 11.2 0.5 11.5 4.8 8.8 2.3 3.8 3.1 2.0

19.1 3.8 4.8 18.2 2.5 17.9 14.7 20.0 26.9 31.2 16.6 21.7

3.5 0.3 0.2 5.4 0.3 5.2 2.3 1.4 0.1 0.4 0.2 0.2

9.5 1.2 1.6 8.7 1.5 8.0 7.0 3.0 1.7 3.6 1.2 2.6

18.6 0.2 4.5 11.6 0.2 5.5 8.7 2.7 0.3 0.3 0.4 0.3

1203 65 74 318 7 132 56 17 28 41 21 10

740 60 68 292 5 119 45 11 22 25 15 7

0.75 0.11 0.11 1.36 0.16 0.71 1.51 0.94 0.66 0.27 0.46 0.41

a Concentrations of Ca, Mg, Zn, and Zn2+ in the soil solution are reported for the unamended control soils (CTRL) and at the Zn dose resulting in 20% effect (EC20) on the potential nitrification rate (PNR) of the uncontaminated control soil. OC is the organic carbon; DOC is the dissolved organic carbon. b Calculated with WHAM.

mL HK medium. This medium, derived from the medium of Krummel and Harms (21), is suited for lithotrophic ammonia oxidizing bacteria, and contains 5 mM (NH4)2SO4, 10 mM NaCl, 0.2 mM MgSO4, 1 mM CaCl2, 1 mM KCl, 0.4 mM KH2PO4, 42 mM HEPES (4-(2-hydroxyethyl)piperazine-1ethanesulfonic acid), and 1 mL L-1 trace solution S8, giving final concentrations in the medium of 11.5 µM Na2-EDTA (Titriplex III), 10 µM FeCl2, 0.5 µM MnCl2, 0.1 µM NiCl2, 0.1 µM CoCl2, 0.1 µM CuCl2, 0.5 µM ZnCl2, 0.1 µM Na2MoO4, and 1 µM H3BO3. All solutions were made in milli-Q water. The pH was corrected to 7.5 using 1 M NaOH or HCl and the medium was autoclaved at 121 °C for 20 min. The culture was grown at 25 °C and continuously shaken at 125 rpm in the dark. The medium was regularly refreshed by centrifuging the culture at 3300g for 15 min, removing the old medium and resuspending the cell pellet in 100 mL fresh medium. All handlings were made in a sterile way, and media and material were autoclaved (121 °C, 20 min) prior to use. Test Medium. All toxicity tests were performed in a modified HK medium with MES (2-(N-morpholino)ethanesulfonic acid; pKa 6.25) as buffer in media of pH 6 or MOPS (3-(N-morpholino)propanesulfonic acid; pKa 7.2) as buffer in media of pH 7 and 8. Both buffers do not complex Zn (22). Preliminary tests showed that the nitrification did not depend on the type of buffering. While nitrification is also observed in acid soils (e.g., soil with pH 4; ref 23), we were not able to grow Nitrosospira cells at a pH lower than 6. This discrepancy between nitrification in soil and in solution is explained more in detail in the Supporting Information. The response of a pure Nitrosospira culture to Zn was tested in solutions with an ionic composition comparable to that of soil pore waters. Therefore, the composition of the original HK medium was modified: no NaCl and trace solution S8 were added, and concentrations of (NH4)2SO4 and KH2PO4 were lowered to 2.5 mM and 5 µM, respectively. The buffers MES or MOPS replaced HEPES and were added in a concentration of 5 mM, the pH was varied between 6 and 8, Mg concentrations between 0.8 and 19 mM, and Ca concentrations between 0.6 and 28 mM. Different combinations of pH conditions and Mg and Ca concentrations allowed quantifying the effects on Zn toxicity to Nitrosospira. Preincubation of Nitrosospira Culture. The original cell culture was washed three times by suspending the centrifuged cell pellet (3300g, 15 min) in 50 mL NaCl 0.9%, centrifuging the suspension (3300g, 15 min), and removing the NaCl solution. The pellet was suspended in a MOPS (42 mM, pH 7) buffered HK medium, and the culture was continuously shaken (125 rpm) at 25 °C in darkness. During the preincubation period of at least 14 days, the MOPS medium was refreshed at least weekly. Two days before the start of the toxicity experiments, the medium was replaced a last time.

Preparation of the Inoculum and Cell Counting. The preincubated Nitrosospira culture was centrifuged at 3300g for 15 min, the medium was removed and the cell pellet was washed three times as mentioned above. Finally, the cell pellet was diluted in 200-500 µL of a solution, containing 0.8 mM MgSO4, 0.6 mM CaCl2 and 5 mM MOPS or MES buffer, depending on the pH of the medium to test. This cell suspension was used to inoculate the test solutions. Nitrosospira cells in the inoculum were counted by DAPI (4′,6diamidino-2-phenylindole dihydrochloride) staining and counting the cells in a Helber bacteria counting chamber (20 µm depth) with Thoma grid (Hawksley, U.K.). The cells were visualized by epifluorescence microscopy (Olympus BX51) at 400× magnification. More details about the cell counting procedure are provided in the Supporting Information. Toxicity Tests in Solution. Fifty mL of each test medium (pH: 6-8; Mg: 0.8-19 mM; Ca: 0.6-28 mM) was prepared and sterilized (121 °C, 20 min). Five mL of the medium was added to duplicate acid washed, sterile tubes and spiked with a ZnCl2 solution (15 mM) to obtain concentrations of 0, 15.3, 51, and 153 µM added Zn in the media of pH 6, or 0, 5.1, 15.3, and 51 µM added Zn in the media of pH 7 and 8. The Ca, Mg, and Zn concentrations of each tube were measured by inductively coupled plasma-optical emission spectroscopy (ICP-OES, Perkin-Elmer, Optima 3300 DV) in a filtered (0.45 µm) and acidified subsample (1-1.5 mL). The remaining medium was inoculated with the washed Nitrosospira culture, which was added to each tube in a final concentration of 5 × 106 cells mL-1. The tubes were homogenized and the medium was divided in two sterile glass tubes with a cotton plug. All tubes were aerobically incubated on a rotary shaker (125 rpm) for 16 h at 25 °C in the dark. Subsequently, the tubes were acidified with 5 M HCl (10 µL mL-1) to stop nitrification, and the NO3-N concentration in each tube was measured colorimetrically (Skalar SA40). The colorimetric reaction is based on the reduction of NO3- to NO2- with hydrazinesulfate, diazotization with sulfanilamide and coupling to N-1-naphtylethylenediamine. The potential nitrification rate (PNR) was determined as the rate at which NO3-N was formed (µM N h-1). Dose-response curves were fitted in the same way as for the soil data, using a log-logistic model, and the Zn concentration causing 20% inhibition of the nitrification (ZnEC20) and its 95% confidence interval were derived. Zinc Speciation in Soil Pore Water and in Soilless Solutions. Zinc speciation in the soil pore water was calculated using the Windermere humic acid model (WHAM) v.6.0.13 (24) with the NIST stability constants for inorganic complexation of Martell et al. (25). Input data were the Zn concentration at which nitrification was reduced by 20% (ZnEC20), Ca and Mg concentration at the ZnEC20 (CaEC20 and VOL. 41, NO. 8, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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MgEC20), soil pH, reactive DOM (26), and the corresponding Cl- concentration. Zn speciation in soilless solutions at the ZnEC20 was determined for each test solution by the resinexchange method of Holm et al. (27), since microorganisms can excrete organic metal-complexing ligands (28). The ratio free/complexed metal can be determined from the difference in solid-liquid concentration ratio between the test solution (with unknown speciation) and a reference solution with known speciation. Detailed information is provided in the Supporting Information.

Results and Discussion Nitrification in Soil. The soils varied widely in physicochemical properties (19). The soil pH ranged from 4.8 to 7.5, and the Ca and Mg concentrations in pore water ranged from 0.5 to 11.5 mM Ca and from 0.2 to 5.4 mM Mg (Table 1). The potential nitrification rate (PNR) in the unamended soil samples varied between 0.11 and 1.51 mmol NO3-N kg-1 d-1 (Table 1), and was reduced by at least 50% at the highest Zn addition in each soil. A dose-response curve was created for each soil. The corresponding Zn concentrations in pore water at which the PNR was reduced by 20% (ZnEC20) were between 7 and 1203 µM Zn (Table 1). Due to cation exchange reactions, Ca and Mg ions were released from the solid phase and their concentrations in pore water increased with increasing Zn dose, so that Ca and Mg concentrations were larger at the ZnEC20 than in unamended soils (Table 1). In soils with similar pH, the ZnEC20 was smaller in soils with low pore water concentrations of Ca (which was the dominant ion in the pore waters), than in soils with higher ionic strength (Figure 1), indicating a protective effect of Ca and Mg. These findings agree with results from aquatic studies (e.g., Zn toxicity to Daphnia magna; ref 29). Comparison of ZnEC20 values in soils with comparable Ca concentrations in pore water shows a decrease in ZnEC20 with increasing pH (e.g., soils n° 1, 4, 6, 8, and 12 in Table 1). This protective effect of protons on metal toxicity agrees with the findings of van Beelen and Fleuren-Kemila¨ (30), who showed that increasing pH increased the toxicity of soluble Zn in soilless cultures of soil microorganisms. Nitrification in Solution. The response of a pure culture of the soil isolate Nitrosospira sp. NpAV (20) to increasing Zn concentrations (0-153 µM added Zn, depending on the pH of the soilless solution) in solutions was assessed. The PNR in solution was reduced by at least 21% at the highest Zn dose, and ZnEC20 values were calculated (Figure 2 and Table 2). For each solution, a PNR value that was more than 50% lower than that of its corresponding duplicate sample, and remarkably lower than PNR values at higher Zn concentrations, was considered to be an outlier and was excluded from statistical analysis. For solution 13, three values were considered to be outliers, whereas no or only one value was excluded for the other solutions. All calculations and analysis were based on measured Zn, Ca, and Mg concentrations in solution at the start of the experiment. The confidence limits of ZnEC20 values, relative to the mean, were up to 90 times larger than in soil (data not shown) due to larger variation between duplicates and were even larger in two solutions where the effect at the highest dose was smaller than 25% (solutions 2 and 5; Table 2). The PNR values in control solutions increased with increasing pH, from about 6 µM h-1 at pH 6 to about 50 µM h-1 at pH 8 (illustrated in Figure 2 for selected solutions), demonstrating the strong inhibitory effect of pH on the nitrifying activity as shown previously for uncontaminated soils (31). The ZnEC20 decreased with increasing pH (Figure 2), and the protective effect of Ca and Mg was also observed in these solution systems (Table 2). Zinc Speciation. Trace metal toxicity is mostly related to the free metal ion concentration in solution (3, 32). Hence, 2994

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FIGURE 1. Potential nitrification rate (PNR) in soils as a function of dissolved Zn in soil solution. Response curves of soils are grouped by pH (A-C), each graph showing a soil with either large (0) or small (4) soil solution concentration of Ca and Mg. The numbers above the curves give the Ca concentration (mM) in the soil solution in the control soil (no Zn added) and at the ZnEC20. The dashed line and corresponding filled symbol indicate the ZnEC20. Error bars show the standard errors. Zn speciation in both soil pore water and the soilless solutions was determined for modeling purposes. The (interpolated) Ca and Mg concentration at the ZnEC20 (CaEC20 and MgEC20) was 1.6-13-fold higher than the Ca and Mg concentration in the unamended soil (Table 1). The speciation analysis indicated that 60-92% of the pore water Zn was present as Zn2+ at the ZnEC20 (Table 1). Zinc speciation in the soilless solutions was determined at the end of the experiment, because metal speciation can change during incubation due to microbial activity and excretion of organic ligands (28). The equilibrium 65Zn activity in the soilless solutions was larger than that in the reference solutions, indicating that Zn in the soilless solution was partly complexed with organic ligands. The calculated free-ion fractions of Zn at the ZnEC20 were between 35 and 80%. The Zn2+EC20 activity of both soil pore water and soilless solutions were used for further calculations in the study. Modeling Toxicity Data. Toxicity data of both ZnCl2 spiked soils and solutions were modeled using two different equations to describe the competitive effect of cations on binding of Zn2+ with the biotic ligand: the BLM equation (33) or a multicomponent Freundlich equation (34). Since increasing proton, Ca and Mg concentrations in both systems

TABLE 2. Composition of the Soilless Solutions (Measured pH, Ca, and Mg Concentration in Solution) with Corresponding Total Zn Concentration (ZnEC20) or Zn2+ Concentration (Zn2+EC20) in Solution at which the PNR was Reduced by 20%a sample n°

pH

Ca (mM)

Mg (mM)

ZnEC20 (µM)

Zn2+EC20 (µM)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8

8.4 8.4 27.7 7.6 7.6 28.2 0.6 1.1 2.1 4.1 2.1 2.0 2.0 2.1 7.7 7.5 28.3

4.3 19.5 3.9 4.0 19.1 4.0 0.8 0.9 0.8 0.9 0.2 4.1 19.3 0.9 4.0 18.8 4.0

12.7 149.2 86.8 22.4 59.2 31.6 12.6 7.2 5.1 7.8 7.0 5.5 17.6 9.4 28.2 20.9 36.5

8.9 106.2 66.3 12.2 36.3 22.9 3.4 3.2 1.9 3.9 3.4 2.1 9.6 4.9 12.8 10.5 28.7

a Concentrations of other nutrients in the soilless solutions: 2.5 mM (NH4)2SO4, 1 mM KCl, 5 µM KH2PO4, 5 mM MES or MOPS.

TABLE 3. Parameter Estimates for the Freundlich-type Model (eq 5) and the Biotic Ligand Model (eq 1) Using All Data (Soils and Soilless Solutions; n ) 29)a Freundlich model

a b c R2

-0.55 (0.54) -0.37 (0.06) 0.87 (0.16) 0.73

biotic ligand model logEC20* (M) logKHBL (L mol-1) logKCaMgBL (L mol-1) R2

-6.35 (0.69) 7.08 (0.74) 3.26 (0.78) 0.71

a The standard deviations (between brackets) were calculated from the correlation matrix according to the procedure described by de Levie (35). Corresponding coefficients of determination for observed versus predicted log(Zn2+)EC20 are shown.

FIGURE 2. Potential nitrification rate (PNR) in soilless solutions as a function of dissolved Zn in solution. Response curves of solutions are grouped by nominal Ca and Mg concentration of (A) 8 and 4 mM, (B) 8 and 20 mM, and (C) 28 and 4 mM (measured concentration in Table 2), each graph showing a solution with either low (4), moderate (O), or high (0) pH. The dashed line and corresponding filled symbol indicate the ZnEC20. increased the Zn2+EC20 concentrations, these ions were assumed to be the major competing ions for binding at the biotic ligand. The following BLM equation was used to predict the Zn2+EC20 activities:

(Zn2+)EC20,Pred ) EC20* [1 + KHBL (H+) + KCaMgBL (CaEC20,MgEC20)] (1) in which EC20* represents the (Zn2+)EC20 in the hypothetical case that no competing ions are present, KHBL and KCaMgBL are the stability constants for binding of H+ and of Ca2+ and Mg2+ at the biotic ligand (L mol-1), (H+) is the proton activity and (CaEC20,MgEC20) is the sum of the Ca2+ and Mg2+ activity at the ZnEC20 (all activities in mol L-1). We used the sum of both cations, because preliminary modeling of (Zn2+)EC20 using (H+), (Ca2+), and (Mg2+) separately in eq 1 revealed similar KCaBL and KMgBL (respectively, 3.25 and 3.43 L mol-1). The fitted parameters were logEC20*, logKHBL, and logKCaMgBL, and the parameters were optimized by minimizing the residual sum of squares of the log-transformed (Zn2+)EC20 values using the Solver function in Microsoft Excel (35). The parameter estimates are given in Table 3. The estimated EC20*

value (0.45 µM) is close to the lowest (Zn2+)EC20 value observed (1.1 µM in solution n° 12; Table 2). The KHBL and KCaMgBL are similar to the values of the Zn BLM for the alga Pseudokirchneriella subcapitata (36). The (Zn2+)EC20 values predicted with the BLM equation were in good agreement with observed values; the predictions differed, at most, by a factor of 4 from the observed values, except for soil n° 5 (Figure 3). In spite of this good prediction, there were some shortcomings to the model. Statistical analysis of the calculated BLM parameters revealed a strong correlation between all parameters (linear correlation coefficients for logEC20* and logKHBL: -0.98, for logEC20* and logKCaMgBL: -0.99, and for logKHBL and logKCaMgBL: 0.96). In other words, the parameters cannot be uniquely estimated since other sets of parameters result in almost equally good predictions, which explains the large standard deviation of the parameter estimates (Table 3). For instance, increasing KHBL and KCaMgBL by 1 order of magnitude while decreasing EC20* by 1 order of magnitude gave almost an identical good fit of the data. In most studies, no uncertainty on the parameters is reported. However, we found that the same problem also holds for data-sets reported in the literature. Rewriting eq 1 on the assumption that ∑(KXBL [X]) . 1, i.e., that cation competition is important, which allows omitting the term 1 in eq 1, yields the following:

(Zn2+)EC20,Pred ) EC20*KCaMgBL[KHBL/KCaMgBL(H+) + (CaEC20,MgEC20)] (2) VOL. 41, NO. 8, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 3. Observed Zn2+ activity at which PNR is reduced by 20% versus the predicted value in soil (squares) and soilless solution (circles), as predicted by the BLM (open symbols; eq 1) or the Freundlich type model (closed symbols; eq 5), using the parameter values given in Table 3. The solid line represents the 1:1 line, and dashed lines represent 4 times over- and underprediction. which shows that the data allow a more reliable estimate of the ratio of stability constants KHBL/KCaMgBL and of the product EC20*KCaMgBL. Since KHBL/KCaMgBL is around 104 (Table 3) and the summed activity of Ca2+ and Mg2+ activity is mostly 0.005 mol L-1 or higher, eq 2 implies that for the higher pH values (pH > 6.5), only Ca competition is important while proton competition is predicted to have minor effects. On the other hand, it also holds that at low pH values (pH < 5.5), Ca competition is not important. These predicted effects are not in agreement with our results in soils, since a Ca effect was also observed at low pH values (e.g., soil n° 1 vs n° 2; Table 1) and a pH effect at high pH values (e.g., soil n° 7 vs n° 11). In the BLM, the biotic ligands are considered to be chemically homogeneous and are represented by a single binding constant. However, some studies have shown that cells have multiple Zn transport mechanisms, and that they are present at the cell surface in unknown combinations. Therefore, it can be expected that site heterogeneity will be important for Zn toxicity, and that sorption of an element on the biotic ligand cannot be described with a single constant (37, 38). Consequently, we also used an alternative approach in which the competitive effect of Ca, Mg, and protons on sorption of Zn to the biotic ligand (BL) was described with a Freundlich-type model, which takes into account site heterogeneity (34): 2+ nZn

Q ) k (Zn )

+ nH

2+

2+ nM

(H ) (Ca ,Mg )

(3)

where Q is the amount of Zn bound to the BL, and k, nZn, nH, and nM are the Freundlich parameters. The Freundlich equation is a simplification, at low metal concentrations, of the Langmuir-Freundlich equation, for which the corresponding affinity distribution of the binding constants is a quasi-Gaussian (Sips) distribution (39). At the 20% effect level, eq 3 can be rewritten as follows:

QEC20 ) k(Zn2+)EC20nZn(H+)nH(CaEC20,MgEC20)nM

(4)

where QEC20 is the amount of Zn bound on the BL at the 20% effect level. Equation 4 can be transformed to the following:

log(Zn2+)EC20,pred ) a + bpH + clog(CaEC20,MgEC20) (5) 2996

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in which a, b, and c are the parameters for this Freundlichtype model (all activities in mol L-1). The parameter estimates, obtained by linear regression of log(Zn2+)EC20 on pH and log(CaEC20,MgEC20) are given in Table 3. Using this equation, all (Zn2+)EC20 values could be predicted within a factor of 4 (Figure 3). The R2 between observed and predicted log(Zn2+)EC20 was similar for the BLM and the Freundlich-type model (Table 3). Overall, the two models performed almost equally well (Figure 3), and gave similar predictions. However, the models are conceptually different: the Freundlich model does not account for finite adsorption capacity, while the BLM does not account for site heterogeneity. Predictions outside the range of the dataset differ strongly. The Freundlich model predicts that an increase in pH with 1 unit results in a 2.3fold decrease of the (Zn2+)EC20, and that a 10-fold increase in the Ca and Mg concentration results in a 7.4-fold increase of the (Zn2+)EC20, irrespective of the soil solution composition. The BLM, on the other hand, predicts that the pH effect becomes negligible at high pH while the Ca and Mg concentration is predicted to have little effect on Zn toxicity at low pH. However, our dataset covered the most relevant range of water and pore water characteristics, and this discrepancy in model outcome outside the calibration range does not really pose a problem, though it indicates that a good fit-of-data does not allow any conclusion about the validity of the model assumptions. It is likely that both models would start to malperform outside the calibration range. Our data suggest that soil nitrifying organisms are exposed to Zn through the soil pore water because the (Zn2+) thresholds agree between soil and soilless culture, and because relative ion competition effects on Zn2+ toxicity are similar. These results suggest little or no solution concentration gradients around soil nitrifying bacteria although these are known to be strongly attached to the soil particles (40). In contrast, previous studies have reported a larger toxicity of Cu, Pb, and Zn to free-swimming Pseudomonas aeruginosa compared to those present in a laboratory generated biofilm, as EC50 values differed more than 25-fold between the freeswimming and biofilm organisms. The difference is attributed to protection of cells within the biofilm by extracellular polymeric substances encasing the biofilm (17).

Acknowledgments This work is financially supported by the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen). We thank Dr. Kristian Brandt for providing Nitrosospira sp. NpAV and Kristin Coorevits for ICP-OES analysis. F.D. thanks the Fund for Scientific Research-Flanders (F.W.O.-Vlaanderen) for a position as postdoctoral researcher.

Supporting Information Available Zn speciation in soil, Zn speciation in soilless solutions: method of Holm et al., cell counting and Nitrosospira sp NpAV in soil and soilless solution. This material is available free of charge via the Internet at http://pubs.acs.org.

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Received for review August 18, 2006. Revised manuscript received January 24, 2007. Accepted January 31, 2007. ES061995+

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