Are Methylmercury Concentrations in the Wetlands

Publisher: AGRONOMY; Journal: JOENQ:Journal of Environmental Quality; Copyright: 2003 Volume: 32; Issue: 6; Manuscript: Q02-0431; DOI: ; PII: TOC Head: Technical Reports; Section Head: Will notify...; Article Type: ARTICLE

J. ENVIRON. QUAL., VOL. 32, NOVEMBER–DECEMBER 2003 SICILIANO ET AL.: METHYLMERCURY CONCENTRATIONS IN WETLANDS

Are Methylmercury Concentrations in the Wetlands of Kejimkujik National Park, Nova Scotia, Canada, Dependent on Geology? Steven D. Siciliano,* Al Sangster, Chris J. Daughney, Lisa Loseto, James J. Germida, Andrew N. Rencz, Nelson J. O’Driscoll, and David R. S. Lean ABSTRACT In the relatively pristine ecosystem in Kejimkujik Park, Nova Scotia, methylmercury (MeHg) concentrations in loons, Gavia immer, are among the highest recorded anywhere in the world. This study investigated the influence of bedrock lithology on MeHg concentrations in wetlands. Twenty-five different wetland field sites were sampled over four different bedrock lithologies; Kejimkujik monzogranite, black sulfidic slate, gray slate, and greywacke. Soil samples were analyzed for ethylmercury (EtHg), MeHg, total Hg, acid-volatile sulfides (AVS), organic matter, and water content as well as the biological parameters, mercury methyltransferase (HgMT) activity, sulfate reduction rates, fatty acid methyl ester (FAME) composition, and acidity. Methylmercury concentrations in the wetlands were highly dependent (P < 0.08) on lithology with no significant difference between bogs, fens, and swamps . Methylmercury concentrations in wetland soils developed on Kejimkujik monzogranite averaged 900 ng kg−1 compared with only 300 ng kg− 1 in wetland soils developed on black sulfidic slate. Fatty acid methyl ester composition was also lithologically dependent (P < 0.001) with biomarkers for Desulfobulbus spp. discriminating between sites containing high and low MeHg concentrations. Levels of MeHg in wetlands were predicted mainly (41% of the sum of squares) by HgMT activity that differed (P < 0.009) between wetlands, with activity in bogs almost three times that present in swamps. Wetland MeHg concentrations are highly dependent on the lithology on which they have developed for largely biological reasons. S.D. Siciliano and J.J. Germida, Dep. of Soil Science, Univ. of Saskatchewan, 51 Campus Drive, Saskatoon, SK, Canada S7N 5A8; L. Loseto, N.J. O’Driscoll, and D.R.S. Lean, Dep. of Biology, Univ. of Ottawa, 30 Marie Curie, Ottawa, ON, Canada K1N 6N5; A. Sangster and A.N. Rencz, Geological Survey of Canada, 601 Booth Street, Ottawa, ON, Canada K1A 0E8; C.J. Daughney, Institute of Geological and Nuclear Sciences, P.O. Box 30368, Lower Hutt, New Zealand. Received 17 Oct. 2002. *Corresponding author ([email protected]). Abbreviations: AVS, acid-volatile sulfides; EtHg, ethylmercury; FAME, fatty acid methyl esters; HgMT, mercurymethyltransferase; MeHg, methylmercury; Q3, third quartile; SAM S-adenosylmethionine; SCM, surface complexation model; SRB, sulfate-reducing bacteria; U, one unit of HgMT activity was defined as the formation of 1 nmol of tetrahydrofolate formed in response to the addition of 1 ng of Hg to the reaction vessel.

In contrast to areas that have received direct inputs of MeHg and Hg to the ecosystem, Kejimkujik National Park in eastern Canada is a relatively pristine, headwater ecosystem; yet, the blood of common loons in the Kejimkujik area contains the highest Hg levels of any loons in North America (Burgess et al., 1998). The increased Hg concentrations present in adult loons were closely reflected in the Hg content of chick blood, which in turn was tightly correlated with Hg levels in fish (Burgess et al., 1998). There are no known point sources of Hg within the park and atmospheric deposition is similar to that found elsewhere in North America, (about 7 µg m−2 yr−1 ) (O'Driscoll et al., 2001). Interestingly, MeHg concentration in the biota and lake water correlates with bedrock lithology. Methylmercury concentrations in lakes on the Kejimkujik monzogranite lithology are two to 10 times greater than that observed in lakes overlying other lithologies and total Hg in fish was 1.4 to 2.1 times greater (O'Driscoll et al., 2001). Mercury

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concentrations in the lakes were also dependent on the geology with lakes on granitic geology having higher total Hg than lakes overlying greywacke (Vaidya and Howell, 2002). A Hg mass balance study of the Big Dam West watershed in Kejimkujik indicated that of the 160 g (σ = 38.4) of Hg inputs directly to the lake, 92% (147 g, σ = 36.7) was due to inflow from wetlands, 7% (11 g, σ = 0.0) was due to wet precipitation and, 1% (2 g, σ = 1.7) was due to ground water inflow (O'Driscoll et al., submitted????). The surface inflow results from over 184 g (σ = 20.2) Hg yr−1 being deposited from the atmosphere to the terrestrial catchments comprising 27 × 106 m−1 . Mercury and MeHg deposition is influenced by forest canopy in other ecosystems (St Louis et al., 2001) and its variation across the Kejimkujik area is unknown. However, atmospherically deposited MeHg is not a significant source to current levels of MeHg in wetlands (Branfireun et al., 1998) so we have assumed that the formation of MeHg from inorganic Hg in the terrestrial zone is a critical process influencing MeHg transfer from terrestrial zones to their adjacent water bodies. Since the underlying lithology of a terrestrial zone is an important determinant of water chemistry and water chemistry plays a central role in Hg transport (Daughney et al., 2002) and methylation (Branfireun and Roulet, 2002), it seemed reasonable to investigate the role of lithology in Hg fate in the terrestrial landscape. Wetlands play a major role in the export of MeHg to the watershed (St Louis et al., 1994; Waldron et al., 2000; Watras et al., 1995). The type and hydrological flow (Branfireun and Roulet, 2002) present in a wetland influences how much MeHg is exported to the watershed. In wetlands, the methylation of inorganic Hg is thought to occur primarily through the activity of sulfate reducing bacteria (SRB) with Hg methylation rates linked to the composition and activity of SRB (Devereux et al., 1996; King et al., 2001; Macalady et al., 2000) as well as the availability of sulfate (Heyes et al., 2000). By definition, the biological methylation of Hg (II) can only occur to that fraction of Hg that is bioavailable. In an environmental setting, the fraction of Hg sorbed to biological colloids is determined by the chemistry of the surface water (Daughney et al., 2002), which in turn is controlled (in part) by the surrounding geology, watershed geometry, and hydrology (Kolka et al., 1999). Thus, while the hydrology of a wetland will undoubtedly play a major role in the methylation of Hg, the underlying lithology will also influence MeHg formation by modifying the biological and chemical factors, which interact with hydrological processes. We hypothesized that MeHg concentrations in Kejimkujik’s wetlands could be, in part, predicted by the lithology of that site. The general till cover over the bedrock terrain is very thin, commonly only 1 to 3 m and there is only limited ( 0) and Kejimkujik monzogranite (2.1 ng kg−1 , median = 0, Q3 > 0). There was no correlation between EtHg and MeHg (r = 0.204) for individual samples. A discriminant analysis identified soil Hg concentrations as the most important parameter separating sites (105 squared distance between groups, 100% success rate) that contained EtHg (227 µg Hg kg−1 , SE = 19.6) from those sites were no EtHg (247 µg Hg kg−1 , SE = 17.3) was detected. To account for differences in bioavailability that are dependent on lithology, we compared organic matter, pH, and AVS across the lithologies (Fig. 2). Kejimkujik monzogranite lithology had the highest percentage of organic matter (91%) of all lithologies and the lowest average soil pH (4.5) but neither of these variables was correlated with MeHg concentrations (r = 0.02 and r = 0.193, respectively) and combined, these variables predicted practically none (r2 = 0.02) of the MeHg variation. Similarly, there was no (P < 0.538) lithological dependence in AVS and no difference between wetlands (P < 0.712) in AVS levels. We have recently developed a surface complexation model (SCM) that predicts 62% of the variation in Hg bound to particulate organic C in Kejimkujik (Daughney et al., 2002). This model which uses dissolved organic matter, particulate organic matter, total Hg and Cl levels as input parameters can be considered as a surrogate for Hg bioavailability because it is bacteria that methylate Hg and sorption to the bacterial surface is the first step in bioavailability. The model explicitly models the sorption of neutral complexes to the cell surface. There were no significant differences in filtered Hg between lithologies with approximately 4.2 ng L−1 present in filtered wetland water. Based on the SCM, Hg bioavailability to microorganisms was dependent on lithology (P < 0.163) with the greatest bioavailability (74%) in Kejimkujik monzogranite lithology. It should be noted that recent works suggests that microorganisms may actively take up Hg from solution (Golding et al., 2002?not in reference section) contradicting earlier assumptions of Hg bioavailability (Barkay et al. 1997). In either case, sorption to the cell surface is necessary so the SCM is a good first estimate of bioavailability. The HgMT activity was highest in bog wetlands (P < 0.009) with activity double that of fens or swamps (Fig. 3). There was no detectable lithological dependence when all wetlands were combined (P < 0.557) and due to unbalanced samples, we were unable to collectively test interactions between wetlands and geology. When considered separately, levels of HgMT activity in the two Kejimkujik monzogranite bogs was much higher (60 U g−1 soil, SE = 4.9) than that seen in the greywacke (34 U g−1 soil, SE = 4.9). In contrast to HgMT, sulfate reduction rates were highest (P < 0.023, Moods Median Test) in fens compared with bogs and swamps (Fig. 3) with no lithological dependence (P < 0.743, Mood’s Median Test?). The composition of the microbial community was dependent (P < 0.001) on lithology with the communities present on Kejimkujik monzogranite clearly separating on the first two principle components from the other lithologies (Fig. 4). Fatty acid methyl esters considered as biomarkers (17:1, 15:1, and 15:0) (Macalady et al., 2000) for Desulfobulbus, were primarily responsible for the separation of Kejimkujik monzogranite communities from the other three

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lithologies as depicted by the ins ert in Fig. 4. Of these biomarker FAMES, 17:1 w7c and 15:1 w8c had a combined importance of 24% for principle Component 1 and 27% for principal Component 2 and this gives rise to the vector drawn in the insert present in Fig. 4. The microbial community composition, especially Desulfobulbus biomarkers, was also an effective (76% accuracy) method of grouping sites into areas of high, medium, and low MeHg concentrations in wetland soil (data not shown). The linear discriminant function responsible for 40% of the variance had the Desulfobulbus biomarker 15:0 anteiso as the most important predictor followed closely by a Desulfovibrio marker iso 16:0. Including all the delineated parameters allows us to predict 84% (P < 0.282) of the MeHg variation in wetlands in the Kejimkujik area: MeHg = 28 − 20Ln Soil Hg − 9ArcSin Organic Matter − 3Soil pH + 0.21Acid Volatile Sulfides + 0.048Sulfate Reduction Rate + 0.62Ln HgMT + 0.14Principal Component 1 (Table 2). Adjusting the predictive power of the equation for the number of parameters included in the equation reduces this estimate to 45% predictive power and identifies the best predictive parameters for MeHg levels in wetlands. The majority of this predictive power was obtained from HgMT activity that accounted for 41% of the sequential sum of squares of the multiple linear regression model (Table 3). Total soil Hg was the second most powerful predictor as determined by best subsets regression and accounted for 19% of the sequential sum of squares in the model. Previous work has indicated that the form of HgMT, cobalamin independent or dependent correlates with methylation of Hg (Siciliano and Lean, 2002). A higher percentage of the observed HgMT activity (55%, n = 4) on Kejimkujik monzogranite was cobalamin independent compared with gray slate (15%, n = 4).

DISCUSSION There was a strong dependence of MeHg concentrations on bedrock lithology in wetland soils. This was tested by a two-way ANOVA with wetlands and lithology as factors. We found that there was little difference in total Hg present in soils but that other chemical factors combined to increase Hg sorption to particulate organic matter as modeled by the SCM. Furthermore, the enzyme postulated to be responsible for MeHg formation was also higher in the Kejimkujik monzogranite. Thus, there is greater bioavailability and methylation activity in Kejimkujik monzogranite, which explains the high MeHg levels found in the wetland soils. It may be that this sequence of events, greater Hg bioavailability and methylation activity, is brought about by factors other than lithology, such as wetland hydrological characteristics, but if so, these factors are correlated with the bedrock lithologies of southern Nova Scotia. We observed that the dependence was related to an interaction between inorganic Hg and levels of biological methylation activity. Total soil inorganic Hg was the most powerful predictor of MeHg concentrations of all the chemical parameters measured. The concentration of total Hg will be one of the important parameters controlling the bioavailability of inorganic Hg for methylation. Divalent Hg is strongly bound to soil organic matter with a log KSOC (KSOC = HgSOC /[Hg2+]) of around 23 (Skyllberg et al., 2000) and this binding is dominated by reduced S present in the organic matter. These authors postulated that reduced sulfide would play little role in soils because it is always in excess and variations in levels would not alter how much Hg was

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sorbed to organic matter. Our work supports the interpretation of Skyllberg et al. (2000) that at the large regional scale, reduced sulfide in wetland soils had little role in Hg methylation. In the case of Hg bioavailability, reduced S, pH, organic matter, and particulate matter are all parameters (Benoit et al., 1999b; Jay et al., 2000; Loux, 1998; Skyllberg et al., 2000) known to not only be important in regulating bioavailability but also to interact with each other. Thus, a comprehensive bioavailability model of Hg in wetland soil will likely require development of a soil Hg-SCM such as the one recently developed for aerobic waters (Daughney et al., 2002). This aerobic-water SCM was able to accurately estimate Hg sorption to POC carbon in Kejimkujik surface waters and in this study, application of the SCM illustrated a strong lithological dependence of Hg sorption to POC in surface waters. The original SCM was developed for conditions prevalent in Kejimkujik area surface waters, that is, low dissolved sulfide and competing mineral sorbants. These assumptions are violated in the soil system and in the case of sulfide; it is known that this will alter the speciation of Hg considerably (Jay et al., 2000). Mineral sorbants in the soil system cannot only alter the bioavailability of Hg via simple adsorption but also the reactivity of Hg toward methylation (Farrell et al., 1998). We did not perform clay mineralogical analysis on our samples but bedrock lithologies often differ in mineral composition and this may be one of the primary routes by which geology acts as a determinant in the Kejimkujik system. Wetland MeHg concentrations were most successfully predicted by HgMT activity. As expected, the HgMT activity was highest in bog samples that also contained the most MeHg (800 ng kg−1 , σ = 350) compared with fens (393 ng kg−1 , σ = 108) and swamps (578 ng kg−1 , σ = 136). The levels of HgMT activity observed in Kejimkujik bogs were very similar to the peak activities observed at Mer Bleu bog in Ontario, Canada (Siciliano and Lean, 2002). While there were differences between lithologies in HgMT activity with Kejimkujik monzogranite having the highest HgMT (31 U g−1 ), followed by greywacke (26 U g−1 ), gray slate (26 U g−1 ), and black sulfidic slate (17 U g−1 ), these differences were not significant and not of the same order of magnitude as MeHg concentrations. There are two possible explanations for this discrepancy. As seen for a small subset of samples, the difference between cobalamin dependent and independent activity corresponded with an increase in MeHg levels across two lithologies. In addition, our sampling campaign was limited to a 14-d period in the early spring when there was still snow on the ground and water temperatures were below 10°C. As was seen in Mer Bleu (Siciliano and Lean, 2002), there is a strong temporal component to methylation activity and our sampling campaign may have missed the peak MeHg formation period in Kejimkujik. There was a striking lithological dependency on microbial community composition with differences in Desulfobulbus biomarker FAMEs being primarily responsible for this separation. In sediments, Desulfobulbus abundance is linked with high MeHg concentrations (Devereux et al., 1996). Biomarkers should not be considered as definitive for that organisms since these biomarkers are based on the concept that there is more 15:0 anteiso present in Desulfobulbus compared to Desulfovibrio but there is still 15:0 anteiso present in Desulfovibrio (Macalady et al., 2000). Thus, our data indicates a predominance of Desulfobulbus biomarkers at sites with high MeHg but alternatively, this may arise if there are significantly more SRBs in general at these sites. This alternative interpretation is not supported by the low sulfate reduction rates observed and that sulfate reduction rates were not related to MeHg concentrations in the wetlands.

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The sites on the four different lithologies present in Kejimkujik National Park are dominated by different forest types with 51% of the forest on Kejimkujik monzogranite sites being coniferous compared with only 34% on the Greywacke sites. Forest composition expressed as percentage of the forest that was coniferous had little power (r2 = 0, P < 0.410) to predict the MeHg levels in wetlands. As expected, the forest composition data was correlated (r > 0.56) with the soil parameters organic matter, soil pH, and AVS. Given the ability of vegetation to alter microbial community composition (Staddon et al., 1997), it is feasible that the lithological dependence we observed was related to plant community composition. Other investigators have found that plant community composition can affect Hg flux from the atmosphere (St Louis et al., 2001) and thus, Hg deposition may have differed between the lithologies. However, other authors suggest that whereas atmospherically deposited Hg(II) is important to wetland Hg processes, deposited MeHg has little influence on MeHg levels present in catchments (Branfireun et al., 1998). There was no lithological difference in dissolved Hg in our study suggesting that atmospheric deposition of Hg did not differ between lithologies but we have no direct evidence that atmospheric deposition is similar or different between lithologies. The interaction between atmospheric deposition, forest composition and wetland processes, which in turn may be partially controlled by hydrology and lithology, requires additional research.

SUMMARY This study demonstrated that MeHg concentrations in wetland soil differ between lithologies. Common environmental parameters such as pH, AVS, sulfate reduction activity, as well as inhibitory anions were not important in determining MeHg concentrations in soil. Rather, this dependence was weakly related to total Hg concentrations, presumably via bioavailability and strongly related to HgMT activity and microbial community composition. The causal cha in linking lithology to the environmental parameters that control MeHg formation was not elucidated from our study. Our results suggest that geology influences Hg bioavailability and the biology responsible for the methylation reaction thereby giving rise to the observed lithological dependence of MeHg in soil as well as wildlife. ACKNOWLEDGMENT The authors thank the staff of Kejimkujik National Park for their help in accessing remote locations. This work was supported by Toxic Substance Research Initiative Project #124 grants to D.R.S. Lean, A. Rencz, and A. Sangster. N. O’Driscoll was supported by NSERC. This is Geological Survey of Canada Contribution #2002153.

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Waldron, M.C., J.A. Colman, and R.F. Breault. 2000. Distribution, hydrologic transport, and cycling of total mercury and methyl mercury in a contaminated river-reservoir-wetland system (Sudbury River; eastern Massachusetts). Can. J. Fish. Aquat. Sci. 57:1080– 1091. Watras, C.J., K.A. Morrison, J.S. Host, and N.S. Bloom. 1995. Concentration of mercury species in relationship to other site-specific factors in the surface waters of northern Wisconsin lakes. Limnol. Oceanogr. 40:556–565. Fig. 1. Bedrock geology of study area with sampling sites indicated. The lower panel indicates the watershed boundaries for the sampling area. Fig. 2. Organic matter and methylmercury (MeHg) (open bars) as well as pH and total Hg (closed bars) in wetlands found on different lithologies. Closed circles indicate acid volatile sulfide or surface complexation model estimate of percentage of total Hg sorbed to bacteria in different lithologies. Note the 1000-fold difference in the scales for MeHg and Hg. Error bars indicate standard error of the estimate. Fig. 3. Influence of wetland type on mercury-methyltransferase (HgMT) activity (closed bars) and sulfate reduction rate (closed circles). Error bars are standard error of methyltransferase activity and one quartile for sulfate reduction rate. U, one unit of HgMT activity was defined as the formation of 1 nmol of tetrahydrofolate formed in response to the addition of 1 ng of Hg to the reaction vessel. Fig. 4. Principle component analysis of fatty acid methyl esters (FAME) present in wetland soil from Kejimkujik monzogranite (diamond), greywacke (circle), black sulfidic slate (square) or gray sulfidic slate (triangle). Open symbols are the average principle component scores for each lithology and closed symbols are the average principle component scores for each site. Inserted graph is the relative weighting of established Desulfobulbus FAME biomarkers for Principle Component 1 and 2. Table 1. Mineral and element composition of rock samples obtained on the different bedrock lithologies. Black sulfidic slate Grey slate (n Greywacke (n = Kejimkujik (n = 35) = 16) 10) monzogranite (n = 7) Element oxide, % SiO 2 62 56 72 72 (78–52)† (72–52) (77–61) (72–70) Al2 O3 19 21 13 14 (25–9) (23–13) (19–10) (15–13) Fe2 O3 7.6 8.6 4.4 3.4 (12–4.8) (11–4.4) (6.3–3.0) (4.4–2.6) MgO 1.9 2.2 1.6 0.92 (3.4–1.4) (2.6–1.4) (2.4–1.0) (1.6–0.71) CaO 0.22 0.72 1.4 1.4 (0.94–0.03) (3.5–0.15) (4.2–0.26) (1.4–0.67) Na2 O 0.86 1.4 2.4 2.4

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K2O TiO 2 P2 O5 MnO Cr2 O3 Loss on ignition Total C Total S

As Ba Be Co Cr Cu Hg, µg kg−1 La Mo Nb Ni Pb Sc Sr

(1.2–0.29) 2.9 (4.2–0.97) 0.88 (1.2–0.47) 0.09 (0.21–0.01) 0.19 (0.51–0.03) 0.01 (0.02–0.00) 4.4 (6.0–2.9) 0.25 (0.79–0.05) 0.68 (2.0–0.01) 12 (120–1) 530 (700–230) 3 (4–1) 14 (28–3) 78 (122–17) 27 (72–1) 1.5 (5.2