A comprehensive sulfate and DOM framework to assess methylmercury formation and risk in subtropical wetlands

Domain: earth_science
Published: 2025-05-07
Editorial outcome: minor_revision

Abstract
Wetlands play a vital role in contaminant cycling and uptake. Understanding how sulfate (SO4 2‒) influences the conversion of inorganic mercury (Hg(II)) to toxic methylmercury (MeHg) is critical for predicting wetland responses to land use and climate change. Here, we sampled surface and pore waters across SO4 2‒ gradients in three freshwater Everglades wetlands to assess linkages between SO4 2‒, MeHg, dissolved organic matter (DOM), and inorganic sulfide (S(‒II)). Increasing SO4 2‒ concentrations increase S(‒II) and DOM concentrations and DOM aromaticity. MeHg concentration shows a unimodal response to surface water SO4 2‒, which reflect high Hg(II) methylation at low-to-intermediate SO4 2‒ concentration (2-12 mg/L) and low Hg(II) methylation at higher SO4 2‒ concentrations (>12 mg/L). MeHg concentrations in surface waters correlate positively with MeHg concentrations in prey fish. The coherent biogeochemical relationships between SO4 2‒ and MeHg concentrations and biologic uptake improve MeHg risk assessment for aquatic food webs and are globally relevant due to anthropogenic and climate-driven increases in SO4 2‒.

Introduction
Mercury (Hg) is a global pollutant that, when converted to neurotoxic methylmercury (MeHg), poses severe risks to wildlife and humans1. Freshwater wetlands are important locations for the cycling of Hg between environmental compartments, with both source (e.g., atmospheric deposition)2 and sink processes (e.g., photo-reduction of inorganic divalent Hg (Hg(II)) to elemental Hg (Hg(0)))3,4 governing Hg(II) concentrations in wetland waters. The microbial conversion of Hg(II) to MeHg is a critical step in the Hg cycle responsive to hydrologic and biogeochemical perturbations due to internal (e.g., nutrient cycling, land and water management) and external factors (e.g., climate change variables)5, which can have cascading effects that influence MeHg risk to biota6. MeHg risk is defined as the potential for MeHg to be formed within or proximal to aquatic systems that results in efficient MeHg assimilation into the aquatic food web. For over three decades7,8, sulfate (SO4 2‒), a terminal electron acceptor for anaerobic microbial metabolism, has been identified as an important geochemical predictor of the potential of MeHg formation in freshwater wetlands9–15. However, due to the individual biogeochemical complexities of sulfur (S), organic carbon (C), and Hg in the environment, there is still uncertainty in the response between SO4 2‒ concentrations and MeHg formation in wetlands and food web uptake16–18, the locations where MeHg formation occurs (e.g., sediments19 versus water column versus periphyton)20,21, and the direct or indirect role of SO4 2‒ reducing bacteria in the conversion of Hg(II) to MeHg19,22. A revisitation of linkages between SO4 2‒ concentrations and the potential for MeHg formation and uptake in biota is needed. Although wetland MeHg concentrations reflect the balance between Hg(II) methylation3,4,19 and MeHg demethylation9,23, differences in MeHg concentration within and across boreal15 and subtropical wetlands9,24 are primarily attributed to differences in Hg(II) methylation. Freshwater environments globally are threatened by increasing SO4 2‒ concentrations due to expansion in agricultural sulfur (S) use (primarily as elemental S)25,26, climate-driven increases in mineral weathering that release SO4 2‒ in boreal and Arctic systems27,28, and sea-level rise that delivers marine SO4 2‒ to coastal wetlands29.

Sulfate (SO4 2‒) exerts primary and secondary controls in MeHg formation through a combination of redox-dependent geochemical and microbial processes. From a geochemical perspective, in freshwater wetlands with low SO4 2‒ (<1 mg/L), Hg(II) aqueous speciation is primarily governed by the binding of Hg(II) to thiol groups in dissolved organic matter (DOM)30. Hg(II) speciation can be drastically altered in wetlands with appreciable SO4 2‒ and labile organic carbon, as dissimilatory SO4 2‒ reduction produces inorganic sulfide (S(‒II)), which outcompetes DOM thiol groups for Hg(II), resulting in the formation of nano-particulate metacinnabar (nano-β-HgS)31. Further, microbially mediated dissimilatory SO4 2‒ reduction, which utilizes soil organic matter (SOM), can catalyze both the release of highly aromatic DOM from soil and sediment29,32,33 and the abiotic sulfurization of DOM, enriching the DOM in thiol groups34. Nascent nano-β-HgS particles are smaller and less crystalline when formed under environmental conditions (i.e., low Hg(II) to DOM)31,35 and in the presence of DOM of higher aromaticity36. From a microbial perspective, SO4 2‒ can have primary and secondary effects on microorganisms that convert Hg(II) to MeHg, which have the requisite hgcAB gene pair37. In pure culture, SO4 2‒ reducing bacteria are highly efficient at converting Hg(II) to MeHg38–40, with the most pronounced MeHg formation by heterotrophic bacteria existing in cultures with intermediate S(‒II) concentrations39, high DOM aromaticity40, and high DOM thiol content41. However, in nature, hgcAB+ organisms span diverse phylogenetic groups beyond SO4 2‒ reducing bacteria, including methanogenic archaea and fermentative organisms19,42. Notably, in two systems with environmental19 and manipulated22 gradients in SO4 2‒, the diversity and abundance of the hgcAB gene pair decreased with increasing SO4 2‒. The combination of SO4 2‒ effects on Hg(II) bioavailability for methylation and activity of the microbial community are understood to contribute to the nonlinear response observed between SO4 2‒ and MeHg8,9,11–15,43. Given the potential for fluctuations in SO4 2‒ concentrations in wetlands in response to land management (e.g., agricultural practices), water management (e.g., stormwater treatment, phosphate mitigation via alum additions)44,45, or climate change processes27–29, as well as the uncertainties in the geochemical and microbial responses pertaining to MeHg formation, ecosystem-scale studies are needed to solidify linkages between SO4 2‒, MeHg formation, and subsequent MeHg uptake in aquatic food webs.

Here, field campaigns were conducted along hydrologic transects in three differing wetlands of the freshwater Florida Everglades, a managed wetland ecosystem with high atmospheric Hg deposition rates2,46. The wetland transects exhibited distinct horizontal geochemical gradients in SO4 2‒ spanning from low SO4 2‒ (<0.5 mg/L) wetlands that receive SO4 2‒ solely from the atmosphere to those highly enriched in SO4 2‒ (>65 mg/L) from agricultural runoff45,47. Across geochemical SO4 2‒ gradients, surface waters and pore waters were sampled for pertinent biogeochemical parameters, including filtered and particulate Hg(II) and MeHg (f.Hg(II), p.Hg(II), f.MeHg, p.MeHg), S species (SO4 2‒, S(‒II)), and dissolved organic carbon (DOC) concentration and DOM composition (specific ultraviolet absorbance at 254 nm (SUVA254)). We present data showing coherence between SO4 2‒ concentrations in wetlands, shifts in DOM composition, and MeHg formation across a comprehensive field study, which included the examination of MeHg concentrations across vertical gradients in wetlands (between surface and pore waters) and lateral gradients across wetlands. Lastly, relationships between MeHg concentrations in surface waters were compared to MeHg concentrations in prey fish (Gambusia holbrooki), an indicator species with a short life span (≤6 months) that reflects recent MeHg risk to the aquatic food web17,43,48. The findings advance a new ecosystem-scale conceptual model of the effects of SO4 2‒ on Hg risk to the aquatic food web and are discussed in context of parallel efforts that quantified the effects of SO4 2‒ on DOM thiol content34, the abundance and metabolic capabilities of hgcAB+ microorganisms19, downgradient impacts on MeHg formation and biouptake in Everglades National Park48, and strategies to mitigate the risk of Hg to wildlife and humans. This information will be vital to anticipate future effects of SO4 2‒ on Hg(II) methylation potential across subtropical wetlands in response to management actions, climate change, and international efforts to mitigate atmospheric Hg releases in the environment.

Results
Chemistry of canals contributing to freshwater Everglades wetlands
Canals, which drain Lake Okeechobee and the Everglades agricultural area45, exert considerable control on the biogeochemistry of waters in the three water conservation areas studied (water conservation areas 2A and 3A (WCA-2A and WCA-3A), and the Arthur R. Marshall Loxahatchee National Wildlife Refuge (LOX)), and exhibit distinct chemistries (Tables S1–S3 and Fig. 1). The levee-6 (L-6) canal, which discharges into northwest WCA-2A, drains water with DOM of higher aromaticity (DOM SUVA254 = 3.48 ± 0.16 L/mg m; avg ± 1 standard deviation) and higher concentrations of DOC (33.1 ± 4.2 mg/L), SO4 2‒ (64.7 ± 32.4 mg/L), and chloride (Cl‒) (131 ± 37.4 mg/L) compared to the levee-28 (L-28) canal (DOM SUVA254 = 3.30 ± 0.34 L/mg m; DOC = 19.6 ± 2.9 mg/L; SO4 2‒ = 6.84 ± 3.65 mg/L; Cl‒ = 32.8 ± 18.0 mg/L), the latter draining into northwest WCA-3A (Fig. 1). The Palm Beach Canal, which is an outer canal along the northeast perimeter of LOX, contains water of lower DOM aromaticity (DOM SUVA254 = 2.63 ± 0.34 L/mg m) and intermediate DOC, SO4 2‒, and Cl‒ concentration compared to the L-6 and L-28 canals (DOC = 19.9 ± 12.5 mg/L; SO4 2‒ = 43.9 ± 40.6 mg/L; Cl‒ = 96.2 ± 58.7 mg/L). Of the four Hg fractions measured from the three canals over the study (f.Hg(II), f.MeHg, p.Hg(II), p.MeHg; n = 23), Hg was primarily present as f.Hg(II) across all sites (Table S3). Particulate fractions accounted for <25% of the total Hg in canal waters (Fig. S1). Of the filtered fractions (f.Hg(II) and f.MeHg), f.MeHg was only responsible for 9-11% and f.Hg(II) accounted for the remaining 89–91% of the THg. Further, concentrations of f.Hg(II) and f.MeHg were similar across the three canals, with mean values ranging from 0.67–0.74 ng/L and 0.07–0.10 ng/L, respectively. One outlier was observed of elevated f.MeHg (1.11 ng/L) from the L-28 canal (08/18/2014). Differences in the chemistry of canal waters are interpreted to reflect upgradient agricultural practices that enrich waters in inorganic anions (SO4 2‒, Cl‒) from agricultural practices45,47 and mobilize highly aromatic DOM from peat soils33, which has important implications on the biogeochemical cycling of Hg in downgradient wetlands.

Surface and pore water biogeochemistry across wetland transects
The chemistry of surface and pore waters across the three wetlands exhibits distinct lateral and vertical differences that reflect proximal canal inputs and biogeochemical transformations of organic C, S, and Hg that arise from these inputs. The highest spatial resolution sampling was conducted in August 2014 (Fig. 2) across WCA-2A (n = 16) and WCA-3A (n = 15), and December of 2015 in LOX (n = 5), with sampling events in other years conducted at a reduced number of sites or only including surface waters (Fig. S2 and Table S2)49. Surface water SO4 2‒ concentrations of wetlands were comparable to adjacent canals at the top of each transect (i.e., near km=0) and exhibited a concentration hierarchy of WCA-2A > LOX > WCA-3A (Fig. 2a–c). With increased distance from canals, surface water SO4 2‒ concentrations consistently decreased (e.g., in Fig. 2, SO4 2‒ decreased from 65.8 to 50.6 mg/L, 22.5 to <0.5 mg/L, and 4.1 to <0.5 mg/L across transects in WCA-2A, LOX, and WCA-3A, respectively). Further, surface waters were sub-oxic to anoxic in all three wetlands, immediately downgradient of canal inputs (Fig. S3a–c), with dissolved oxygen concentrations generally increasing with distance from canal inputs49. The oxidation-reduction potential (ORP) of wetlands surface water and pore waters (Fig. S3d–f) reflected the degree of canal influence, with significantly lower ORP in pore waters of WCA-2A (‒271 ± 12.3 mV; average ± std) compared to WCA-3A (‒168.7 ± 18.4 mV) or the interior of LOX (LOX 8, ‒25 mV) (Welch’s t-test; p < 0.001). At the most downgradient site in WCA-3A, which is proximal to the L-29 canal, notable increases in SO4 2‒ and Cl‒ concentrations were observed (Fig. 2b) due to canal backflow into WCA-3A, as supported by the Everglades depth estimation network (EDEN) flow model (Fig. 1)50. The Florida Everglades is naturally a low SO4 2‒ environment, with concentrations between 0.1–1.0 mg/L in regions unimpacted by agricultural S inputs45, and therefore SO4 2‒ concentrations observed in interior WCA wetlands greatly exceeded background concentrations (up to ~70-fold) and were distributed across the entire range observed (≤0.5–72.0 mg/L; Fig. S4), creating vastly different water quality conditions across downgradient freshwater wetlands.

Several lines of evidence support the prominence of dissimilatory SO4 2‒ reduction in wetlands downgradient of canal inputs, explaining the decrease in surface water SO4 2‒ concentration with increased distance from canals. First, in sediment pore waters, SO4 2‒ concentrations were significantly lower than corresponding surface waters (Mann–Whitney rank sum test, p < 0.001), by ≤60.5, ≤26.5, and ≤3.5 mg/L in WCA-2A, LOX, and WCA-3A, respectively (Fig. 2a–c). Second, concentrations of inorganic sulfide (S(‒II)), a byproduct of dissimilatory SO4 2‒ reduction, were highest in pore waters of WCA-2A (S(‒II) = 1.6–9.4 mg/L), intermediate at locations in LOX and WCA-3A nearest canals (S(‒II) ≤ 0.45 and ≤ 0.16 mg/L, respectively), and below detection limit at locations in LOX and WCA-3A with SO4 2‒ ≤ 0.5 mg/L (S(‒II) ≤ 0.01 mg/L) (Fig. 2d–f); this hierarchy matched the magnitude of negative ORP across the wetlands (Fig. S3d–f). Although pore water SO4 2‒ and S(‒II) concentrations varied with distance from the canal (Fig. 2d–f), particularly across WCA-2A, a significant positive correlation was observed between pore water SO4 2‒ and S(‒II) concentrations across all sites (Fig. S5; R2 = 0.64, p < 0.001; n = 60). Notably, S(‒II) concentrations were above the detection limit (S(‒II) > 0.01 mg/L) in anoxic surface waters of WCA-2A (Fig. S6) but below the detection limit in surface waters from WCA-3A and LOX. Third, in wetland locations with evidence of SO4 2‒ reduction, we observed consistent decreases in the molar ratio of SO4 2‒ to Cl‒ with increased distance from canals (SO4 2‒/Cl‒; Fig. 2g–i), the latter being a conservative analyte inert to biogeochemical transformations. Concentrations of Cl‒ were largely uniform across the WCA-2A and WCA-3A (Fig. S7)49 and therefore decreases in the molar SO4 2‒/Cl‒ are interpreted to be primarily due to microbial SO4 2‒ reduction, consistent with previous observed increases in δ34S of SO4 2‒ due to reduction of isotopically light S47, the abundance of genes of SO4 2‒ reducing bacteria (e.g., dsrA)19, and landscape SO4 2‒ models51. These wetland transects document SO4 2‒ contamination of the WCAs, extending >10 km downgradient of active points of canal water release (WCA-2A, WCA-3A) or through intrusion from canals (LOX). Wetland SO4 2‒ concentrations governed the spatial extent of SO4 2‒ reducing conditions, with S(-II) accumulating in pore waters across all sites as a function of SO4 2‒ availability (Fig. S5) and extending to surface waters in WCA-2A (Fig. S6).

Canal contributions also had a marked influence on the DOC concentration and DOM composition within wetlands. Across wetland gradients, surface water DOC concentrations and DOM SUVA254, a proxy for aromatic C content52, were consistent between neighboring canals and adjacent wetland sites (Fig. 2j–o). In wetland pore waters, however, DOC concentrations were significantly higher compared to surface waters (Mann–Whitney rank sum test, p < 0.001, n = 70), particularly in regions with active SO4 2‒ reduction near canal inputs (Fig. 2j–l), and DOM in pore waters was of modestly higher aromaticity (DOM SUVA254; Welch’s t-test, p < 0.001, n = 70; Fig. 2m–o). Higher DOC concentration and greater DOM aromaticity in wetland pore waters near canal inputs compared to surface waters are interpreted to be the result of SO4 2‒ stimulating degradation of peat by SO4 2‒ reducing bacteria33 that release DOM of higher aromaticity (e.g., phenolic groups)29,32. Further, the anoxic (Fig. S3a–c), sulfidic conditions that prevail due to SO4 2‒ inputs are known to prevent enzymatic degradation of aromatic DOM53 and promote the sulfurization of DOM, the latter enriching DOM in thiol functional groups proportional to SO4 2‒ inputs to wetlands34. With increased distance from canals in WCA-2A and WCA-3A, surface water DOC concentrations decreased (e.g., from 37.0 to 32.7 and 23.1 to 15.0 mg/L, respectively) and DOM SUVA254 decreased (e.g., from 3.7 to 3.1 and 3.9 to 2.4 L/mg m, respectively) (Fig. 2m, n), likely the result of the photochemical transformation of DOM54 and autochthonous DOM production in wetland surface waters55. The decadic absorption coefficient of DOM at 254 nm (α254), which is a bulk DOM metric that scales positively with DOC concentrations and DOM SUVA254, showed similar trends across the three wetlands with higher DOM α254 near canal inputs and in wetlands with higher SO4 2‒49.

The effects of SO4 2‒ on DOM quantity and composition were observed across all wetland surface waters over the seven sampling events of this study (Fig. 3a–b), with significant positive correlations between SO4 2‒ and DOC concentration (R2 = 0.52, p < 0.001; n = 92) and SO4 2‒ concentration and DOM SUVA254 (R2 = 0.30, p < 0.001; n = 92). These relationships are interpreted to arise from upgradient and within-wetland processes resulting from the biogeochemical cascade due to SO4 2‒ effects on DOM mobilization from peat29,32,33. Greater variability is observed between correlations of DOC concentration and DOM SUVA254 and SO4 2‒ concentration at lower SO4 2‒ concentrations (Fig. 3a, b), which we interpret to be the result of canal waters with intermediate SO4 2‒ concentrations stimulating aromatic DOM release and SO4 2‒ reduction that depletes available SO4 2‒ (Fig. S5). In summary, canal water SO4 2‒ inputs lower the wetland redox status and stimulate S(‒II) production and the release of aromatic DOM across distinct lateral and vertical geochemical gradients within all three Everglades wetlands, and subsequently these biogeochemical changes govern the geochemical nature of Hg(II)31,36 and bioavailability for methylation39,40.

Mercury speciation and biological uptake across wetland transects
The lateral and vertical spatial distribution of Hg fractions was tightly coupled to the biogeochemical cascade linked to canal SO4 2‒ inputs. Across all wetlands, particulate Hg fractions were measured (p.Hg(II), p.MeHg)49 and were a minor fraction (accounted for ≤10% of the total Hg) (Fig. S1), consistent with previous observations4, and thus the analyses in this study focused on f.Hg(II) and f.MeHg. Concentrations of f.Hg(II) in wetland surface waters were consistent with those of adjacent canals (Fig. 4a–c) and showed modest variability from up- to downgradient along wetland transect and between surface and pore waters. Modestly higher f.Hg(II) concentrations were observed in pore waters with elevated DOC concentration, but f.Hg(II) concentration did not linearly correlate to DOC concentration (R2 = 0.06; n = 112), consistent with previous observations in the Everglades4. Rather, f.Hg(II) concentration exhibited a nonlinear relationship to SO4 2‒ concentration, where f.Hg(II) concentrations were low at SO4 2‒ < 1.0 mg/L, increased between 1 and 10 mg/L SO4 2‒, and decreased at SO4 2‒ > 10 mg/L (Fig. 3c). There was considerable variability in the relationship between f.Hg(II) and SO4 2‒ concentration, and thus the fit of data was not of statistical significance (p = 0.09; SI Section S1). We interpret the relationship to be from SO4 2‒ (1) increasing f.Hg(II) concentration at low-to-intermediate SO4 2‒ concentration, due to increases in DOC concentration and DOM SUVA254 (Fig. 3a, b) that enhance complexation of Hg(II)30, and (2) decreasing f.Hg(II) concentration at high SO4 2‒ concentration through S(‒II) scavenging f.Hg(II) and forming nano-β-HgS(s)31,36 that aggregate35. Although additional source and sink processes also influence f.Hg(II) concentrations in Everglades wetlands, including rainfall delivery of f.Hg(II)2,46, photo-reduction of Hg(II) to Hg(0)3,4, and partitioning of Hg(II) to peat43, SO4 2‒ exhibits notable control on the concentration of f.Hg(II), which can limit MeHg formation in wetlands.

The concentration of f.MeHg and percentage of total Hg as MeHg (% MeHg) showed dramatic differences between the three wetlands, with distinct vertical trends between surface and pore waters and lateral trends across wetlands. The % MeHg term is used to normalize f.MeHg concentration data to the total Hg concentration at a given location, as f.Hg(II) concentrations varied by an order of magnitude within and between the studied wetlands (e.g., Fig. 4a–c and S8a, b) and is the precursor for f.MeHg9,56. Canals draining into WCAs typically had f.MeHg concentrations and % MeHg of 0.10 ng/L and 10%, respectively (Table S3 and Fig. S8), with rare instances of higher concentrations (e.g., L-28 canal during August 2014). In WCA-2A, which had the highest SO4 2‒ loading, f.MeHg concentrations and % MeHg were lowest near the canal input (0.01–0.04 ng/L and 1.1–3.4% MeHg, respectively; Fig. 4d and Fig. S8). Further downgradient, average f.MeHg concentrations and % MeHg were higher in surface waters (0.27 ± 0.05 ng/L and 16.4 ± 2.3% MeHg, respectively; ± 1 standard deviation) compared to pore waters (0.06 ± 0.04 ng/L and 4.5 ± 2.8% MeHg, respectively) or the L-6 canal (Mann–Whitney rank sum test, p < 0.001, n = 14). In WCA-3A, which had lower SO4 2‒ loading than WCA-2A, f.MeHg concentrations and % MeHg were highest near the L-28 canal input, were greater in pore waters compared to surface waters, and decreased monotonically with distance from the canal (Fig. 4e, h and Fig. S8d, f) consistent with decreases in surface water SO4 2‒ (Fig. 2b). The highest f.MeHg and % MeHg levels observed across all three wetlands were in pore waters (≤5.0 ng/L and ≤84.5%, respectively) and surface waters (≤2.5 ng/L and ≤60%, respectively) of WCA-3A near the L-28 canal input, which is consistent with other studies on MeHg spatial distribution across the system4,43,51. In LOX, which had the widest range in SO4 2‒ concentrations, f.MeHg and % MeHg were low adjacent to the canal (≤0.09 ng/L and ≤13.8%, respectively) (Fig. 4f, i), increased to a maximum approximately 4 km from the canal (≤1.50 ng/L and ≤47%, respectively), and declined in the interior of the wetland (≤0.07 ng/L and ≤6.2%, respectively) were SO4 2‒ concentrations were <1 mg/L; similar behavior was observed in both surface and pore waters f.MeHg concentration across the LOX wetland SO4 2‒ gradient.

Across all wetland surface waters sampled over the seven field campaigns, a nonlinear unimodal trend was observed between surface water SO4 2‒ and f.MeHg concentrations (Fig. 3d). A nonlinear, 3-parameter equation was used to fit field data, defined in Eq. 1,

f:MeHg = a × e [ ‒0.5 × ln ( SO4 2‒ / x0 ) / b ] 2 (1)

where a, b, and x0 were 11.9, 1.30, and 27.6, respectively (R2 = 0.41, p < 0.001; n = 93). A maximum in f.MeHg concentration was observed at a SO4 2‒ concentration between 4 and 6 mg/L, and lower f.MeHg concentrations were observed at lower and higher SO4 2‒ concentrations. There was good agreement between observed and predicted f.MeHg concentrations at observed f.MeHg concentrations ≥ 0.1 ng/L (Fig. S9a) with no systematic difference in residual f.MeHg concentrations (i.e., the difference between observed and predicted f.MeHg concentrations) across the range of SO4 2‒ concentration (Fig. S9b), indicating the unimodal fit was robust across the conditions of the three wetlands. At both high (>30 mg/L) and low SO4 2‒ concentration (<1 mg/L), which corresponded to low f.MeHg concentration (<0.1 ng/L), a modest discrepancy was noted between observed and predicted f.MeHg concentrations (Fig. S9a). Across all wetlands, the % MeHg was significantly correlated (R2 = 0.77, p < 0.001; n = 168) to the concentration of f.MeHg in water (Fig. S10), which has been observed in the Everglades9,19 and other systems10,15 to correspond with faster measured rates of MeHg production. Thus, wetlands with higher aqueous f.MeHg and % MeHg are interpreted to reflect recent MeHg production, as MeHg that is produced is susceptible to sink processes (e.g., photo-demethylation57 and adsorption to peat)58.

Vertical and lateral spatial trends in f.MeHg concentration and % MeHg in response to SO4 2‒ reflect a combination of (1) the redox state of wetland surface and pore waters, (2) geochemical processes governing Hg(II) aqueous speciation31,36 and bioavailability39–41,59, and (3) the microbial communities with the pre-requisite hgcAB gene pair for methylation37. Below we detail the observations from low to high SO4 2‒ concentration across the three wetlands and interpret environmental f.MeHg concentrations to reflect the balance between Hg(II) methylation3,4,19 and MeHg demethylation9,23, with differences primarily being driven by differences in Hg(II) methylation9,15,24. At SO4 2‒ concentrations <1 mg/L, observed in the middle of WCA-3A and LOX, f.MeHg concentrations were low in surface and pore waters, interpreted to be a combination of the absence of S(‒II) and higher redox state of the water column and wetland sediments (Fig. S3), lower f.Hg(II) concentration, DOC concentration, and DOM SUVA254 (Fig. 3a–c), and lower DOM thiol content34; all of these conditions decrease the bioavailability of Hg(II) to methylation39–41. Although higher hgcAB gene abundance was observed in peat of low SO4 2‒ Everglades wetlands19, the low ambient MeHg observed under these conditions is attributed to high wetland redox state and low Hg(II) bioavailability. The modest disagreement between observed and predicted f.MeHg at SO4 2‒ concentrations <1 mg/L (Fig. S9a) simply reflects the low MeHg formation under low, ambient levels of SO4 2‒ that are not well fit using a 3-parameter unimodal function. At intermediate SO4 2‒ concentrations (2–6 mg/L), such as in LOX and the upgradient portions of WCA-3A (Fig. 4e, f), f.MeHg concentrations were elevated in sulfidic pore waters compared to oxygenated surface waters, which is interpreted to reflect enhanced MeHg formation in surficial wetland sediments and advection and diffusion to surface waters3. The highest f.MeHg concentration and % MeHg were observed under these conditions (Figs. 3d, 4e), where microbial hgcAB gene abundance is elevated in sediments19 and sulfidic pore waters have high DOC concentration and DOM of more aromatic and thiol group content34, which promote Hg(II) methylation39–41 likely as nano-β-HgS(s)31,36. At locations of high SO4 2‒ concentrations (>12 mg/L) in WCA-2A downgradient from canals (Fig. 4d, g), f.MeHg concentration and % MeHg were notably higher in surface waters compared to pore waters. This observation cannot be explained by MeHg formation in sediments and advective or diffusive flux60,61, but may be attributed to MeHg formation by periphyton associated with emergent and submerged aquatic vegetation in the water column20,21. The shallow wetlands studied here are unlikely to support bulk water column methylation observed in deeper, thermally stratified waters where suspended particulate materials accumulate62,63. Lastly, at locations of high SO4 2‒ concentration in WCA-2A near the canal, f.MeHg concentration was low in both surface and pore waters (Fig. 4d, g), which is attributed to high S(‒II) conditions in surface and pore waters that decrease the concentration and bioavailability of f.Hg(II) (Fig. 3c) via the formation31,36 and aggregation35 of nano-β-HgS(s) and the low microbial abundance of communities with the hgcAB genes19. Despite the elevated concentrations of highly aromatic, sulfurized DOM34 under these sulfidic conditions, crystalline nano-β-HgS(s)36 will form and dramatically decrease f.Hg(II) concentrations in the wetland pore and surface waters (Figs. 3c, 4a) and contributes to decreased MeHg formation64.

Despite many inferential studies that concluded direct links between SO4 2‒ loading, the activity of SO4 2‒ reducing bacteria, and MeHg production3,4,9,21,45, a recent microbial metagenomic analysis of sediments across these same sites did not observe hgcAB+ organisms with the genes for dissimilatory SO4 2‒ reduction19. Rather, MeHg concentration and experimental methylation rates were governed by synergy between the hgcAB abundance of other microbial clades and DOM composition (SUVA254)19. We interpret that SO4 2‒ inputs directly alter Hg(II) geochemistry and bioavailability and indirectly alter the microbial metabolism, which stimulates MeHg formation at low-to-intermediate SO4 2‒ concentrations (2–12 mg/L) by SO4 2‒ reducing bacteria consuming fermentation products and/or stimulating methanogenic activity through syntrophy19.

The field data underlying these biogeochemical relationships span multiple years (2012–2019) and seasons (May and December) (Table S2) and leverage geochemical34, hydrological, and microbial insights19, providing a comprehensive dataset to develop a framework for MeHg production and risk. Taken together, a highly consistent trend is observed across all wetland surface waters between concentrations of SO4 2‒, the DOM α254 (which scales positively with increases in DOC concentrations and DOM SUVA254), and f.MeHg concentration (Fig. 5). We interpret the spread in f.MeHg at a given SO4 2‒ concentration (Figs. 3d, 5) to be the effects of seasonality on MeHg formation, as noted previously4,17, with higher observed MeHg formation in the spring and summer months (Fig. S11) due to higher rates of microbial metabolism and regular rainfall delivering Hg(II)3 to wetlands. The unimodal relationship here between SO4 2‒ and f.MeHg concentration (Fig. 3d, 5) is consistent with the conceptual model first proposed by Gilmour and Henry (1994)8 but incorporates recent innovations in the understanding of Hg(II) nano-scale geochemistry and the complexities of microbial Hg(II) methylation, which provides mechanistic insights that explain MeHg formation across the greater Everglades16 and in response to increases43 and decreases in SO4 2‒ loading51. We assert that the clear coherence in the relationship between SO4 2‒ and f.MeHg concentration here is a product of the study design, with field campaigns that sampled lateral hydrologic flow paths from canal sources downgradient across wetlands, resolved vertical gradients between wetland surface waters and sediment pore waters, and coupled routine biogeochemical data (e.g., Figs. 2–5) with parallel efforts on SO4 2‒ effects on DOM composition34 and abundance and metabolic capabilities of hgcAB+ microorganisms19. Although the assertion of SO4 2‒ is a master variable on MeHg formation in the Everglades is not in agreement with conclusions from state environmental reports65,66, which may be due to differences in study design or approaches used for biogeochemical characterization, the observed findings are congruent with studies on the effects of SO4 2‒ on MeHg formation in diverse wetlands9–15.

The concentrations of f.MeHg in wetland surface waters significantly correlated with the concentration of MeHg in gambusia (Fig. 6; R2 = 0.68; p < 0.001; n = 33), a resident fish species17. The total Hg concentration of Gambusia was primarily MeHg (91.2 ± 14.1%, n = 33)49. Provided that these resident prey fish live relatively short lives (≤6 months) and feed on a mixture of periphyton and zooplankton17, the data provide strong support that SO4 2‒ promotes MeHg formation in surficial sediments and compartments of the water column resulting in enhanced risk of MeHg bioaccumulation at the base of the aquatic food web. Figure 7 synthesizes a framework on the association between SO4 2‒, DOM, and the potential for MeHg formation in proximity to aquatic food webs, which dictates MeHg risk. We further conclude that water concentrations of f.MeHg may be a good proxy to predict food web risk in the Everglades due to the strong relationship observed here and within Everglades National Park48. The highest gambusia MeHg concentrations were observed at locations with intermediate SO4 2‒ concentrations, with fish MeHg concentrations exceeding 1000 ng/g dry weight, similar to that reported previously across the WCAs67 and greater Everglades ecosystem16,68. Taken together, this study shows coherence in the underlying hydrologic and biogeochemical processes that govern MeHg risk in the freshwater Everglades (Fig. 7), which support the use of SO4 2‒ concentration to model risk across the freshwater ecosystem51 and to forecast the influence of water management decisions on MeHg formation and food web bioaccumulation in Everglades National Park48.

Methods
Field sampling locations
Field sites were selected to follow existing hydrologic and geochemical gradients across three freshwater, sawgrass-dominated wetlands of the Florida Everglades: water conservation areas 2A and 3A (WCA-2A, WCA-3A), and the Arthur R. Marshall Loxahatchee National Wildlife Refuge (LOX) (Fig. 1 and Supplementary Information (SI) Table S1). WCA-2A and WCA-3A receive high and intermediate concentrations of sulfate from canal inputs that drain upgradient agricultural lands, respectively, and generally exhibit decreasing sulfate concentrations from north to south34,45. Surface water flow vectors typically observed across WCA-2A and 3A are shown in Fig. 1, based on the Everglades Depth Estimation Network (EDEN) Surface-Water Interpolation Model Version 350. The WCA-2A transect consisted of 16 sites over 14.5 km within the wetland that followed water flow south from the levee-6 (L-6) canal inputs to the middle of WCA-2A; one additional site of the L-6 canal immediately upgradient of the wetland was sampled to characterize the water discharging into WCA-2A from the control structure. The WCA-3A transect consisted of 15 sites over 39.7 km, starting at the terminus of the levee-28 (L-28) canal and extending south to the intersection of WCA-3A and the L-29 canal. Due to lack of access to the L-28 canal within WCA-3A, the L-28 canal was sampled at the junction with highway I-75 to assess the composition of water entering WCA-3A (Fig. 1). LOX, in contrast to WCA-2A and WCA-3A, generally exhibits lower sulfate concentrations due to the interior regions being primarily rainfall-driven and hydrologically isolated from canal inputs by a perimeter canal34,45. However, contributions of canal-derived constituents (e.g., SO4 2‒, chloride (Cl‒)) intrude across the levees and penetrate the interior of LOX45,74. Five locations were sampled in LOX from the interior (LOX 8) to the levee near the L-40 canal (LOX-136) (Fig. 1), which spanned 12.5 km. Sites across the three WCAs were previously evaluated to quantify the effects of SO4 2‒ on DOM reduced sulfur content and speciation34 and microbial metagenomic sequencing for the Hg methylation genes (hgcAB+)19.

Water collection and analyses
Wetland and canal locations were sampled approximately once annually from 2012 to 2019, spanning from May to December. Table S2 summarizes the sampling date ranges, cumulative precipitation and wet Hg deposition data (on an annual basis and the 3 months prior to sampling) from local stations maintained by the National Atmospheric Deposition Program46, and air temperature data during sampling. The cumulative annual precipitation and wet Hg deposition over the years of the study were within the range typically observed at these sites, based on available data records (1997–2023; Table S2). In total, 189 and 23 discrete water samples were collected from wetlands (WCA-2A, n = 99; WCA-3A, n = 78; LOX, n = 12)49 and canals75, respectively, across the study period during seven field campaigns. The density of samples across the three wetlands aimed to (1) span the complete range of SO4 2‒ concentrations of the freshwater Florida Everglades45 with comparable density as a function of SO4 2‒ concentration and (2) have higher sample density at the low-to-intermediate concentration range of SO4 2‒ (≤0.5–12 mg/L) (Fig. S4). At times, transects were sampled in a truncated design (Table S2), where some of the sites shown in Fig. 1 were skipped to best meet the above mentioned sampling goals.

At all sites, surface water was collected in 2 L polyethylene terephthalate (PETE) bottles at the air-water interface and stored in coolers on wet ice until processing the same day. For wetland sites only, pore water was collected 10 cm below the sediment-water interface at a rate of 100 mL min−1 using a Teflon sipper connected to Teflon tubing and a peristaltic pump. The sipper was repositioned laterally by ~0.5 m every 10 min to not deplete sediment pore water.

First, pore water temperature, conductivity (Orion four-cell conductivity electrode), pH (Orion ROSS Ultra™ electrode), dissolved oxygen (DO) concentration (Orion RDO optical probe), and oxidation-reduction potential (ORP; Orion ORP Triode electrode) were measured using a flow-through cell (Geotech; 40 mL dead volume) and multi-parameter meters (Orion Star™ A329, Beckman Coulter pHi 410)56. Next, pore waters were in-line filtered during collection (QFF, 0.7 μm pore size, pre-combusted at 550°C, Whatman™) for the following analyses: sulfide (high-density polyethylene (HDPE) bottles, preserved with 50% volume/volume (v/v) sulfide antioxidant buffer), inorganic anions (HDPE bottles, no preservation, stored at 4°C), major cations anions (HDPE bottles, no preservation, stored at 4°C), DOC concentration and DOM ultraviolet and visible (UV-vis) light absorption (pre-baked amber borosilicate glass vials at 450°C for 4.5 h, no preservation, stored at 4°C), and filtered total Hg (f.THg) and filtered MeHg (f.MeHg) (acid-cleaned Teflon bottles, preserved with 1% trace-metal grade hydrochloric acid). Pore water particulate total Hg (p.THg) and particulate MeHg (p.MeHg) concentrations were not measured due to potential artifacts during sample collection. Surface waters were filtered within 8 h of collection by vacuum filtration through a QFF for the identical set of analyses as pore water samples detailed above; QFF filters were frozen (−20°C) for quantification of p.THg and p.MeHg concentrations. Field replicates of wetland surface waters and pore waters (n = 8) were sampled in 5% of total samples49. The average relative percent deviations of field replicates for concentrations of f.THg, f.MeHg, DOC, and SO4 2‒ were 5.5, 4.2, 0.6, and 2.8%, respectively.

Complete details on the analysis methods and limits of quantification are provided in an associated ScienceBase data release49. Sulfide was quantified within 12 h of sample collection by ion-selective electrode. Major inorganic anions (Cl‒, nitrate (NO3 ‒), SO4 2‒) were quantified by ion chromatography76. DOC concentration was quantified by persulfate oxidation (OI Analytical, model 700)77. UV-vis absorption spectra were measured from 190 to 800 nm, and decadic absorbance values were converted to absorption coefficients as

α λ = A λ / l (2)

where α λ is the decadic absorption coefficient (cm−1), A λ is the absorbance, and l is the path length (cm). The DOM specific ultraviolet absorbance at 254 nm (SUVA254), a proxy for DOM aromaticity52 that indicates DOM source and reactivity to Hg(II)19,36,40, was calculated as:

SUVA254 = α 254 / [DOC] (3)

by dividing the α 254 (m−1) by DOC concentration (mg L−1). Mercury measurements were made at the US Geological Survey Mercury Research Laboratory (Madison, WI). THg measurements (f.THg, p.THg) were made by BrCl oxidation (0.2 M; 1% v/v for f.THg and 5% for p.THg), stannous chloride reduction, dual amalgamation, and cold vapor atomic fluorescence spectroscopy (CVAFS) detection following a modified version of US Environmental Protection Agency (EPA) method 1631, Revision E (Brooks-Rand TDM-II)78. Filtered and particulate MeHg were analyzed using a modified version of the US EPA method 163079 with isotope dilution. Approximately 20 pg of isotopically-enriched Me199Hg and 1 mL of 1.6 M copper SO4 2‒ solution were added to 40 mL aliquots for MeHg analysis. Ambient MeHg was determined by relating the ratio of added Me199Hg to Me202Hg after distillation, aqueous phase ethylation, trapping on Tenax (Buchem B.V.), isothermal gas chromatography separation, and detection by inductively coupled plasma mass spectrometry (iCAP, Thermo Scientific) using an automated MeHg analyzer (MERX-M, Brooks-Rand). All field process blanks (n = 15) and quality assurance and quality control data are provided in the SI (Section S2; Fig. S12). The concentration of filtered Hg(II) (f.Hg(II)) was calculated as:

f.Hg(II) = f.THg ‒ f.MeHg (4)

In cases where the concentration of f.MeHg was below the daily detection limit (n = 14 instances of 189 wetland and canal samples)49, the daily detection limit was used in the calculation of f.Hg(II). Dissolved gaseous Hg, reported at <0.04 ng L−1 in the Everglades3, was assumed to have minimal influence on calculated f.Hg(II) values.

Fish collection and analyses
Gambusia holbrooki (termed gambusia) were collected from wetland sites using a 30 cm diameter Teflon sieve. Gambusia was selected because they have a short lifespan (≤6 months), feed on a mixture of periphyton and zooplankton, and reflect MeHg availability to the proximal aquatic food web in the recent past17,43,48. A composite sample was collected for each location, often consisting of 20–30 individual fish. Samples were frozen on-site (‒80°C), lyophilized, and homogenized via ball mill. Biological samples were first digested in 4.5 M Omnitrace nitric acid prior to biological MeHg analysis80. After the completion of MeHg analysis, samples were oxidized with bromine monochloride (BrCl, 10% v/v) and analyzed for total Hg by CVAFS using USEPA Method 1631, Revision E78.

Statistical analyses
Statistical comparisons between variables were assessed using linear regression analysis and paired t-tests (SigmaPlot v. 14.5); p values < 0.05 were considered statistically significant. For paired t-tests, a normality test (Shapiro–Wilk) was first performed. Data that passed the normality test were analyzed by a Welch’s t-test, where equal variances are not assumed, and those that did not pass the normality tests were analyzed by the Mann–Whitney rank sum test (suitable for non-parametric data).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript investigated role of sulfate loading on the methylation of Hg(II) in the surface water and pore water of the\nsubtropical wetlands to predict its future response to the management of land and water as well as climate change affecting\nsulfate concentrations in wetland waters. For this purpose, sulfate, sulfide, SUVA, DOC, THg and MeHg concentrations\nwere analyzed from the surface and pore water samples. The authors found that sulfate increases Hg(II) methylation in its\nlow to intermediate levels through enhancing Hg(II) availability and Hg(II) methylating communities across the wetland\nlength in the three represented zones. While experimental methods and data interpretation are solid and discussion is well\ndescribed based on thorough literature review, my only concern is the novelty of this work, since the unimodal response of\nMeHg on sulfate concentration has been known for a while (lines 307-320). Revision suggestions are found below.\n1. Lines 74-75: Suggest to add quantitative information on ‘high and intermediate’ concentration ranges.\n2. Lines 91-92: “….. to those highly enriched in SO42‒ (> 65 mg/L) in rheotrophic wetlands (?).” Suggest to add ‘rheotrophic’\nor other words proper here.\n3. Lines 145-146: Suggest to insert DO concentrations in Figure 2 or Supporting Information.\n4. Lines 169-170: “therefore decreases in the molar SO4/Cl are interpreted to be primarily due to microbial SO4 reduction.”\nDoes it mean a decline of DO following the distance from the canal? Please clarify this vagueness.\n5. Lines 182-185: “Higher DOC concentration and greater DOM aromaticity in wetland pore waters near canal inputs are\ninterpreted to be the result of SO4 stimulating degradation of peat by SO4 reducing bacteria that releases DOM of higher\naromaticity.” Suggest to give example molecular groups that can be released to water via peat degradation.\n6. Lines 210-211 “Across all wetlands, particulate Hg fractions were measured (p.Hg(II), p.MeHg) and were a minor fraction\n(accounted for ≤10% of the total Hg) (Figure S3).” However, Figure S3 does not show particulate Hg fraction.\n7. Lines 251-257: A relatively large difference is observed between the measured and predicted MeHg concentrations in the\nlow MeHg range (Figure S7a). The reason of this errors should be discussed.\n8. Lines 251-257: Figure S7 (B) was not explained in the MS.\n9. Lines 257-260: Why does this correlation (%MeHg/THg vs filtered MeHg) mean recent MeHg production? Suggest to give\ndetailed explanation.\n10. Lines 286-290: Aggregation of nano-HgS(s) was suggested as a reason for low Hg(II) methylation in the WCA-2A canal\nzone. How about the role of high DOM at the same site?\n11. Lines 295-298: I agree with this interpretation, however, the role of redox potential cannot be ignored, since sulfate\nreduction rate and Hg(II) methylation rates are directly related to the anaerobic microbial activities.\n12. Lines 321-326: Suggest to add a brief explanation on ecology of gambusia to justify the positive correlation between fish\nMeHg and surface water filtered MeHg concentration. What is the major carbon source of this species?\n13. Lines 342: Wondering how climate change increases sulfate contraption in freshwater ecosystem.\n14. Figure 7: HgcAB was not analyzed in this study. Suggest to include SO4/Cl instead of HgcAB as it was used as a\nsurrogate.\n15. My only concern is the novelty of this work, since unimodal responses of MeHg on sulfate concentration have been\nknown for a while, as described in the MS (lines 307-320). Please clearly emphasize the novelty and novelty of this study in\nthe abstract or conclusion.", "reviewer_2": "General comments\nThis manuscript presents an original study that adds to the existing body of knowledge surrounding sulphate and\nmethylmercury dynamics in wetlands and will certainly be of interest to the mercury research community. Though some\npolishing of language is necessary, the methods are clearly described and the manuscript is reasonable to follow. However,\npresumably to stay within the word limit, the authors exclude some details that would be helpful to ensure a reader’s\nunderstanding. My comments are primarily requesting clarification, on these two fronts and other points detailed below:\nFirst, in the title and throughout the manuscript, the authors refer to the idea of ‘methylmercury risk’, but this is never clearly\ndefined. Is risk equivalent to MeHg concentrations? In Fig 7, this seems to be implied, but also related to bioavailability and\nhgcAB abundance? High background [MeHg] could suggest that a system is less likely to experience increases due to\nperturbations, and therefore at lower ‘risk’.\nSecond, the field methods are unclear without going into the SI. It appears that WCA-3A was sampled less than WCA-2A,\nand LOX less frequently than either. Differences in these sampling timelines are not explained, nor are the possible effects\nof sampling at different times throughout the years. This could be beneficial in terms of covering a wider range of flow\nconditions but also seems like it would be a confounding factor in the concentrations observed in fish, since they would be at\na different stage in the life cycle.\nDetailed comments\nAbstract\nLine 19: This is quite specific for the start of an abstract. Consider opening with a broader statement regarding MeHg in\nwetlands.\nLines 20-21: Consider ‘land and water management strategies and climate change effects’ for specificity.\nLines 22-23: Consider rearranging to ‘We sampled surface and pore waters across SO4 gradients of three freshwater\nwetlands in the Florida Everglades…’\nIntro\nLine 51: Here and throughout, rather than SO4 ‘levels’, consider ‘concentrations’ or ‘loads’ for greater specificity.\nLine 83: Here and throughout, land and water management is mentioned, but the introduction thus far only mentions\nagriculture. Please expand.\nResults and Discussion\nLine 111: Should say '…water conservation areas studied...’\nLine 112: Comma should be after ‘(LOX))’ in next line.\nLines 141-142: This is quite confusing; is there a way to rephrase without using ‘distance from canals’ twice?\nLine 155: Here and throughout, there are comparisons such as ‘notably lower’, ‘decreases’, etc. These would benefit from\nsupport of some simple statistics.\nLine 182: Similar or modestly higher aromaticity compared to surface water?\nLine 191: The connection between photochemical transformation of DOM and autochthonous DOM production to increased\ndistance from canals is unclear.\nLine 222: Typo: ‘qualitative’\nLine 226: Consider expanding on the ‘additional source and sink processes’ or removing the statement.\nLine 229: What does %MeHg tell us? E.g. what is it an indicator of that makes it distinct from [MeHg]?\nLine 249: Typo?\nLine 282: Typo: notably\nLine 292: Typo: observe\nLine 296: Not sure that the results of the study really support that SO4 inputs ‘indirectly alter the microbial metabolism’.\nLines 299-300: Consider adding climate summaries (e.g. average annual temperature, total precip) to SI to illustrate\nrepresentativeness of data collected.\nLine 316: ‘SO4 is a master variable’ seems like an overconfident assertion, especially given the limited within-year temporal\ncoverage of the study.\nLines 323-324: Consider also adding movement patterns throughout the life cycle to tie observations to locations. Given the\nshort life span, did the varied sampling timeline influence the observations at all?\nLine 361: Consider including estimated timeline of response for local interventions as well.\nMethods\nConsider adding a brief section detailing statistical analyses.\nLine 380: Change ‘following’ to ‘follow’ and remove ‘span’.\nLine 383: How do WCA-2A and WCA-3A differ from each other? If they are very similar, what value does the second add?\nLine 386: Figure caption says GARDEN rather than EDEN; presumably this is the same model under different names? If so,\nsticking with one would be better.\nLine 388: in L-6, is L an acronym or abbreviation for something?\nLine 404-405: Additional details are warranted here. For example, there looks to have been no sampling in 2016. WCA-3A\nwas not sampled in 2012, and LOX was only sampled in 2015 and 2019. Is that correct? If so, the current description is quite\nmisleading. Please also add reasoning for truncating transects in later years of the study.\nLine 449: Please report Hg QA/QC info, at least in the SI.\nLine 455: Consider adding reasoning for selecting this species for readers unfamiliar with the Everglades."}, "author_response": "Authors Note:\nWe have carefully considered the comments from the two reviewers and have revised the\nmanuscript based on the reviewers’ comments or provided detailed responses to the comments\nbelow. All responses are shown in blue text, and line numbers reference the Track Changes\nversion of the revised manuscript. Revised text are shown indented and italicized. In addition to\nthe two journal reviewer comments, the manuscript also underwent peer review by a federal\nemployee (Dr. Chris Eckley, U.S. EPA), which is part of Fundamental Science Practices for\nmanuscript approval by the U.S. Geological Survey. A few minor modifications were made in\nresponse to the review by Dr Eckley, which are shown in Track Changes in the revised\nmanuscript. We appreciate the invitation to submit a revision of this manuscript for\nconsideration. Thank you for your time.\n____________________________________________________________________________\n______________\nReviewer #1 (Remarks to the Author):\nThis manuscript investigated role of sulfate loading on the methylation of Hg(II) in the surface\nwater and pore water of the subtropical wetlands to predict its future response to the\nmanagement of land and water as well as climate change affecting sulfate concentrations in\nwetland waters. For this purpose, sulfate, sulfide, SUVA, DOC, THg and MeHg concentrations\nwere analyzed from the surface and pore water samples. The authors found that sulfate\nincreases Hg(II) methylation in its low to intermediate levels through enhancing Hg(II) availability\nand Hg(II) methylating communities across the wetland length in the three represented zones.\nWhile experimental methods and data interpretation are solid and discussion is well described\nbased on thorough literature review, my only concern is the novelty of this work, since the\nunimodal response of MeHg on sulfate concentration has been known for a while (lines 307-\n320). Revision suggestions are found below.\nWe have made several modifications to the manuscript to highlight the novelty of the study,\nwhich focus on (1) the linkages established between geochemical and hydrological processes\nand MeHg formation and (2) this being the first study that links water quality conditions directly\nto MeHg formation and update in the aquatic food web. It is important to recognize that the\nobservations reported are at the ecosystem scale (Figure 1), as they covered the three major\nfreshwater wetlands of the Florida Everglades. These modifications to highlight the novelty were\nmade in adherence to the Nature Communications Formatting Instructions, which state “Avoid\nphrases like “novel”, “new”, “for the first time”, and “unprecedented” throughout the manuscript”.\nAbstract: Lines 32-35\n“The study reports coherence between SO 2‒ and MeHg concentrations and biologic\n4\nuptake that permits an advancement in MeHg risk assessment to aquatic food webs that\nincorporate geochemical, microbial, and hydrological wetland processes, which has\nglobal implications due to the threat of increased SO 2‒ from anthropogenic sulfur uses\n4\nand climate change.”\nIntroduction: Lines 57-58 & 108-113\n“A revisitation of linkages between SO 2‒ concentrations and the potential for MeHg\n4\nformation and uptake in biota is needed.”\n“The findings advances a new ecosystem-scale conceptual model of the effects of SO 2‒\n4\non Hg risk to the aquatic food web and are discussed in context of parallel efforts that\nquantified the effects of SO 2‒ on DOM thiol content,34 the abundance and metabolic\n4\ncapabilities of hgcAB+ microorganisms,19 downgradient impacts on MeHg formation and\nbiouptake in Everglades National Park,48 and strategies to mitigate the risk of Hg to\nwildlife and humans.”\nResults & Discussion: Lines 343-346, 351-357, 391-395\n“The field data underlying these biogeochemical relationships span multiple years (2012-\n2019) and seasons (May and December) (Table S2) and leverage geochemical,34\nhydrological, and microbial insights,19 providing a comprehensive dataset to develop a\nframework for MeHg production and risk.”\n“The unimodal relationship here between SO 2‒ and f.MeHg concentration (Figures 3b,\n4\n5) is consistent with the conceptual model first proposed by Gilmour and Henry (1994)8\nbut incorporates recent innovations in the understanding of Hg(II) nano-scale\ngeochemistry and the complexities of microbial Hg(II) methylation, which provides\nmechanistic insights that explain MeHg formation across the greater Everglades16 and in\nresponse to increases43 and decreases in SO 2‒ loading.51”\n4\n“The comprehensive framework presented here (Figure 7) for the Florida Everglades\nsupport that efforts to decrease SO 2‒ concentrations from agricultural sources have\n4\npromise to decrease aqueous and biological MeHg concentrations in wetlands (Figures\n5, 6), offering a local strategy to mitigate Hg contamination.”\n1. Lines 74-75: Suggest to add quantitative information on ‘high and intermediate’ concentration\nranges.\nWe have added clarification on the sulfate concentration ranges defined as low, intermediate,\nand high, at a later portion of the manuscript (Lines 96-98, 462-465; see new Figure S4), and\nsimplified the presentation here in the Introduction.\nLines 85-88\n“The combination of SO 2‒ effects on Hg(II) bioavailability for methylation and activity of\n4\nthe microbial community are understood to contribute to the non-linear response\nobserved between SO 2‒ and MeHg,8,9,11–15,43”\n4\n2. Lines 91-92: “….. to those highly enriched in SO42‒ (> 65 mg/L) in rheotrophic wetlands (?).”\nSuggest to add ‘rheotrophic’ or other words proper here.\nWe appreciate the suggestion from the reviewer. However, the terminology of “rhoetrophic” is a\nregional-specific term of a wetland with continuous high-water table. We have chosen to forego\nadding a specific term here, but have modified the presentation to clarify that the wetlands have\nstanding water year round (Lines 96-98).\n“The wetland transects exhibited distinct horizontal geochemical gradients in SO 2‒\n4\nspanning from low SO 2‒ (< 0.5 mg/L) wetlands that receive SO 2‒ solely from the\n4 4\natmosphere to those highly enriched in SO 2‒ (> 65 mg/L) from agricultural runoff.44,46”\nunderstands the flow vectors are for surface flow (Lines 434-436)\n“Surface water flow vectors typically observed across WCA-2A and 3A are shown in\nFigure 1, based on the Everglades Depth Estimation Network (EDEN) Surface-Water\nInterpolation Model Version 3.49”\n3. Lines 145-146: Suggest to insert DO concentrations in Figure 2 or Supporting Information.\nWe appreciate the suggestion and have added DO and ORP data to the SI in a new figure\n(Figure S3). We have also revised the presentation to further the comparison to include both DO\nand ORP, two important metrics that differ in response to sulfate.\nFigure S3. Measurements of (a-c) oxidation-reduction potential (ORP) and (d-f) dissolved oxygen (O ) of\n2\nsurface and pore waters from Water Conservation Area 2A (WCA-2A) (August, 2014), WCA-3A (August,\n2014), and the Arthur R. Marshall Loxahatchee National Wildlife Refuge (LOX) as a function of distance\nfrom canal inputs (November, 2015). Dashed lines are presented to guide the eye.\nLines 153-160\n“Further, surface waters were sub-oxic to anoxic in all three wetlands immediate\ndowngradient of canal inputs (Figure S3a-c), with concentrations generally increasing\nwith distance from canal inputs.49 The oxidation-reduction potential (ORP) of wetlands\nsurface water and pore waters (Figure S3d-f) reflected the degree of canal influence on\nwetland redox status, with significantly lower ORP in pore waters of WCA-2A (‒271 ±\n12.3 mV; average ± std) compared to WCA-3A (‒168.7 ± 18.4 mV) or the interior of LOX\n(LOX-8, ‒25 mV) (Welch’s t-test; p<0.001).”\n4. Lines 169-170: “therefore decreases in the molar SO4/Cl are interpreted to be primarily due\nto microbial SO4 reduction.” Does it mean a decline of DO following the distance from the\ncanal? Please clarify this vagueness.\nPlease see our response to the comment above that expanded the study to include DO\nconcentration data.\n5. Lines 182-185: “Higher DOC concentration and greater DOM aromaticity in wetland pore\nwaters near canal inputs are interpreted to be the result of SO4 stimulating degradation of peat\nby SO4 reducing bacteria that releases DOM of higher aromaticity.” Suggest to give example\nmolecular groups that can be released to water via peat degradation.\nWe have added an example of a type of DOM molecular group that would be released, which is\nfrom the mechanistic studies on this topic. (Lines 201-204)\n“Higher DOC concentration and greater DOM aromaticity in wetland pore waters near\ncanal inputs compared to surface waters are interpreted to be the result of SO 2‒\n4\nstimulating degradation of peat by SO 2‒ reducing bacteria33 that releases DOM of higher\n4\naromaticity (e.g., phenolic groups).29,32”\n6. Lines 210-211 “Across all wetlands, particulate Hg fractions were measured (p.Hg(II),\np.MeHg) and were a minor fraction (accounted for ≤10% of the total Hg) (Figure S3).” However,\nFigure S3 does not show particulate Hg fraction.\nWe appreciate the reviewer identifying the incorrect Figure call out. We have revised the text to\nproperly call out Figure S1. We also revised Figure S1 to show the particulate percentage\n(rather than the filtered percentage) to improve clarity.\nFigure S1. Box plots present median and quartile ranges of percentage of (a) total total Hg as particulate\nHgT and (b) total MeHg as particulate MeHg between surface waters of Water Conservations Areas\n(WCA-2A, 3A, LOX) and canals that drain into these wetlands (L-6 and L-28 canals). Error bars represent\n10-90% percentiles, outliers are shown as data points, and p-values present results from a paired t-tests\nbetween WCA and canal data.\n7. Lines 251-257: A relatively large difference is observed between the measured and predicted\nMeHg concentrations in the low MeHg range (Figure S7a). The reason of this errors should be\ndiscussed.\nWe have expanded the discussion to detail the discrepancy and include an explanation of why\nthere is higher differences between measured and predicted MeHg concentrations at low\nenvironmental MeHg\nLines 286-289\n“At both high (>30 mg/L) and low SO 2‒ concentration (<1 mg/L), which corresponded to\n4\nlow f.MeHg concentration (< 0.1 ng/L; Figure S8a), a modest discrepancy was noted\nbetween observed and predicted f.MeHg concentrations.”\nLines 310-313\n“The modest disagreement between observed and predicted f.MeHg at SO 2‒\n4\nconcentrations < 1 mg/L (Figure 3d) simply reflects the low MeHg formation under low,\nambient levels of SO 2‒ that are not well fit using a 3-parameter unimodal function.”\n4\n8. Lines 251-257: Figure S7 (B) was not explained in the MS.\nWe added a sentence to the main text explaining the use of residual f.MeHg as an assessment\nof the unimodal equation fit. (Lines 282-286)\n“There was good agreement between observed and predicted f.MeHg concentrations at\nobserved f.MeHg concentrations ≥ 0.1 ng/L (Figure S7a) with no systematic difference\nin residual f.MeHg concentrations (i.e., the difference between observed and predicted\nf.MeHg concentrations) across the range of SO 2‒ concentration (Figure S7b), indicating\n4\nthe unimodal fit was robust across the conditions of the three wetlands.”\n9. Lines 257-260: Why does this correlation (%MeHg/THg vs filtered MeHg) mean recent MeHg\nproduction? Suggest to give detailed explanation.\nWe have expanded this paragraph to better explain why high % MeHg and high concentrations\nof MeHg are supportive of recent production. The reasons are that higher MeHg concentration\ncould be due to more inorganic Hg(II) that is available to methylated, but an increase in both\nMeHg concentration and the percentage of total Hg as MeHg can only be explained by greater\nlocal production. (Lines 291-296)\n“Further, across all wetlands, the %MeHg was significantly correlated (R2=0.77, p<0.001;\nn=168) to the concentration of f.MeHg in water (Figure S8), which has been observed in\nthe Everglades9,19 and other systems10,15 to correspond with faster measured rates of\nMeHg production. Thus, wetlands with higher aqueous f.MeHg and %MeHg are\ninterpreted to reflect recent MeHg production, as MeHg that is produces is susceptible to\nsink processes (e.g., photo-demethylation,57 adsorption to peat).58”\n10. Lines 286-290: Aggregation of nano-HgS(s) was suggested as a reason for low Hg(II)\nmethylation in the WCA-2A canal zone. How about the role of high DOM at the same site?\nWe expanded the discussion to discuss this point in greater depth. (Lines 331-334)\n“Despite the elevated concentrations of highly aromatic, sulfurized DOM34 under these\nsulfidic conditions, crystalline nano-β-HgS(s)36 will form and dramatically decrease\nf.Hg(II) concentrations in the wetland pore and surface waters (Figures 3c, 4a) and\ncontributes to decreased MeHg formation.64”\n11. Lines 295-298: I agree with this interpretation, however, the role of redox potential cannot be\nignored, since sulfate reduction rate and Hg(II) methylation rates are directly related to the\nanaerobic microbial activities.\nWe have included data in Figure S3 with oxidation reduction potential (ORP) field\nmeasurements, and amended the text that used statistics to show significant differences\nbetween the three wetlands. Directly linking ORP to microbial activity is not feasible, however,\nas the latter is governed by factors controlling microbial activity (e.g., terminal electron acceptor\navailability, reduced carbon availability), whereas the former is a measurement of potential of\nthe system based on various redox couples. Thus, we appreciate the suggestion of the reviewer\nto include the ORP data, and these data strengthen the presentation of how sulfate directly\ninfluences redox state of the wetlands, but we cannot expand the presentation to link the redox\npotential to rates of microbial activity.\nLines 157-160\n“The oxidation-reduction potential (ORP) of wetlands surface water and pore waters\n(Figure S3d-f) reflected the degree of canal influence on wetland redox status, with\nsignificantly lower ORP in pore waters of WCA-2A (‒271 ± 12.3 mV; average ± std)\ncompared to WCA-3A (‒168.7 ± 18.4 mV) or the interior of LOX (LOX-8, ‒25 mV)\n(Welch’s t-test; p<0.001).”\nLines 223-227\n“In summary, canal water SO 2- inputs lower the wetland redox status and stimulate S(‒\ngeochemical gradients within all three Everglades wetlands, and subsequently these\nbiogeochemical changes govern the geochemical nature of Hg(II)31,36 and bioavailability\nfor methylation.39,40”\nDetails on the collection of ORP and DO data have been added to the Methods section. We\nchose to include this in the main text, as Reviewer #2 highlighted the need for all methods\ndetails in the main text for clarity.\nLines 474-476\n“First, pore water temperature, conductivity (Orion four-cell conductivity electrode), pH\n(Orion ROSS Ultra™ electrode), dissolved oxygen (DO) concentration (Orion RDO\noptical probe), and oxidation-reduction potential (ORP; Orion ORP Triode electrode)\nwere measured using a flow-through cell (Geotech; 40 mL dead volume) and multi-\nparameter meters (Orion Star™ A329, Beckman Coulter pHi 410).56”\n12. Lines 321-326: Suggest to add a brief explanation on ecology of gambusia to justify the\npositive correlation between fish MeHg and surface water filtered MeHg concentration. What is\nthe major carbon source of this species?\nWe have added information in several locations to justify the use of gambusia for this study,\ntheir life span, and primary carbon sources.\nLines 105-108\n“Lastly, relationships between MeHg concentrations in surface waters were compared to\nMeHg concentrations in prey fish (Gambusia holbrooki), an indicator species with a short\nlife span (≤ 6 months) that reflects recent MeHg risk to the aquatic food web.17,47”\nLines 523-525\n“Gambusia was selected because they have a short life span (≤ 6 months), feed on a\nmixture of periphyton and zooplankton, and therefore will reflect MeHg availability to the\nproximal aquatic food web in the recent past.17,47”\nThe original content in the manuscript contained information on the carbon source in the\nparagraph noted by the reviewer (Line 346).\n13. Lines 342: Wondering how climate change increases sulfate contraption in freshwater\necosystem.\nWe presume the reviewer is suggesting that these climate processes result in “contraction” of\nfreshwater ecosystems. We modified the sentence in question to use this phrase.\nLines 389-391\n“For example, enhanced mineral weathering in the Arctic has increased SO 2‒\n4\nconcentrations in the Mackenzie River by 45% in the last 60 years28 and sea-level rise is\nthreatening coastal wetlands with marine SO 2‒ that will result in the contraction of\n4\nfreshwater ecosystems.29”\n14. Figure 7: HgcAB was not analyzed in this study. Suggest to include SO4/Cl instead of\nHgcAB as it was used as a surrogate.\nWhile the reviewer is correct, we did measure hgcAB at the same time as samples collected in\nthe present study and those results have been published. Microbial hgcAB measurements were\ncollected at sites that spanned the entire sulfate gradient documented in this study (across all\nthree wetlands), and at the same depth as pore water samples collected here. Therefore, we\nhave strong rationale to assist in interpretation of the present study. In the figure caption, we\nhave cited the source of this interpretation (to clarify this to the reader), and at numerous\nlocations throughout the manuscript we state that the present study leverages microbial insights\ngained from Peterson et al. (2023) (Lines 111, 308, 331, 449-451). No other changes were\nmade.\n15. My only concern is the novelty of this work, since unimodal responses of MeHg on sulfate\nconcentration have been known for a while, as described in the MS (lines 307-320). Please\nclearly emphasize the novelty and novelty of this study in the abstract or conclusion.\nPlease see our modification listed above on the novelty of the study (below the general\ncomment by Reviewer #1).\nReviewer #2 (Remarks to the Author):\nGeneral comments\nThis manuscript presents an original study that adds to the existing body of knowledge\nsurrounding sulphate and methylmercury dynamics in wetlands and will certainly be of interest\nto the mercury research community. Though some polishing of language is necessary, the\nmethods are clearly described and the manuscript is reasonable to follow. However, presumably\nto stay within the word limit, the authors exclude some details that would be helpful to ensure\na reader’s understanding. My comments are primarily requesting clarification, on these two fronts\nand other points detailed below:\nFirst, in the title and throughout the manuscript, the authors refer to the idea of ‘methylmercury\nrisk’, but this is never clearly defined. Is risk equivalent to MeHg concentrations? In Fig 7,\nthis seems to be implied, but also related to bioavailability and hgcAB abundance? High background\n[MeHg] could suggest that a system is less likely to experience increases due to perturbations,\nand therefore at lower ‘risk’.\nWe appreciate the suggestion for clarity by the reviewer. We have added statements in the\nIntroduction and Results & Discussion to define MeHg “risk”.\nLines 48-50\n“MeHg risk is defined as the potential for MeHg to be formed within or proximal to\naquatic systems that results in efficient MeHg assimilation in the aquatic food web.”\nLines 373-375\n“Figure 7 synthesizes a framework on the association between SO 2‒, DOM, and the\n4\npotential for MeHg formation in proximity to aquatic food webs, which dictates MeHg\nrisk.”\nSecond, the field methods are unclear without going into the SI. It appears that WCA-3A was\nsampled less than WCA-2A, and LOX less frequently than either. Differences in these sampling\ntimelines are not explained, nor are the possible effects of sampling at different times throughout\nthe years. This could be beneficial in terms of covering a wider range of flow conditions but also\nseems like it would be a confounding factor in the concentrations observed in fish, since they\nwould be at a different stage in the life cycle.\nIt is unclear to the authors what the reviewer is referring to, in stating the “field methods are\nunclear without going to the SI”. There are no methods presented in the SI (aside from detailed\nQA/QC methods that were added based on comments from Reviewer #2), as all the methods\nare presented in the main text. We have revised the methods presentation to expand on the\njustification for sampling the various wetlands at different intervals.\nThe reviewer asked for more extensive discussion on the role of seasonality, which was already\nincluded in the original submission (see underlined text shown below). The text shown below\ndiscusses the potential role of season, but given the many variables (time of year, calendar\nyear, wetland location, season), the data are best explained by the explanatory variable of\nsulfate concentration (Figure 3d, Figure 5) which highlights that those other factors are\nsecondary. No other changes were made.\nLines 343-351\n“The field data underlying these biogeochemical relationships span multiple years (2012-\n2019) and seasons (May and December) (Table S2), providing a comprehensive dataset\nto develop a framework for MeHg production and risk. Taken together, a highly\nconsistent trend is observed across all wetland surface waters between concentrations\nof SO 2‒, the DOM α (which scales positively with increases in DOC concentrations\n4 254\nand DOM SUVA ), and f.MeHg concentration (Figure 5). We interpret the spread in\n254\nf.MeHg at a given SO 2‒ concentration (Figures 3d, 5) to be the effects of seasonality on\nspring and summer months (Figure S10) due to higher rates of microbial metabolism\nand regular rainfall delivering Hg(II)3 to wetlands.”\nDetailed comments\nAbstract\nLine 19: This is quite specific for the start of an abstract. Consider opening with a broader\nstatement regarding MeHg in wetlands.\nWe have added a short introductory sentence to the Abstract (Lines 16-17)\n“Wetlands are critical environments for the biogeochemical cycling and ecological uptake\nof contaminants.”\nLines 20-21: Consider ‘land and water management strategies and climate change effects’ for\nspecificity.\nAccepted.\nLines 22-23: Consider rearranging to ‘We sampled surface and pore waters across SO4\ngradients of three freshwater wetlands in the Florida Everglades…’\nIntro\nAccepted\nLine 51: Here and throughout, rather than SO4 ‘levels’, consider ‘concentrations’ or ‘loads’ for\ngreater specificity.\nHere and throughout the entire manuscript, “levels” has been revised to “concentrations”,\nwhen referencing sulfate and any other constituent. We thank the reviewer for this suggestion to\nimprove clarity in presentation.\nLine 83: Here and throughout, land and water management is mentioned, but the introduction\nthus far only mentions agriculture. Please expand.\nWe have expanded this sentence to include more examples of water management actions.\n(Lines 88- 93)\n“Given the potential for fluctuations in SO 2‒ concentrations in wetlands in response to\n4\nland management (e.g., agricultural practices), water management (e.g., storm water\ntreatment, phosphate mitigation via alum additions),43,44 or climate change processes,27–\n29 as well as the uncertainties in the geochemical and microbial responses pertaining to\nMeHg formation, ecosystem-scale studies are needed to solidify linkages between SO 2‒\n4\n, MeHg formation, and subsequent MeHg uptake in aquatic food webs.”\nResults and Discussion\nLine 111: Should say '…water conservation areas studied...’\nAccepted\nLine 112: Comma should be after ‘(LOX))’ in next line.\nAccepted\nLines 141-142: This is quite confusing; is there a way to rephrase without using ‘distance from\ncanals’ twice?\nRevised. Lines 150-153.\n“With increased distance from canals, surface water SO 2‒ concentrations consistently\n4\ndecreased (e.g., in August 2014, SO 2‒ decreased from 65.8 to 50.6 mg/L, 22.5 to <0.5\n4\nmg/L, and 4.1 to <0.5 mg/L across transects in WCA-2A, LOX, and WCA-3A,\nrespectively).”\nLine 155: Here and throughout, there are comparisons such as ‘notably lower’, ‘decreases’, etc.\nThese would benefit from support of some simple statistics.\nWe have added a section to the Methods with the statistical approaches used, and expanded\nthe statistical tests across populations of data or between variables. There are instances where\n“qualitative” language is retained the manuscript, as standard statistical tests were not suitable\nfor portions of the data.\nModifications include:\nLines 171-173\n“First, in sediment pore waters, SO 2‒ concentrations were significantly lower than\n4\ncorresponding surface waters (Mann-Whitney Rank Sum Test, p<0.001), by ≤ 60.5, ≤\n26.5, and ≤ 3.5 mg/L in WCA-2A, LOX, and WCA-3A, respectively (Figures 2a-2c).”\nLines 198-201\n“In wetland pore waters, however, DOC concentrations were significantly higher\ncompared to surface waters (Mann-Whitney Rank Sum Test, p<0.001, n=70), particularly\nin regions with active SO 2‒ reduction near canal inputs (Figure 2j-2l), and DOM in pore\n4\nwaters was of similar or modestly higher aromaticity (DOM SUVA ; Welch’s t-test,\n254\np<0.001, n=70; Figure 2m-2o).”\nLines 260-263\n“Further downgradient, average f.MeHg concentrations and %MeHg were higher in\nsurface waters (0.27±0.05 ng/L and 16.4±2.3 %MeHg, respectively; ±1 standard\ndeviation) compared to pore waters (0.06±0.04 ng/L and 4.5±2.8 %MeHg, respectively)\nor the L-6 canal (Mann-Whitney Rank Sum Test, p<0.001, n=14).”\nWe have added a section to the methods that details the statistical approaches used. Lines 530-\n535.\n“Statistical comparisons between variables were assessed using linear regression\nanalysis and paired t-tests (SigmaPlot v.14.5); p-values < 0.05 were considered of\nstatistical significance. For paired t-tests, a normality test (Shapiro-Wilk) was first\nperformed. Data that passed the normality test were analyzed by a Welch’s t-test, where\nequal variances are not assumed, and those that did not pass the normality tests were\nanalyzed by Mann-Whitney Rank Sum Test (suitable for non-parametric data).”\nLine 182: Similar or modestly higher aromaticity compared to surface water?\nAccepted.\nLines 201-204\n“Higher DOC concentration and greater DOM aromaticity in wetland pore waters near\ncanal inputs compared to surface waters are interpreted to be the result of SO 2‒\n4\nstimulating degradation of peat by SO 2‒ reducing bacteria33 that releases DOM of higher\n4\naromaticity (e.g., phenolic groups).29,32”\nLine 191: The connection between photochemical transformation of DOM and autochthonous\nDOM production to increased distance from canals is unclear.\nWe have revised the statement for clarity. Lines 207-211.\n“With increased distance from canals in WCA-2A and WCA-3A, surface water DOC\nconcentrations decreased (e.g., from 37.0 to 32.7 and 23.1 to 15.0 mg/L, respectively)\nand DOM SUVA decreased (e.g., from 3.7 to 3.1 and 3.9 to 2.4 L/mg m, respectively)\n254\n(Figure 2m, 2n), likely the result of the photochemical transformation of DOM54 and\nautochthonous DOM production in wetland surface waters.55”\nLine 222: Typo: ‘qualitative’\n“qualitative” was removed from the sentence in question.\nLine 226: Consider expanding on the ‘additional source and sink processes’ or removing the\nstatement.\nWe have expanded this statement to include the one other sink process, which is adsorption of\nHg(II) to peat. The revised list of “source and sink processes” is complete, as it covers the major\nprocesses that will influence the instantaneous concentration of Hg(II) at any location.\nLines 247-250\n“Although additional source and sink processes also influence f.Hg(II) concentrations in\nEverglades wetlands, including rainfall delivery of f.Hg(II),2,45 photo-reduction of Hg(II) to\nHg(0),3,4 and partitioning of Hg(II) to peat,47 SO 2‒ exhibits notable control on the\n4\nconcentration of f.Hg(II), which can limit MeHg formation in wetlands.”\nLine 229: What does %MeHg tell us? E.g. what is it an indicator of that makes it distinct from\n[MeHg]?\nWe appreciate the suggestion to improve clarity in presentation. We have revised this to provide\nrationale up front in this section on the use of %MeHg (shown below, Lines 253-255) and in\nLines 291-293 we detail how we interpret these results in context of previous studies.\nLines 253-255\n“The %MeHg term is used to normalize f.MeHg concentration data to the total Hg\nconcentration at a given location, as f.Hg(II) concentrations varied by an order of\nmagnitude within and between the studied wetlands (e.g., Figures 4a-c, S6a-b) and is\nthe precursor for f.MeHg.9,55”\nLines 291-293\n“Across all wetlands, the %MeHg was significantly correlated (R2=0.77, p<0.001; n=168)\nto the concentration of f.MeHg in water (Figure S10), which has been observed in the\nEverglades9,19 and other systems10,15 to correspond with faster measured rates of\nMeHg production.”\nLine 249: Typo?\nIt is unclear to us what is potentially a typo in this statement. We reviewed it and deemed it to be\ngrammatically correct.\nLine 282: Typo: notably\nAccepted. We thank the reviewer for identifying this typo.\nLine 292: Typo: observe\nAccepted. We thank the reviewer for identifying this typo.\nLine 296: Not sure that the results of the study really support that SO4 inputs ‘indirectly alter the\nmicrobial metabolism’.\nWe are confident in this interpretation, as it is informed by genome-resolved metagenomics,\nwhich was able to identify the metabolic capabilities of the microorganisms with the hgcAB gene\npair. No changes were made.\nLines 299-300: Consider adding climate summaries (e.g. average annual temperature, total\nprecip) to SI to illustrate representativeness of data collected.\nWe have added information to Table S2 that includes the temperature at the time of sampling,\naccumulative precipitation and total Hg deposition (both annually and over the three month\nperiod prior to sampling), and annual data from 1997-2023. The Methods section was revised to\nmake this clear to the reader.\nLines 455-460.\n“Table S2 summarizes the sampling date ranges, cumulative precipitation and wet Hg\ndeposition data (on an annual basis and the 3 months prior to sampling) from local\nstations maintained by the National Atmospheric Deposition Program,46 and air\ntemperature data during sampling. The cumulative annual precipitation and wet Hg\ndeposition over the years of the study were within the range typically observed at these\nsites, based on available data record (1997-2023; Table S2).”\nLine 316: ‘SO4 is a master variable’ seems like an overconfident assertion, especially given the\nlimited within-year temporal coverage of the study.\nThe reviewer is mistaken, claiming that the study is a “limited, within-year temporal coverage”.\nAs we detail, the data were collected over seven field campaigns spanning 8 calendar years,\nand between the calendar months of May to December (e.g., as detailed in Table S2).\nTherefore, we do not agree that the statement is an overconfident assertion, as all the field data\nshow coherence between the role of sulfate and MeHg concentration (Figure 3d, Figure 5). No\nchanges were made.\nLines 323-324: Consider also adding movement patterns throughout the life cycle to tie\nobservations to locations. Given the short life span, did the varied sampling timeline influence\nthe observations at all?\nAs shown in Figure 6, across all wetlands (regardless of sampling time), there was a strong\ncorrelation between surface water MeHg and fish. Although it would be an interesting\nconsideration to expand the discussion of the paper to include the movement patterns of\ngambusia, it is beyond the scope of this study and not feasible with the available data.\nRevised text in the Methods outlines why we selected these fish and cites other studies that\nused them as indicator fish. No other changes were made.\nLines 523-525\n“Gambusia were selected because they have a short life span (≤ 6 months), feed on a\nmixture of periphyton and zooplankton, and reflect MeHg availability to the proximal\naquatic food web in the recent past.17,43,48”\nLine 361: Consider including estimated timeline of response for local interventions as well.\nThe original manuscript highlighted an estimated response to local interventions (≤1-2 years),\nbut we have revised the statement for clarity.\nLines 395-397\n“Local reductions in SO 2‒ concentration or load may yield a relatively fast response, as\n4\nprevious work in the Everglades demonstrated that declines in SO 2‒ could elicit rapid\n4\nreductions (i.e., ≤ 1-2 years) in MeHg concentrations.51”\nMethods\nConsider adding a brief section detailing statistical analyses.\nAccepted. See response above.\nLine 380: Change ‘following’ to ‘follow’ and remove ‘span’.\nAccepted. We thank the reviewer for identifying this typo.\nLine 383: How do WCA-2A and WCA-3A differ from each other? If they are very similar, what\nvalue does the second add?\nWe have clarified that WCA-2A and 3A how high and intermediate concentrations of sulfate, or\nagricultural influence, which is why they were selected.\nLines 432-434\n“WCA-2A and WCA-3A receive high and intermediate concentrations of sulfate from\ncanal inputs that drain upgradient agricultural lands, respectively, and generally exhibit\ndecreasing sulfate concentrations from north to south.34,44”\nLine 386: Figure caption says GARDEN rather than EDEN; presumably this is the same model\nunder different names? If so, sticking with one would be better.\nWe appreciate the suggestion and have revised the main text and captions to only use\n“Everglades Depth Estimation Network (EDEN)” (Lines 162, 436, 760)\nLine 388: in L-6, is L an acronym or abbreviation for something?\nWe have revised the presentation to clarify that the “L” stands for levee, as that is the control\nstructure. This is defined at first presentation (Line 122, 125) and in the methods section (Line\n438, 441) for all canals.\nLine 404-405: Additional details are warranted here. For example, there looks to have been no\nsampling in 2016. WCA-3A was not sampled in 2012, and LOX was only sampled in 2015 and\n2019. Is that correct? If so, the current description is quite misleading. Please also add\nreasoning for truncating transects in later years of the study.\nCorrect, we did not sample wetlands in 2016, which was due to unexpected health\ncircumstances of one of the co-PIs of the project (George Aiken).\nWe have added additional details to justify the sampling plan across the wetlands in the\nmethods and when introducing the sampling plan. The reason to sample “truncated” transects\nwas to (1) sample the complete range of sulfate concentrations documented in freshwater\nwetlands of the Florida Everglades with approximately uniform sample density over the\nintermediate to high sulfate concentration range (12 – 72 mg/L), (2) and have higher sample\ndensity at the low-to-intermediate concentration range of sulfate (0-12 mg/L), which has been\ndocumented to result in the largest differences in MeHg in a variety of ecosystems. The\nhistogram below shows the distribution of surface water sulfate concentrations in this study,\nwhich has been added to the SI (new Figure S4). The reviewer is correct that wetlands were\nsamples in different density, but the goals of the study were to use the three wetlands to cover\nthe entire gradient, which was achieved.\nFigure S4. A histogram sulfate (SO 2‒) concentrations in the three wetlands of the study, with an sampling\n4\nemphasis on low-to-intermediate concentrations (0-12 mg/L) and equal distribution of samples at\nintermediate-to-high SO 2‒ concentration (12-72 mg/L).\n“The Florida Everglades is naturally a low SO 2‒ environment, with concentrations\n4\nbetween 0.1-1.0 mg/L in regions unimpacted by agricultural S inputs,44 and therefore\nSO 2‒concentrations observed in interior WCA wetlands greatly exceeded background\n4\nconcentrations (up to ~70-fold) and were distributed across the entire range observed\n(≤0.5 – 72.0 mg/L; Figure S4), creating vastly different water quality conditions across\ndowngradient freshwater wetlands.”\nLines 462-467\n“The density of samples across the three wetlands aimed to (1) span the complete range\nof sulfate concentrations of the freshwater Florida Everglades44 with comparable density\nas a function of SO 2‒ concentration and (2) have higher sample density at the low-to-\n4\nintermediate concentration range of sulfate (≤0.5-12 mg/L) (Figure S4). At times,\ntransects were sampled in a truncated design (Table S2), where some of the sites\nshown in Figure 1 were skipped to best meet the abovementioned sampling goals.”\nLine 449: Please report Hg QA/QC info, at least in the SI.\nWe have included all QA/QC information for the analysis of total and methylmercury in the SI\n(Section S2), and included a figure with summary statistics for field process blanks. This is\nreferenced in the main text methods.\nMain Text Lines 513-514\n“All field process blanks and quality assurance and quality control data are provided in\nthe SI (Figure S12).”\nSI Content: See SI Section S2: Quality Assurance and Quality Control on Mercury\nMeasurements (SI Lines 48-76\nFigure S12. A comparison of concentrations of field process blanks (n=15) and environmental samples\nfrom the study wetlands including (a) particulate total Hg (p.THg) (n=126), (b) particulate methylmercury\n(p.MeHg) (n=126), (c) filtered total Hg (f.THg) (n=197), and (d) filtered methylmercury (f.MeHg) (n=197).\nThe horizonal dashed gray line presents the method detection limit.\nLine 455: Consider adding reasoning for selecting this species for readers unfamiliar with the\nEverglades.\nPlease see our response to Reviewer#1, comment #12.\nR1: Suggest to correct Figure 7 title for better reading: 'due to' was used four times.\nWe have revised Figure 7 caption to improve clarity and reduce redundant phrases.\nFigure 7. Conceptual framework for sulfate (SO 2‒) and dissolved organic matter (DOM)\n4\neffects on methylmercury (MeHg) risk in subtropical wetlands. Low risk is observed at high\n(~>15 mg/L) and low (<1 mg/L) SO 2‒ that facilitate unfavorable conditions for MeHg formation,\n4\ndue to geochemical bioavailability of Hg(II), wetland redox status, and hgcAB abundance of\nmicrobial community.19 High risk is observed at intermediate SO 2‒ (3-12 mg/L) that facilitate\n4\nsuitable redox status, Hg(II) bioavailability (due to DOM aromaticity36,40 and thiol content),34,41 and\nhgcAB abundance19 that collectively promote MeHg formation in proximity to the aquatic food\nweb."}, {"round": 2, "reviewer_comments": {"reviewer_1": "1) All the comments and suggestions were answered well.\n2) Suggest to correct Figure 7 title for better reading: 'due to' was used four times.", "reviewer_2": "I am satisfied that my concerns have been addressed and have no further suggestions for revision."}, "author_response": ""}]

Decision letter