Chemical and Physical Controls on Mercury Source Signatures in

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Characterization of Natural and Affected Environments

Chemical and Physical Controls on Mercury Source Signatures in Stream Fish from the Northeastern United States Sarah E. Janssen, Karen Riva-Murray, John F. DeWild, Jacob M Ogorek, Michael T. Tate, Peter C. Van Metre, David P. Krabbenhoft, and James Coles Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.9b03394 • Publication Date (Web): 07 Aug 2019 Downloaded from pubs.acs.org on August 14, 2019

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Chemical and Physical Controls on Mercury Source Signatures in Stream Fish from the Northeastern United States

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Sarah E. Janssen1*, Karen Riva-Murray2, John F. DeWild1, Jacob M. Ogorek1, Michael T. Tate1, Peter C. Van Metre3, David P. Krabbenhoft1, and James F. Coles4

7 8 9 10 11 12 13 14 15 16 17 18 19

1United

States Geological Survey, Upper Midwest Water Science Center, Middleton, Wisconsin 53562, USA

2United

States Geological Survey, New York Water Science Center, Troy, New York 12180, USA

3United

4United

States Geological Survey, Texas Water Science Center Austin, Texas 78754, USA

States Geological Survey, New England Water Science Center Northborough, Massachusetts, USA

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* Corresponding Author: Sarah E. Janssen, [email protected], USGS Upper Midwest Science Center, Middleton, WI 53562

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Abstract

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Streams in the northeastern U.S. receive mercury (Hg) in varying proportions

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from atmospheric deposition and legacy point sources, making it difficult to attribute

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shifts in fish concentrations directly back to changes in Hg source management.

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Mercury stable isotope tracers were utilized to relate sources of Hg to co-located fish

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and bed sediments from 23 streams across a forested to urban-industrial land-use

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gradient within this region. Mass-dependent isotopes (δ202Hg) in prey and game fish at

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forested sites were depleted (medians -0.95 and -0.83 ‰, respectively) in comparison

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to fish from urban-industrial settings (medians -0.26 and -0.38 ‰, respectively); the

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forested site group also had higher prey fish Hg concentrations. The separation of Hg

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isotope signatures in fish was strongly related to in-stream and watershed land-use

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indicator variables. Fish isotopes were strongly correlated with bed sediment isotopes,

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but the comparison of isotopic composition between fish and sediment was variable due

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to differing ecosystem-specific drivers controlling the extent of MeHg formation. The

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multivariable approach of analyzing watershed characteristics and stream chemistry

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reveals that the Hg isotope composition in fish is linked to current and historic Hg

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sources in the northeastern U.S. and can be used to trace bioaccumulated Hg.

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Introduction

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Mercury (Hg) contamination of fish is an important issue due to human and

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wildlife health concerns, and Hg levels frequently exceed concentrations associated

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with harmful effects to humans1 and wildlife2 in the northeastern United States (U.S.).

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Sources of Hg to aquatic habitats in the northeastern U.S. include atmospheric

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deposition from regional emissions, such as coal-fired power plants in the Ohio River

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Valley3, which can directly deposit onto waterbodies as well as to their watersheds.

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Additionally, in urban regions Hg from point source emissions of gaseous Hg0 4 and

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from legacy contamination can also contribute to Hg source loads.2 The distribution of

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waterbodies having high levels of fish Hg is likely influenced by the spatial pattern of

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source type and concentration, including proximity to legacy contamination. In addition

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to source characteristics, fish Hg levels are influenced by physio-chemical

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characteristics and ecological factors of the waterbody that enhance mercury transport,

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methylmercury (MeHg) formation, and food web bioaccumulation.5,6 The accumulation

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of MeHg in fish tissue, which can constitute >90 % of the total Hg (HgT),5 has led to

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statewide, regional, and waterbody specific freshwater fish consumption advisories

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across the northeastern U.S.1 Additionally, biological Hg ‘hotspots’ have also been

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identified where fish Hg levels pose risks to piscivorous birds, mammals, and other

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wildlife.2, 7

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In recent decades, the relative influence of industrial Hg point sources and legacy

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sources has declined in the northeastern U.S., and atmospheric deposition is currently

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the dominant source of Hg to the region.8 While these findings are encouraging, the

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relative importance of these legacy declines is difficult to interpret without baseline

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knowledge of relative source attribution (e.g. direct deposition, terrestrial runoff,

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wastewater, point source) to fish.9, 10 This becomes problematic given the differences in

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bioavailability between different Hg sources.6 Hence, these variations in Hg source

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profiles can hinder efforts to understand bioaccumulation and to monitor biota Hg trends

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in relation to Hg source trends. This challenge can be directly addressed with Hg stable

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isotopes, which provide a tool for source differentiation in both bed sediments and fish.93 ACS Paragon Plus Environment

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11

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mass-independent fractionation (MIF, denoted as Δ199Hg and Δ200Hg)12 allows for a

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tertiary tracer approach to define Hg sources.13-17 Researchers have found success

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using Hg isotopes to evaluate point-source contamination in sediments 9-11, 18-21 and to

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assess broad-scale source differences in biota.22-24 However, it is difficult to apply these

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studies across multiple waterbodies that can contain diverse land cover as well as Hg

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sources. Studies that have mostly focused on fish tissue have occurred within lakes 13,

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19, 21, 25, 26

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Finally, sediments have been the focus of most existing source-tracking and exposure

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studies for isotopes 14, 31-35 despite the reported lack of connection between sediment

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and fish tissue HgT concentrations.36-37

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The use of both mass-dependent fractionation (MDF, expressed as δ202Hg) and

and estuarine systems, 27, 28 and only a few have considered streams.29, 30

Measuring Hg isotope compositions in fish is important for source tracking

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applications because fish are the dominant MeHg exposure pathway to humans and

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fish-consuming wildlife. However, source tracking utilizing fish tissue can be

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complicated by reaction mechanisms that imprint isotopic fractionation onto source

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signatures prior to bioaccumulation (e.g. methylation 38, 39) and during metabolism.40, 41

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One of the largest shifts of isotope signature prior to bioaccumulation can arise from

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photochemical processing, specifically photodemethylation and photoreduction.42 These

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fractionations can be accounted for, because photochemical demethylation produces a

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predictable shift in δ202Hg which can be used to estimate the source signatures of MeHg

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prior to photochemistry.26-28 However, interpreting fish Hg isotopic compositions is

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difficult because of the limited availability of Hg isotope data in other environmental

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compartments,9, 10 particularly for freshwater streams which serve as comparative 4 ACS Paragon Plus Environment

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markers.29, 30 Hence the utility of Hg isotopic ratios for determining Hg sources to biota

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within streams is not well established.

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In 2016, the U.S. Geological Survey conducted the Northeastern Stream Quality

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Assessment (NESQA) as part of the National Water Quality Assessment project.43, 44 In

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the NESQA, biological, chemical, and physical characteristics were determined in 95

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streams across a range of urban, residential, agricultural, and forested watersheds. This

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provided an opportunity to conduct a Hg isotope study on a subset of sites that were

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selected along a gradient of forested to urban-industrial land use. The aim of this study

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was to determine if source signatures are conserved in fish tissue and vary in relation to

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land-use, thus providing a vital tool for resource managers in future mitigation of fish Hg

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burdens. Here, we couple the use of Hg stable isotope analysis in fish tissue and

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streambed sediments, collected from 23 of these streams, with Hg concentration data,

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water quality parameters, and watershed characteristics. With this first regional-scale

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study of Hg isotopes in stream fish and bed sediments, we examine the controls that

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physical and chemical watershed features exert over the preservation of Hg isotope

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compositions in fish.

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Materials and Methods

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Site Selection and Characterization

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Twenty-three streams were selected to span a watershed land-use gradient from

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mostly undeveloped (largely forested, some rural) to dense urban-industrial (Fig. 1,

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Table S1). These sites corresponded with a shift in potential Hg source from

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terrestrially-cycled Hg (i.e. atmospheric deposition to the forest canopy and soils) to 5 ACS Paragon Plus Environment

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urban-industrial Hg (impervious surface run-off and current or legacy point sources).

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The 23 streams were selected from the original 95 NESQA sites to include sites in

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cities, suburbs, and largely undeveloped settings, and to distribute the three types of

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settings across the study area to the extent possible. Sites were then classified as

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‘forested-rural’, ‘residential’, or ‘urban-industrial’ (Fig. 1, Table S1) according to data

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from three sources: urban-developed land cover data from the National Land Cover

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Dataset of 2011,45 industrial land-use data from the U.S. conterminous wall-to-wall

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anthropogenic land-use trends analysis for 2012,46 and data on number of industrial

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locations and other potential contaminant sources tallied from a geospatial coverage

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provided by the EPA Federal Registry System (FRS).47 The FRS was used to indicate

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the potential occurrence of industrial point sources of contamination, both current and

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legacy, that would not necessarily be quantified by the percent industrial land-use

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metric. The FRS data resulted in an urban-industrial classification of several sites in

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‘suburban’ settings, and the absence of ‘residential’ sites from some parts of the study

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area.

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All streams were wadable and contained areas of riffle habitat with coarse

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substrate; watershed area ranged from 12 km2 to 187 km2 (Table S1). Additional

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watershed characteristics derived for each site include road density48, percent

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wetlands49, topographic wetness index, and mean basin slope. Median bankfull channel

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width was obtained for each site from 11 transect measurements44, spaced 15 m apart,

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made during August 2016. Simulated 9 month (March - November 2010) accumulated

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wet and dry Hg deposition data (µg of Hg m-2) generated by Ye et al., 2018 50 were

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used, along with an inverse distance weighting approach, to estimate mean watershed

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wet, dry, and total deposition fluxes at each site.

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Sample Collection

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Streambed surface sediments were collected at each site within a 150-meter

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stream reach in August 2016.44 At each site, 6-10 depositional zones, pools or edge

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habitats in which relatively fine, organic-rich sediment accrues, were targeted. Plugs of

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sediment were collected from the top 2 cm of each depositional zone. A 50 mL syringe

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was used to draw sediment in until a plug with a height of 2 cm was obtained. Sediment

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samples were kept on ice in the field, then frozen, and shipped to the USGS Mercury

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Research Lab (MRL, Middleton, WI) for analysis.

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Regionally common prey and game fish species were targeted for collection at

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each site during August 2016; alternate species were collected where the targeted

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species were not encountered (SI Methods, Table S2). Non-migratory species

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considered top predators at each site were targeted as game fish. Game fish specimens

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were not retained if stocking practices, specimen appearance, and (or) specimen

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condition suggested hatchery origin. Additionally, game fish were not retained if smaller

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size classes of the species were not observed at the site, indicating a lack of natural

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reproduction. In the field, specimens were rinsed with deionized (DI) water, placed in

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clean plastic bags, and then frozen. Further processing performed at the USGS New

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York Water Science Center (USGS NYWSC) laboratory included: thawing; triple-rinsing

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in DI water; weighing; measuring; sorting into single-species composites of whole prey

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fish; obtaining individual skinless fillets of game fish; placing samples into clean plastic

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bags; freezing; and shipping to the MRL for analysis.

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Water samples were collected once weekly during July 18 – August 5 from each

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site. Samples collected for analysis of major ions, nutrients, and pH, were collected and

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analyzed according to methods described elsewhere.44 Water collection and analysis

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methods for determination of unfiltered MeHg (UMeHg); unfiltered HgT (UTHg);

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sediment MeHg, ultraviolet absorbance at 254 nm (UVA254), dissolved organic carbon

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(DOC), and specific ultraviolet absorbance (SUVA) are detailed in the supporting

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information. Water quality results from the selected streams are available in an

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associated data release51and Table S3.

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Total Hg and Isotope Analysis in Fish and Sediment Samples

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Total mercury concentrations (HgT) in fish and sediments were analyzed via

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direct combustion coupled to atomic absorption detection52 at the MRL. Certified

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reference materials International Atomic Energy Agency (IAEA) SL-1 (lake sediment)

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and IAEA 407 (fish homogenate) were measured with sediment and fish samples,

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respectively. Concentration results of reference materials were within acceptable

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recovery ranges for IAEA 407 212 ± 6 ng g-1 (n = 6) and IAEA SL-1 127 ± 3 ng g-1 (n =

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3) with a detection limit of 0.3 ng per analysis. Analysis for HgT, MeHg, and other

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analytes in water and sediments are detailed in the supplementary methods. Fish HgT

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was converted to a wet weight basis for this study, using percent moisture values in

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individual fish samples.

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In preparation for isotope analysis, fish tissue was digested with concentrated

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nitric acid at 90°C for 8 hours, followed by further oxidation with bromine monochloride

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(9:1 v/v HNO3:BrCl).13 Sediment samples were digested in aqua regia (3:1 v/v

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HCl:HNO3) and heated at 90°C for 8 hours.13 Fish and sediment digests were analyzed

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for HgT to ensure complete recovery and then diluted to concentrations of 1.0 ng mL-1

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and to 7). The PCA was conducted on a set of selected,

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non-redundant (i.e., not co-linear) environmental variables that were transformed, as

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needed, to approximate normality (Table 1). Variable selection for the PCA was focused

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on generating synthetic variables related to Hg source conditions (i.e., relative

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importance of atmospheric deposition to terrestrial landscapes versus current and

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legacy point sources), as well as to indicators of Hg processing and transport. Physio-

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chemical and watershed variables that were good indicators of land use (e.g. forest

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cover, road density, chloride concentration), as well as several variables indicating Hg

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processing and cycling (e.g. DOC, UVA254, and Hg concentrations) were used for this

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analysis (Table 1). Correlations of bed sediment δ202Hg and Δ199Hg with environmental 10 ACS Paragon Plus Environment

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variables and PCA site scores were analyzed for comparison with fish results. Bed

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sediment THg and MeHg were normalized to organic carbon, based on loss on ignition

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(LOI). Separate correlation analyses with Hg isotopes were conducted for selected

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environmental variables that could not be adequately transformed for inclusion in the

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PCA analysis or that were highly correlated with other variables in the PCA. Statistical

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analyses were performed with SAS software, version 9.4 (SAS Institute, Inc., Cary, NC);

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0.05 was used for all tests.

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Results and Discussion

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Variation of Mercury Stable Isotopes in Fish Tissue and Sediment

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Mass dependent fractionation ranged from -0.02 ‰ to -1.10 ‰ across all fish

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samples (n = 69; Fig. S1, Table S2). The overall ranges of δ202Hg in prey fish (from -

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0.02 ‰ to -1.10‰) and game fish (from -0.05 ‰ to -0.97 ‰) were similar (Fig. S1).

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Sediment δ202Hg ranged from -0.26 to -1.28 ‰ across all streams (Table S4).

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Measurements of Δ199Hg in fish ranged from -0.05 to 0.98 ‰ (Fig. S1), which is

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similar to ranges previously reported for estuarine,28 stream,30 and coastal fish.22 The

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highest Δ199Hg was observed in two largely-forested sites (NY_LBeaver and

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VT_Saxtons) that have watersheds characterized by little wetland area, high mean

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basin slope, and relatively low topographic wetness index (Table S1). No significant

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difference was observed in mean Δ199Hg between prey fish and game fish across all

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streams. The slope of Δ199/ Δ201Hg across all sites and species was 1.18 ± 0.02 (1SD,

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r2= 0.91, p < 0.01, n=69, York regression) (Fig. S2), an indicator that water column

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photochemical reduction and photodemethylation processes are both being preserved

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in the fish tissue.42 Sediments displayed a lower range of Δ199Hg (0.08 to -0.33 ‰), with

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11 of the 23 sites showing negative Δ199Hg (Table S4). Additionally, sites that displayed

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negative Δ199Hg in sediments also displayed depleted MDF values less than -0.80 ‰, a

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common signature observed in matrices such as leaf litter and soils, suggesting a Hg

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source tied to atmospheric deposition and foliar uptake.15, 54

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The MIF of even isotopes is commonly associated with either dry or wet atmospheric

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deposition that display negative and positive Δ200Hg, respectively.13-17, 54-55 No Δ200Hg

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was detected in fish or sediments (≤ 0.10 ‰) in this study, other than in one fish sample

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from NY_Allen (Table S2, S4). The lack of Δ200Hg across most fish in this study

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contradicts deposition models of the northeastern U.S. that suggest deposition is the Hg

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source in remote regions. 8, 56 The Δ200Hg signature is thought to be created in the

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tropopause and is suggested to represent a global Hg0 pool.57 We propose two possible

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explanations for the lack of atmospheric signature in these samples. The first is related

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to the opposing signatures that are observed in precipitation (+Δ200Hg) and gaseous

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elemental Hg (-Δ200Hg), if these pools are equally responsible for deposition in the

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region then the net isotopic signature for Δ200Hg would be undetected. A second

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potential cause may be related to the high number of emission sources within

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northeastern U.S.56, 58; these likely do not undergo extensive atmospheric transport and

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hence do not obtain the Δ200Hg signature.

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Land-Use Influence on Fish MDF

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Strongly depleted δ202Hg signatures (δ202Hg < -0.90 ‰), observed in 12 of the 18 fish samples from forested sites (Table S2), have signals similar to previous studies of

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plants and soils, which were attributed to atmospheric deposition of Hg.10, 14, 15, 17, 59

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Other studies have concluded that such negative δ202Hg signatures arise from foliar

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uptake of atmospheric gaseous Hg(0) that is further preserved in soils after organic

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matter degradation and Hg evasion processes.15 Additionally, the enriched signals

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(δ202Hg > -0.40‰) observed in 21 of the 38 fish samples from urban-industrial sites

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(Table S2) are within ranges previously reported for legacy-contaminated sediments.31-

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35

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Site mean δ202Hg was significantly higher in the urban-industrial group than the

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forested-rural group in both prey fish (p 100 ng g-1 have depleted signatures (-0.66 ‰ to -1.07 ‰), while 8 of 10

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samples with Hg concentrations < 100 ng g-1 have enriched signatures (-0.53 to -0.10). 14 ACS Paragon Plus Environment

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The link between higher concentrations and highly-negative δ202Hg in these prey fish

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suggests that Hg derived from atmospheric deposition to the terrestrial landscape is the

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dominant source of bioavailable Hg in forested regions, whereas impervious surface

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runoff and legacy contamination are important sources in more urban settings.

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Increased bioavailability of Hg in streams in remote regions61-62has previously been

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linked to ecosystem factors such as higher methylation potentials in riparian zone soils

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62

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conclusion of others that methylation efficiency is an important factor 64 when examining

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the potential of bioaccumulation of different Hg sources.

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MDF Changes in Response to Environmental Gradients

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and enhanced transport due to more complex DOC. 63 Our results support the

The streams in this study exhibited a wide range of instream chemical and

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physical characteristics and environmental settings (Tables S1, S3, S4), that could

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produce an isotopic gradient across the region. The PCA, which incorporated

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watershed, water quality, and bed sediment variables associated with Hg sources and

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Hg processing (Table 1), produced three main eigenvectors (henceforth ‘axes’).

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Together, these first three axes explained 71% of the variation in the environmental

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data set, with 59% cumulatively explained by Axes 1 and 2 (Table 1). Axis 1 was

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interpreted as an urban-intensity gradient, based on (1) relatively high positive loadings

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(i.e. correlations) of road density, atmospheric deposition, chloride concentration, and

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nutrient concentration, (2) relatively high negative loadings of forest-shrub land cover,

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and (3) moderate positive loadings of UTHg in water and THg in bed sediment (Table

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1). Site mean δ202HgCOR in both prey fish and game fish were strongly related to this

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gradient, as indicated by strong positive regressions with site scores along PCA Axis 1, 15 ACS Paragon Plus Environment

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(r2 = 0.81 and p90% of the total Hg concentration for game fish5 and >75% for prey

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fish,68 in this study, which suggests that these offsets between sediment and fish tissue

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may be related to MeHg production. Hence, the connection between sediments and the

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isotopic signature of bioaccumulated Hg could further be complicated by the rates of

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sediment methylation38, 39 and demethylation.69 If methylation is assumed to create an

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isotopically depleted pool due to kinetic MDF, the counter to this would be microbial

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demethylation, which would cause an enrichment of heavy isotopes in the MeHg pool.

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These basic fractionation patterns could then be used to estimate the controlling

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mechanism creating the sediment-fish offset (Fig. 4).

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In the current study, 78% of all fish samples (spanning across 18 sites) were

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isotopically enriched in δ202HgCOR in relation to the co-located bed sediment δ202Hg (Fig.

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4). The disconnect between δ202HgCOR in fish and δ202Hg in sediment is similar to that

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observed in estuarine and riparian systems.27,28 The extent of fish tissue enrichment in

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relation to sediments is not consistent across sites, with offsets 0.3‰ at a forested site (VT_Saxtons) and an urban-industrial site (NY_Bronx). Only

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three sites showed the opposite pattern of more depleted values in fish than sediment;

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these were two forested sites (NY_LBeaver, NY_Cross) and one residential site 19 ACS Paragon Plus Environment

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(NY_Muscoot). If the sediment is the prominent source of MeHg to the food web, simple

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fractionation patterns would lead to the conclusion that most of these sites are exhibiting

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a high rate of demethylation. However, the cause of this enrichment could be due to

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more complicated factors controlling this source offset. For example, the active pools of

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Hg available for microbial methylation might not be isotopically similar to the total

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sediment measurements.39 The enrichment of heavier isotopes in the pool available for

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methylation could also create the offset attributed to demethylation in past studies.27,28

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In addition to varying widely across sites, the relation between fish and sediment

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MDF was highly variable within some sites, and different fish samples from the same

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site could be grouped into either demethylation- or methylation-dominated categories

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(e.g. VT_Saxtons, NY_LeyCreek, and NY_Allen) (Fig. 4). These observations indicate

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the incorporation of different MeHg sources in fish than in sediments from the same

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sites. The measurement of the isotopic composition of sediment HgT to infer

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bioaccumulation likely does not encompass all the potential sources available to fish

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species. One case highlighting different potential MeHg sources is VT_Saxtons, where

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the prey fish and game fish show opposite sediment offsets (Fig. 4). We hypothesize

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that game fish have a larger and more diverse foraging range, possibly even feeding

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upstream closer to two legacy-contaminated stream sections outside the sampling

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reach. In contrast, prey fish, such as Blacknose Dace, likely spend their entire life cycle

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within the 150 meter sampling reach and are more representative of the general

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watershed conditions of the study site.70 The high variability of the offsets within these 3

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sites also indicates that our understanding of fractionation during the geochemical and

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microbial cycling of Hg is still incomplete and is not sufficient to connect the isotopic 20 ACS Paragon Plus Environment

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signature in sediment to the bioaccumulated Hg. The direct measurement of MeHg

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isotopic composition 71, 72 would be needed in future studies to alleviate this uncertainty

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and understand this offset between biota and sediments. While this method of

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assessing fish Hg sources may work in areas of severe sediment contamination or in

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species with a reliance on the sediment-dwelling benthos 18,27, this may not be

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appropriate for streams with mainly coarse-grained substrate across the northeastern

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U.S., hence caution is recommended when interpreting Hg sediment sources to food

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webs when these offsets are present.

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In this study, we demonstrate the preservation of different Hg isotope source

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signatures in fish from streams across the northeastern U.S. Fish from streams across a

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broad watershed development gradient were shown to preserve a δ202Hg signature that

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distinguishes between forested and urban-industrial settings and is strongly related to a

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land-use gradient. This indicates that the Hg source signature is preserved in fish

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despite additional fractionation processes that can occur prior to and during

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bioaccumulation. The results presented here provide support for the use of fish tissue

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as a tracer for bioaccumulated Hg in streams and for the use of fish tissue isotopes

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rather than reliance on sediment isotope measurements for food web source

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assessment in similar systems. This study highlights the potential use of fish tissue

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isotopic compositions to track changes in the relative importance of atmospheric and

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industrial Hg inputs and establishes source end members in a biological matrix, which is

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critical to achieving a more widespread application of Hg isotope measurements in

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aquatic systems. The future application of Hg isotope measurements in fish tissue

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allows for the potential of distinguishing different watershed sources of Hg that are 21 ACS Paragon Plus Environment

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bioaccumulating into the food web, an important step for management and remedial

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activity.

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Acknowledgements

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This work was supported as part of the Northeast Stream Quality Assessment portion of

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the National Water-Quality Assessment (NAWQA), the USGS Toxic Substances

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Hydrology Program, and New York State Energy Research and Development Authority

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(NYSERDA) contract # 37346. Any use of trade, product, or firm names in this

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publication is for descriptive purposes only and does not imply endorsement by the U.S.

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Government.

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The authors declare no competing financial interest.

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Supporting Information

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The following files are available free of charge: extended methods, figure comparing

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δ202Hg and the Δ199Hg values in fish, plot of photochemical slope, variation of δ202Hg

494

across fish species, δ202Hg vs δ202HgOR comparison, correlation plot of PCA Axes and

495

fish tissue δ199Hg, geomorphic and land-use characteristics of sampling sites; water

496

chemistry values for sites, NESQA fish isotope and concentration data, sediment

497

isotope and concentration data, Spearman rank correlation results for sediments and

498

fish tissue. All data presented in this manuscript are also available in the associated

499

USGS data release.48

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503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550

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Perrot, V.; Epov, V. N.; Pastukhov, M. V.; Grebenshchikova, V. I.; Zouiten, C.; Sonke, J. E.; Husted, S.; Donard, O. F. X.; Amouroux, D., Tracing sources and bioaccumulation of mercury in fish of Lake Baikal− Angara River using Hg isotopic composition. Environ. Sci. Technol. 2010, 44, (21), 8030-8037. Wiederhold, J. G.; Smith, R. S.; Siebner, H.; Jew, A. D.; Brown, G. E., Jr.; Bourdon, B.; Kretzschmar, R., Mercury isotope signatures as tracers for Hg cycling at the New Idria Hg mine. Environ. Sci. Technol. 2013, 47, (12), 6137-45. Lepak, R.; Yin, R.; Janssen, S. E.; Krabbenhoft, D. P.; Ogorek, J.; DeWild, J. F.; Tate, M. T.; Hurley, J. P., Factors Affecting Mercury Stable Isotopic Distribution in Piscivorous Fish of the Great Lakes Environ. Sci. Technol. 2018, 52 (5): 2768-2776 Senn, D. B.; Chesney, E. J.; Blum, J. D.; Bank, M. S.; Maage, A.; Shine, J. P., Stable isotope (N, C, Hg) study of methylmercury sources and trophic transfer in the Northern Gulf of Mexico Environ. Sci. Technol. 2010, 44, (5), 1630-1637. Tsui, M. T.; Blum, J. D.; Kwon, S. Y.; Finlay, J. C.; Balogh, S. J.; Nollet, Y. H., Sources and transfers of methylmercury in adjacent river and forest food webs. Environ. Sci. Technol. 2012, 46, (20), 10957-64. Blum, J. D.; Popp, B. N.; Drazen, J. C.; Anela Choy, C.; Johnson, M. W., Methylmercury production below the mixed layer in the North Pacific Ocean. Nature Geosci. 2013, 6, (10), 879-884. Xu, X.; Zhang, Q.; Wang, W.-X., Linking mercury, carbon, and nitrogen stable isotopes in Tibetan biota: Implications for using mercury stable isotopes as source tracers. Sci. Rep. 2016, 6, 25394. Sherman, L. S.; Blum, J. D., Mercury stable isotopes in sediments and largemouth bass from Florida lakes, USA. Sci.Total Environ. 2013, 448, 163-175. Gehrke, G. E.; Blum, J. D.; Slotton, D. G.; Greenfield, B. K., Mercury Isotopes Link Mercury in San Francisco Bay forage fish to surface sediments. Environ. Sci. Technol. 2011, 45, (4), 1264-1270. Kwon, S. Y.; Blum, J. D.; Chen, C. Y.; Meattey, D. E.; Mason, R. P., Mercury isotope study of sources and exposure pathways of methylmercury in estuarine food webs in the Northeastern U.S. Environ. Sci. Technol. 2014, 48, (17), 10089-10097. Tsui, M. T. K.; Blum, J. D.; Finlay, J. C.; Balogh, S. J.; Kwon, S. Y.; Nollet, Y. H., Photodegradation of methylmercury in stream ecosystems. Limnol. Oceanog. 2013, 58, (1), 13-22. Tsui, M. T.; Blum, J. D.; Finlay, J. C.; Balogh, S. J.; Nollet, Y. H.; Palen, W. J.; Power, M. E., Variation in terrestrial and aquatic sources of methylmercury in stream predators as revealed by stable mercury isotopes. Environ. Sci. Technol. 2014, 48, (17), 10128-35. Liu, J.; Feng, X.; Yin, R.; Zhu, W.; Li, Z., Mercury distributions and mercury isotope signatures in sediments of Dongjiang, the Pearl River Delta, China. Chem. Geol. 2011, 287, (1-2), 81-89. Sonke, J. E.; Schäfer, J.; Chmeleff, J.; Audry, S.; Blanc, G.; Dupré, B., Sedimentary mercury stable isotope records of atmospheric and riverine pollution from two major European heavy metal refineries. Chem. Geol. 2010, 279, (3-4), 90-100. Mil-Homens, M.; Blum, J.; Canário, J.; Caetano, M.; Costa, A. M.; Lebreiro, S. M.; Trancoso, M.; Richter, T.; de Stigter, H.; Johnson, M.; Branco, V.; Cesário, R.; Mouro, F.; Mateus, M.; Boer, W.; Melo, Z., Tracing anthropogenic Hg and Pb input using stable Hg and Pb isotope ratios in sediments of the central Portuguese Margin. Chem. Geol. 2013, 336, 62-71. Foucher, D.; Hintelmann, H.; Al, T. A.; MacQuarrie, K. T., Mercury isotope fractionation in waters and sediments of the Murray Brook mine watershed (New Brunswick, Canada): Tracing mercury contamination and transformation. Chemical Geol. 2013, 336, 87-95. 24 ACS Paragon Plus Environment

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Yin, R.; Krabbenhoft, D. P.; Bergquist, B. A.; Zheng, W.; Lepak, R. F.; Hurley, J. P., Effects of mercury and thallium concentrations on high precision determination of mercury isotopic composition by Neptune Plus multiple collector inductively coupled plasma mass spectrometry. J. Anal. At. Spectrom. 2016, 31, (10), 2060-2068. Demers, J. D.; Sherman, L. S.; Blum, J. D.; Marsik, F. J.; Dvonch, J. T., Coupling atmospheric mercury isotope ratios and meteorology to identify sources of mercury impacting a coastal urban-industrial region near Pensacola, Florida, USA. Global Biogeochem. Cy. 2015, 29, (10), 1689-1705. Fu, X.; Marusczak, N.; Wang, X.; Gheusi, F.; Sonke, J. E., Isotopic composition of gaseous elemental mercury in the free troposphere of the Pic du Midi observatory, France. Environ. Sci. Technol. 2016, 50, (11), 5641-5650. Huang, J.; Chang, F. C.; Wang, S.; Han, Y. J.; Castro, M.; Miller, E.; Holsen, T. M., Mercury wet deposition in the eastern United States: characteristics and scavenging ratios. Environ. Sci. Proc. Impact. 2013, 15, (12), 2321-2328. Chen, J.; Hintelmann, H.; Feng, X.; Dimock, B., Unusual fractionation of both odd and even mercury isotopes in precipitation from Peterborough, ON, Canada. Geochim. Cosmochim. Ac. 2012, 90, 33-46. Selin, N. E.; Jacob, D. J.; Park, R. J.; Yantosca, R. M.; Strode, S.; Jaeglé, L.; Jaffe, D., Chemical cycling and deposition of atmospheric mercury: Global constraints from observations. J. Geophys. Res.-Atmos. 2007, 112, D2, 1-14. Jiskra, M.; Wiederhold, J. G.; Skyllberg, U.; Kronberg, R.-M.; Hajdas, I.; Kretzschmar, R., Mercury deposition and re-emission pathways in boreal forest soils investigated with Hg isotope signatures. Environ. Sci. Technol. 2015, 49, (12), 7188-7196. Zheng, W.; Hintelmann, H., Isotope fractionation of mercury during Its photochemical reduction by low-molecular-weight organic compounds. J. Phys.Chem. A. 2010, 114, (12), 4246-4253. Harris, R. C.; Rudd, J. W. M.; Amyot, M.; Babiarz, C. L.; Beaty, K. G.; Blanchfield, P. J.; Bodaly, R. A.; Branfireun, B. A.; Gilmour, C. C.; Graydon, J. A.; Heyes, A.; Hintelmann, H.; Hurley, J. P.; Kelly, C. A.; Krabbenhoft, D. P.; Lindberg, S. E.; Mason, R. P.; Paterson, M. J.; Podemski, C. L.; Robinson, A.; Sandilands, K. A.; Southworth, G. R.; St. Louis, V. L.; Tate, M. T., Whole-ecosystem study shows rapid fish-mercury response to changes in mercury deposition. P. Natl. A. Sci. 2007, 104, (42), 16586-16591. Wiener, J. G.; Knights, B. C.; Sandheinrich, M. B.; Jeremiason, J. D.; Brigham, M. E.; Engstrom, D. R.; Woodruff, L. G.; Cannon, W. F.; Balogh, S. J., Mercury in soils, lakes, and fish in Voyageurs National Park (Minnesota):  Importance of atmospheric deposition and ecosystem factors. Environ. Sci. Technol. 2006, 40, (20), 6261-6268. Selvendiran, P.; Driscoll, C. T.; Montesdeoca, M. R.; Bushey, J. T., Inputs, storage, and transport of total and methyl mercury in two temperate forest wetlands. J. Geophys. Res.Biogeo. 2008, 113, (G2), 1-15. Chamlers, A.T., Krabbenhoft, D.P., Van Metre, P.C., Nilles, M.A. Effects of urbanization on mercury deposition and accumulation in New England. Environ. Pollut. 2014, 192, 104112. Kritee, K.; Blum, J. D.; Johnson, M. W.; Bergquist, B. A.; Barkay, T., Mercury stable isotope fractionation during reduction of Hg(II) to Hg(0) by mercury resistant microorganisms. Environ. Sci. Technol. 2007, 41, (6), 1889-1895. Jiskra, M.; Wiederhold, J. G.; Bourdon, B.; Kretzschmar, R., Solution speciation controls mercury isotope fractionation of Hg(II) sorption to goethite. Environ. Sci. Technol. 2012, 46, (12), 6654-62.

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Hanley, K.; Wollheim, W.; Salisbury, J.; Huntington, T.; Aiken, G. R., Controls on dissolved organic carbon quantity and chemical character in temperate rivers of North America. Global Biogeochem. Cy. 2013, 27, (2), 492-504. Razavi, N.R., Cushman, S.F., Halfman, J.D., Massey T., Beutner R., and Cleckner L.B., Mercury bioaccumulation in stream food webs of the Finger lakes in central New York State, USA. Ecotox. Environ. Safe. 2019, 172, 265-272. Kritee, K.; Barkay, T.; Blum, J. D., Mass dependent stable isotope fractionation of mercury during mer mediated microbial degradation of monomethylmercury. Geochim. Cosmochim. Ac. 2009, 73, (5), 1285-1296. Hill, J. Grossman, G.D., Home range estimates for three North American stream fishes. Copeia. 1987, 1987, (2), 376-380. Janssen, S. E.; Johnson, M. W.; Blum, J. D.; Barkay, T.; Reinfelder, J. R., Separation of monomethylmercury from estuarine sediments for mercury isotope analysis. Chem. Geol. 2015, 411, (0), 19-25. Masbou, J.; Point, D.; Sonke, J. E., Application of a selective extraction method for methylmercury compound specific stable isotope analysis (MeHg-CSIA) in biological materials. J. Anal. At. Spectrom. 2013, 28, (10), 1620-1628.

718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734

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735

Table 1. Environmental variable statistics and correlations with first three axes resulting

736

from principal components analysis (PCA) of selected variables from 23 streams in the

737

northeastern U.S. The highest absolute loadings for each axis are bolded, intermediate

738

are in regular font, and the lowest are in grey font. Abbreviations are defined as dw, dry

739

weight; UMeHg, unfiltered methylmercury; UTHg, unfiltered total mercury; THg, total

740

mercury; MeHg, methylmercury; LOI; loss on ignition.

Variable (units)

median (minmax)

Road density in watershed (km of road/ 100 km2) Atmospheric deposition, total, at site (ug/m2)

9.7 (2.0-24.0)

fourth root

0.34

-0.12

0.12

19.5 (15.9)

Rank

0.30

0.09

-0.07

square root

-0.02

0.40

-0.21

none

-0.37

-0.05

0.06

log base 10

0.35

0.07

-0.03

rank

0.31

-0.20

-0.06

rank

0.31

0.17

0.13

log base 10

0.23

-0.02

0.26

log base 10

-0.10

0.37

0.30

log base 10

-0.20

0.36

0.06

square root

0.22

0.21

-0.41

square root

0.16

0.45

-0.10

none

-0.02

0.40

0.25

none

0.06

-0.24

-0.21

Wetlands in watershed (%) Forest & shrub land in watershed (%) Total Nitrogen (mg/L) Sulfate (mg/L) Chloride (mg/L) UTHg (µg/L) UMeHg (µg/L) MeHg:THg in unfiltered water (%) DOC (mg/L) UVA254(abs/cm) SUVA (L/mgC/m) pH

6 (1.0-20) 36 (10-91) 0.688 (0.2-1.2) 9.44 (2.9-238) 137.7 (7.6-243) 1.26 (0.5-10.2) 0.09 (0.02-0.6) 7 (1-43) 4.62 (2.2-9.2) 0.104 (0.05-0.2) 2.27 (1.4-3.2) 7.4 (6.5-8.5)

Transformation used in PCA

Eigenvectors Percent variance explained (eigenvalue) Axis 1 Axis 2 Axis 3 38% 21% 12% (6.48) (3.51) (2.11)

THg in bed sediments (ng/g dw; loi-normalized)

7.5 (1.3-47.6)

log base 10

0.27

-0.03

0.41

MeHg in bed sediments (ng/g dw; loi-normalized)

0.146 (0.04-1.8)

log base 10

-0.08

-0.12

0.52

MeHg:THg in bed sediments (%)

1.4 (0.7-21.2)

rank

-0.29

-0.02

-0.12

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741 742 743 744 745 746 747 748 749 750 751 752 753

Fig 1: Map of land cover and sampling sites for the mercury stable isotope portion of the

754

Northeast Stream Quality Assessment (NESQA). Land cover is based on the National

755

Land Cover dataset 2011.45

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756 757

Fig. 2: a) Hg isotope compositions (δ202Hg) and b) total Hg concentrations in 23 streams across the northeastern United

758

States, grouped according to land-use type. Boxplots are based on site mean concentration and isotope compositions in

759

composites of whole prey fish, skinless fillets of individual game fish, and bed sediment (LOI normalized); the number of

760

sites is denoted by n. Boxplots represent the 25-75th quartile for data with medians and means denoted by the center line

761

and square symbol, respectively. Whiskers represent the 25th percentile less 1.5 times the interquartile range (IQR) and

762

the 75th percentile plus 1.5 times the IQR, and outliers are denoted by filled symbols.

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764 765 766 767 768 769 770 771 772 773 774 775 776

Regressions between δ202Hgcor values in fish and δ202Hg in sediment in

777

Fig 3.

778

relationship to PCA Axis 1, the urban intensity gradient. The urban-intensity gradient is

779

characterized by increasing (from left to right) road density, atmospheric Hg deposition,

780

and concentrations of nitrogen, sulfate, chloride, and decreasing forest cover. Strong

781

relationships between δ202Hg and this gradient independently confirm the relationship

782

between isotopic source signature in fish and land use. Dashed lines represent linear

783

regressions; results have p < 0.0001 in all cases.

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784 785 786 787 788 789 790 791 792 793

Fig. 4: Isotopic relationship (δ202Hg) between sediments and fish tissue. Fish tissue

794

δ202Hgcor represents the isotope signature of fish tissue (whole prey fish or game fish

795

fillets0) prior to photochemical demethylation as applied in the literature.24, 26, 27 The line

796

represents the situation when sediment and fish tissue isotopic compositions are

797

isotopically the same. Site abbreviations correspond with site names listed in Table S1.

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TOC art for manuscript 248x190mm (150 x 150 DPI)

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