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Environmental Science: Processes & Impacts View Article Online

DOI: 10.1039/C5EM00495K

Environmental Impact Statement Mercury exposure through fish consumption may lead to adverse health effects, particularly impacting pregnant women and children. The Grand Lake watershed includes one of the largest reservoirs in Oklahoma and is a popular fishing destination for local recreational and subsistence fishermen, among whom consumption of local fish may account for the majority of dietary mercury intake. Moreover, reservoirs often have higher fish mercury concentrations than lakes due to their unique hydrodynamics. This study aims at exploring the key factors associated with fish mercury concentrations both within and among reservoirs through an extensive survey of over 30 fish species and 1300 samples in Grand Lake watershed and an intersystem analysis of 32 biogeochemical and ecological factors across 61 reservoirs.

Environmental Science: Processes & Impacts Accepted Manuscript

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1

Key Contributors to Variations in Fish Mercury Within and Among

2

Freshwater Reservoirs in Oklahoma, USA

3

Zhao Donga*, Robert A. Lynchb, Laurel A. Schaidera1

4 5

a

Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA

6

b

University of Oklahoma Health Sciences Center, Oklahoma City, OK 73126, USA

7 8

* Corresponding author contact information: tel: +1-617-432-5554; fax:+1-617-432-3349;

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email: [email protected]

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1

Present address: Silent Spring Institute, Newton, MA 02458, USA

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1

Environmental Science: Processes & Impacts Accepted Manuscript

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Abstract

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Elevated fish mercury (Hg) concentrations in freshwater ecosystems worldwide are a significant

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human and ecological health concern. Mercury bioaccumulation and biomagnification in lakes

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and reservoirs are controlled by numerous biogeochemical and ecological factors, contributing to

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variability in fish Hg concentrations both within and among systems. We measured total mercury

17

concentrations ([THg]) and stable isotopes (δ15N, δ13C) in over 30 fish species in two connected

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subtropical freshwater reservoirs (Grand Lake and Lake Hudson, Oklahoma, USA), their

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tributaries, and local farm ponds, all of which are potentially impacted by nearby atmospheric Hg

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sources. We also conducted an inter-system analysis among 61 reservoirs in Oklahoma to

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explore biological, chemical and physical factors associated with fish [THg] across systems. We

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found that [THg] for most species in Grand Lake and Lake Hudson were relatively low

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compared to other reservoirs in Oklahoma. There were significant spatial variations in many

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species within and between Grand Lake and Lake Hudson, even after accounting for length

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and/or trophic position (based on δ15N). Fish in local farm ponds, commonly used in the

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agricultural regions for raising game fish, had 2-17 times higher [THg] than fish of similar length

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in nearby reservoirs. The inter-system analysis revealed that pH, water color, rainfall, and

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nutrients are the best predictors of fish [THg] across systems. Our results provide insight into the

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key factors associated with fish [THg] variations both within and across systems, and may be

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useful for exposure assessment and for identifying sites and water bodies prone to high fish [THg]

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as monitoring priorities.

32 33

Keywords: fish; impoundment; mercury biomagnification; methylmercury; spatial variation

34 35

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Environmental Science: Processes & Impacts Accepted Manuscript

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Introduction Elevated concentrations of mercury (Hg) have been detected in freshwater fish globally1-4.

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Mercury bioaccumulation in commonly consumed fish has become a global health concern,

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primarily due to potential human health effects of exposure to methylmercury (MeHg),

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especially for fetuses and children5, even at low levels associated with typical rates of fish

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consumption6. In the U.S., fish and shellfish consumption is the primary non-occupational source

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of MeHg exposure in the general population7, and thousands of fish consumption advisories have

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been issued for freshwater bodies8. Elevated Hg concentrations in fish have also been associated

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with neurological and/or reproductive effects in fish9, piscivorous birds and mammalian

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wildlife10, particularly in systems close to major point sources and in regions that receive high

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levels of atmospheric deposition11.

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Mercury is released to the environment through both natural processes and human activities.

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Coal combustion is a major anthropogenic source, accounting for 24% of global emissions12.

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While Hg is primarily emitted to the atmosphere in inorganic species, a portion of Hg that enters

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aquatic systems is transformed into MeHg by sulfate- and iron-reducing bacteria in anoxic water,

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sediments, and wetlands13, 14. Biomagnification of MeHg results in orders of magnitude higher

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concentrations in top predators, many of which are consumed by humans, piscivorous birds and

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wildlife.

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Variations in fish Hg concentrations are determined to some degree by the amount of Hg

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entering a system from atmospheric deposition15, 16 and discharges from mines and other local

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sources17, 18. However, even among lakes and reservoirs located in the same region that receive

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similar levels of atmospheric Hg deposition, fish Hg concentrations can vary considerably19 due

3

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to the complex interactions among processes that determine net Hg methylation, bioavailability,

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uptake and trophic transfer.

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Mercury bioaccumulation and biomagnification in freshwater ecosystems are influenced

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by numerous ecological, biogeochemical, and physical factors20, which can lead to variation in

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MeHg in predator fish on multiple scales. First, among individuals of the same species, MeHg

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concentrations tend to be positively correlated with size and age21, while low-Hg prey22 and

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faster growth rates23 have been associated with

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variations in MeHg concentrations among species are related to food chain structure and trophic

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position24 and to species-specific efficiency of trophic transfer of MeHg25. Third, within a water

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body, rates of net methylation and supply of MeHg to primary producers are influenced by water

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quality parameters such as dissolved organic matter26, pH27, 28, temperature29, and sulfate (SO42-)

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concentration30, as well as rates of primary productivity31. Fourth, characteristics of the water

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body and its watershed, such as surface area32, age of reservoirs33 or ponds34, water level35,

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wetland coverage36, and precipitation37, may also contribute to variations in MeHg production

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and fate.

lower fish MeHg concentrations. Second,

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Many studies have explored factors associated with spatial variations in fish Hg

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concentrations in lakes and reservoirs24, 38-40. However, very few studies have simultaneously

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examined variations both within and among systems, while the factors most closely associated

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with variations in fish Hg concentrations may be scale-dependent. For instance, across many

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lakes covering a range of geological settings, pH may vary widely and be a key variable in

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explaining variations in Hg bioavailability and uptake, whereas within a lake, the range may be

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too small to observe variations in Hg concentrations as a function of pH. In addition, most

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studies on Hg biomagnification in lakes and reservoirs in North America were conducted in

4

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temperate zones19, 24, 29, 41, and relatively few42-44 have focused on subtropical regions despite

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higher Hg emissions from power plants in these areas45.

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To evaluate key factors that explain differences in fish Hg concentrations within and

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among reservoirs, we examined variations in Hg concentrations in fish occupying a range of

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habitats and trophic positions from two connected freshwater reservoirs in south central U.S.,

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which are located within 100 km of six coal-fired power plants (CFPPs). In addition, we sampled

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fish from local farm ponds, commonly used to raise game fish in the U.S. (50,000 constructed

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annually46) and other parts of the world, and “may be one of the largest unstudied Hg pollution

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problems in the U.S” 47. To interpret our findings in a broader geographical context, we assessed

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variations in fish Hg concentrations among 61 reservoirs in this region by conducting correlation

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and regression analyses using 32 biogeochemical and watershed parameters. Our results provide

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insights into the key factors that affect the distribution of fish Hg concentrations both within and

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among subtropical freshwater reservoirs, and may be helpful for identifying priorities for

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monitoring Hg in biota and for guiding health-oriented environmental regulations and

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management practices in general.

96 97

Method

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Site characteristics

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We conducted in-depth sampling in two connected reservoirs in northeastern Oklahoma,

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Grand Lake O’ The Cherokees (Grand Lake) and Lake Hudson, located within the humid

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subtropical climate zone in south central U.S. Grand Lake, impounded in 1941, is the third

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largest reservoir in Oklahoma and a popular fishing destination, with a surface area of about 200

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km2 and mean and maximum depths of 11.1 and 40.5 m, respectively48. Its primary tributaries

5

Environmental Science: Processes & Impacts Accepted Manuscript

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are the Neosho River (69% of inflow), Spring River (16% of inflow), and Elk River (15% of

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inflow) (Figure 1). Grand Lake has been classified as eutrophic based on phosphorus

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concentrations (0.03-0.19 mg/L)49. There is limited wetland coverage, distributed primarily along

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the shorelines in the upper reaches, covering about 8.5 km2. Lake Hudson is located downstream

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of Grand Lake (Figure 1), which is the main source of its flow, and was impounded in 1964. It

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covers approximately 45 km2 and is also classified as eutrophic ([P]: 0.01–0.14 mg/L)49. It also

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has very limited wetland area, covering only 0.6 km2 48 mainly due to its steep shoreline and

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rocky substrates that limit plant growth.

112 113 114

Sample collection Between April 2010 and February 2013, about 1300 fish representing more than 30

115

species were collected throughout Grand Lake and its tributaries, Lake Hudson, and nearby farm

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ponds. Most of the species are commonly consumed by local residents50 or are sport fish. Around

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68% of these fish were collected by the Oklahoma Department of Wildlife Conservation

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(ODWC) as part of routine fish population surveys, primarily using gill nets. The rest of the

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samples were donated by local anglers, caught by hook and line or noodling (hand fishing). To

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evaluate spatial variability, we divided Grand Lake and Lake Hudson into three sections based

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on hydrodynamics: upper (riverine), mid (transition zone), and lower (lacustrine). Hydrological

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differences were more pronounced in Grand Lake than Lake Hudson. Samples were also

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collected from five major tributaries of Grand Lake (Spring River, Neosho River, Elk River,

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Horse Creek and Honey Creek) and from the area below the Pensacola Dam (between the

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reservoirs). Monthly water chemistry data was provided by the Grand River Dam Authority

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(GRDA, unpublished data) for most sections of Grand Lake and its tributaries.

6

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Samples of five species (N = 1-12) from seven farm ponds were donated by local pond

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owners. All of the ponds were located within the Grand Lake watershed. It is estimated that over

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200,000 farm ponds have been built in Oklahoma, and they are commonly used as water sources

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for livestock and irrigation, and to grow game fish51.

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Fish were weighed and measured for total length upon collection, and a small piece of

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skinless fillet (about 30 g) was harvested from each fish along the spine and just behind the head.

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In addition, stomach contents were collected from several predator species. To obtain stomach

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contents, body cavity contents were removed through an incision in the abdomen of each fish

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and the stomach was then separated from the remainder of the contents. The stomach was sliced

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open and any relatively intact and identifiable prey fish were removed, weighed and measured.

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All samples were then placed in acid-washed, pre-weighed 50 mL polypropylene centrifuge

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tubes, frozen and shipped overnight on ice to the Trace Metals Laboratory at Harvard T.H. Chan

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School of Public Health (Boston, MA).

140 141

Our sampling protocols have been reviewed and approved by the HMA Standing Committee on Animals at the Harvard Medical School.

142 143 144

Hg analyses All fish samples were freeze-dried in a benchtop FreeZone Freeze Dry System (Labconco,

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Kansas City, MO) for 72 hours. Wet and dry weights of each sample were obtained immediately

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before and after freeze-drying. The average water content in fish samples was 78 ± 7.3%. All Hg

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results hereafter were reported on a wet weight basis. Freeze-dried samples were homogenized

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manually within centrifuge tubes using acid-cleaned Teflon stir rods.

7

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Total Hg concentrations ([THg]) were determined for 1179 fillet and stomach content

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samples on a DMA-80 Direct Mercury Analyzer (Milestone Inc., Shelton, CT), following a

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method of thermal decomposition, amalgamation, and atomic absorption spectrophotometry52.

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The DMA was calibrated with newly made HgCl2 solutions, and the calibration curve was

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checked daily with varying masses of a certified reference material (CRM), usually fish protein

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(DORM-3). At least one method blank and one lobster hepatopancreas CRM (TORT-2) were

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analyzed with every 10 samples. The average recovery was 102 ± 8.5% for DORM-3 (n=106)

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and 107 ± 9.2% for TORT-2 (n=128). Duplicates were analyzed for 10% of the samples, with an

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average relative percent difference (RPD) of 14%.

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Forty-five fillet samples from Grand Lake and Lake Hudson from 12 species were

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analyzed for MeHg at the Dartmouth College Trace Element Analysis Laboratory, by automated

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purge and trap gas chromatography interfaced with inductively coupled plasma mass

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spectrometry (GC-ICP-MS)53. A blank spike and a CRM, either mussel tissue (NIST 2976) or

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DORM-3, were analyzed with every 10 samples, with average recoveries of 94 ± 1.1% (n=3) and

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92 ± 0.8% (n=3), respectively. Duplicates were analyzed for 10% of the samples, with RPDs

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ranging from 2 to 8%.

165 166 167

Stable isotope analyses Nitrogen and carbon stable isotopes are commonly used ecological metrics of food chain

168

dynamics. Stable nitrogen isotope ratio (δ15N) is a continuous and integrative index of trophic

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position54 and fractionates approximately 3.4‰ at each trophic transfer55. Stable carbon isotope

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ratio (δ13C) reflects the dietary carbon source at the base of the food chain, and fractionates at a

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less consistent rate of 0.05, except for blue catfish, crappie and shad.

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Length and TP were not transformed since the studentized residuals of all regression models met

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assumptions of normality (p>0.05 for Shapiro-Wilk test and Kolmogorov-Smirnov test). Horse

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Creek was used as the reference location since all 10 species were sampled there.

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In order to evaluate our results in a broader geographical context and to further examine

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the key factors that explain differences in Hg bioaccumulation among reservoirs in this region,

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we analyzed correlations between fish [THg] across reservoirs in Oklahoma and 32 aquatic

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biogeochemical and watershed parameters. Using a pooled dataset containing fish [THg]

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Environmental Science: Processes & Impacts Accepted Manuscript

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measurement data from both national sampling campaigns59 and ODEQ sampling events

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between 2007 and 2010 (ODEQ, unpublished data) in Oklahoma reservoirs, fish [THg] was

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regressed against length for largemouth bass, and sampling location (i.e., reservoir) was included

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in the model as a categorical variable. The resulting slope and intercepts were then used to

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predict [THg] in a 14″ (36 cm) largemouth bass in each reservoir. The regression and prediction

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were performed by ODEQ based on a model developed by U.S. Geological Survey60. Prior to our

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analysis, we performed natural log-transformations on these [THg] data to ensure a normal

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distribution (p=0.35, Shapiro-Wilk test).

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In our inter-system analysis, we included parameters related to water chemistry (pH,

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alkalinity, true color, apparent color, Secchi depth, salinity, turbidity, temperature), biology

228

(pheophytin, chlorophyll-a) and nutrients (nitrate nitrogen [NO3-N], nitrite nitrogen [NO2-N],

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ammonia nitrogen [NH4-N], total phosphorus [P], N:P ratio, oxidation-reduction potential,

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trophic index, sulfate [SO4], summer hypoxia frequency, etc.) in the bottom water. These data

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were provided by the Oklahoma Water Resources Board (OWRB) for over 120 lakes throughout

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Oklahoma between 2005 and 201249, nearly all of which were reservoirs. We also included total

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surface area, average annual rainfall, and watershed wetland coverage, which were all calculated

234

from a spatial analysis, as well as reservoir age. For each lake, we calculated an average value

235

for each variable and the final dataset included 61 reservoirs for which we had overlapping data

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on fish [THg] and explanatory variables (Supplemental Table S1). The reservoirs in this final

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dataset are all established reservoirs at least 17 years (average 54 years) since the impoundment,

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with surface areas ranging from 0.4 to 403 km2. We calculated the Spearman’s correlation

239

coefficient (ρ) between fish [THg] and each variable, and also performed a multivariate linear

240

regression, using the same parameters as predictors of fish ln[THg]. A bidirectional stepwise

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Environmental Science: Processes & Impacts Accepted Manuscript

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regression based on AIC score (Akaike Information Criterion, a commonly used indicator for

242

model goodness-of-fit) was performed to eliminate covariates that were not significant predictors

243

of fish [THg]. The variance inflation factors (VIF) for all covariates in the final model were

244

below 3.5, suggesting little multicollinearity. Results for all correlation tests and regressions

245

were reported at a significance level of 0.05.

246 247

RStudio version 0.98.978 (with R version 3.1.1) was used to perform all statistical analyses. The spatial analysis was conducted in ArcGIS 10.1.

248 249

Results and Discussion

250

Fish Hg concentrations in Grand Lake and Lake Hudson

251

Most of the species examined in this study had relatively low [THg] (Table 1). With the

252

exception of gar (Lepisosteidae), mean [THg] for all species was below the U.S. EPA’s fish

253

tissue residue criterion (TRC; 300 ng/g, based on an assumed fish consumption rate of 17.5 g

254

/day for the general adult population61) and the EPA wildlife criterion (WC) value for trophic

255

level 4 fish such as largemouth bass and flathead catfish (346 ng/g, for the protection of

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piscivorous mammalian wildlife62). Among fillet samples collected from Grand Lake, the

257

average [THg] ranged from 15 ± 12 ng/g (shad) to 530 ng/g (gar, n=2). Average [THg] for fish

258

species lower on the food chain, such as shad, carp (Cyprinus carpio), buffalo, and perch/sunfish,

259

were all below the EPA WC for trophic level 3 fish (77 ng/g). No samples from Lake Hudson

260

exceeded the EPA fish TRC or level 4 WC, with the average [THg] ranging from 9.5 ± 2.4 ng/g

261

(shad) to 91 ng/g (gar, n=2). Stomach contents generally had [THg] below 40 ng/g, and the

262

average concentrations were 3 (white bass) to 6 (flathead catfish) times lower than those in the

263

corresponding fillet samples.

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Fillet samples of all species contained 95% MeHg or above, except for shad (82%),

265

which occupy a lower trophic level (Supplemental Table S2). Therefore, [THg] is a good

266

surrogate for MeHg concentrations in our fillet samples.

267

Across both Grand Lake and Lake Hudson, average total length ranged from 15 ± 2.3 cm

268

(sunfish) to 97 ± 15 cm (spoonbill; Table 2). In general, [THg] in fillets increased with length,

269

with the exception of three lower trophic level species (sunfish, spoonbill, and shad). Among 11

270

species with a total sample size N≥10, [THg] was significantly (p2. Species Gara

(Lepisosteidae) Flathead Catfish (Pylodictis olivaris) Fillet Stomach Contents Spotted Bass (Micropterus punctulatus) Largemouth Bass (Micropterus salmoides) Fillet Stomach Contents Wiper (M. chrysops x M. saxatilis) White Bass (Morone chrysops) Fillet Stomach Contents Striped Bass (Morone saxatilis) Smallmouth Bass (Micropterus dolomieu) Crappieb (Pomoxis spp.) Fillet Stomach Contents Drum (Aplodinotus grunniens) Fillet Stomach Contents White Catfish (Ameiurus catus) Blue Catfish (Ictalurus furcatus) Fillet

Grand Lake and Tributaries

Lake Hudson

Farm Ponds

N

Mean [THg] ± SD

% > TRC

N

Mean [THg] ± SD

% > TRC

2

530

100

2

91

0

38 2 2

220 ± 150 34 79

24 0 0

99 9 4

78 ± 60 15 ± 8.9 72 ± 43

1.0 0 0

4

41 ± 33

0

165 2 2 3

47 ± 34 16 42 34 ± 22

0 0 0 0

59

52 ± 51

0

130 3

30 ± 24 6.2 ± 0.3

0 0

14 4

18 ± 25 7.1 ± 2.3

0 0

29 1 5

130 ± 190 41 72 ± 53

10 0 0

10

31 ± 18

0

116

59 ± 55

1.8

69

40 ± 26

0

31

N

Mean [THg] ± SD

% > TRC

12

400 ± 250

33

3

86 ± 110

0

2

172

0

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Environmental Science: Processes & Impacts

Stomach Contents Channel Catfish (Ictalurus punctatus) Fillet Stomach Contents Sunfishc (Lepomis spp.) Catfish (Ictalurus sp.) Common Carp (Cyprinus carpio) Buffalod (Ictiobus spp.) River Carpsucker (Carpiodes carpio) Spoonbill (Polyodon spathula) Shade (Dorosoma sp.) Turtle (unidentified) Fillet Leg Crayfish (Whole) Total N

2

14

0

2

8.8

0

102 1 48 1 4 50 1 43 39

48 ± 28 15 31 ± 27 27 67 ± 54 54 ± 39 48 40 ± 24 15 ± 12

0 0 0 0 0 0 0 0 0

18

38 ± 17

0

1 2 4

3.0 84 23 ± 26 910

0 0 0

3 18

28 ± 17 52 ± 33

0 0

1 36

7.1 9.5 ± 2.4

0 0

240

a

includes shortnose gar and longnose gar; includes white crappie, black crappie, and unidentified species of crappie; c includes bluegill sunfish, green sunfish, redear sunfish, warmouth, longear sunfish and unidentified species of sunfish; d includes largemouth buffalo and smallmouth buffalo; e includes gizzard shad and unidentified species of shad. b

32

1

560

100

11

120 ± 110

50

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Table 2. Summary of length, trophic position (TP), lipid normalized δ13C (δ13Cadj) for 11 species with N≥10, and Spearman’s correlation coefficients of [THg] (ng/g) and length, TP, and δ13Cadj for each species. Species are color-coded according to typical trophic position. Species Crappie White Bass Largemouth Bass Flathead Catfish Blue Catfish Drum Sunfish Channel Catfish Spoonbill Buffalo Shad

N 148 225 121 46 192 39 59 127 56 73 75

Mean ± sd

Spearman's Correlation with [THg]

Lengtha (cm)

TPb

δ13Cadj (‰)b

Length

TP

δ13Cadj

27 ± 4.4 31 ± 7.8 37 ± 6.0 82 ± 25 47 ± 18 30 ± 13 15 ± 2.3 41 ± 13 97 ± 15 42 ± 11 23 ± 4.6

4.1 ± 0.31 4.0 ± 0.35 3.9 ± 0.46 3.7 ± 0.32 3.6 ± 0.42 3.5 ± 0.44 3.4 ± 0.21 3.2 ± 0.53 3.4 ± 0.24 3.2 ± 0.27 2.8 ± 0.53

-28 ± 0.86 -28 ± 0.52 -27 ± 1.0 -27 ± 1.2 -28 ± 1.0 -28 ± 1.9 -27 ± 1.4 -26 ± 1.5 -28 ± 2.1 -28 ± 1.6 -27 ± 1.4

0.55*** 0.61*** -0.46*** 0.43** 0.76*** 0.88*** 0.18 0.51*** 0.21 0.81*** -0.13

0.12 0.19 0.45*** 0.31^ 0.25 0.47* -0.32* 0.21 -0.072 0.23 0.41*

0.45*** 0.035 0.10 0.49** 0.58*** 0.68*** 0.039 -0.016 0.47^ 0.15 0.16

a

Include samples from all locations; Only include samples from Grand Lake and its tributaries. ^: 0.05

Key contributors to variations in fish mercury within and among freshwater reservoirs in Oklahoma, USA.

Elevated fish mercury (Hg) concentrations in freshwater ecosystems worldwide are a significant human and ecological health concern. Mercury bioaccumul...
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