A National Pilot Study of Mercury

Contamination of Aquatic Ecosystems

Along Multiple Gradients:

Bioaccumulation in Fish

NROK

YELL

SACR

NVBR

SANA

OAHU

COOK

TRIN

ACAD

LTEN

MOBL

SOFL

SANT

UIRB

MIAM

ALMN

LINJ

DELR

NECB

GRSL

> 0.30

0.15<x< 0.30

< 0.15 mg/kg wet wt.

Biological Science Report

USGS/BRD/BSR–2001-0009

U.S. Department of the Interior

U.S. Geological Survey
Technical Report Series 

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Front cover: The U.S. map shows 20 USGS National Water Quality Assessment (NAWQA) basins sampled in 

this study, categorized by geometric mean of mercury concentration in fish fillet samples. Basins shaded in gray 

delineate NAWQA study units not sampled. 
A National Pilot Study of Mercury 

Contamination of Aquatic Ecosystems 

Along Multiple Gradients: 

Bioaccumulation in Fish 

Biological Science Report 

USGS/BRD/BSR–2001-0009 

September 2001 

by 

William G. Brumbaugh1,

David P. Krabbenhoft2,

Dennis R. Helsel3,

James G. Wiener4,

and 

Kathy R. Echols1

1

U.S. Geological Survey, Columbia Environmental Research Center, 4200 New Haven Rd, Columbia, MO 65201 2

U.S. Geological Survey, Wisconsin District Mercury Laboratory, 8505 Research Way, Middleton, WI 53719 3

U.S. Geological Survey, Office of the Regional Geologist, Central Region, PO Box 25046, MS-911, Denver, CO

80225 4

University of Wisconsin-La Crosse, River Studies Center, Cowley Hall, Room 4032, 1725 State St., LaCrosse, WI 

54601 
Contents 

Abstract........................................................................................................................................................................1

Introduction..................................................................................................................................................................2

The USGS National Mercury Pilot Study...................................................................................................2

Experimental Section...................................................................................................................................................2

Study Design...................................................................................................................................................2

Sample Collection and Preparation.............................................................................................................3

Hg Determination..........................................................................................................................................4

Age Determination.........................................................................................................................................4

Statistical Analysis and Modelling...............................................................................................................4

Quality Assurance..........................................................................................................................................5

Results and Discussion................................................................................................................................................5

Mean Fish Concentration by Basin.............................................................................................................6

Basins of Concern for Human Health.........................................................................................................7

Sources and Factors Enhancing Bioaccumulation of Hg in Fish.............................................................8

Ranking of Basins by Hg in Fish, Sediment, and Water...........................................................................10

Correlation of Water and Sediment Parameters with Hg Bioaccumulation.........................................11

Principal Components Analysis (PCA)......................................................................................................13

Model for the Bioaccumulation of Hg in Fish...........................................................................................14

Relations of Hg in Fish, Sedimentt, and Water to Land Use Patterns...................................................16

Summary.....................................................................................................................................................................19

Acknowledgements.....................................................................................................................................................19

References...................................................................................................................................................................19

Appendix.....................................................................................................................................................................22

Concentrations of mercury in fish collected from USGS NAWQA Hg-Pilot Study basins, 

June through October, 1998...........................................................................................................................22 

ii 
List of Tables 

Table 1. Basins, number of sites, and number of fish samples analyzed.........................................................................3

Table 2. Measured mercury concentrations (μg/g dry wt.) for fish reference tissues .....................................................5

Table 3. Summary statistics for mercury concentrations (μg/g wet wt.) in fish fillet samples .......................................6

Table 4. Ranking of basins by geometric mean mercury concentration of fish fillet..................................................8

Table 5. Fish samples with fillet Hg concentrations greater than 0.50 μg/g wet wt........................................................9

Table 6. Top six study units based on ranking of individual sites according to various Hg criteria..........................11

Table 7. Correlation of measured parameters with bioaccumulation of Hg in fish....................................................12

List of Figures 

Figure 1. Geometric mean of Hg concentration in fish fillet samples collected for each of the 20 basins................7

Figure 2. Principal Components Analysis - Factor Loadings for Hg Concentration in Fish (all species)..................13

Figure 3. Principal Components Analysis - Factor Loadings for Hg Concentration in Largemouth Bass.................14

Figure 4. Principal Components Analysis - Factor Loadings for Hg Concentration in Largemouth Bass, 

excluding weight, length, and age................................................................................................................15

Figure 5. Length-normalized concentration of Hg in fish (all species) as a function of MeHg 

concentration in water...................................................................................................................................16

Figure 6. Length-normalized concentration of Hg in largemouth bass as a function of MeHg 

concentration in water...................................................................................................................................17

Figure 7. Geometric mean of Hg or MeHg in fish, water, and sediment for each land use category.........................18

Figure 8. Geometric mean of MeHg bioconcentration factor (MeHgfish / MeHgwater ) for all species 

and for largemouth bass, for each land use category...................................................................................18

iii
1 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

A National Pilot Study of Mercury Contamination of Aquatic Ecosystems 

Along Multiple Gradients: Bioaccumulation in Fish 

Abstract: Water, sediment, and fish were sampled in the summer and fall of 1998 at 106 sites from 20 U.S. watershed basins to examine relations of mercury (Hg) and methylmercury (MeHg) in aquatic ecosystems. 

Bioaccumulation of Hg in fish from these basins was evaluated in relation to species, Hg and MeHg in surficial 

sediment and water, and watershed characteristics. Bioaccumulation was strongly (positively) correlated with 

MeHg in water (r = 0.63, ρ < 0.001) but only moderately with the MeHg in sediment (r = 0.33, ρ < 0.001) or total 

Hg in water (r = 0.28, ρ < 0.01). Of the other measured parameters, pH, DOC, sulfate, sediment LOI, and the percent wetlands of each basin were also significantly correlated with Hg bioaccumulation in fish. The best model for 

predicting Hg bioaccumulation included MeHg in water, pH of the water, % wetlands in the basin, and the AVS 

content of the sediment. These four variables accounted for 45% of the variability of the fish fillet Hg concentration normalized (divided) by total length; however, the majority was described by MeHg in water. A MeHg water 

concentration of 0.12 ng/L was on average, associated with a fish fillet Hg concentration of 0.3 mg/kg wet weight 

for an age-3 fish when all species were considered. For age-3 largemouth bass, a MeHg water concentration of 

0.058 ng/L was associated with the 0.3 mg/kg fillet concentration. Based on rankings for Hg in sediment, water, 

and fish, sampling sites from the following five study basins had the greatest Hg contamination: Nevada Basin and 

Range, South Florida Basin, Sacramento River Basin (California), Santee River Basin and Coastal Drainages 

(South Carolina), and the Long Island and New Jersey Coastal Drainages. A sampling and analysis strategy based 

on this pilot study is planned for all USGS NAWQA study units over the next decade. 

Key Words: Mercury, methylmercury, bioaccumulation, fish, water, sediment 

Suggested Citation: 

Brumbaugh, W. G., Krabbenhoft, D. P., Helsel, D. R., Wiener, J. G., and Echols, K. R., 2001, A National Pilot 

Study of Mecury Contamination of Aquatic Ecosystems Along Multiple Gradients: Bioaccumulation in Fish, 

USGS/BRD/BSR–2001-0009, iii + 25 pp. 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 2

INTRODUCTION 

Methylmercury (MeHg) is a potent neurotoxin that 

is among the most widespread contaminants affecting 

our Nation’s aquatic ecosystems. Human fishconsumption advisories for Hg in fish have been issued 

in more than 40 states and account for more than eighty 

percent of all such advisories in the Nation (USEPA, 

1998). While the threat to humans is very real, there is 

potentially a more serious threat to piscivorous wildlife, 

which consume relatively large quanitities of fish 

(Wiener and Spry, 1995). In Part One of this study 

(Krabbenhoft and others, 1999), Hg methylation efficiency was evaluated in sediment and water from 

watersheds that were sampled concurrently with the 

fish described by this report. Among other findings, 

MeHg production efficiency was highest in Eastern 

coastal basins containing high wetland densities. 

Nationwide, MeHg production was highest in subbasins characterized as mixed agriculture and forested. 

In this report, relationships among Hg and MeHg in 

sediment and water are compared with bioaccumulation 

in fish axial muscle (the dominant repository for MeHg 

in fish) for 20 basins nationwide. The importance of 

total Hg load, methylation efficiency, MeHg in sediments and water, and selected watershed characteristics 

in determining the bioaccumulation of Hg in fish is 

assessed. 

The USGS National Mercury Pilot Study 

This study was conducted jointly by the National 

Water Quality Assessment (NAWQA) program, Toxic 

Substances Hydrology program, Wisconsin District 

Mercury Laboratory (WDML), and Columbia 

Environmental Research Center (CERC) of the U.S. 

Geological Survey. The overall objective was to identify ecosystem characteristics that favor the production 

and bioaccumulation of MeHg and to compare bioaccumulation rates on a national basis. Bioaccumulation of 

Hg in fish is a complex function of total Hg load, 

methylation efficiency, fish size, and the food chain 

dynamics in a given water body (Kidd and others, 

1995). Consequently, aquatic ecosystems with high 

loads may have only moderate bioaccumulation in fish 

if methylation efficiency is low and conversely, significant bioaccumulation may result when loading is low if 

methylation efficiency is high. Regional- and nationalscale fish surveys have been conducted in the past for 

Hg and other bioaccumulative contaminants. However, 

this is the first national-scale study in which water, 

sediment, and fish were sampled together with lowlevel Hg speciation analysis. 

EXPERIMENTAL SECTION 

Study Design 

The major design characterics of this study were (1) 

national scope, (2) sampling of water, sediment, and 

predator fish muscle, (3) consistent use of ultra-trace 

clean sampling methods, (4) ultra-trace total and 

methyl-mercury analytical procedures, and (5) analysis 

of all routine water and sediment quality parameters. 

Sampling was conducted from June to October, 1998 at 

3 to 8 sites from 20 of the 59 study units (front cover 

and Table 1) of the USGS NAWQA program 

(http://water.usgs.gov/nawqa). Nationally, these basins 

span the dominant east-to-west mercury deposition gradient (USEPA, 1997) and represent a wide range of 

environmental settings. Individual study basin teams 

were asked to choose sites within a basin which 

spanned gradients of wetland density, surface water pH, 

sulfate, total organic carbon, and suspected or known 

Hg loading. Most sampling sites were on streams. 

Some of the sites had high Hg loading from known Hg 

point sources. 

Field crews were asked to focus on largemouth bass 

(Micropterus salmoides) or other black bass 

(Micropterus sp.) of age 3 years (estimated from 

regional growth rate data, when available) and to collect five individuals per site for compositing. Although 

collection objectives were not always met, all fish samples submitted were analyzed. In some cases, fish were 

analyzed individually to avoid creating composites of 

multiple species or ages. Axial muscle (fillet) was targeted for Hg analysis because it is generally the dominant and most stable repository in fish (Goldstein and 

others, 1996). Only total Hg was determined in the fish 

because virtually all of the Hg in the fillet is present as 

MeHg (Bloom, 1992). Black bass were targeted as 

ubiquitous predator fish which could facilitate interbasin comparisons. Also, they might be expected to 

correlate well with localized sediment and water conditions because they normally inhabit relatively small 

ranges as compared to nomadic predators such as walleye (Stizostedion vitreum) or white bass (Morone 

chrysops), (Carlander, 1977). However, if black bass 

species were expected to be absent at one or more sites 

within a basin, samplers were advised to collect a predator species common to the entire basin so that gradients within each basin could be examined. 

Age-3 fish were targeted because: (1) they should 

be relatively plentiful and of reasonable size for sampling fillets, (2) differences in Hg accumulation 

between males and females of the same size should be 

small, i.e., sexual growth dimorphism for largemouth 

bass is reportedly minimal up to this age (Lange and 
3 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009 

Table 1. Basins, number of sites, and number of fish samples analyzed. 

Abbrev. Study Basin Name no. sites no. samplesa

ACAD Acadian-Ponchartrain Basin 5 5 

ALMN Allegheny and Monongahela River Basins 5 6 

COOK Cook Inlet Basin (Alaska) 4 6 

DELR Delaware River Basin 9 12 

GRSL Great Salt Lake Basins 2 4 

LINJ Long Island and N.J. Coast Drainages 4 13 

LTEN Lower Tennessee River Basin 3 8 

MIAM Miami River Basin (Ohio) 7 13 

MOBL Mobile River and Tributaries 7 15 

NECB New England Coastal Basin 5 5 

NROK Northern Rockies Intermontane Basins 2 2 

NVBR Nevada Basin and Range 1 8 

OAHU Oahu Island 6 6 

SACR Sacramento River Basin 5 11 

SANA Santa Ana River Basin 4 4 

SANT Santee River Basin and Coastal Drainages 5 5 

SOFL South Florida Basin 2 6 

TRIN Trinity River Basin 5 18 

UIRB Upper Illinois River Basin 5 6 

YELL Yellowstone River Basin 5 6 a Samples per basin, each consisting of either a homogenized composite or an individual depending on size and species 

submitted. 

others, 1994) and (3) age-3 fish should be old enough 

to exhibit significant bioaccumulation of Hg. Older 

fish generally bioaccumulate higher concentrations of 

Hg but would be more difficult to capture in a consistent age class. Also, concentrations of Hg in older fish 

might be less representative of recent conditions contributing to the observed concentrations of Hg in the 

sediment and water. 

Sample Collection and Preparation 

Sampling and analysis of sediment and water was 

described in Part One of this study (Krabbenhoft and 

others, 1999). Of note, surface water was not filtered 

and sediments were taken from the top 2 to 4 cm. 

Ultra-trace protocols were followed for the sampling of 

water for Hg. Fish samples were collected by the most 

efficient means available, usually by electroshocking or 

gill-netting. Each fish was rinsed in stream water, 

measured for length and weight, double bagged in zipseal plastic, and placed on dry ice as soon as possible. 

Samples from the ACAD and SANT basins were filleted by field crews, who also determined the ages of their 

specimens. Most samples were shipped within 48 

hours of collection, but some were stored frozen for 1 

to 2 weeks before shipment. Once received by CERC, 

they were stored at –20 °C for 3 to 6 months before the 

fillets were prepared for analysis. 

Before removing fillets, individual fish from each 

site were thawed at room temperature for 1 to 2 hours, 

depending on size. Several scales were removed from 

behind the gill cover for aging. Each fish was then 

rinsed with laboratory-grade deionized (DI) water ( > 

10 Mohm-cm) and placed on a polypropylene cutting 

board situated in a polypropylene bin. Fillet knives 

with either ceramic (ZrO) or titanium-aluminum alloy 

(for larger fish) blades were used to remove a skinless, 

boneless (belly flap removed) fillet from the left side of 

each specimen. Each fillet (including those removed 

by field crews) was chopped into 2-cm square sections, 

placed in a heavy-duty polyethylene zip-seal freezer 

bag, rinsed twice with ultra-pure (UP) water (18 

Mohm-cm), drained thoroughly and returned to the 

freezer. Between samples, the knife and cutting board 

were scrubbed with tap water and detergent, then rinsed 

with DI water, 1% (v/v) ultra-pure nitric acid, and 

HPLC-grade methanol. Equipment and cleaning procedures used for the few samples filleted by field crews 

were not necessarily as described above. However, we 

assume that potential surface contamination of all fillets 

was minimized by rinsing twice with UP water before 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 4

analysis. 

For each site, fillets of the same species were composited for all fish of a similar size (assumed to be of 

similar age). However, for many sites the sampled fish 

varied greatly in size and apparent age, consequently 

some individuals were analyzed separately to avoid 

compositing fish of differing ages. For a few sites, the 

fish collected were too small (< 50 g) to conveniently 

remove a fillet; these specimens were chopped and 

processed either whole or whole, less heads. After all 

samples were filleted, the frozen muscle sections were 

placed into an acid-washed borosilicate glass jar and 

lyophilized (freeze-dried) to a constant dry weight at -

5°C with a vacuum of about 100 mtorr. Lyophilization 

facilitates sample manipulation and storage but does 

not cause loss of biologically-incorporated Hg from tissue (LaFleur, 1973; Lasorsa and Allen-Gil, 1995). The 

dry product was briefly blended with a hand-held highspeed bio-homogenizer having a polystyrene bowl fitted with a stainless steel cutting blade. The base and 

blade assembly were washed between samples with 

detergent and hot water, rinsed with UP water, and 

dried with filtered compressed air. A representative 

portion of each homogenate was immediately transferred to a borosilicate glass vial fitted with a telfonlined cap for storage in a desiccator. 

Hg Determination 

Tissue samples were digested before determination 

of Hg with microwave heating in sealable tetra-fluorinated ethylene (TFE) pressure vessels. Five mL of 

HNO3 and 0.5 mL of HCl (each sub-boiled in quartz 

and stored in a TFE bottle) were added to a 0.5-g dry 

tissue sample and the vessel was sealed and placed 

overnight in a water bath at 70°C. The vessel was 

cooled, vented, then heated with a 3-step microwave 

program. After cooling, 1 mL of ultra-pure 30% H202 

was added, the vessel was sealed, and the 3-step heating program was repeated. The vessel was again 

cooled and the liquid contents were quantitatively 

transferred and diluted to 100 mL with 1% (v/v) HCl in 

an acid-cleaned polyethylene bottle. After briefly mixing, a 30-mL portion of the digestate was immediately 

transferred to a borosilicate glass tube and capped until 

analysis. 

Analysis for Hg was conducted by cold-vapor atomic absorption spectrophotometry with flow injection 

sample introduction and stannous chloride reduction. 

Standards used for calibration included solutions containing 0.0, 5.0, 10.0, and 20.0 ng Hg/mL. Quality 

assurance samples analyzed included method (digestion) blanks, reference tissues, replicate samples, predigestion spikes (MeHg), post-digestion spikes (Hg2+), 

and calibration and blank verification solutions. 

Sample results were blank-corrected based on the mean 

of three method blanks processed with each digestion 

set. 

Age Determination 

Age was estimated by scale analysis (Jearld, 1983) 

except for fish from SOFL and ACAD study units, for 

which sagittal otiliths were analysed (Porak and others, 

1988). Scales were soaked in 70% ethanol to clean 

debris, increase transparency and soften them for flattening. Annuli were determined by two separate readers with the aid of a microfiche reader. A third reader 

was used in the case of discrepancies. All scale samples (about 10 per fish) were examined for each fish; 

the scale with the clearest markings was then used by 

all readers. Because samples were collected in late 

summer and fall, numerical ages of individuals that 

were spring spawners were assigned increments of 0.5 

yr, whereas fall spawners (e.g., Salmonidae) were 

assigned increments of whole years. For example, a 

largemouth bass determined to be age-0 or age-1 was 

assigned a value of 0.5 or 1.5 yr, respectively. Due to 

resource limitations, not all individuals for composite 

samples were aged. Rather, the average for two representative individuals was used to estimate the age for 

each composite. Consequently, the age assigned for 

each composite was either a whole number or an increment of 0.5. 

Statistical Analysis and Modelling 

Linear regression and correlation analysis was conducted using the following variables: Hg concentration 

(μg/g wet wt.) in fish (Hgfish), fish age (yr), fish length 

(m), fish weight (kg), methylmercury concentration 

(ng/g dry wt.) in sediment (MeHgsed), total mercury 

concentration (ng/g dry wt.) in sediment (HgTotsed), 

methylmercury concentration (ng/L) in water 

(MeHgwater), total mercury concentration (ng/L) in 

water (HgTotwater), percent methyl mercury in 

sediment, acid-volatile sulfide (AVS) in sediment 

(μmol/g dry wt.), sediment percent loss on ignition 

(LOI - an estimate of organic matter), dissolved organic 

carbon (DOC) in water (mg/L), sulfate concentration in 

water (watsulf), water pH (watpH), and % wetlands (of 

basin). We examined both Hgfish and Hgfish divided by 

weight, length, or age, as the dependent variable. 

Statistical analysis did not include results for fish determined to be less than one year of age, nor the results 

from the NBVR basin because of the extraordinarily 

high concentrations. For the multiple regression, residuals and partial plots were used to determine whether 

transformations were needed to meet the assumptions 
5 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

of a good regression model (Helsel and Hirsch, 1992). 

The natural logarithm was used for Hgfish, MeHgwater, 

HgTotwater, HgTotsed, and MeHgsed, and a cube root 

transformation for AVS, to obtain approximately normally-distributed residuals with constant variance. 

Several reasonable candidate regression models were 

selected using the adjusted R2 (coefficient of determination) statistic. From this list, the one with the best predictive power (lowest PRESS statistic) was chosen. 

For principal components analysis (PCA), all data were 

processed using SIMCA-P (ver 8.0, Umetrics AB). The 

models and principal components were evaluated using 

pattern recognition of score (sample) plots and loading 

(variable) plots. As with the regression models, NVBR 

data was excluded from the analysis. Additionally, a 

subset consisting of sites where largemouth bass 

(LMB) were collected was modeled and evaluated in 

the same manner as the complete data set. For PCA 

only, the full data set and the LMB subset were also 

analyzed with the three size variables (age, length, 

weight) excluded so that influences of the remaining 

independent variables on Hgfish could be more clearly 

examined. 

Quality Assurance 

Quality control results for the fish determinations of 

Hg were as follows: recovery of pre-digestion spikes 

of MeHg averaged 102.3 % (s.d. 4.2, n = 16); mean 

recovery for post digestion spikes of Hg2+ was 98.5 % 

(s.d. 5.1, n = 25). The measured values for three reference fish samples were in good agreement with certified or control ranges (Table 2). Precision for triplicate 

determinations (including digestion and analysis) averaged 2.6 % relative standard deviation (RSD) and 

ranged from 0.6 to 7.5% RSD (n = 8). The method 

detection limit, calculated for each of the three digestion blocks based on three times the pooled standard 

deviation of the method blanks (three per block) and a 

low-level sample analyzed in triplicate, ranged from 

0.004 to 0.020 μg/g wet wt. Overall, eight of the nine 

method blanks were near or below the instrument 

detection limit (about 0.05 μg/L). The one elevated 

blank (0.3 μg/L) resulted in a higher reporting method 

detection limit (0.020 μg/g wet wt.) for samples determined in the same digestion block. However, virtually 

all sample concentrations were considerably above this 

highest blank. Consequently, the potential error associated with this worst-case blank was relatively small and 

it would affect the accuracy of only the very lowest 

sample concentrations. Overall, the results for quality 

assurance samples indicated good accuracy and precision for the study samples. 

RESULTS AND DISCUSSION 

Complete sample site information, species, weights, 

lengths, ages, and mercury concentrations in fish samples are listed in the Appendix; summary statistics are 

given in Table 3. For fish greater than 0.5 yr in age, the 

arithmetic means for total length, weight, and age were 

as follows: all species – 260 mm, 324 g, 3.2 yr; largemouth bass – 280 mm, 420 g, 3.2 yr; smallmouth bass 

– 261 mm, 299 g, 3.2 yr. For all fish samples (n = 159) 

the following statistics for Hg concentration (μg/g wet 

wt.) were obtained: arithmetic mean, 0.478; geometric 

mean, 0.218; median, 0.206; minimum, 0.018; maximum, 5.84. For largemouth bass (n = 50) these same 

statistics were 0.510, 0.329, 0.292, 0.045 and 4.22; for 

smallmouth bass (n = 37) the values were 0.244, 0.195, 

0.205, 0.042 and 1.05, respectively. In comparison, the 

nationwide geometric mean for 27 largemouth bass 

composites sampled as part of the 1984 National 

Contaminant Biomonitoring Program (NCBP, Schmitt 

and Brumbaugh, 1990) is estimated at 0.31 μg/g wet 

weight for the fillet based on a conversion equation 

from whole fish (Goldstein and others, 1996). Thus, in 

general the national mean concentration of Hg in largemouth bass from our study (0.33) is similar to samples 

collected 15 years previously for the NCBP. Of course, 

this comparison does not account for possible 

differences in age or size of the samples, or differences 

in watershed coverage. 

Table 2. Measured mercury concentrations (μg/g dry wt.) for fish reference tissues (n =3 for each). 

MATERIAL Fish Matrix Measured Certified or

I. D. (Common Name) Mean (std.dev.) Control Range

CERC STB Whole Striped Bass 2.21 (0.01) 2.26 + 0.51

NIST RM-50 Albacore Tuna Fillet 0.99 (0.04) 0.95 + 0.10

NRCC Dorm-1 Dogfish Fillet 0.90 (0.06) 0.80 + 0.07
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 6 

Table 3. Summary statistics for mercury concentrations (μg/g wet wt.) in fish fillet samples. 

Statistic All Samples Largemouth Bass Smallmouth Bass 

(n = 159) (n = 50) (n = 37) 

Mean 0.478 0.510 0.244 

Median 0.206 0.292 0.205 

Geometric Mean 0.218 0.329 0.194 

Minimum 0.018 0.045 0.042 

Maximum 5.84 4.22 1.05 

Mean Fish Concentration by Basin 

The geometric means of fish Hg concentrations for 

each of the 20 study unit basins are presented in Figure 

1. Because Hg concentrations in fish from a given 

body of water are usually a function of size or age 

(Wiener and others, 1990, Lange and others, 1994) and 

various sizes and species of fish were collected, the 

geometric means for the Hg concentrations normalized 

(divided) by weight, length, and age are also presented 

in Table 4. All age-0 fish (n = 7) were excluded for 

this comparison due to the high relative uncertainty 

associated with the assignment of a fractional age of 

less than one. For comparing Hg in fish between 

waterbodies, it would be preferable to conduct an 

analysis of covariance between concentration and size 

and adjust each treatment (site) mean to a uniform size 

variable (Sorenson and others, 1990; Lange and others, 

1993). However, for most of our sites we had insufficient observations for this approach. As indicated in 

Table 4, NVBR, SOFL, SANT, and SACR basins consistently ranked high by any of four measures of Hg 

bioaccumulation in fish. The YELL, ACAD, NECB, 

and LINJ basins also ranked high or moderately high 

by these measures. The extraordinarily high concentration for NVBR fish compared with the other basins 

(Figure 1) is striking. Indeed, sections of the Carson 

River Basin are reported to be among the most severely 

Hg-contaminated in the world (Bonzongo and others, 

1996). However, our data from this basin as a whole 

are greatly skewed relative to the other basins because 

all samples came from one severely contaminated site 

(Lahontan Reservoir). Similarly, fish samples from the 

SOFL unit were limited to two rather contaminated 

sites, which probably yielded a somewhat elevated 

mean for that study unit basin, although Hg contamination there is widespread. Means among the other 18 

basins varied by a factor of about 20. The wide variety 

of fish species that were sampled probably factored into 

this range. Whereas over 65% of our samples were 

either largemouth-, smallmouth-, spotted-, or white 

bass, at least 16 other species were also represented. 

Also, sampling sites were selected to represent a gradient of environmental conditions and Hg levels, but they 

do not necessarily represent a systematic coverage of 

each entire basin. Nevertheless, the rankings listed in 

Table 4 give a reasonable guide as to the relative Hg 

contamination in fish among the basins sampled. 

Ranking of basins for fish concentrations normalized by either length or age tended to mirror the rankings for non-adjusted concentrations. However, normalization by weight yielded some differences in rankings when compared to rankings by other means. For 

example, fish from the NECB and COOK study units 

ranked much higher for weight-normalized data as 

compared to length- or age-normalized data. However, 

samples from each of these two study units were quite 

small in size and were of a species that was uncommon 

for the data set (mixed sunfish and dolly varden, 

respectively). Also, the fillet data for some of the samples from these two study units were actually estimated 

from whole-body analysis based on a conversion equation derived from larger species (Goldstein and others, 

1996). In the case of length-adjusted data, the largest 

specimens might have been favored due to the fact that 

as most fish age they have diminished increases in 

length relative to weight (Carlander, 1977). On the 

other hand, normalization by weight may have favored 

fish samples that were very small because regression 

equations for Hg concentration with fish weight tend to 

have a higher positive y-intercept for Hg contaminated 

systems relative to length-normalized data (Lange and 

others, 1994). These combined factors might explain 

why small sunfish from the NECB ranked highest by 

the weight-normalized criteria, but ranked fourth or 

lower by other measures (Table 4). Regardless of the 

fish ranking method chosen, the MeHg concentrations 
7 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

NVBR*

SOFL

SANT

SACR

YELL

ACAD

LINJ

DELR

NECB

LTEN

MIAM

TRIN

ALMN

MOBL

GRSL

SANA

NROK

UIRB

COOK

OAHU

Hgfish (geom. mean)

Figure 1. Geometric mean of Hg concentration in fish fillet samples collected for each of the 20 basins. *Samples from NVBR represent only one site (Lahontan Reservoir). 

in both the sediment and water from the NECB basin 

were relatively high (Krabbenhoft and others, 1999), 

therefore, a high ranking for the fish is not surprising. 

But the comparison of bioaccumulation for NECB samples with the other basins must be viewed with caution 

because sunfish do not bioaccumulate Hg as rapidly as 

larger predator species and the fillet concentrations 

were estimated from the whole body measurements. In 

any event, a statewide Hg advisory is presently in effect 

for Massachusetts (where all of the NECB samples 

were collected). 

Basins of Concern for Human Health 

Our study was not designed to address the safety of 

consuming fish from the various participating study 

units, or to assess Hg exposure risks to fish and 

wildlife. Most, if not all of the basins of concern have 

already been identified by state and other federal agencies. Assessing the toxicological significance of Hg 

concentrations in fish with respect to populations of 

fish and fish-consuming wildlife is a complex matter 

that would be difficult to address from our data considering the the limited number of samples collected for 

each basin. Sensitivity to MeHg exposure can vary 

greatly among species and the rate of accumulation in 

fish apparently affects the toxicity (Wiener and Spry, 

1996). Furthermore, the concentration of Hg in tissues 

other than the axial muscle, such as the brain or in the 

eggs, would generally be more useful for assessing 

potential impacts on fish (Wiener and Spry, 1996), 

whereas whole-body concentrations might be more 

meaningful for assessing impacts to piscivorous waterfowl and mammals (Wolfe and others, 1998). In order 

to address human health risks from fish consumption, 

we would have targeted fish older than 3 years, which 

typically contain higher concentrations of Hg and are 

more commonly sought by anglers. But because 

human health issues invariably arise when nation-wide 

fish residue data is examined, this aspect is briefly 

addressed. 

Fish from our study that had Hg concentrations 

above 0.50 μg/g wet weight are listed in Table 5. 

Historically, 0.50 μg/g was a commonly reported 

human health advisory Hg fish concentration applicable 

to consumers of “high risk” categories, e.g., children, 

expectant mothers, and sub-populations whose diets 

include large percentages of fish (U.S. EPA, 1998). 

Recently, the U.S. EPA reduced the human health Hg 

fish criteria to 0.30 μg/g wet weight (U.S. EPA, 2001). 

Our results document that Hg contamination in U.S. 

freshwater fish is a widespread problem. One or more 

samples from nine of the 20 basins exceeded the 0.50 

ug/g wet weight criteria and 15 of the basins had at 

least one sample above the 0.30 criteria. State fish 
----- 

USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 8 

Table 4. Ranking of basins by geometric mean mercury concentration of fish fillet (μg/g wet wt) : unadjusted, 

or normalized by age, length, and weight. 

Rank

Basin and geometric mean concentration (μg/g wet)

a 

unadjusted ÷ age (yr)b ÷ length (m) ÷ weight (kg) 

1 NVBRc

 (3.34) NVBRc (0.86) NVBRc (9.2) NECBd (8.7) 

2 SOFL (0.95) SOFL (0.30) SOFL (3.1) NVBR (4.8) 

3 SANT (0.70) SACR (0.15) SANT (2.6) SOFL (2.6) 

4 SACR (0.46) NECBd

 (0.12) NECBd (2.3) LINJ (2.5) 

5 YELL (0.44) YELL (0.12) SACR (1.5) SANT (2.2) 

6 ACAD (0.39) ACAD (0.12) ACAD (1.5) COOKe

 (2.1) 

7 LINJ (0.29) LINJ (0.12) LINJ (1.3) LTEN (1.7) 

8 DELR (0.26) LTEN (0.10) YELL (1.2) ACAD (1.5) 

9 NECBd

 (0.25) DELR (0.08) LTEN (1.1) SANA (1.2) 

10 LTEN (0.24) ALMN (0.06) DELR (0.9) SACR (1.1) 

11 MIAM (0.17) SANA (0.06) COOKe

 (0.8) DELR (0.9) 

12 TRIN (0.17) MIAM (0.05) MIAM (0.7) MOBL (0.9) 

13 ALMN (0.17) TRIN (0.05) SANA (0.7) YELL (0.8) 

14 MOBL (0.15) MOBL (0.05) TRIN (0.6) MIAM (0.8) 

15 GRSL (0.13) GRSL (0.04) ALMN (0.6) UIRB (0.8) 

16 SANA (0.12) UIRB (0.04) MOBL (0.6) TRIN (0.6) 

17 NROK (0.12) NROK (0.03) UIRB (0.5) ALMN (0.6) 

18 UIRB (0.10) COOKe

 (0.03) GRSL (0.4) GRSL (0.4) 

19 COOKe

 (0.07) OAHU (0.01) NROK (0.4) NROK (0.3) 

20 OAHU (0.03) OAHU (0.2) OAHU (0.2) 

a Excludes age-0 fish.
 b No age data available for SANT.
 c All samples from one site (Lahanton Reservoir). 
 d Estimate for fillet based on log [muscle] = 0.35 + 0.92*log[whole body] (Goldstein and others, 1996). 
 e

Dolly varden only; fillet concentration estimated for 2 of 3 samples. 


consumption advisories for Hg are currently in effect 

for most sites in the nine basins that exceeded the 0.50 

criteria; exceptions include the SACR, MIAM, and 

MOBL basins. In addition, five states not included in 

our study (VT, MI, NH, IN, MO) currently have 

statewide advisories in effect for consumption of one or 

more species of freshwater fish due to Hg. Two other 

states not covered (MN and WI) have Hg advisories on 

a large number of water bodies. 

Sources and Factors Enhancing 

Bioaccumulation of Hg in Fish 

Among the primary basins of concern, the geographic and land-use categories varied greatly for the 

sub-basins from which fish above advisory concentrations were sampled. However, fish from our study with 

concentrations above 0.50 μg/g were most commonly 

from coastal or lowland primary basins, e.g. SOFL, 

SANT, LINJ, ACAD, SACR, MOBL. Presumably, the 

relatively high percentages of wetlands in these lowland basins enhance methylation rates and in turn, 

bioaccumulation rates of Hg in fish (St. Louis and others, 1994; Hurley, 1995: Krabbenhoft and others, 

1999). The sources of Hg among these basins varies 

widely. 

In the NVBR and SACR basins, nearby cinnabar 

(HgS) deposits and elemental Hg in streambeds resulting from past gold mining amalgamation practices continue to contribute to elevated Hg concentrations in fish 

(Bonzango and others, 1996; Domagalski, 1998). In 

the YELL basin, elevated Hg concentrations in reservoir fish have been associated with coal and phosphate 

deposits of Wyoming and Montana (May and 

McKinney, 1981). In a detailed study of that basin, it 

was concluded that elevated Hg in reservoir fish resulted primarily from weathering of soils and rocks 

upstream and that reservoirs furthest upstream 
--

--

--

--

--

9 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

Table 5. Fish samples with Hg fillet concentrations greater than 0.50 μg/g wet wt (-- = no data). 

Mean

Wet Hg conc. a Study Weight μg/g wet Advisory

Unit Site Name Species (no. of indiv.) (g) wt. In Effect?

NVBR Lahontan Reservoir, NV White Bass (8) 694 3.36 Yes

SACR Sacramento Slough nr. Knights Largemouth Bass (1) 1471 2.17 Nob

Landing, CA

SOFL Water Conservation District 3A15, FL Largemouth Bass (3) 788 2.15 Yes

SANT N. Fork Edisto R. nr. Fairview Largemouth Bass (1) 907 1.82 Yes

Crossroad, SC

SACR Bear River @ Hwy 70, CA Largemouth Bass (1) 518 1.21 Nob

SACR Bear River @ Hwy 70, CA Smallmouth Bass (1) 467 1.10 Nob

LINJ Great Egg Harbor @ Sicklerville, NJ Chain Pickerel (2) 172 0.91 Yesc

ACAD Bogue Falaya R. @ Covington, LA Largemouth Bass (8) 0.83 Yesd

ACAD Tangipahoa R. @ Robert, LA Largemouth Bass (8) 0.77 Yesd

YELL Shoshone River, @ mouth nr. Kane, Walleye (5) 817 0.70 Yes

WY

YELL Bighorn Lake @ Hwy14A, WY Walleye (5) 896 0.68 Yese

YELL Bighorn River nr. Kane, WY Walleye (5) 452 0.66 No

YELL Shoshone River @ mouth nr. Kane, Walleye (1) 1444 0.66 No

WY

SACR Sacramento Slough nr. Knights

Landing, CA

Largemouth Bass (1) 1156 0.65 No

MOBL Satilpa Creek nr. Coffeeville, AL Spotted Bass (2) 140 0.65 No

LINJ Great Egg Harbor @ Sicklerville, NJ Largemouth Bass (1) 49 0.65 Yes

SANT N. Fork Edisto River nr. Branchville, Largemouth Bass (1) 0.63 Yes

SC

MOBL Satilpa Creek nr. Coffeeville, AL Largemouth Bass (1) 92 0.62 No

LINJ Great Egg Harbor @ Sicklerville, NJ Chain Pickerel (5) 84 0.59 Yes

SANT S. Fork Edisto River @ Springfield, Largemouth Bass (1) 0.58 Yes

SC

SANT S. Fork Edisto River nr. Canaan, SC Largemouth Bass (1) 0.55 Yes

SOFL Water Conservation District U3 Largemouth Bass (3) 254 0.55 Yes

SACR Bear River @ Hwy 70, CA Smallmouth Bass (1) 150 0.54 Nob

MIAM E. Fork L. Miami R. nr Williamsburg, Smallmouth Bass (1) 608 0.51 No

OH

a

Source: USEPA, 1998 b

Advisory by state of California pending (J. Domagalaski, pers. commun., April 1999) c

Statewide advisory for bass and pickerel in New Jersey. d Statewide monitoring program for Hg in fish currently in progress. e

Advisory in effect for state of Montana but not Wyoming (April 1999).
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 10

exhibited higher bioaccumulation rates because of 

greater susceptibility to flood events (Phillips and others, 1984). Flooding results in greater scouring of Hg 

from soils but more importantly methylation of waterborne Hg is enhanced when terrestial vegetation is 

inundated for extended periods of time (which increases the dissolved organic carbon in the water) as is the 

case when new reservoirs are filled (Bodaly and others, 

1997). 

There may be localized point sources of Hg in the 

ACAD basin associated with Hg-charged manometers 

used with natural gas wells; however, this is primarily a 

problem in northeast Louisiana (Facemire and others, 

1995). The state of Louisiana and the USGS have been 

engaged in a statewide assessment of Hg contamination 

in fish since 1993 (Louisiana Department of 

Environmental Quality, 1999). Selected water bodies 

in the SANT and MOBL basins may still be impacted 

by past uses of mercury in the chloralkali and paper 

mill industries (May and McKinney, 1981). However, 

widespread elevation of Hg in fish from the SANT 

basin has generally not been traceable to specific industrial or wastewater discharges (South Carolina 

Department of Health and Environmental Control, 

1999). 

Overlaying the numerous point sources is a broader 

contribution from atmospheric deposition of mercury 

originating primarily from emissions associated with 

waste incineration and coal combustion (Hanisch, 

1998). Atmospheric deposition rates of mercury are 

generally greatest in Florida and the northeastern U.S. 

(USEPA, 1997). However, many lakes in the upper 

Midwest have also apparently been affected by atmospheric deposition and those with low buffering capacity 

(and depressed pH) are likely to have high Hg accumulations in fish (Sorenson and others, 1990; Wiener and 

others, 1990). There is currently debate as to how 

localized the effects of atmospheric deposition of Hg 

are with respect to the emission sources and ultimately, 

if proposed U.S. atmospheric emission controls for Hg 

would be effective in reducing Hg burdens in fish 

(Hanisch, 1998). An index of atmospheric Hg accumulation (AHA) developed in part one of this study indicated that among the study units examined, the NVBR, 

NROK, GRSL, COOK, and SACR basins are most 

influenced by ground-based Hg sources, whereas the 

ALMN, DELR, LINJ, SANT, and SOFL basins are 

most influenced by atmospheric sources of Hg. 

Ranking of Basins by Hg in Fish, Sediment, 

and Water 

The six basins with the greatest contamination, as 

determined by ranking of individual sites for selected 

fish, sediment, and water Hg measures, are presented in 

Table 6. Only the highest ranking site from each study 

unit was considered for this comparison, i.e., for some 

criteria multiple sites from one study unit may have 

ranked above sites from other study units, but only one 

site from each study unit is presented. The seven Hg 

criteria evaluated included 1) concentration (μg/g wet) 

of Hg in fish (Hgfish), 2) Hgfish divided by fish age (yr), 

3) Hgfish divided by fish length (m), 4) methylmercury 

concentration (ng/g dry wt.) in sediment (MeHgsed), 5) 

total mercury concentration (ng/g dry wt.) in sediment 

(HgTotsed ), 6) methylmercury concentration (ng/L) in 

water (MeHgwater), and 7) total mercury concentration 

(ng/L) in water (HgTotwater). For the ranking of sites 

based on Hgfish normalized by age, age-0 fish (n = 7) 

were excluded due to the large relative error in asssigning a fractional age. 

Based on the three fish criteria the following study 

units had samples that ranked at least twice in the top 

six: NVBR, SOFL, SACR, LINJ, and SANT (Table 6). 

Basins with sites ranking once in the top six included 

ACAD, YELL, MOBL, and NECB. Study unit basins 

having a site that ranked in the top six for both 

sediment and fish criteria included NVBR, SOFL, 

NECB, SANT, and LINJ. Conversely, basins with a 

site in the top six for sediment criteria but not for fish 

included: GRSL, COOK, and OAHU. The NROK 

basin contained a sampling site that was among the 

highest for HgTot and MeHg in sediment (S. Fork 

Coeur d’Alene R), but fish were not collected there 

because impacts of mining activity has made them 

scarce. Despite relatively high HgTot and MeHg in 

sediments at the Weber R. (GRSL) site, mountain 

whitefish (Prosopium williamsoni) collected there were 

below the median Hg concentration (0.206) for all samples in this study. However, this species feeds primarily on aquatic insects (Carlander, 1977) and therefore 

may not bioaccumulate Hg as rapidly as piscivorous 

fishes. The Deshka R. (COOK) and Lake Wilson 

(OAHU) sites were notable because despite having elevated concentrations of Hg in the sediments, each was 

among the very lowest for the concentration of Hg in 

fish (albeit for sculpin and tilapia, respectively). The 

Deshka R. site had an unusually high concentration of 

MeHg in the sediment (5.1 ng/g) considering the HgTot 

was only 21 ng/g, whereas sediment from the Lake 

Wilson site was relatively high in HgTot but only moderate in MeHg. 

Basins having a site ranking high for Hg in water as 

well as for fish included NVBR, SOFL, SANT, SACR, 

and LINJ. Essentially all of the highest ranking sites 

for MeHgwater also ranked high for Hgfish. However, 
11 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

Table 6. Top six study units based on ranking of individual sites according to various Hg criteria. Values for fish are means of up to 7 

individuals; sediment and water data are single samples from each site. Only the highest site from each study unit was considered in 

the overall rankings for each criteria. 

Criteria #1 #2 #3 #4 #5 #6

1. Hgfish NVBR SOFL SACR SANT LINJ ACAD

(ug/g wet wt.) 3.36 2.15 1.80 1.80 0.82 0.79

Site Lahontan Res. WC3-A15 Sacramento Sl. N.Fk. Edisto R. Gr. Egg Hbr. Bogue Falaya R.

2. Hgfish/ agea NVBR SOFL SACR LINJ YELL MOBL

(ug/g wet / yr) 0.86 0.66 0.40 0.38 0.25 0.22

Site Lahontan Res. WC3-A15 Sacramento Sl. Gr. Egg Hbr. Big Horn R. Satilpa Cr.

3. Hgfish/ length NVBR SOFL SANT LINJ SACR NECB

(ug/g wet / m) 9.2 6.0 4.4 3.9 3.6 3.1

Site Lahontan Res. WC3-A15 N. Fk. Edisto R. Gr. Egg Hbr. Sacramento Sl. Ipswich R.

4. MeHgsed LINJ NECB NROK SOFL SANT COOK

(ng/g) 10.9 9.9 8.2 7.8 6.8 5.1

Site Swan R. Ipswich R. Coeur d’ Alene R. WC3-A15 N. Fk. Edisto Deshka R.

R.

5. HgTotsed NROK NVBR NECB GRSL OAHU SOFL

(ng/g) 4520 4130 b 2480 1040 300 288

Site Coeur d’ Alene R. Carson R. Neponset R. Weber R. Lake Wilson WC3-A15

6. MeHgwater SANT NVBR SOFL ACAD NECB LINJ

(ng/L) 1.5 1.3 b 0.61 0.46 0.44 0.34

Site N. Fk. Edisto R. Carson R. WC2-U3 Bayou Lacassine Ipswich R. Gr. Egg Hbr.

7. HgTotwater NVBR OAHU GRSL SACR SANA LINJ

(ng/L) 656b 24 22 18 15 12

Site Carson R. Nuuanu Res. Weber R. Bear R. Santa Ana R. Gr. Egg Hbr.

a

excludes age-0 fish due to high relative error in assigning fractional age. No age data

available for SANT unit. b

based on average of sites immediately above and belowLahontan Reservoir.

three basins had sites that ranked high for HgTotwater 

but not for Hgfish. These included OAHU (Nuunanu 

Res.), SANA (Santa Ana R.), and GRSL (Weber R.). 

Correlation of Water and Sediment 

Parameters with Hg Bioaccumulation 

A summary of the correlation of each measured 

variable (transformed as necessary to meet linearity 

requirements) with length-normalized mercury concentrations in fish is given in Table 7. Based on the initial 

analysis of our data, weight and length were about 

equally correlated with Hgfish concentrations. But 

because of possible anomalies previously mentioned for 

rankings normalized by weight, we normalized by 

length for the correlation analysis. The correlation for 

age was significantly lower than for either length or 

weight, perhaps because the sample age was by design 

confined to a relatively narrow range and the resolution 

was limited to 0.5 units. Had our dataset consisted of 

samples of more widely varying ages, perhaps age 

would have been more useful. As indicated in Table 7, 

all of the measured parameters except HgTotsed and 

AVSsed were significantly correlated with Hg bioaccumulation. The relative strength for correlation of bioaccumulation in fish with measures of Hg in water and 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 12 

Table 7. Correlation of measured parameters with bioaccumulation of Hg in fish. 

correlation (r) with loge(Hgfish/length)

parameter transformation all species largemouth bass

MeHgwater

MeHgsed

HgTotwater

HgTotsed

DOCwater

pHwater

sulfatewater

LOIsed

AVSsed

% wetland

loge 0.623 *** 0.712***

None 0.332*** 0.596***

loge 0.277** 0.453**

loge ns ns

loge 0.331*** ns

None -0.371*** -0.496**

loge -0.339*** -0.685***

None 0.250** 0.420**

cube root ns ns

None 0.413*** 0.523***

*** = p < 0.001; ** = p < 0.01; ns = no significant correlation (p > 0.05)

sediment was: MeHgwater > MeHgsed > HgTotwater >> 

HgTotsed (no significant correlation). The correlation 

between MeHgwater and MeHgsed was significant but 

relatively weak (r = 0.306, ρ = .0009). With the exception of DOC, all variables that were correlated with 

bioaccumulation exhibited stronger relationships for 

largemouth bass than for all species combined. 

The positive relationship of Hg bioaccumulation 

with % wetlands, DOC, and sediment LOI (a proxy for 

organic matter) is widely documented (St. Louis and 

others, 1994, McMurtry and others, 1989, Mason and 

Lawrence, 1999). Higher MeHg production is generally associated with increases in organic matter in either 

the water column or in sediments because of enhanced 

microbial activity. But whereas low to moderate levels 

of DOC usually correlate with enhanced methylation 

rates of Hg (especially if the DOC is from terrestrial 

sources), high levels may act to reduce methylation and 

bioaccumulation (Winfrey and Rudd, 1990, Grieb and 

others, 1990, Driscoll and others, 1995). For reasons 

that are unclear, our Hgfish data exhibited a significant 

positive correlation with DOC for all species combined, 

but not for largemouth bass. The bioacumulation of 

mercury in fish usually increases in waters of low pH 

(Wiener and others, 1990, Cope and others, 1990, Grieb 

and others, 1990, McMurtry and others, 1990) and the 

results from our nationwide sampling was no exception. 

In addition to other factors, lower water pH enhances 

Hg methylation and reduces loss of volatile Hg species 

from the water column by evasion (Winfrey and Rudd, 

1990). Our data also exhibited a highly significant, 

negative correlation of Hg bioaccumulation with sulfate. The relationship was similar when either sites 

affected by mining, agriculture, or both were excluded 

from the analysis (ag and mining activity are often 

associated with elevated concentrations of sulfate in 

nearby drainges). At this time, the reason for the 

inverse relationship is unclear. Elevated levels of sulfate might be expected to correlate positively with Hg 

bioaccumulation rates because of the presence of sulfate in acidic precipitation (which has been associated 

with increased Hg bioaccumulation) and because of the 

role of sulfate-reducing bacteria that are directly 

involved in the methylation of mercury in water. 
13 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

However, others have reported both positive and negative correlations of bioaccumulation with sulfate, 

depending on the watershed type (Grieb and others, 

1990) and in general, most studies suggest that sulfate 

is not a determinant variable in the production of MeHg 

(Winfrey and Rudd, 1990). 

Principal Components Analysis (PCA) 

Factor loadings from the two most significant principal components of the PCA are presented graphically 

as vectors in Figures 2 (all species) and 3 (largemouth 

bass). Principal components 1 and 2 accounted for 

44% and 54% of the variability for all species and for 

largemouth bass, respectively. From these plots, it is 

clear that a measure of fish size was the dominant 

variable influencing factor 2 (vectors in the positive ydirection) whereas the variables associated with the 

presence of organic matter (DOC, MeHgwater, LOI, % 

wetland, and MeHgsed) each had a similar level of 

influence on factor 1 (vectors in positive x-direction). 

For largemouth bass only, there was a third statistically 

significant factor (not plotted in Figure 3) that accounted for an additional 14% of the variability. Therefore, a 

second PCA was conducted for largemouth bass only, 

but with the measures of length, weight, and age 

excluded, to allow for convenient examination of the 

first and third principal components. We expect that 

the exclusion of size factors may only be useful for 

data of a single fish species that are of relatively uniform size/age, as was the case for the largemouth bass 

in this study. With this plot (Figure 4), the importance 

of MeHg, especially in the water, on the fish Hg concentration is readily apparent because the Hgfish and 

MeHgwater appear as nearly identical vectors. In agreement with the simple regression analysis for largemouth 

bass (Table 7), DOC appears to correlate less strongly 

with the Hgfish than many of the other parameters. It 

also appears that along with pH, sulfate, and AVS, 

DOC “counteracts” the influence of TotHgwater on 

Hgfish (vectors are opposite in the y-direction). 

However, the influence of DOC for the largemouth bass 

subset was probably greatly affected by the sites in the 

SOFL basin, which had the highest DOC values. And 

in fact, data for the SOFL sites fall near or outside the 

95% confidence ellipse (interval) for PCA site score 

plots, indicating the SOFL sites were unique with 

respect to the variables analyzed in comparison to the 

other basins sampled. 

-0.3

-0.1

0.1

0.3

0.5

-0.3 -0.1 0.1 0.3 0.5

factor 1 (25%)

factor2(19

%)

Hg (fish)

TotHg

(water)

DOC

MeHg (water)

LOI (sed)

Me % wetlan d Hg

(sed) TotHg

(sed)

AVS

(sed)

sulfate

pH

age

length weight

(0,0)

Figure 2. Principal Components Analysis - Factor Loadings for Hg Concentration in Fish (all species). 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 14

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6

factor 1 (33%)

factor 2 (21%)

(0,0)

weight

length

age

pH

AVS (sed)

sulfate

Hg (fish)

DOC

TotHg (sed)

MeHg (sed)

LOI (sed)

% wetlan d

MeHg (water)

TotHg

(water)

Figure 3. Principal Components Analysis - Factor Loadings for Hg Concentration in Largemouth Bass. 

Model for the Bioaccumulation of Hg in Fish 

An overall regression model for the bioaccumulation of Hg in fish was developed with the following 

candidate variables: fish weight (kg), fish total length 

(mm), fish age (yr), MeHgwater (ng/L) , HgTotwater 

(ng/L), MeHgsed (ng/g dry) HgTotsed (ng/g dry), DOC 

(mg/L), LOI (% dry wt), sediment AVS (μmol/g dry), 

water pH, and percent wetlands of each basin. 

Variables were transformed when necessary to meet the 

assumptions of linear regression. We also determined 

stable isotope ratios (C and N) in the fillets as a potential measure of trophic position (Kendall and others, 

2000). However, the results were difficult to interpret 

(e.g., stable isotope ratios for the sediments would have 

been useful for adjusting for basin source differences) 

and consequently that data is not included in this report. 

For all fish combined, the following 4-variable model 

was deemed most useful based on the highest adjusted 

R2 (44.6%) and lowest PRESS statistic (48.6): 

loge(Hg/length) = -3.55 + 0.408 loge(MeHgwater) 

+ 0.021 (%wetland) 

– 0.269 pH – 0.121 (AVS)1/3 

For our samples the MeHgwater was by far the most 

useful predictor of Hg bioaccumulation “rate” (assuming fish length increases approximately linearly with 

time); it accounted for 30 of the 45% of the variability 

described by the model. Essentially, all of the other 

non-mercury parameters were measured because they 

were expected to influence the production MeHg. As it 

was correlated with several other of the explanatory 

variables, MeHgsed added no new explanatory power to 

the above regression equation. Many of our sampling 

sites were flowing (non-stratifying) waters in which the 

sediment-water boundary might be expected to be the 

most important Hg-methylation zone for the water body 

(Krabbenhoft and Gilmour, 1998). Also, because sediments act as a sink for most contaminants, the MeHg 

load in the sediment might be expected to provide a 

better indicator of the long term exposure for the age-3 

fish that were targeted in our study. Poor correlation of 

Hg in fish with HgTot in sediments has been widely 

documented (Wiener and others, 1984; Harrison and 

Klaverkamp, 1990; Sorensen and others, 1990). 

However, relatively few studies have been conducted 

that directly compared MeHg in sediments with Hg in 
15 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

fish. Our results suggest that on a national basis, 

MeHg in water is a much better predictor of concentrations in fish than is MeHg in the sediment, and that 

other sediment-related variables (e.g., AVS, %wetlands) 

probably replicate any ability of MeHg in sediment to 

predict Hg in fish. However, limnologic sampling conditions may greatly affect this relationship. 

Presumably, fish tend to bioaccumulate a large percentage of their Hg burden during warmer months 

when rates of feeding and microbial methylation of Hg 

are highest. In waters that stratify, mixing of anoxic 

hypolimnetic water during fall “turnover” can result in 

rapid increases of mercury accumulation in zooplankton and young-of-year fishes (Slotten and others, 1995). 

Also, hypolimnetic tailrace water below stratified reservoirs may become enriched in MeHg during early fall 

(Canavan and others, 2000). We collected samples 

when water levels were generally at low flow - a condition that tends to favor an increase in concentrations of 

MeHg in the water. Because of these seasonal factors, 

our samples might have exhibited improved correlations with methylmercury concentrations in water relative to that in the sediment. Calculations presented by 

Mason and Lawrence (1999) suggest that both the 

sediment and water column can be significant contributors of MeHg to fish via food chain pathways. 

However, the greater importance of MeHg in the water 

relative to the sediment for our model indicates that 

MeHg production in surficial sediments may be of minimal consequence in some water bodies, perhaps 

because it is not effectively transported to the water 

column. Fluxes of MeHg from sediments to the water 

column are reported to be considerable only under 

anoxic conditions (Gill and others, 1999) because 

apparently, MeHg generated at the redox boundary is 

effectively trapped by sorption to solids in oxic 

sediment surface layers (Gagnon, and others, 1996). 

Therefore, for flowing, non-stratifying waters like most 

that were sampled in our study, effective transfer of 

MeHg to the water column from sediments might only 

occur for sediments that are prone to resuspension from 

wind or other factors (Bloom, and others, 1999). 

The positive coefficient for % wetlands and the negative coefficient for pH with our model is in agreement 

with most other studies. Wetlands can be significant 

sources of MeHg and their presence can promote 

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5

factor 1 (40%)

fa

ctor 2 (18

%)

(0,0)

Hg (fish)

MeHg (water)

MeHg (sed)

% wetlan d

TotHg (sed)

LOI (sed)

DOC

TotHg (water)

AVS (sed)

sulfate

pH

Figure 4. Principal Components Analysis - Factor Loadings for Hg Concentration in Largemouth Bass, excluding 

weight, length, and age. 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 16

MeHg production because, in addition to other factors, 

they provide DOC (and enhance microbial activity) to 

the watershed (Rudd, 1995). Bioaccumulation of Hg in 

fish usually increases in waters of low pH, primarily 

because the water column retains more Hg under acidic 

conditions (Winfrey and Rudd, 1990). A minor, but 

statistically significant factor with our bioaccumulation 

model, was the sediment acid-volatile sulfide (AVS), 

which exhibited a negative coefficient. Such a result 

might seem contradictory, because wetland sediments 

usually contain considerable AVS, yet Hg bioaccumulation rates are positively correlated with the presence of 

wetlands. It may be that highly anaeorbic wetlands, 

which typically contain very high AVS in the sediments, do not contribute to increased bioaccumulation 

of Hg in fish in the same way that more aerobic wetlands do. Also, it is possible that some of the MeHg in 

the water originated considerably upstream from our 

sampling sites. As discussed in Part One of this report, 

the methylation efficiency of Hg was found to decrease 

in sediments containing very high AVS, presumably 

because of the strong affinity of sulfides for Hg, which 

make it less available. Perhaps the small, but negative 

coefficient of AVS (as the cube root) for our model 

accounts for decreased methylation efficiency, or a net 

removal of MeHg from water, at very high AVS concentrations. 

Regression plots of length-normalized fish concentrations for all species and for largemouth bass versus 

MeHg concentration in water are indicated in Figures 5 

and 6, respectively. Based on these data, a water MeHg 

concentration of 0.12 ng/L was associated with a fish 

fillet Hg concentration of 0.30 μg/g for an age-3 fish 

when all species are considered. For age-3 largemouth 

bass a water MeHg concentration of 0.058 ng/L was, on 

average, associated with the 0.30 μg/g fillet concentration. In addition to fish species and age, other factors 

that might affect this relationship include seasonal and 

hydrologic conditions during water sampling, and prey 

availability and dietary pathways for the sampled fish. 

Although the diet is generally the dominant vector for 

bioaccumulation of MeHg in predator fish, the strong 

correlation with MeHg in water indicates that the water 

column was the primary source (at the base of the food 

chain) for the majority of our sites. It is important to 

note that our water samples were not filtered for the 

determination of Hg, although most were collected during low flow and consequently were relatively low in 

suspended solids. Additional studies are needed to 

define the limitations in estimating fish concentrations 

from MeHg concentrations in water, and to determine 

the sampling conditions that maximize the predictive 

power of water analyses. 

Relation of Hg in Fish, Sediment, and Water to 

Land Use Patterns 

All of the study basins were heterogeneous with 

respect to land cover and use. For the purposes of this 

All Species y = 0.4923x + 1.2189

R2 = 0.3881

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

-6 -5 -4 -3 -2 -1 0 1

ln[MeHgwater] (ng/L)

ln[Hgfish/len] (mg/kg / m)

Figure 5. Length-normalized concentration of Hg in fish (all species) as a function of MeHg concentration in water. Excludes NVBR 

basin. 
17 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

Largemouth Bass y = 0.3999x + 1.3184

R2 = 0.5075

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

-5 -4 -3 -2 -1 0 1

ln[MeHgwater] (ng/L)

ln[Hgfish/len] (mg/kg / m)

Figure 6. Length-normalized concentration of Hg in largemouth bass as a function of MeHg concentration in water. 

analysis, the sub-basins above each of the sampling 

sites were categorized into one of the five following 

broad classes: agriculture dominant (Ag.); mixed agriculture and forest (A/F); background or reference site 

(Bkg.); current or abandonded mining activities near 

site (Mine); and urban or industrial activity near sampling site (Urb.). The land-use categories assigned to 

individual sites are listed in Part One of this report. 

The geometric means for each of the five Hg parameters and five land use catogories are depicted in Figure 

7. Rankings for concentrations of Hg in fish were as 

follows: A/F >> Mine >Ag > Urb.~ Bkd. Forested 

watersheds have been previously identified with high 

Hg methylation rates (Hurley and others, 1995). Also, 

A/F basins from our study often contained higher percentages of wetlands, which overall, contribute to higher methylation efficiency. Sub-basins characterized as 

mining-impacted ranked highest for HgTot in both 

sediment and water, and second in MeHg in water. As 

previously discussed, several of the mining basins sampled had past gold-mining operations where Hg amalgamation practices were used. Thus, although the 

methylation rates are not necessarily high in many of 

these basins, the overwhelming loads of HgTot in the 

watershed can yield relatively high concentrations of 

MeHg in the water and Hg in fish. Surprisingly, subbasins categorized as urban had a comparatively low 

mean for Hgfish but ranked fairly high for the HgTot 

and MeHg in sediment. At first glance, one might suspect that this discrepancy was due to a species bias, i.e., 

fewer top predators present in urban areas. But in fact, 

most of the fish sampled from urban sub-basins were 

either largemouth- or smallmouth bass. Interestingly, 

the correlation between MeHgwater and MeHgsed was 

highly significant for urban sites (r = 0.606, ρ = .0002) 

but it was not significant for any other land-use category. The factors affecting the bioaccumulation of Hg in 

fish from urban settings deserves additional research. 

The bioaccumulation factor (BAF) for MeHg in 

water to Hg in fish muscle (assumed to be all MeHg) is 

plotted in Figure 8 for each land-use category (and the 

SOFL basin) for either largemouth bass or all species 

combined. The SOFL unit was considered separately 

because of its unique character and because most other 

sites were flowing streams. There are no clear 

differences for BAFs among land-uses for all species 

combined. However, a trend opposite of that observed 

for fish concentrations (Figure 7) is apparent for BAFs 

for largemouth bass alone, i.e., the land-use categories 

with the highest fish and water concentrations (A/F and 

Mine) have the lowest BAFs, and vice-versa. Perhaps 

most striking is the comparatively low BAF for SOFL, 

where MeHg concentrations in water are generally 

high. A similar trend was observed for BAFs normalized by fish length, which indicates that overall, there 

was not a remarkable bias due to size differences of 

fish collected among land-use categories. The inverse 

relationship of BAF with the concentration of MeHg in 

water suggests that lower concentrations of MeHg in 

water are more efficiently biotransferred than are higher 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 18

2

1.8

1.6

Bkg

A/F Mine Ag Urb

Hg fish

MeHg waterx 10

HgTot water/10

MeHg sediment

HgTot sediment /100

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Figure 7. Geometric mean of Hg or MeHg in fish, water, and sediment for each land use category (see text for land use definitions). 

Number of observations = 13, 42, 23, 15, and 34, for A/F, Mine, Ag., Bkg, and Urb, respectively. Excludes South Florida basin. 

Urb. Bkg. Ag. Mine A/F SOFL

all species

largemouth bass

0

1

2

3

4

5

6

7

8

Me

Hg BAF

x 106 (fish/water)

for each land use category

Figure 8. 

. 

Geometric mean of MeHg bioconcentration factor (MeHgfish / MeHgwater ) for all species and for largemouth bass, 

concentrations. This might result from lower assimilation (or greater elimination) by fish at higher MeHg 

concentrations. Or perhaps water quality factors that 

increase the MeHg production rate (like high DOC) 

also serve to reduce the relative bioavailablity and ultimately the BAF because of increased complexation of 

MeHg. These results warrant further investigation. But 

regardless of the water quality or type, high concentrations of MeHg in water will generally produce high 

concentrations in fish. 
19 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

SUMMARY 

Mercury contamination of waterways is a widespread problem and sources and accumulation rates in 

fish vary among basins. One or more fish fillet samples from nine of 20 basins examined in this pilot study 

had Hg concentrations above the historical advisory 

level of 0.50 μg/g wet weight and 15 of the basins had 

at least one sample above EPA’s 2001 criteria of 0.30 

μg/g wet weight. Based on rankings of selected water, 

sediment, and fish criteria, sampling sites from the following five basins exhibited the greatest Hg contamination: Nevada Basin and Range, South Florida, 

Sacramento Basin, Santee Basin and Coastal Drainages, 

and the Long Island and New Jersey Coast Drainages. 

The concentrations of Hg in fish were correlated 

strongly with MeHg in water, but only moderately with 

MeHg in sediment or HgTot in water. There was no 

correlation between Hg in fish and total Hg in 

sediment. The concentration of MeHg in water was by 

far the most useful variable for predicting the Hg bioaccumulation in fish. However, percent wetlands (+), pH 

of water (-) , and sediment AVS (-) also contributed significantly to the model. Based on our data, a MeHg 

water concentration of 0.12 ng/L was on average, associated with a fish fillet Hg concentration of 0.30 μg/g 

wet weight for an age-3 fish when all species were considered. For age-3 largemouth bass a MeHg water concentration of 0.058 ng/L was associated with the 0.30 

μg/g fillet concentration. Additional studies are needed 

to define the limitations in estimating fish concentrations from MeHg concentrations in water, and to determine the sampling conditions that maximize the predictive power of water analyses. 

Based on ranking criteria, sub-basins categorized as 

mixed agriculture/forest and mining-impacted had the 

most consistent contamination of Hg in all three sample 

matrices (water, sediment, and fish). The greatest discrepancy for rankings of Hg in fish and in sediments 

was for urban watersheds, where sediments often 

ranked high but fish usually ranked low. The bioaccumulation factor (MeHgfish / MeHgwater) was lowest for 

land-use categories having the highest concentrations of 

MeHg in water, which indicates that low concentrations 

of MeHg in water are more efficiently biotransferred 

than higher concentrations. Nevertheless, high concentrations of MeHg in water will generally produce high 

concentrations in fish. A sampling and analysis strategy based on this pilot study is planned for all USGS 

NAWQA study units over the next decade. We expect 

those results to provide a comprehensive national characterization of mercury contamination and bioaccumulation in our aquatic ecosystems. 

ACKNOWLEDGEMENTS 

The authors are indebted to all NAWQA study-basin 

teams who participated in the study and demonstrated 

great diligence, commitment, and enthusiam in the collection of the samples. We thank Jude Smith and 

coworkers with the U.S. Fish and Wildlife Service 

(Albuquerque, NM) for conducting age determinations 

and Dr. Ted Lange (Florida Fish and Game) for providing Hg measures in fish from South Florida. We 

acknowledge our colleagues Jesse Arms, Mike Walther, 

and Mark Olson for technical assistance, Robin Lipkin 

and Cory Stephens for assistance with manuscript 

preparation, and Chris Schmitt and Denny Buckler for 

helpful review comments. 

REFERENCES 

Bloom, N.S. 1992, On the Chemical Form of Mercury 

in Edible Fish and Marine Invertebrate Tissue. Can. 

J. Fish. Aquat. Sci., 49:1010-1017. 

Bloom, N.S., Gill, C.A., Cappellino, S., Dobbs, C., 

McShea, L., Driscoll, C., Mason, R.P., and Rudd, J. 

1999, An Investigation Regarding Speciation and 

Cycling of Mercury in Lavaca Bay Sediments. 

Environ. Sci. Technol. 33:7-13. 

Bodaly, R.A., St. Louis, V.L., Paterson, M.J., Fudge, 

R.J.P., Hall, B.D., Rosenberg, D.M., and Rudd, 

R.W.M., 1997, Biaccumulation of Mercury in the 

Aquatic Food Chain in Newly Flooded Areas, Sigel, 

A. and Sigel, H. eds., Mercury and its Effects on 

Environment and Biology:Marcel Dekker, New 

York, NY, pp. 259-287. 

Bonzongo, J-C; Heim, K. J., Chen, Y., Lyons, W. B., 

Warwick, J. J., Miller, G. C., and Lechler, P. J., 

1996, Mercury Pathways in the Carson RiverLahontan Reservoir System, Nevada, USA. Environ. 

Toxicol. Chem. 15:677-683. 

Canavan, C.M., Caldwell, C.A., Bloom, N.S., 2000, 

Discharge of Methylmercury-Enriched 

Hypolimnetic Water from a Stratified Reservoir. Sci. 

Tot. Environ. 260:159-170. 

Carlander, K.D., 1977, Handbook of freshwater biology. Volumes 1 and 2. Iowa State University Press, 

Ames, Iowa. 

Cope, W.G., Wiener, J.G., and Rada, R.G. 1990. 

Mercury Accumulation in Yellow Perch in 

Wisconsin Seepage Lakes: Relation to Lake 

Characteristics. Environ. Toxicol. Chem. 9:931-940. 

Jearld, A. Jr., 1983, Age Determination, Nielsen, L.A. 

and Johnson, D.L., eds., Fisheries Techniques, 

American Fisheries Society, Bethesda, MD, pp. 301-

324. 
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 20

Domagalski, J., 1998, Occurrence and Transport of 

Total and Methyl Mercury in the Sacramento River 

Basin, California. J. Geochem. Explor. 64:277-291. 

Driscoll, C.T., Blette, V., Yan, C., Schofield, C.L., 

Munson, R., and Holsapple, J., 1995, The Role of 

Dissolved Organic Carbon in the Chemistry and 

Bioavailability of Mercury in Remote Adirondack 

Lakes. Water Air Soil Pollut. 80:499-508. 

Facemire, C., Augspurger,T., Bateman, D., Brim, M., 

Conzelmann, P., Delchamps, S., Douglas, E., Inmon, 

L., Looney, K., Lopez, F., Masson, G., Morrison, D., 

Morse, N. and Robison, A., 1995, Impacts of 

Mercury Contamination in the Southeastern United 

States. Water Air Soil Pollut. 80:923-926. 

Furautani, A., and Rudd, J.W.M., 1980, Measurement 

of Mercury Methylation in Lake Water and 

Sediment Samples. Appl. Environ. Microbiol. 

40:770-776. 

Gagnon, C., Pelletier, E., Mucci, A., Fitzgerald, W.F. 

1996. Diagenetic Behavior of Methylmercury in 

Organic-Rich Coastal Sediments. Limnol. Oceanogr. 

41:428-434. 

Gill, G. A., and Bruland, K.W., 1990, Mercury 

Speciation in Surface Freshwater Systems in 

California and Other Areas. Environ. Sci. Technol. 

24:1392-1400. 

Gill, G. A., Bloom, N.S., Cappellino, S., Driscoll, C., 

Dobbs, C., McShea, L., Mason, R.P., and Rudd, J. 

1999, Sediment-water Fluxes of Mercury in Lavaca 

Bay, Texas. Environ. Sci. Technol. 33:663-669. 

Goldstein, R. M., Brigham, M.E., and Stauffer, J.C., 

1996, Comparison of Mercury Concentrations in 

Liver, Muscle, Whole Bodies, and Composites of 

Fish from the Red River of the North. Can. J. Fish. 

Aquat. Sci. 53:244-252. 

Grieb, T.M, Driscoll, C.T., Gloss, S.T., Schofield, C.L., 

Bowie, G.L., and Porcella, D.B., 1990. Factors 

Affecting Mercury Accumulation in Fish in the 

Upper Michigan Penisula. Environ. Toxicol. Chem. 

9:919-930. 

Hanisch, C., 1998, Where is Mercury Deposition 

Coming From? Environ. Sci. Technol. 32:176-179A. 

Harrison, S. E., and J. F. Klaverkamp, 1990. Metal 

Contamination in Liver and Muscle of Northern 

Pike (Esox lucius) and White Sucker (Catostomus 

commersoni) and in Sediments from Lakes Near the 

Smelter at Flin Flon, Manitoba. Environ. Toxicol. 

Chem. 9:941-956. 

Helsel D. R. and Hirsch, R. M., 1992, Statistical 

Methods in Water Resources, Elsevier, Amsterdam, 

529 pps. 

Hurley, J. P., Benoit, J.M., Babiarz, C.L., Shafer, M. 

M., Andren, A.W., Sullivan, J.R., Hammond, R., 

and Webb, D.A., 1995, Influences of Watershed 

Characteristics on Mercury Levels in Wisconsin 

Rivers. Environ. Sci. Technol. 29:1867-1875. 

Kendall, C., Battaglin, W.A., Cabana, G., Chang, C.C., 

Silva, S. R., Porter, S.D., Goolsby, D.A., Campbell, 

D.H., Hooper, R. P., Schmitt, C.J. 1999. Isotopic 

Tracing of Nitrogen Sources and Cycling in the 

Mississippi River Basin. U.S. Geological Survey 

Toxic Substances Hydrology Program – Proceedings 

of the technical meeting, Charleston, S.C., March 8-

12, 1999. U.S.G.S. Water-Resources Investigations 

Report 99-4018B, Vol 2, p 339-343. 

Kidd, K,A., Heelein, R.H., Fudge, R.J.P., and Hallard, 

K.A., 1995, The Influence of Trophic Level as 

Measured by δ15N on Mercury Concentrations in 

Freshwater Organisms. Water Air Soil Pollut. 80: 

1011-1015. 

Korthals, E.T., and Winfrey, MR., 1987, Seasonal and 

Spatial Variations in Mercury Methylation and Demethylation in an Oligotrophic Lake. Appl. 

Environ. Microbiol. 53:2397-2404. 

Krabbenhoft, D.P., Gilmour, C.C., Benoit, J.M., 

Babiarz, C.L., Andren, A.W., Hurley, J.P., 1998, 

Methyl Mercury Dynamics in Littoral Sediments of 

a Temperate Seepage Lake. Can. J. Fish. Aquat. Sci. 

55:835-844. 

Krabbenhoft, D.P., Wiener, J.G., Brumbaugh, W.G., 

Olson, M.L., DeWild, J.F., and Sabin, T.J., 1999, A 

National Pilot Study of Mercury Contamination of 

Aquatic Ecosystems Along Multiple Gradients. U.S. 

Geological Survey Toxic Substances Hydrology 

Program – Proceedings of the technical meeting, 

Charleston, S.C., March 8-12, 1999. U.S.G.S. WaterResources Investigations Report 99-4018B, Vol 2, p 

147-160. 

Lafleur, P.D. , 1973, Retention of Mercury When 

Freeze-drying Biological Materials. Anal. Chem. 

45:1534-1536. 

Lange, T.R., Royals, H.E., and Connor, L.L. , 1993, 

Influence of Water Chemistry on Mercury 

Concentration in Largemouth Bass from Florida 

Lakes. Trans. Am. Fish. Soc. 122:74-84. 

Lange, T.R., Royals, H.E., and Connor, L.L. , 1994, 

Mercury Accumulation in Largemouth Bass 

(Micropterus salmoides) in a Florida Lake. Arch. 

Environ. Contam. Toxicol. 27:466-471. 

Lasorsa, B. and Allen-Gil, S., 1995, The 

Methylmercury to Total Mercury Ratio in Selected 

Marine, Freshwater, and Terrestrial Organisms. 

Water Air Soil Pollut. 80:905-913. 

Louisiana Department of Environmental Quality, 1999, 

www.deq.state.la.us/owr/mercury.htm. 

May, T. W. and McKinney, G.L. , 1981, Cadmium, 

Lead, Mercury, Arsenic, and Selenium 
21 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

Concentrations in Freshwater Fish, 1976-77 – 

National Pesticide Monitoring Program. Pesticides 

Monitoring Journ. 15:14-38. 

Mason, R.P. and Lawrence, A.L., 1999, Concentration, 

Distribution, and Bioavailability of Mercury and 

Methylmerncury in Sediments of Baltimore Harbor 

and Chesapeake Bay, MD, USA. Environ. Toxicol. 

Chem. 18:2438-2447. 

McMurtry, M.J., Wales, D.L., Scheider, W.A., Beggs, 

G.L., and Dimond, P.E., 1989. Relationship of 

Mercury Concentrations in Lake Trout (Salvelinus 

namaycush) and Smallmouth Bass (Micropterus 

dolomieui) to the Physical and Chemical 

Charateristics of Ontario Lakes. Can. J. Fish. Aquat. 

Sci. 46:426-434. 

Phillips, G.R., Medvick, P.A., Skaar, D.R., and Knight, 

D.E., 1984, Factors Affecting Mobilization, 

Transport and Bioavailability of Mercury in 

Reservoirs of the Upper Missouri River Basin. U.S. 

Fish and Wildlife Service, Montana Cooperative 

Fishery Research Unit, technical report No. 10, 64 

pps. 

Porak, W., Coleman, W.S., and Crawford, S., 1988, 

Age, Growth, and Mortality of Florida Largemouth 

Bass Utilizing Otiliths. Proceedings of the Annual 

Conference of Southeastern Association of Fish and 

Wildlife Agencies 40:206-215. 

Rudd, J. W. M., 1995, Sources of Mercury to 

Freshwater Ecosystems: A Review. Water Air Soil 

Pollut. 80:697-713. 

Schmitt, C. J., and Brumbaugh, W.G., 1990, National 

Contaminant Biomonitoring Program: 

Concentrations of Arsenic, Cadmium, Copper, Lead, 

Mercury, Selenium, and Zinc in U.S. Freshwater 

Fish, 1976-1984. Arch. Environ. Contam. Toxicol. 

19:731-747. 

Slotton, D.G., Reuter, J.E., and Goldman, C.R., 1995, 

Mercury Uptake Patterns of Biota in a Seasonally 

Anoxic Northern California Reservoir. Water Air 

Soil Pollut. 80:841-850. 

Sorensen, J.A., Glass, G.E., Scmidt, K.W., Huber, J.K., 

Rapp, Jr., R., 1990, Airborne Mercury Deposition 

and Watershed Characteristics in Relation to 

Mercury Concentrations in Water, Sediments, 

Plankton, and Fish of Eighty Northern Minnesota 

Lakes. Environ. Sci. Technol. 24:1716-1727. 

SAS Institute, Inc., 1989, SAS/STAT User’s Guide, 

Vers. 6, Fourth Ed., Vol. 1 & 2, Cary, NC, 846 pp. 

South Carolina Dept.of Health and Environmental 

Control, 1999, www. state.sc.us/dhec/fsmerc.htm. 

Southworth, G.R., Turner, R. R., Peterson, M. J., and 

Bogle, M. A. , 1995, Form of Mercury in Stream 

fish Exposed to High Concentrations of Dissolved 

Inorganic Mercury. Chemosphere 30:779-787. 

St. Louis, V.L., Rudd, J.W.M., Keely, C.A., Beaty, K.G., 

Bloom, N.S., and Flett, R.J., 1994, Importance of 

Wetlands as Sources of Methyl Mercury to Boreal 

Forest Ecosystems: Can. J. Fish. Aq. Sci. 51:1065-

1076. 

USEPA, 1996, National Listing of Fish and 

Consumption Advisories Database: United States 

Environmental Protection Agency, EPA-823-C-96-

011, Office of Water, Washington , DC, 7 diskette 

set. 

USEPA, 1997, Mercury Study Report to Congress, 

United States Environmental Protection Agency, 

EPA-452-97-003-010, Office of Air and Radiation, 

Washington , DC, 1980 pp. 

USEPA, 2001, Water Quality Criterion for Protection of 

Human Health: Methylmercury, United States 

Environmental Protection Agency, EPA-823-R-01-

001, January 2001, Office of Water, Washington , 

DC. 

Watras, C.J., Bloom, N.S., Claas, S.A., Morrison, K.A., 

Gilmour, C.C., and Craig, S.R., 1995, 

Methylmercury Production in the Anoxic 

Hypolimnion of a Dimistic Seepage Lake. Water Air 

Soil Pollut. 80:735-745. 

Wiener, J.G., 1982, Method for Detecting 

Trace-Element Contamination of Fish Samples from 

Handling. Environ. Sci. Technol. 16:90-93. 

Wiener, J. G., Martini, R. E., Sheffy, T. B., and Glass, 

G. E., 1990, Factors Influencing Mercury 

Concentrations in Walleyes in Northern Wisconsin 

Lakes. Trans. Am. Fish. Soc. 119:862-870. 

Wiener, J. G., G. A. Jackson, T.W. May, and B. P. Cole, 

1984. Longitudinal Distribution of Trace Elements 

(As, Cd, Cr, Hg, Pb, and Se) in Fishes and 

Sediments in the Upper Mississippi River. In 

Contaminants in the Upper Mississippi River. 

Butterworth Pub. Stoneham, MA, pps. 139-170. 

Wiener, J.G. and Spry, D.J., 1995, Toxicological 

Significance of Mercuryin Freshwater Fish. In 

Environmental Contaminants in Wildlife: 

Interpreting Tissue Concentrations, Heinz, G.; Beyer, 

N.; Redmond-Norwood, A.W.; eds. Lewis 

Publishers, Boca Raton, FL. Pp 297-339. 

Winfrey, M.R. and Rudd, J.W.M., 1990, Environmental 

Factors Affecting the Formation of Methylmercury 

in Low pH Lakes. Environ. Toxicol. & Chem. 9:853-

869. 

Wolfe, M.F., Schwarzbach, S., and Sulaiman, R.A., 

1998, Effects of Mercury on Wildlife: A 

Comprehensive Review. Environ. Toxicol. Chem. 

17:146-160. 

Zillioux, E.J., Porcella, D.B, and Benoit, J.M., 1993, 

Mercury Cycling and Effects in Freshwater Wetland 

Ecosystems. Environ. Toxicol. Chem. 12:2245-2264. 
-- --

--

-- --

--

--

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--

USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 22 

Appendix. Concentrations of mercury in fish collected from USGS NAWQA Hg-Pilot Study basins, June

through October, 1998. No. fish indicates number of fish in each composite sample. Sample species with a superscript were analyzed as whole-body less head; those with b superscript were analyzed as whole

body. All others are fillet tissue. See text for assignment of age. CERC = Columbia Environmental

Research Center; -- = no data.

CERC # S.U. Site Species

No.

Fish

Mean

Weight (g)

Mean Total

Length (mm)

Mean Age

(yr)

μg Hg / g

dry wet

18221-1 ALMN Clarion R. @ Ridgeway, PA Smallmouth Bass 2 745 363 4.5 1.495 0.327

18222-1 ALMN Dunkard Cr. @ Shannopin, PA Smallmouth Bass 4 130 223 3.0 1.102 0.204

18223-1 ALMN Youghiogheny R. @ Sutersville, PA Smallmouth Bass 1 292 290 2.5 0.439 0.072

18224-1 ALMN Allegheny R. @ NewKensington, PA Smallmouth Bass 3 108 206 1.5 0.449 0.087

18225-1 ALMN Tenmile Cr. nr. Amity, PA Smallmouth Bass 2 430 312 4.0 1.517 0.288

18226-1 ALMN Tenmile Cr. nr. Amity, PA Largemouth Bass 1 592 329 3.5 0.941 0.181

18227-1 LINJ Muddy Run @ Centerton, NJ Chain Pickerel 2 307 345 4.0 0.781 0.159

18227-2 LINJ Muddy Run @ Centerton, NJ Chain Pickerel 4 10 120 0.5 0.475 0.100

18228-1 LINJ Muddy Run @ Centerton, NJ Largemouth Bass 2 362 295 3.0 1.760 0.334

18228-2 LINJ Muddy Run @ Centerton, NJ Largemouth Bass 2 110 192 3.0 1.088 0.207

18228-3 LINJ Muddy Run @ Centerton, NJ Largemouth Bass

a 1 21 119 0.5 0.567 0.132

18229-1 LINJ Passaic R. @ Millington, NJ Redfin Pickerel 2 81 229 2.5 1.811 0.340

18230-0 LINJ Passaic R. @ Millington, NJ Redfin Pickerel

b 4 12 112 0.5 0.624 0.125

18231-1 LINJ Passaic R. @ Millington, NJ Largemouth Bass 2 179 212 2.5 1.286 0.262

18232-1 LINJ Passaic R. @ Millington, NJ Smallmouth Bass 1 25 118 0.5 1.522 0.276

18233-1 LINJ Swan R. @ E. Patchague, NY Redfin Pickerel 7 36 166 2.0 0.460 0.073

18234-1 LINJ Great Egg Harbor @ Sicklerville, NJ Chain Pickerel 2 172 284 3.0 4.511 0.816

18234-2 LINJ Great Egg Harbor @ Sicklerville, NJ Chain Pickerel 5 84 237 1.5 2.911 0.495

18235-1 LINJ Great Egg Harbor @ Sicklerville, NJ Largemouth Bass 1 49 148 1.5 3.212 0.575

18236-1 UIRB Des Plains R. @ Russell, IL Bowfin 1 617 337 3.5 1.014 0.174

18237-1 UIRB Nippersink Cr. Abv. Wonder Lake, IL Smallmouth Bass 2 84 180 1.5 0.330 0.066

18238-1 UIRB Salt Cr. @ Western Springs, IL Smallmouth Bass 3 70 175 2.0 0.489 0.088

18239-1 UIRB Pitner Ditch nr. LaCrosse, IN Largemouth Bass 3 154 219 3.0 0.707 0.129

18240-1 UIRB Mukwanago R. @ Mukwanago, WI Rock Bass 4 62 143 2.0 0.575 0.107

18241-1 UIRB Mukwanago R. @ Mukwanago, WI Largemouth Bass 1 114 182 2.5 0.412 0.075

18242-1 LTEN Sequatchie R. nr. Whitwell, TN Largemouth Bass 1 228 250 3.5 2.275 0.421

18242-2 LTEN Sequatchie R. nr. Whitwell, TN Largemouth Bass 3 114 214 2.5 1.449 0.262

18243-1 LTEN Buffalo R. nr. Flatwoods, TN Largemouth Bass 1 351 282 3.5 1.256 0.241

18244-1 LTEN Buffalo R. nr. Flatwoods, TN Largemouth Bass 1 132 212 2.5 2.143 0.390

18245-1 LTEN Buffalo R. nr. Flatwoods, TN Largemouth Bass 1 35 144 1.5 1.398 0.217

18246-1 LTEN Indian Cr. nr. Madison, AL Largemouth Bass 2 288 280 2.5 0.871 0.163

18247-1 LTEN Indian Cr. nr. Madison, AL Largemouth Bass 1 470 324 3.5 1.325 0.256

18248-1 LTEN Indian Cr. nr. Madison, AL Largemouth Bass 2 38 148 1.5 0.720 0.130

18249-0 COOK S. Fk. Campbell Cr. nr. Anchorage, AK Slimy Sculpinb 5 23 0.292 0.069

18250-1 COOK S. Fk. Campbell Cr. nr. Anchorage, AK Dolly Varden 5 141 233 0.429 0.086

18251-0 COOK Chester Cr @ Artic Blvd, Anchorage, AK Slimy Sculpinb 5 20 0.152 0.036

18252-1 COOK Costello Cr. nr. Colorado & Denali, AK Dolly Vardenb 1 35 158 0.164 0.036

18252-2 COOK Costello Cr. nr. Colorado & Denali, AK Dolly Vardenb 4 11 114 0.101 0.021

18253-0 COOK Deshka R. NR. Willow, AK Slimy Sculpinb 10 35 0.246 0.060

18254-0 NECB Stillwater R. NR. Sterling, MA Mixed Sunfishb 5 12 84 0.796 0.173

18255-0 NECB Neponset R. @ Norwood, MA Mixed Sunfishb 4 50 127 3.5 0.457 0.116
-

--

--

-

23 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

CERC # S.U. Site Species

No.

Fish

Mean

Weight (g)

Mean Total

Length (mm)

Mean age

(yr)

μg Hg / g

dry wet

18256-0 NECB Aberjona R. @ Winchester, MA Mixed Sunfishb 5 23 94 0.236 0.055

18257-0 NECB Saugus R. @ Ironworks@ Saugus, MA Mixed Sunfishb 4 19 100 0.486 0.107

18258-0 NECB Ipswich R. @ S. Middleton, MA Mixed Sunfishb 5 33 114 2.5 1.423 0.349

18259-0 DELR Schuylkill R. @ Philadelphia, PA Smallmouth Bass 5 317 308 4.1 1.616 0.323

18260-0 DELR Delaware R. @ Trenton, NJ Smallmouth Bass 5 749 371 4.3 1.439 0.288

18261-0 DELR Delaware R. @ Port Jervis, NY Smallmouth Bass 4 294 276 3.5 1.654 0.331

18262-0 DELR Lehigh R. @ Glendon, PA Smallmouth Bass 5 338 297 3.5 0.648 0.130

18263-1 DELR Racoon Cr. @ Swedesboro, NJ Chain Pickerel 1 330 372 3.5 1.521 0.287

18263-2 DELR Racoon Cr. @ Swedesboro, NJ Chain Pickerel 1 105 254 0.5 0.687 0.126

18264-1 DELR Little Lehigh Cr. @ E. Texas, PA Brown Trout 3 141 233 0.148 0.031

18265-1 DELR Hay Cr. nr. Birdsboro, PA Smallmouth Bass 1 557 335 3.5 1.587 0.333

18265-2 DELR Hay Cr. nr. Birdsboro, PA Smallmouth Bass 2 221 258 2.5 1.457 0.290

18266-1 DELR Manatawny Cr. nr. Pottstown, PA Smallmouth Bass 3 206 253 3.5 0.883 0.169

18267-1 DELR Tulpehocken Cr. nr. Bernville, PA Smallmouth Bass 1 354 283 3.5 1.113 0.236

18268-1 DELR L. Neshaminy Cr. nr. Neshaminy, PA Smallmouth Bass 2 180 236 3.0 1.398 0.268

18269-1 SACR Colusa Basin Drain , CA Largemouth Bass 4 644 343 4.8 1.945 0.393

18270-1 SACR Sacramento Slough nr. Knights Landing Largemouth Bass 1 1471 550 4.5 10.734 1.803

18270-2 SACR Sacramento Slough nr. Knights Landing Largemouth Bass 1 1156 390 5.5 3.214 0.633

18270-3 SACR Sacramento Slough nr. Knights Landing Smallmouth Bass 1 675 324 4.5 2.220 0.466

18271-1 SACR Cottonwood Cr. nr. Cottonwood, CA Smallmouth Bass 1 401 315 3.5 1.264 0.264

18271-2 SACR Cottonwood Cr. nr. Cottonwood, CA Smallmouth Bass 5 115 193 1.5 0.438 0.092

18272-1 SACR Bear River @ Hwy 70 nr. Rio Oso, CA Largemouth Bass 1 518 325 3.5 5.983 1.119

18272-2 SACR Bear River @ Hwy 70 nr. Rio Oso, CA Smallmouth Bass 1 467 288 3.5 5.442 1.050

18273-1 SACR Bear River @ Hwy 70 nr. Rio Oso, CA Smallmouth Bass 1 150 220 2.5 2.695 0.499

18274-1 SACR Bear River @ Hwy 70 nr. Rio Oso, CA Mountain Whitefish 1 549 390 2.0 1.376 0.246

18275-1 SACR Putah Cr. nr. Davis, CA Largemouth Bass 5 62 158 1.5 1.320 0.247

18276-1 SANA South Fork Santa Ana River, CA Brown Trout 6 90 194 1.5 0.743 0.127

18277-1 SANA Santa Ana R. @ Hammer Rd. Largemouth Bass 2 54 158 2.0 0.743 0.140

18278-1 SANA Santa Ana R. blw. Prado Dam Mixed Sunfish 10 53 136 2.0 0.685 0.118

18279-1 SANA Mill Cr. @ Chino - Corona Rd. Common Carp 5 393 311 3.0 0.694 0.114

18280-1 NVBR Lahontan Res., NV White Bass 1 435 310 3.5 9.381 1.895

18280-2 NVBR Lahontan Res., NV White Bass 1 435 325 2.5 29.06 5.696

18280-3 NVBR Lahontan Res., NV White Bass 1 490 334 3.5 32.61 5.837

18280-4 NVBR Lahontan Res., NV White Bass 1 615 350 3.5 7.387 1.418

18280-5 NVBR Lahontan Res., NV White Bass 1 437 335 3.5 16.42 3.219

18280-6 NVBR Lahontan Res., NV White Bass 1 883 380 4.5 13.34 2.881

18280-7 NVBR Lahontan Res., NV White Bass 1 879 392 4.5 16.01 3.634

18280-8 NVBR Lahontan Res., NV White Bass 1 1171 472 5.5 24.90 5.154

18281-1 YELL Bighorn R. @ Kane, WY Walleye 5 452 373 2.5 3.289 0.635

18282-1 YELL Tongue R. @ State Line nr. Decker Smallmouth Bass 1 299 270 3.5 0.743 0.153

18283-1 YELL Yellowstone R. @ Sidney, MT Sauger 2 176 294 3.0 1.287 0.250

18284-1 YELL Bighorn Lake @ Hwy 14A Causeway Walleye 5 896 453 4.0 3.382 0.676

18285-1 YELL Shoshone R. @ Mouth nr. Kane, WY Walleye 1 1444 535 5.5 3.249 0.669

18285-2 YELL Shoshone R. @ Mouth nr. Kane, WY Walleye 5 817 437 4.5 3.452 0.666

18286-1 ACAD Tangipahoa R. @ Robert, LA Largemouth Bass 8 562 335 4.2 3.789 0.743

18287-1 ACAD Turtle Bayou nr. Bayou Penchant, LA Largemouth Bass 8 387 292 2.5 0.999 0.206

18288-1 ACAD Bayou Teche nr. St. Martinville, LA Largemouth Bass 8 334 298 3.1 1.320 0.260
USGS NATIONAL PILOT STUDY OF MERCURY IN FISH 24

No.

Fish

Mean

Weight (g)

Mean Total

Length (mm)

Mean age

(yr)

μg Hg / g

CERC # S.U. Site Species dry wet

18289-1 ACAD Bogue Falaya R. @ Covington, LA Largemouth Bass 8 392 306 3.5 4.098 0.791

18290-1 ACAD Bayou Segnette nr. Barataria, LA Largemouth Bass 8 487 326 2.8 1.027 0.209

18291-1 GRSL Cub R. nr. Richmond, UT Largemouth Bass 2 136 204 4.5 1.369 0.271

18292-1 GRSL Weber R. nr. Coalville, UT Mountain Whitefish 1 833 391 4.0 0.628 0.141

18292-2 GRSL Weber R. nr. Coalville, UT Mountain Whitefish 2 545 374 4.0 0.535 0.117

18292-3 GRSL Weber R. nr. Coalville, UT Mountain Whitefish 2 317 300 3.0 0.364 0.073

18293-1 TRIN Trinity R. belowDallas, TX Bluegill Sunfishb 2 19 95 1.5 0.412 0.064

18294-1 TRIN Trinity R. belowDallas, TX Bluegill Sunfishb 1 38 120 2.5 0.494 0.079

18295-1 TRIN Trinity R. belowDallas, TX Mixed Sunfish 2 77 162 2.5 0.431 0.064

18296-1 TRIN Trinity R. belowDallas, TX Flathead Catfish 1 1087 470 -- 0.910 0.159

18297-1 TRIN White Rock Lake Dallas TX Largemouth Bass 1 91 186 0.5 0.270 0.045

18298-1 TRIN White Rock Lake Dallas TX Largemouth Bass 2 341 282 3.5 0.252 0.051

18299-1 TRIN White Rock Lake Dallas TX Largemouth Bass 1 663 345 3.5 0.586 0.117

18300-1 TRIN Lake Livingston, TX Largemouth Bass 1 1305 412 4.5 1.179 0.249

18300-2 TRIN Lake Livingston, TX Largemouth Bass 1 849 366 4.5 1.876 0.373

18300-3 TRIN Lake Livingston, TX Largemouth Bass 2 526 324 5.0 1.226 0.249

18300-4 TRIN Lake Livingston, TX Largemouth Bass 2 306 278 4.0 0.645 0.125

18301-1 TRIN Clear Cr. nr. Sanger, TX Spotted Bass 1 40 150 0.5 1.411 0.258

18302-1 TRIN Clear Cr. nr. Sanger, TX Spotted Bass 1 87 180 0.5 0.861 0.157

18303-1 TRIN Clear Cr. nr. Sanger, TX Spotted Bass 1 142 228 3.5 1.450 0.299

18304-1 TRIN Clear Cr. nr. Sanger, TX Channel Catfish 1 372 380 -- 2.245 0.341

18304-2 TRIN Clear Cr. nr. Sanger, TX Channel Catfish 2 114 248 -- 0.841 0.133

18305-1 TRIN Trintity R. nr. Crockett, TX Largemouth Bass 1 311 260 3.5 0.631 0.127

18306-1 TRIN Trintity R. nr. Crockett, TX Flathead Catfish 3 191 262 -- 0.716 0.110

18307-1 NROK Clark Fork at Turah, MT Mountain Whitefish 5 551 356 4.5 0.641 0.155

18308-1 NROK Clark Fork at St. Regis, MT Mountain Whitefish 5 264 294 3.5 0.436 0.092

18309-1 MIAM Little Miami R. @ Milford, OH Smallmouth Bass 3 55 153 1.5 0.244 0.042

18310-1 MIAM Little Miami R. @ Milford, OH Smallmouth Bass 1 698 340 5.5 1.393 0.276

18311-1 MIAM Whitewater R. nr. Nultown, IN Smallmouth Bass 1 80 187 2.5 0.792 0.135

18312-1 MIAM Whitewater R. nr. Nultown , IN Smallmouth Bass 1 129 220 2.5 0.701 0.128

18313-1 MIAM Whitewater R. nr. Nultown, IN Smallmouth Bass 2 257 270 4.0 1.038 0.198

18314-1 MIAM E. Fork, L. Miami R. Williamsburg, OH Smallmouth Bass 1 107 205 2.5 1.108 0.205

18315-1 MIAM E. Fork, L. Miami R. Williamsburg, OH Smallmouth Bass 2 386 302 3.5 1.859 0.359

18316-1 MIAM E. Fork, L. Miami R. Williamsburg, OH Smallmouth Bass 1 608 350 4.5 2.524 0.520

18317-1 MIAM Stillwater R. @ Union, OH Smallmouth Bass 3 130 217 2.5 1.074 0.180

18318-1 MIAM Stillwater R. @ Union, OH Smallmouth Bass 1 284 275 3.5 0.706 0.138

18319-1 MIAM Great Miami R. nr. Tipp City, OH Smallmouth Bass 4 178 242 3.5 0.649 0.117

00012-1 MIAM Mad R. @ Hwy 41 Smallmouth Bass 1 518 325 5.5 1.355 0.271

00013-1 MIAM Great Miami R. @ Hamilton Smallmouth Bass 2 345 292 3.5 0.565 0.113

18523-1 OAHU Kawainui Canal, HI Tilapia 5 127 188 4.0 0.157 0.030

18524-1 OAHU Ala Wai Canal, HI Tilapia 5 124 179 2.0 0.115 0.020

18525-1 OAHU Hoomaluhia Reservoir, HI Tilapia 5 49 133 3.0 0.116 0.018

18526-1 OAHU Nuuanu Reservoir, HI Tilapia 5 249 226 4.0 0.317 0.063

18527-1 OAHU Waikele Stream, HI Smallmouth Bass

a 1 32 135 0.5 0.189 0.050

18528-1 OAHU S. Fork Lake Wilson, HI Tilapia 5 302 250 4.5 0.237 0.046

18529-1 MOBL Shades Cr., AL Longear Sunfish 8 29 118 3.0 0.718 0.122

18530-1 MOBL Alabama R. @ Claiborne, AL Black Crappie 2 210 245 3.0 0.810 0.146

18530-2 MOBL Alabama R. @ Claiborne, AL Black Crappie 1 94 180 2.5 0.411 0.067
--

--

--

--

--

--

--

25 BIOLOGICAL SCIENCE REPORT USGS/BRD/BSR–2001-0009

No. Mean Mean Total Mean age μg Hg / g

CERC # S.U. Site Species Fish Weight (g) Length (mm) (yr) dry wet

18531-1 MOBL Alabama R. @ Claiborne, AL

18531-2 MOBL Alabama R. @ Claiborne, AL

18531-3 MOBL Alabama R. @ Claiborne, AL

18532-1 MOBL Satilpa Cr near Coffeeville, AL

18532-2 MOBL Satilpa Cr near Coffeeville, AL

18533-1 MOBL Town Cr at Tupelo, MS

18534-1 MOBL Tombigbee R. nr. Coffeeville Lock, AL

18534-2 MOBL Tombigbee R. nr. Coffeeville Lock, AL

18535-1 MOBL Coosa River at Rome, GA

18535-2 MOBL Coosa River at Rome, GA

18535-3 MOBL Coosa River at Rome, GA

18536-1 MOBL ChickasawCr., AL

00001-1 SANT N. Fork Edisto R, nr. Fairviewcrossroad

00002-1 SANT N. Fork Edisto R. nr. Branchville, SC

00003-1 SANT South Edisto R. nr Springfield, SC

00004-1 SANT S. Fork Edisto R. nr Canaan, SC

00005-1 SANT Saluda R., SC

00006-1 SOFL Water Conservation 3A15, FL

00007-1 SOFL Water Conservation 3A15, FL

00008-1 SOFL Water Conservation 3A15, FL

00009-1 SOFL Water Conservation U3, FL

00010-1 SOFL Water Conservation U3, FL

00011-1 SOFL Water Conservation U3, FL

Spotted Bass 2 754 365 3.5 0.837 0.147

Spotted Bass 2 262 275 3.5 0.789 0.149

Spotted Bass 2 158 240 2.5 0.486 0.094

Largemouth Bass 1 92 194 2.5 3.078 0.551

Spotted Bass 1 140 235 3.5 3.213 0.601

Channel Catfisha 10 32 160 0.359 0.073

Largemouth Bass 2 588 350 4.5 1.572 0.313

Largemouth Bass 4 252 269 3.0 1.761 0.351

Black Crappie 1 453 304 3.5 0.653 0.125

Black Crappie 1 266 249 2.5 0.153 0.027

Black Crappie 1 140 204 2.5 0.163 0.030

Bluegill Sunfisha 2 31 118 1.108 0.248

Largemouth Bass 1 907 410 9.015 1.803

Largemouth Bass 1 84 180 3.130 0.626

Largemouth Bass 1 517 310 2.860 0.572

Largemouth Bass 1 83 170 2.725 0.545

Largemouth Bass 1 900 390 2.355 0.471

Largemouth Bass 1 1694 507 4.8 21.1 4.22

Largemouth Bass 1 205 250 1.8 4.10 0.82

Largemouth Bass 1 466 325 2.8 7.10 1.42

Largemouth Bass 1 307 301 3.8 3.30 0.66

Largemouth Bass 1 227 273 2.8 1.85 0.37

Largemouth Bass 1 229 264 3.8 3.15 0.63
REPORT DOCUMENTATION PAGE REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188 

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and 

maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, 

including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, 

VA 22202-4302, and to the Office of Management and Budget. Paperwork Reduction Project (0704-0188), Washington, DC 20503. 

1. AGENCY USE ONLY (Leave Blank) 2. REPORT DATE 

September2001

3. REPORT TYPE AND DATES COVERED 

Biological Science Report

4. TITLE AND SUBTITLE 

A National Pilot Study of Mercury Contamination of Aquatic Ecosystems Along Multiple

Gradients: Bioaccumulation in Fish

5. FUNDING NUMBERS 

6.AUTHOR(S) 

William G. Brumbaugh, David P. Krabbenhoft, Dennis R. Helsel, James G. Wiener, Kathy R.

Echols

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

U.S. Department of the Interior

U.S. Geological Survey, Biological Resources Division

Columbia Environmental Research Center

Columbia, MO 65201

8. PERFORMING ORGANIZATION 

REPORT NUMBER 

USGS/BRD/BSR—2001-0009

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 

U.S. Department of the Interior

U.S. Geological Survey

Biological Resources Division

Reston, VA 20192

10. SPONSORING/MONITORING 

AGENCY REPORT NUMBER 

11. SUPPLEMENTARY NOTES 

12a. DISTRIBUTION/AVAILABILITY STATEMENT 

Release unlimited. Available from the National Technical Information Service, 5285 Port Royal

Road, Springfield, VA 22161 (1-800-553-6847 or 703-487-4650). Available to registered users

from the Defense Technical Information Center, Attn: Help Desk, 8722 Kingman Road, Suite

0944, Fort Belvoir, VA 22060-2618 (1-800-225-3842 or 703-767-9050).

12b. DISTRIBUTION CODE 

13. ABSTRACT (Maximum 200 words) Bioaccumulation of mercury (Hg) in fish sampled at 106 sites from 20 U.S. watershed basins was

evaluated in relation to species, Hg and methylmercury (MeHg) in surficial sediment and water, and watershed characteristics.

Bioaccumulation of Hg was strongly (positively) correlated with MeHg in water but only moderately with the MeHg in sediment or

total Hg in water. The best model for predicting Hg bioaccumulation included MeHg in water, pH of the water, % wetlands in the

basin, and the AVS content of the sediment; however, MeHg in water explained most of the model variability. Based on our data,

a MeHg water concentration of 0.12 ng/L was on average, associated with a fish fillet Hg concentration of 0.3 mg/kg wet weight

for an age-3 fish when all species were considered. For age-3 largemouth bass, a MeHg water concentration of 0.058 ng/L was

associated with the 0.3 mg/kg fillet concentration. Based on rankings for Hg in sediment, water, and fish, sampling sites from the

following five study basins had the greatest Hg contamination: Nevada Basin and Range, South Florida Basin, Sacramento River

Basin (California), Santee River Basin and Coastal Drainages (South Carolina), and the Long Island and New Jersey Coastal

Drainages.

14. SUBJECT TERMS (key words) 

Mercury, methylmercury, bioaccumulation, fish, water, sediment

15. NUMBER OF PAGES

iii + 25 

16. PRICE CODE 

17. SECURITY CLASSIFICATION 

OF REPORT 

Unclassified

18. SECURITY CLASSIFICATION 

OF THIS PAGE 

Unclassified

19. SECURITY CLASSIFICATION 

OF ABSTRACT 

Unclassified

20. LIMITATION OF ABSTRACT 

Unlimited

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