National Water-Quality Assessment Program 

Toxic Substances Hydrology Program 

Mercury in Fish, Bed Sediment, and Water from 

Streams Across the United States, 1998–2005

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2009–5109
Cover:

Center: Wetland-basin stream site. (Photograph by Dennis A. Wentz, U.S. Geological Survey.)

Insets left to right: 

Inset 1: Urban-basin stream site. (Photograph by Barbara C. Scudder, U.S. Geological Survey.) 

Inset 2: Mined-basin stream site. (Photograph by Barbara C. Scudder, U.S. Geological Survey.) 

Inset 3: Forested-basin stream site. (Photograph by Faith A. Fitzpatrick, U.S. Geological Survey.) 

Inset 4: Agricultural-basin stream site. (Photograph by Barbara C. Scudder, U.S. Geological Survey.)
Mercury in Fish, Bed Sediment, and 

Water from Streams Across the 

United States, 1998–2005

By Barbara C. Scudder, Lia C. Chasar, Dennis A. Wentz, Nancy J. Bauch, 

Mark E. Brigham, Patrick W. Moran, and David P. Krabbenhoft

National Water-Quality Assessment Program

Toxic Substances Hydrology Program

Scientific Investigations Report 2009-5109

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2009

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

To order this and other USGS information products, visit http://store.usgs.gov

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Scudder, B.C., Chasar, L.C., Wentz, D.A., Bauch, N.J., Brigham, M.E., Moran, P.W., and Krabbenhoft, D.P., 2009, 

Mercury in fish, bed sediment, and water from streams across the United States, 1998–2005: U.S. Geological Survey 

Scientific Investigations Report 2009–5109, 74 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with reliable scientific information 

that helps to enhance and protect the overall quality of life and that facilitates effective management of water, 

biological, energy, and mineral resources (http://www.usgs.gov/). Information on the Nation’s water resources 

is critical to ensuring long-term availability of water that is safe for drinking and recreation and is suitable 

for industry, irrigation, and fish and wildlife. Population growth and increasing demands for water make the 

availability of that water, now measured in terms of quantity and quality, even more essential to the long-term 

sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support 

national, regional, State, and local information needs and decisions related to water-quality management and 

policy (http://water.usgs.gov/nawqa). The NAWQA Program is designed to answer: What is the quality of our 

Nation’s streams and groundwater? How are conditions changing over time? How do natural features and 

human activities affect the quality of streams and groundwater, and where are those effects most pronounced? 

By combining information on water chemistry, physical characteristics, stream habitat, and aquatic life, the 

NAWQA Program aims to provide science-based insights for current and emerging water issues and priorities. 

During 1991–2001, the NAWQA Program completed interdisciplinary assessments and established a baseline 

understanding of water-quality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study 

Units (http://water.usgs.gov/nawqa/studyu.html). 

National and regional assessments are ongoing in the second decade (2001–2012) of the NAWQA Program 

as 42 of the 51 Study Units are selectively reassessed. These assessments extend the findings in the Study 

Units by determining status and trends at sites that have been consistently monitored for more than a decade, 

and filling critical gaps in characterizing the quality of surface water and groundwater. For example, increased 

emphasis has been placed on assessing the quality of source water and finished water associated with many of 

the Nation’s largest community water systems. During the second decade, NAWQA is addressing five national 

priority topics that build an understanding of how natural features and human activities affect water quality, 

and establish links between sources of contaminants, the transport of those contaminants through the 

hydrologic system, and the potential effects of contaminants on humans and aquatic ecosystems. Included are 

studies on the fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation 

of mercury in stream ecosystems, effects of nutrient enrichment on aquatic ecosystems, and transport of 

contaminants to public-supply wells. In addition, national syntheses of information on pesticides, volatile 

organic compounds (VOCs), nutrients, trace elements, and aquatic ecology are continuing. 

The USGS aims to disseminate credible, timely, and relevant science information to address practical and 

effective water-resource management and strategies that protect and restore water quality. We hope this 

NAWQA publication will provide you with insights and information to meet your needs, and will foster 

increased citizen awareness and involvement in the protection and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all water-resource 

issues of interest. External coordination at all levels is critical for cost-effective management, regulation, 

and conservation of our Nation’s water resources. The NAWQA Program, therefore, depends on advice 

and information from other agencies—Federal, State, regional, interstate, Tribal, and local—as well as 

nongovernmental organizations, industry, academia, and other stakeholder groups. Your assistance and 

suggestions are greatly appreciated.

 Matthew C. Larsen

Associate Director for Water
iv

This page intentionally left blank.
v

Contents

Foreword ........................................................................................................................................................iii

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

Introduction ....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................2

Study Design..........................................................................................................................................3

Methods...........................................................................................................................................................5

Field Data Collection.............................................................................................................................5

Ancillary Data Collection.....................................................................................................................6

Laboratory Analyses.............................................................................................................................8

Data Analyses........................................................................................................................................8

Quality Control.......................................................................................................................................9

Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water.........................................9

Fish ..................................................................................................................................................10

Bed Sediment ......................................................................................................................................19

Stream Water ......................................................................................................................................23

Comparisons to Benchmarks and Guidelines.........................................................................................27

Comparisons Among Fish, Bed Sediment, and Stream Water.............................................................27

Comparisons Between Mined and Unmined Basins .............................................................................30

Factors Related to Mercury Bioaccumulation in Fish ...........................................................................32

Comparisons Among Land-Use/Land-Cover Categories .............................................................32

Fish Species-Specific Relations with Environmental Characteristics ......................................33

Bed-Sediment Relations with Environmental Characteristics ............................................................42

Stream-Water Relations with Environmental Characteristics ............................................................46

Discussion of Findings and Comparison with Other Studies................................................................46

Summary and Conclusions.........................................................................................................................50

Acknowledgments.......................................................................................................................................51

References....................................................................................................................................................51

Appendix 1. Definitions for variable abbreviations used in tables 5 and 6.....................................72
vi

Figures

Figure 1. Map showing streams sampled for mercury, 1998–2005 .............................. 4

Figure 2. Graph showing land-use/land-cover categories for basins sampled for mercury, 

1998–2005, and for all U.S. stream basins ................................................ 5

Figure 3. Map showing sites in mined basins sampled for mercury, 1998–2005, and all 

known gold and mercury production mining sites .................................... 7

Figure 4. Map showing spatial distribution of fish species most commonly 

sampled for mercury, 1998–2005 ......................................................... 11

Figure 5. Map showing spatial distribution of total mercury concentrations in game fish, 

1998–2005 .................................................................................... 13

Figure 6. Graph showing frequency distribution of total mercury concentrations in fish, 

1998–2005 .................................................................................... 14

Figure 7. Map showing spatial distribution of length-normalized total mercury 

concentrations in largemouth bass, 1998–2005.......................................... 15

Figure 8. Map showing spatial distribution of length-normalized total mercury 

concentrations in smallmouth bass, 1998–2005.......................................... 16

Figure 9. Map showing spatial distribution of length-normalized total mercury 

concentrations in rainbow-cutthroat trout, 1998–2005 ................................. 17

Figure 10. Map showing spatial distribution for percentiles of length-normalized total 

mercury concentrations in brown trout, 1998–2005 .................................... 18

Figure 11. Map showing spatial distribution of total mercury concentrations in bed 

sediment, 1998–2005 ........................................................................ 20

Figure 12. Graphs showing frequency distribution of mercury concentrations in 

bed sediment, 1998–2005 .................................................................. 21

Figure 13. Map showing spatial distribution of methylmercury concentrations in 

bed sediment, 1998–2005 .................................................................. 22

Figure 14. Map showing spatial distribution of total mercury concentrations in 

unfiltered stream water,1998–2005 ...................................................... 24

Figure 15. Graphs showing frequency distribution of mercury concentrations 

in unfiltered water, 1998–2005 ............................................................ 25

Figure 16. Map showing spatial distribution of methylmercury concentrations in 

unfiltered stream water, 1998–2005 ...................................................... 26

Figure 17. Boxplot showing statistical distributions of mercury concentrations in fish, 

bed sediment, and water, 1998–2005 ...................................................... 28

Figure 18. Boxplots showing statistical distributions of mercury concentrations in bed 

sediment and unfiltered water at stream sites in mined and unmined basins, 

1998–2005 .................................................................................... 31

Figure 19. Boxplot showing statistical distributions of length-normalized mercury 

concentrations in largemouth bass for U.S. streams draining various 

land-use/land-cover categories, 1998–2005 ............................................. 32
vii

Figures—Continued

Figure 20. Redundancy Analysis (RDA) showing relative importance of selected 

environmental characteristics (blue arrows and labels) to concentrations 

of mercury in largemouth bass (green arrows and labels), 1998–2005 ............... 35

Figure 21. Graph showing correlations between length-normalized mercury 

concentrations in fish and selected environmental characteristics, 1998–2005 ... 36

Figure 22. Graphs showing Biota Accumulation Factors (BAF) for fish in relation to 

selected environmental characteristics, 1998–2005 .................................... 41

Figure 23. Graphs showing correlations between mercury in bed sediment and 

selected environmental characteristics in unmined basins, 1998–2005 ............ 43

Figure 24. Graphs showing correlations between mercury in unfiltered water and 

selected environmental characteristics in unmined basins, 1998–2005 ............ 47

Tables

Table 1. Number of sites on United States streams sampled for mercury, 1998–2005 ...... 3

Table 2. Summary of fish species sampled for mercury in U.S. streams, 1998–2005 ......... 10

Table 3A. Summary statistics for mercury in U.S. streams, 1998–2005: 

Total mercury in fish ........................................................................ 12

Table 3B. Summary statistics for mercury in U.S. streams, 1998–2005: Total and 

methylmercury and ancillary chemical characteristics of bed sediment ............ 19

Table 3C. Summary statistics for mercury in U.S. streams, 1998–2005: Total and 

methylmercury and ancillary water quality characteristics of unfiltered 

stream water.................................................................................. 23

Table 4A. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish 

from U.S. streams, 1998–2005: BAFs for fish with respect to water and bed 

sediment, all species........................................................................ 28

Table 4B. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish 

from U.S. streams, 1998–2005: BAFs for fish with respect to water, individual 

species ....................................................................................... 29

Table 4C. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish 

from U.S. streams, 1998–2005: BAFs for fish with respect to bed sediment, 

individual species ........................................................................... 30

Table 5. Spearman rank correlation coefficients (rs) for relations between 

length-normalized total mercury in composite samples of fish and selected 

environmental characteristics for U.S. streams, 1998–2005 ........................... 34

Table 6. Spearman rank correlation coefficients (rs) for relations between selected 

environmental characteristics from U.S. streams, 1998–2005 ........................ 44

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 

1998–2005 .................................................................................... 59
viii

Conversion Factors

Multiply By To obtain

Length

nanometer (nm) 0.00000003937 inch (in.)

micrometer (μm) 0.00003937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd)

kilometer (m) 0.6214 mile (mi) 

Volume

liter (L) 0.2642 gallon (gal) 

liter (L) 33.82 ounce, fluid (fl. oz)

Area

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.

Concentrations of chemical constituents in water are given either in milligrams per liter 

(mg/L), micrograms per liter (μg/L), or nanograms per liter (ng/L). Concentrations of chemical 

constituents in fish tissue are given in micrograms per gram (μg/g); those in sediment are given 

in nanograms per gram (ng/g).
Mercury in Fish, Bed Sediment, and Water from Streams 

Across the United States, 1998–2005

By Barbara C. Scudder, Lia C. Chasar, Dennis A. Wentz, Nancy J. Bauch, Mark E. Brigham, Patrick W. Moran, 

and David P. Krabbenhoft

Abstract 

Mercury (Hg) was examined in top-predator fish, bed 

sediment, and water from streams that spanned regional and 

national gradients of Hg source strength and other factors 

thought to influence methylmercury (MeHg) bioaccumulation. 

Sampled settings include stream basins that were agricultural, 

urbanized, undeveloped (forested, grassland, shrubland, and 

wetland land cover), and mined (for gold and Hg). Each site 

was sampled one time during seasonal low flow. Predator 

fish were targeted for collection, and composited samples 

of fish (primarily skin-off fillets) were analyzed for total Hg 

(THg), as most of the Hg found in fish tissue (95–99 percent) 

is MeHg. Samples of bed sediment and stream water were 

analyzed for THg, MeHg, and characteristics thought to 

affect Hg methylation, such as loss-on-ignition (LOI, a 

measure of organic matter content) and acid-volatile sulfide 

in bed sediment, and pH, dissolved organic carbon (DOC), 

and dissolved sulfate in water. Fish-Hg concentrations at 27 

percent of sampled sites exceeded the U.S. Environmental 

Protection Agency human-health criterion of 0.3 micrograms 

per gram wet weight. Exceedances were geographically 

widespread, although the study design targeted specific 

sites and fish species and sizes, so results do not represent 

a true nationwide percentage of exceedances. The highest 

THg concentrations in fish were from blackwater coastalplain streams draining forests or wetlands in the eastern and 

southeastern United States, as well as from streams draining 

gold- or Hg-mined basins in the western United States (1.80 

and 1.95 micrograms THg per gram wet weight, respectively). 

For unmined basins, length-normalized Hg concentrations 

in largemouth bass were significantly higher in fish from 

predominantly undeveloped or mixed-land-use basins 

compared to urban basins. Hg concentrations in largemouth 

bass from unmined basins were correlated positively with 

basin percentages of evergreen forest and also woody wetland, 

especially with increasing proximity of these two landcover types to the sampling site; this underscores the greater 

likelihood for Hg bioaccumulation to occur in these types 

of settings. Increasing concentrations of MeHg in unfiltered 

stream water, and of bed-sediment MeHg normalized by LOI, 

and decreasing pH and dissolved sulfate were also important 

in explaining increasing Hg concentrations in largemouth bass. 

MeHg concentrations in bed sediment correlated positively 

with THg, LOI, and acid-volatile sulfide. Concentrations of 

MeHg in water correlated positively with DOC, ultraviolet 

absorbance, and THg in water, the percentage of MeHg in bed 

sediment, and the percentage of wetland in the basin.

Introduction 

Mercury (Hg) is a global pollutant that ultimately makes 

its way into every aquatic ecosystem through the hydrologic 

cycle. Anthropogenic (human-related) sources are estimated 

to account for 50–75 percent of the annual input of Hg to the 

global atmosphere and, on average, 67 percent of the total Hg 

in atmospheric deposition to the United States (Meili, 1991; 

U.S. Environmental Protection Agency, 1997; Seigneur and 

others, 2004). Elevated Hg concentrations that are attributed 

to atmospheric deposition have been documented worldwide 

in aquatic ecosystems that are remote from industrial sources 

(Fitzgerald and others, 1998). 

Methylation—the microbially mediated conversion of 

inorganic Hg to the organic form, methylmercury (MeHg)—is 

the single most important step in the environmental Hg cycle 

because it greatly increases Hg toxicity and bioaccumulation 

potential. Laboratory studies estimate the bioaccumulation 

potential for MeHg to be a thousand-fold that of inorganic 

Hg (Ribeyre and Boudou, 1994). In aquatic ecosystems, 

MeHg is found in elevated concentrations in top predators, 

and physiological effects have been demonstrated at low 

concentrations (Briand and Cohen, 1987; Eisler, 1987; Wiener 

and Spry, 1996; U.S. Environmental Protection Agency, 2001; 

Rumbold and others, 2002; Tchounwou and others, 2003; 

Yokoo and others, 2003; Eisler, 2004). The process by which 

Hg is accumulated into the lower trophic levels of aquatic 

food webs is not well understood (Wiener and others, 2003). 

Although diet has been demonstrated to be the dominant 

mechanism of MeHg uptake in fish (Hall and others, 1997), 

factors such as size, age, community structure, feeding habits, 

and food-chain length are also important in the ultimate MeHg 

fish-tissue concentration (Wong and others, 1997; Atwell and 

others, 1998; Trudel and others, 2000; Wiener and others, 

2003).
2 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Accumulation of MeHg in fish tissue is considered a 

significant threat to the health of both wildlife and humans. 

Approximately 95 percent or more of the Hg found in most 

fish fillet/muscle tissue is MeHg (Huckabee and others, 1979; 

Grieb and others, 1990; Bloom 1992). Women of child-bearing 

age and infants are particularly vulnerable to effects from 

consumption of Hg-contaminated fish (U.S. Environmental 

Protection Agency, 2001). As of 2006, most States (48; no 

advisories in Alaska or Wyoming), the District of Columbia, 

one territory (American Samoa), and two Tribes have issued 

fish-consumption advisories for Hg (U.S. Environmental 

Protection Agency, 2007). These advisories represent 

14,177,175 lake acres and 882,963 river miles, or 35 percent 

of the Nation’s total lake acreage and about 25 percent of its 

river miles. 

Studies of Hg in aquatic environments have focused 

mostly on lakes, reservoirs, and wetlands because of the 

predominance of lakes with Hg concerns and the importance 

of wetlands in Hg methylation (Bloom and others, 1991; 

Driscoll and others, 1994; Hurley and others, 1995; 

Krabbenhoft and others, 1995; St. Louis and others, 1994 

and 1996; Westcott and Kalff, 1996; U.S. Environmental 

Protection Agency, 1997; Fitzgerald and others, 1998; 

Kotnik and others, 2002). Increasingly, however, studies 

of streams and rivers have contributed significantly to our 

understanding of Hg in these complex ecosystems (Hurley 

and others, 1995; Balogh and others, 1998; Domagalski, 1998; 

Wiener and Shields, 2000; Peckenham and others, 2003; 

Dennis and others, 2005). Sources of regional or national 

fish-Hg data include a U.S. Environmental Protection Agency 

(USEPA) assessment of fish-Hg concentrations in streams 

in the western United States (Peterson and others, 2007); 

the USEPA National Lake Fish Tissue Studies (http://www.

epa.gov/waterscience/fish/study/); the National Contaminant 

Biomonitoring Program (NCBP) of the U.S. Fish and 

Wildlife Service, which later became the Biomonitoring of 

Environmental Status and Trends (BEST) program of the 

U.S. Geological Survey (USGS) (Schmitt and others, 1999, 

2002 and 2004; Hinck and others, 2004a, 2004b, 2006, 2007); 

fish-Hg data compiled from 24 research and monitoring 

programs in northeastern North America (Kamman and others, 

2005); and a large compilation of many State, Federal, and 

Tribal fish-Hg datasets (Wente, 2004; see also http://emmma.

usgs.gov/datasets.aspx).

Currently, it is difficult to directly compare fish-Hg 

concentrations across the Nation by using any compilation 

of fish-Hg data. Several issues must be resolved before 

making effective use of other agencies’ datasets, and review 

of other-agency data is beyond the scope of this report. These 

issues include (1) use of multiple analytical laboratories and 

analytical methods; (2) inconsistent or unknown data quality; 

(3) large variations in sample characteristics, including 

fish species, size, and tissue sampled; (4) incomplete site 

information (for example, locations of some sites are not 

adequately described, and some georeferenced sites may not 

be coded as to site type, such as lake, stream, or reservoir); 

and (5) incomplete sample information (for example, species, 

length, or tissue sampled are not known). Several of these 

issues have been described in greater detail by Wente (2004), 

who has developed a promising statistical modeling approach 

to account for variation in fish-Hg levels by species, size, 

and tissue sampled. It is not known, however, whether the 

approach performs equally well in streams as it does in lakes, 

or whether it performs consistently among various regions of 

the Nation. These issues emphasize the need for a nationwide 

assessment of Hg in streams for fish, bed sediment, and water 

based on consistent methods, as is provided by the study 

described herein.

Purpose and Scope

The primary objective of this report is to describe the 

occurrence and distribution of total mercury (THg) in fish 

tissue in streams in relation to regional and national gradients 

of Hg source strength (including atmospheric deposition, 

gold and Hg mining, urbanization) and other factors that are 

thought to affect Hg bioaccumulation, including wetland and 

other land-use/land-cover types (LULC). Secondary objectives 

are to evaluate THg and MeHg in streambed (bed) sediment 

and stream water in relation to these gradients and to identify 

ecosystem characteristics that favor the production and 

bioaccumulation of MeHg.

The data discussed here are presented by Bauch and 

others (2009). They were aggregated from 6 studies covering 

a total of 367 sites across the Nation (table 1). The majority 

of sites (266) were part of 2 studies conducted collaboratively 

by the USGS National Water-Quality Assessment (NAWQA) 

and Toxics Substances Hydrology Programs. The earliest of 

these, the USGS National Mercury Pilot Study (Krabbenhoft 

and others, 1999; Brumbaugh and others, 2001) sampled 107 

streams across the Nation in 1998. During 2002 and 2004–5, 

an additional 159 streams were sampled by the NAWQA 

Program to complement those sampled during the 1998 

National Mercury Pilot Study; the additional sampling sites 

were chosen to increase spatial coverage and to supplement 

source and environmental factors that previously were 

underrepresented. An additional 101 stream sites were 

sampled as part of 4 regional USGS studies in the CheyenneBelle Fourche River Basins, 1998–99 (S.K. Sando, USGS, 
Introduction 3

unpublished data, 2005); Delaware River Basin, 1999–2001 

(Brightbill and others, 2003); New England Coastal Basins, 

1999–2000 (Chalmers and Krabbenhoft, 2001); and the Upper 

Mississippi River Basin, 2004 (Christensen and others, 2006). 

The regional studies used sample-collection, processing, and 

analytical techniques that were comparable to those in the 

two national studies, thus allowing direct comparison of the 

results.

Study Design

Sampled streams were predominantly within the 

boundaries of NAWQA study areas, which are major 

hydrologic basins (fig. 1). These major hydrologic basins 

encompass 45 percent of the land area of the conterminous 

United States, some portion of each of the 50 States, and 

60–70 percent of water use and population served by public 

water supply (Leahy and others, 1990; Helsel, 1995; Gilliom 

and others, 2001); they represent broad ranges of hydrologic 

and geologic settings, LULC, and population density. Within 

each major basin, streams were selected to represent the 

specific environmental settings of interest. The resulting 

network of sites reflects conditions across the United States. 

Gilliom and others (1995), Helsel (1995), and Horowitz and 

Stephens (2008) discuss the advantages of the NAWQA design 

for sampling small streams at a national scale. 

Specific site-selection criteria within each of the major 

hydrologic basins were based on targeted environmental 

settings thought to be important with regard to the source, 

concentration, or biogeochemical behavior of Hg in aquatic 

ecosystems in that basin (table 7, at back of report). Settings 

of particular interest included agricultural areas (enhanced 

runoff of dissolved and colloidal Hg associated with organic 

matter; particulate Hg from eroded soils); urban areas 

(elevated local depositional sources; enhanced Hg runoff due 

to impervious surfaces); undeveloped areas (atmospheric Hg 

deposition source only); and mined areas (cinnabar mining; 

historical gold mining, in which elemental Hg was used 

as an amalgamating agent). Site categories of agricultural, 

urban, undeveloped, and mixed LULC are consistent with the 

definitions provided by Gilliom and others (2006): 

• Agricultural basins contained greater than 50 percent 

agricultural land and less than or equal to 5 percent 

urban land. 

• Urban basins contained greater than 25 percent urban 

land and less than or equal to 25 percent agricultural 

land. 

• Undeveloped basins were primarily forest, herbaceous 

grassland, shrubland, tundra, and wetland, and 

contained less than or equal to 5 percent urban land 

and less than or equal to 25 percent agricultural land. 

• Mixed-land-use basins included all remaining LULC 

combinations. 

Compared with all streams in the conterminous United States, 

this targeted sampling for Hg may have overrepresented urban 

basins and underrepresented undeveloped basins (fig. 2). 

Slightly more than two-thirds of the sampled Hg sites were 

in the eastern half of the United States compared with the 

western half (west of the Mississippi River). 

Each site was sampled one time, typically during seasonal 

low flow in late summer, for Hg and related constituents in 

top-predator (piscivorous) fish, bed sediment, and stream 

water. This multimedia approach on a national scale was 

considered to be critical for helping to understand controls 

on Hg partitioning, bioaccumulation, and biomagnification 

(Krabbenhoft and others, 1999). Many studies have shown 

that mature top-predator fish generally reflect the highest 

potential Hg concentrations in aquatic food webs (Francesconi 

and Lenanton, 1992; Weiner and Spry, 1996; Boudou and 

Ribeyre, 1997; Morel and others, 1998; Kim and Burggraaf, 

1999). Thus, largemouth bass was the piscivorous fish species 

targeted for collection. At sites where this species was not 

available in sufficient numbers, alternate top-predator fish 

species were collected. 

Table 1. Number of sites on United States streams sampled for 

mercury, 1998–2005.

[Regional studies: CHEY, Cheyenne-Belle Fourche River Basins, 1998–99; 

DELR, Delaware River Basin, 1999–2001; NECB, New England Coastal 

Basins, 1999–2000; and UMIS, Upper Mississippi River Basin, 2004]

Description Number of 

sites

Study components

1998 National Mercury Pilot Study 107

2002–05 Additional national studies 159

Regional studies: CHEY, DELR, NECB, UMIS 101

Total number of sites 367

Mercury data available

Fish mercury data 291

Bed-sediment and water mercury data 352

Fish, bed-sediment, and water mercury data 274
4 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 01

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170°W 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

EXPLANATION

Studies

1998 National Mercury Pilot Study2002–5 studiesCHEY-regional studyDELR-regional studyNECB-regional studyUMIS-regional studyNAWQA study area

Figure 1. Streams sampled for mercury, 1998–2005. (Regional studies are: CHEY, Cheyenne-Belle Fourche River Basins, 1998–9; DELR, Delaware River Basin, 

1999–2001; NECB, New England Coastal Basins, 1999–2000; and UMIS, Upper Mississippi River Basins, 2004.)
Methods 5

11-7093-c Mercury SIR_fig 02

0

10

20

30

40

50

60

70

Hg sampling sites U.S. streams

PROPORTION OF BASINS, IN PERCENT

Agricultural

Urban

Undeveloped

Mixed

Figure 2. Land-use/land-cover 

categories for basins sampled for 

mercury, 1998–2005, and for all U.S. 

stream basins.

Methods

Methods for field data collection, ancillary data 

collection, laboratory analyses, and quality control are 

summarized below and described in detail elsewhere 

(primarily in Bauch and others, 2009; see also Lewis and 

Brigham, 2004; Lutz and others, 2008; Scudder and others, 

2008). All data presented in this report are published in Bauch 

and others (2009).

Field Data Collection

Fish were collected primarily by electrofishing, but 

also by rod/reel and gill nets. Largemouth bass (3-year age 

class) were targeted for collection; alternate top predators 

were selected if largemouth bass were not available. Fish 

were measured for total length and weight. Fish axial muscle, 

primarily skinless fillet (skin-on fillet at four sites in the Upper 

Mississippi River Basin regional study), was dissected from 

most fish in the field or laboratory by use of trace-metal clean 

procedures (Scudder and others, 2008). Fish weighing less 

than about 60 g were processed as whole-body or headless 

fish (15 sites). For all samples except those collected during 

2004–5, 1 to 10 fish (median of 5 fish) of the same species 

and similar size for a site were composited to form a single 

composite sample for analysis of THg. Fish collected during 

2004–5 were processed individually for laboratory analyses. 

After processing, fish samples were frozen until analysis. 

Fish were not collected in the Cheyenne-Belle Fourche River 

Basins.

Bed-sediment samples were collected by use of tracemetal clean sampling techniques (Shelton and Capel, 1994; 

Lutz and others, 2008). A Teflon® or plastic scoop was used 

to remove the upper 2 to 4 cm of bed sediment from 5 to 10 

depositional areas; samples were composited in Teflon® or 

plastic containers into a single sample for each site. Each 

sample was homogenized and subsampled for THg and MeHg, 

loss-on-ignition (LOI, a measure of organic matter content), 

acid-volatile sulfide (AVS), and sand/silt particle size (percent 

less than 63 μm) analyses. Samples were unsieved, so as to 

minimize disturbance of the natural partitioning of MeHg 

and THg in the bed sediment and volatilization of sulfides. 

Subsamples for Hg analysis were placed in Teflon® vials and 

frozen. 

Stream-water samples were collected by dipping Teflon®

or PETG (Nalgene) bottles in the centroid of streamflow 

by use of trace-metal clean techniques (Olson and DeWild, 

1999; Lewis and Brigham, 2004). Unfiltered THg samples 

were acidified to 1 percent HCl by volume; unfiltered MeHg 

samples were stored in a dark cooler until frozen (Krabbenhoft 

and others, 1999). Samples for filtered THg and MeHg 

analyses were passed through quartz fiber filters (47-mm 

diameter, 0.7-μm pore size) in the field, placed into Teflon®

bottles, acidified to 1 percent HCl by volume, and stored in 

the dark. Filters were placed on dry ice and stored frozen 

until analysis of particulate THg and MeHg. Samples were 

collected for additional water-quality characteristics, such 

as pH, specific conductance, ultraviolet (UV) absorbance, 

specific UV absorbance (SUVA) at 254 nanometers (nm), 

and concentrations of dissolved organic carbon (DOC), 

sulfate, and suspended sediment (total suspended sediment 

concentration and fraction less than 63 μm). Streamflow was 

measured one time during Hg sampling at sites without stream 

gages.
6 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Ancillary Data Collection

A detailed description of selected ancillary spatial data 

for each stream basin is given in Bauch and others (2009). 

Stream-basin boundaries were delineated by using 1:24,000- 

to 1:250,000-scale digital topographic and hydrologic 

maps (Nakagaki and Wolock, 2005) or 30-m resolution 

Elevation Derivatives for National Applications (EDNA) 

reach catchments (U.S. Geological Survey, 2002). To verify 

accuracy, additional independent checks were made of 

selected basin boundaries. Natural features and potential 

human influences within the study basins were characterized 

by using Geographic Information System (GIS) coverages. 

LULC information was obtained from 30-m resolution 

National Land Cover Data (NLCD) that were based on 

satellite imagery from the early to mid-1990s (Vogelmann 

and others, 2001) and modified and enhanced (NLCDe 92) 

with Geographic Information Retrieval and Analysis System 

(GIRAS) data to give 25 LULC categories, as described in 

Nakagaki and Wolock (2005). These were the most up-todate, nationally consistent LULC data at the time of our 

analysis. All LULC values used in our report are percentages 

of total basin area. Four initial groupings of sites were based 

on criteria in Gilliom and others (2006): agricultural, urban, 

undeveloped, and mixed. To address the possibility that 

conditions observed at the sampling site were influenced more 

by LULC closer to the site than by LULC farther from the site, 

LULC percentages were weighted by the inverse Euclidean 

distance from the site and reported as distance-weighted 

LULC. This resulted in a basin-scale percentage for each 

LULC category that was adjusted for spatial proximity to the 

sampling site; an area of a particular LULC category that was 

closer to the site received a higher weight and value than an 

area farther away (Wente, 2000; Falcone and others, 2007). 

Gold and Hg mining can result in significant 

contributions of Hg to aquatic systems, so it was important 

to characterize sites with regard to this particular land use. 

Potential sources of Hg from past or current mining operations 

were determined for each stream basin by using the Mineral 

Availability System/Mineral Industry Location System (MAS/

MILS) database from the Bureau of Mines (V.C. Stephens, 

U.S. Geological Survey, written commun., 2004), which is 

now part of the Mineral Resources Data System (MRDS) of 

the USGS (U.S. Geological Survey, 2004). The sites were 

identified as (1) Hg mining operations, in general, (2) Hg 

“producers,” (3) gold mining operations, in general, and 

(4) gold “producers.” Producers included current or past 

production mining operations. The highest densities of gold 

or Hg production mining sites are in Arkansas, California, 

Colorado, Idaho, Montana, and Nevada. A total of 89 basins 

were designated as “mined” and treated separately for the 

purposes of our data analyses; however, this distinction 

was made only for data analyses in our report and does not 

necessarily imply impacts of mining in these basins (fig. 3). 

In addition, our study was not designed specifically to address 

impacts of mining, so there may be areas of intense gold and 

Hg mining that were not represented. Mined basins in the 

eastern United States represented only gold mining.

Key soil characteristics were compiled from the U.S. 

Department of Agriculture State Soil Geographic (STATSGO) 

database (U.S. Department of Agriculture, 1994). Percent 

organic matter, soil erodibility factor, and land-surface slope 

were from Wolock (1997) and were linked by mapping-unit 

identification code to a 100-m resolution national grid of 

STATSGO geographic mapping units. 

Basin hydrologic data were derived from various sources. 

Mean annual precipitation is the average value predicted 

from the Parameter-elevation Regressions on Independent 

Slopes Model (PRISM) (Daly, Neilson, and Phillips, 1994; 

Daly, Taylor, and Gibson, 1997) based on annual precipitation 

(1961–90) at 2-km resolution obtained from the Spatial 

Climate Analysis Service at Oregon State University, 

Corvallis, Oreg. Mean base-flow index, potential and actual 

evapotranspiration, and topographic-wetness index values 

were as calculated for each basin on national grids of 1 km 

(Wolock and McCabe, 2000; Wolock, 2003a, 2003b; D.M 

Wolock, U.S. Geological Survey, written commun., 2007). 

Data from the National Atmospheric Deposition Program 

(NADP) included information about measured wet Hg 

deposition. Annual precipitation-weighted Hg deposition 

concentrations for sites in the Mercury Deposition Network 

(MDN; Roger Claybrooke, Illinois State Water Survey, written 

commun., 2005) were averaged for 2000–2003. There were 

few MDN sites in the western United States, so the mean 

value for the seven most western MDN sites of the country 

(4.56 μg/m2) was assigned to Western States (Arizona, 

California, Colorado, Idaho, Kansas, Montana, Nebraska, 

Nevada, New Mexico, North Dakota, Oklahoma, Oregon, 

South Dakota, Utah, Washington, and Wyoming). Mean 

basin wet-deposition concentrations of Hg were computed by 

overlaying the basins with the average Hg deposition maps for 

2000 through 2003. Finally, Hg loading rates were computed 

by multiplying the MDN basin-averaged concentrations by the 

mean annual modeled PRISM precipitation (Daly, Neilson, 

and Phillips, 1994; Daly, Taylor, and Gibson, 1997). In 

addition, wet, dry, and THg deposition rates were estimated by 

using modeled results from Seigneur and others (2004).
Methods

7

Figure 3. Sites in mined basins sampled for mercury, 1998–2005, and all known gold and mercury production mining sites (present and historical). [Locations for production 

mining sites from Mineral Availability System-Mineral Industry Location System of the U.S. Bureau of Mines and Mineral Resources Data System of the U.S. Geological Survey) (U.S. Geological Survey, 2004.]

11-7093_fig 03

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined basins sampled for HgGold and Hg production mining sites

100°

90°

80°

70° 110°

120°

30°

40°

40°

30°

75° 70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°
8 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Laboratory Analyses

Fish samples were analyzed only for THg because 

95 percent or more of the Hg found in most fish fillet/muscle 

tissue is MeHg (Huckabee and others, 1979; Grieb and others, 

1990; Bloom 1992). Five laboratories were used for these 

analyses over the course of the study: 

• USGS Columbia Environmental Research Center 

(CERC; 1998 National Mercury Pilot Study),

• USGS National Water Quality Laboratory (NWQL; 

2002 samples; Delaware River Basin regional study, 

2001 samples),

• Texas A&M University Trace Element Research 

Laboratory (TERL; 2004–5 samples),

• USGS Wisconsin Mercury Research Laboratory 

(WMRL; Delaware River Basin regional study, 1999 

samples; New England Coastal Basins regional study), 

and

• River Studies Center, University of Wisconsin, La 

Crosse, Wis. (Upper Mississippi River Basin regional 

study, 2004 samples). 

Analytical Hg procedures for all laboratories except 

TERL included digestion and quantification with cold vapor 

atomic fluorescence spectroscopy (CVAFS) according to 

USEPA Methods 3052 and 7474, or modifications of USEPA 

Method 1631 Revision E (U.S. Environmental Protection 

Agency, 1996a and b, 2002; Olson and DeWild, 1999; 

Brumbaugh and others, 2001). The TERL analyzed fish 

samples for Hg by thermal decomposition, amalgamation, and 

atomic absorption spectrophotometry according to USEPA 

Method 7473 (U.S. Environmental Protection Agency, 1998). 

Fish ages were estimated from sagittal otoliths, scales, or 

spines by the CERC (1998 samples) or the USGS South 

Carolina Cooperative Fish and Wildlife Research Unit 

(Columbia, S.C.; 2002 and 2004–05 samples) (Jearld, 1983; 

Porak and others, 1986; Brumbaugh and others, 2001). 

Bed sediment, stream water, and suspended particulate 

material were analyzed for THg and MeHg by the WMRL in 

Middleton, Wis. THg in stream water and particulate material 

was analyzed by use of CVAFS according to USEPA Method 

1631 Revision E (U.S. Environmental Protection Agency, 

1996a and b, 2002), with modifications by the WMRL (Olson 

and others, 1997; Olson and DeWild, 1999; Olund and others, 

2004). MeHg in stream water and particulate samples was 

determined by distillation, aqueous-phase ethylation, gasphase separation, and CVAFS (Bloom, 1989, as modified by 

Horvat and others 1993; Olson and DeWild, 1999; DeWild 

and others, 2002). Bed-sediment samples were analyzed 

for THg and MeHg by use of similar analytical procedures 

as those described above for stream water and particulate 

samples, with some modifications (DeWild and others, 2004; 

Olund and others, 2004). 

Bed-sediment LOI was determined by the WMRL 

by using methods described in Heiri and others (2001). 

AVS was analyzed by the WMRL (1998 samples and New 

England Coastal Basin regional study) or by the USGS 

Sulfur Geochemistry Laboratory (SGL) in Reston, Va. 

(2002 and 2004–5 samples; Upper Mississippi River Basin 

regional study). At the WMRL, AVS samples were acidified 

with hydrochloric acid, anti-oxidant buffer was added, and 

sulfide was determined with an ion-specific electrode (Allen 

and others, 1991). At the SGL, AVS was extracted with 

hydrochloric acid, re-precipitated as silver sulfide, and percent 

by weight of AVS determined gravimetrically (Allen and 

others, 1991; Bates and others, 1993). 

DOC concentrations in water were determined by 

the USGS National Research Program Organic Carbon 

Transformations Laboratory (NRP OCTL) in Boulder, Colo., 

(1998 and 2004–5 samples; Upper Mississippi River Basin 

regional study) or by the WMRL (Cheyenne-Belle Fourche 

River Basins regional study) using a persulfate wet oxidation 

method described in Aiken (1992). For 2002 samples and the 

Delaware River Basin, DOC concentrations were analyzed 

at the NWQL with UV-promoted persulfate oxidation and 

infrared spectroscopy (Brenton and Arnett, 1993). SUVA 

was measured by the NRP OCTL as the UV absorbance of a 

water sample at 254 nm, divided by the DOC concentration 

(Weishaar and others, 2003); SUVA units are liters per 

milligram carbon per meter. Stream-water samples were 

analyzed for sulfate by ion chromatography (Fishman and 

Friedman, 1989).

Data Analyses

Biota Accumulation Factors (BAFs) for fish with respect 

to water and bed sediment were computed as follows: 

10 b w

b

w

BAF = Log (C /C ),

where

C is the wet-weight Hg concentration in the fish,

in milligrams per kilogram and,

C is the MeHg concentration in filtered water,

in milligrams per liter, or the MeHg

concentration in bed sediment, in milligrams

 per kilogram.

(1)
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water 9

Although fish-Hg concentrations on a wet-weight (ww) basis 

were used for computing water BAFs (Watras and Bloom, 

1992), fish-Hg concentrations on a dry-weight (dw) basis were 

used for sediment BAFs because only dry-weight-based bed 

sediment values were available. Higher BAFs indicate greater 

differences between Hg concentrations in fish with respect to 

Hg concentrations in water or bed sediment.

Concentrations of Hg in each composite sample of fish 

were normalized by the mean fish length for that sample 

(units are micrograms per gram per meter), and these 

length-normalized Hg concentrations for fish were used in 

comparisons to environmental characteristics. This was done 

to minimize the effect of age and growth rate on evaluations of 

any relations to environmental characteristics. Previous studies 

have shown that Hg concentrations in fish tend to increase 

with fish age, and length is commonly used as a surrogate for 

age in normalizing Hg concentrations. 

Concentrations of THg and MeHg in unfiltered water 

were used for analysis of Hg in streams. For those sites with 

filtered and particulate THg and MeHg data but no unfiltered 

data, unfiltered THg and MeHg concentrations were computed 

by summing filtered and particulate fractions. Suspended 

particulate concentrations were expressed on a mass basis 

(nanograms of Hg per gram of particulate material) by 

dividing particulate Hg concentrations by suspended-sediment 

concentrations (DeWild and others, 2004). 

Parametric statistical tests were used, where possible, 

after transforming data to meet assumptions of normal 

distributions; nonparametric tests were used when 

normalization was not possible. Mann-Whitney U tests were 

used to assess differences in Hg concentrations between 

sites grouped as mined basins compared to unmined 

basins. Because of concerns with unequal sample sizes 

among groups and non-normality of residuals, one-way 

ANOVA tests on ranked data were used to compare Hg 

concentrations among LULC groups for selected media. 

Principal Components Analysis (PCA) and Spearman rank 

correlation (rs

, Spearman correlation coefficient) were used 

to select the subset of variables for stepwise multiple-linear 

regression and Redundancy Analysis (RDA); less responsive 

metrics were eliminated. PCA and RDA were done in 

CANOCO Version 4.5 with centering and standardization of 

previously transformed variables (ter Braak, 2002). RDA is 

a constrained form of multiple regression and was used with 

forward selection as an alternative exploratory tool to evaluate 

which suite of environmental characteristics best explained 

the variation of Hg concentrations in fish, bed sediment, and 

water. The reduced-model RDA was used with Monte Carlo 

testing. Data Desk version 6.1 (Data Description, Inc., 1996) 

and S-Plus version 7.0 (Insightful Corporation, 1998–2005) 

were used for Spearman correlations, Mann-Whitney U tests, 

ANOVA tests, and stepwise multiple-linear regression. All 

statistical tests were considered significant at a probability 

level of 0.05 unless otherwise stated. 

Quality Control

The quality (bias and variability) of Hg data for fish was 

evaluated by using laboratory blank and replicate samples, 

spike recoveries, and reference materials; quality-assurance 

results are presented in Bauch and others (2009). Each type of 

quality-control sample was not available for all laboratories. 

Results indicated low bias and good reproducibility in Hg data 

for fish samples analyzed at the CERC, TERL, and University 

of Wisconsin-La Crosse. Results for fish samples analyzed at 

the NWQL in 2002 indicated possible low bias and moderate 

variability in fish-Hg concentrations, and this may have 

reduced the strength of some relations between fish Hg and 

environmental characteristics. The quality of bed-sediment 

and water THg and MeHg data was investigated through 

blank and replicate samples collected in the field (Bauch 

and others, 2009). Unfiltered, filtered, and particulate THg 

and MeHg generally were either not detected in most blank 

samples or were detected at concentrations that would not 

affect data analysis. However, overlap of some high particulate 

THg concentrations in blanks with low concentrations in 

environmental samples may indicate a small positive bias 

of particulate THg for some environmental data. Variability 

in THg and MeHg determined from field-replicate samples 

depended on the type of sample—unfiltered or filtered water, 

particulate, or bed sediment—and concentrations being 

analyzed; however, there was no effect on data analysis. 

Spatial Distribution of Mercury in Fish, 

Bed Sediment, and Stream Water

The spatial distributions of Hg in fish, bed sediment, and 

water were assessed by use of maps and exceedance frequency 

distributions. The majority of sites were in the eastern half of 

the United States, and most but not all sites in mined basins 

were in the western half of the United States (west of the 

Mississippi River; fig. 3). 
10 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Fish

No one fish species could be used across the United 

States for comparative assessment of fish Hg accumulation. 

Fish were collected at 291 sites, and 34 fish species made 

up the total set of samples (table 2). The most commonly 

collected fish were largemouth bass (Micropterus salmoides; 

62 sites), smallmouth bass (Micropterus dolomieu; 60 sites), 

brown trout (Salmo trutta; 22 sites), pumpkinseed (Lepomis 

gibbosus; 18 sites), rock bass (Ambloplites rupestris; 17 

sites), spotted bass (Micropterus punctulatus; 14 sites), 

rainbow trout (Oncorhynchus mykiss; 14 sites), cutthroat 

trout (Oncorhynchus clarkii; 12 sites), and channel catfish 

(Ictalurus punctatus; 12 sites) (fig. 4). Hg comparisons across 

species should be viewed with caution as different species 

accumulate Hg at different rates, and concentrations generally 

increase with increasing age or length of the fish. 

Hg was detected (> 0.01 μg/g THg ww) in all fish 

collected and ranged from 0.014 to 1.95 μg/g ww; the median 

value was 0.169 μg/g ww (table 3A). The highest fish-Hg 

concentrations among all sampled sites generally were for 

fish collected from forest- or wetland-dominated coastal-plain 

streams in the eastern and southeastern United States and from 

streams that drain gold- or Hg-mined basins in the western 

United States (fig. 5). The highest value (1.95 μg/g ww) 

was from a composite sample of smallmouth bass from the 

Carson River at Dayton, Nev., a site in a basin with known Hg 

contamination from historical gold mining. The next highest 

value (1.80 μg/g ww) was from a composite of largemouth 

bass from an unmined basin—the North Fork Edisto River 

near Fairview Crossroads, S.C. Largemouth, smallmouth, and 

spotted bass had the highest mean and median concentrations, 

whereas brown trout, rainbow-cutthroat trout, and channel 

catfish had the lowest. Concentrations of Hg in trout were 

generally low compared to those in all other sampled fish, 

and the median value was less than 0.1 μg/g ww (table 3A). 

Fish-Hg concentrations were less than about 0.33 μg/g ww 

at 75 percent of sites and less than about 0.60 μg/g ww at 

90 percent of sites (fig. 6).

Table 2. Summary of fish species sampled for mercury in U.S. 

streams, 1998–2005.

[Abbreviations: n, number of sites where fish species was collected; gamefish species shown in bold]

Family Common name Latin name n

Bowfins Bowfin Amia calva 1

Catfishes White catfish Ameiurus catus 1

Yellow bullhead Ameiurus natalis 1

Brown bullhead Ameiurus nebulosus 2

Blue catfish Ictalurus furcatus 1

Channel catfish Ictalurus punctatus 12

Flathead catfish Pylodictis olivaris 2

Cichlids Blackchin tilapia Sarotherodon 

melanotheron

1

Minnows Common Carp Cyprinus carpio 1

Creek chub Semotilus atromaculatus 1

Perches Sauger Sander canadensis 1

Walleye Sander vitreus 2

Pikes Chain pickerel Esox niger 6

Sculpins Slimy sculpin Cottus cognatus 2

Suckers White sucker Catostomus commersonii 1

Sunfishes Roanoke bass Ambloplites cavifrons 1

Rock bass Ambloplites rupestris 17

Redbreast sunfish Lepomis auritus 8

Green sunfish Lepomis cyanellus 8

Green × Longear 

Sunfish (hybrid)

Lepomis cyanellus x L. 

megalotis

1

Pumpkinseed Lepomis gibbosus 18

Bluegill Lepomis macrochirus 8

Longear sunfish Lepomis megalotis 1

Shoal bass Micropterus cataractae 2

Red-eyed bass Micropterus coosae 1

Smallmouth bass Micropterus dolomieu 60

Spotted bass Micropterus punctulatus 14

Largemouth bass Micropterus salmoides 62

Black crappie Pomoxis nigromaculatus 2

Trout Cutthroat trout Oncorhynchus clarkii 12

Rainbow trout Oncorhynchus mykiss 14

Mountain whitefish Prosopium williamsoni 3

Brown trout Salmo trutta 22

Dolly Varden Salvelinus malma 2

Total number of fish sampling sites 291
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water

11

11-7093_fig 04

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Largemouth bassSmallmouth bassRock bassSpotted bassPumpkinseedRainbow-Cutthroat troutBrown troutChannel catfish

100°

90°

80°

70° 110°

120°

30°

40°

40°

30°

75° 70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 4. Spatial distribution of the fish species most commonly sampled for mercury, 1998–2005.
12 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 3A. Summary statistics for mercury in U.S. streams, 1998–2005: Total mercury in fish. [THg concentrations are in micrograms per gram on a wet-weight basis; fish length in centimeters. Abbreviations: n, number of samples (with number of samples from mined basins in parentheses for family and species level); Std Dev, standard deviation; –, not computed] Parameter Site grouping Mercury concentration Fish length n Mean Median Std Dev Minimum Maximum Mean Range All fish All sites 0.261 0.169 0.278 0.014 1.95 – – 291 Sites in unmined basins 0.238 0.165 0.241 0.014 1.80 – – 232 Sites in mined basins 0.351 0.235 0.379 0.020 1.95 – – 59 All fish, by family Sunfish family All sites 0.304 0.213 0.289 0.020 1.95 – – 203 (33) Trout family All sites 0.109 0.089 0.115 0.014 0.588 – – 53 (20) Catfish family All sites 0.200 0.097 0.351 0.036 1.58 – – 19 (3) Pike family All sites 0.344 0.288 0.251 0.060 0.769 – – 6 (0) Perch family All sites 0.517 0.635 0.232 0.250 0.666 – – 3 (3) Other All sites 0.078 0.060 0.051 0.030 0.175 – – 7 (0) Species most commonly sampled Largemouth bass All sites 0.460 0.333 0.346 0.081 1.80 29.7 15.8 - 47.0 62 (10) Smallmouth bass All sites 0.245 0.204 0.257 0.020 1.95 26.2 12.6 - 41.5 60 (9) Rock bass All sites 0.175 0.139 0.118 0.039 0.506 16.0 8.96 - 20.8 17 (0) Spotted bass All sites 0.485 0.420 0.228 0.148 0.943 28.8 17.2 - 37.0 14 (5) Pumpkinseed All sites 0.139 0.111 0.095 0.042 0.379 10.6 6.66 - 13.7 18 (2) Rainbow-cutthroat trout All sites 0.110 0.070 0.137 0.014 0.588 20.7 13.2 - 28.1 26 (7) Brown trout All sites 0.113 0.091 0.098 0.014 0.457 28.0 19.4 - 51.3 22 (9) Channel catfish All sites 0.084 0.080 0.029 0.036 0.131 33.3 16.0 - 47.7 12 (2)
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water

13

11-7093_fig 05

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined Unmined

Less than or equal to 0.1Greater than 0.1 to 0.2Greater than 0.2 to 0.3Greater than 0.3

Total mercury, game fish,  in micrograms per gram wet weight

100°

90°

80°

70° 110°

120°

30°

40°

40°

30°

75° 70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 5. Spatial distribution of total mercury concentrations in game fish, 1998–2005.
14 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093-c_fig 06

EXCEEDANCE FREQUENCY, IN PERCENT

 TOTAL MERCURY IN FISH,IN MICROGRAMS PER GRAM WET WEIGHT

USEPA criterion for human health = 0.3 μg/g

Concern level for piscivorous mammals = 0.1 μg/g

0.01

0.10

1.00

10.00

0102030405060708090100

Unmined

Mined

Figure 6. Frequency distribution of total mercury concentrations in fish, 1998–

2005, showing the percentage of samples that equalled or exceeded benchmark 

or guideline concentrations. [USEPA methylmercury criterion for human health 

(U.S. Environmental Protection Agency, 2001) = 0.3 μg/g wet weight; concern 

level for piscivorous mammals (Yeardley and others, 1998) = 0.1 μg/g wet weight.]

Distributions of length-normalized THg concentrations 

for the top four fish species collected (largemouth bass, 

smallmouth bass, rainbow-cutthroat trout, and brown trout) 

are each shown separately on U.S. maps in figures 7 through 

10. Largemouth bass were collected across the broadest area 

of all fish species but were mostly in eastern and southern 

U.S. streams (fig. 7). The highest length-normalized THg 

concentrations in largemouth bass were found in coastal 

streams in unmined basins of Louisiana, Georgia, Florida, 

and North and South Carolina; one stream in a mined basin 

from California was in this group of highest fish THg, but 

concentrations at this site were lower than at most of the 

coastal unmined sites in the group. In contrast, smallmouth 

bass were not collected in the southern part of the United 

States but instead were commonly collected in the upper 

Midwest and northeastern United States (fig. 8); the highest 

length-normalized THg concentrations were at western sites 

in mined basins, but also from the Hudson River in New York. 

Rainbow and cutthroat trout were collected only in western 

States and were the primary target top-predator fish for sites 

in Oregon and Washington (fig. 9). Because of their similar 

habitats, feeding habits, and ability to hybridize where their 

ranges overlap, these two species were combined for purposes 

of data analysis. The highest length-normalized THg values in 

rainbow-cutthroat trout were found at stream sites in mined, 

urban, and geothermally affected basins in tributaries to the 

Willamette Basin in western Oregon, and in North Creek near 

Bothell, Wash., an urban site on a tributary to Puget Sound. 

Brown trout were collected in isolated areas across the United 

States, and the highest length-normalized THg concentrations 

for this fish species were at several sites in mined basins of 

Colorado and Nevada and in three unmined, undeveloped 

basins of southern California, Colorado, and New York 

(fig. 10).
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water

15

11-7093_fig 07

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined

Length-normalized total mercury, 

Unmined

 wet-weight basis, largemouth bass,  as percentiles

Less than 25%

25 to 49%50 to 74%75 to 89%

Greater than or equal to 90%

100°

90°

80°

70° 110°

120°

30°

40°

40°

30°

75° 70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 7. Spatial distribution of length-normalized total mercury concentrations in largemouth bass, 1998–2005.
16 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 08

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined

Length-normalized total mercury, 

Unmined

 wet-weight basis, smallmouth bass,  as percentiles

Less than 25%

25 to 49%50 to 74%75 to 89%

Greater than or equal to 90%

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 8. Spatial distribution of length-normalized total mercury concentrations in smallmouth bass, 1998–2005.
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water

17

11-7093_fig 09

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

EXPLANATION

Mined

Length-normalized total mercury, 

Unmined

 wet-weight basis, rainbow-cutthroat trout, as percentiles

Less than 25%

25 to 49%50 to 74%75 to 89%

Greater than or equal to 90%

100°

90°

80°

70° 110°

120°

30°

40°

40°

30°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 9. Spatial distribution of length-normalized total mercury concentrations in rainbow-cutthroat trout, 1998–2005.
18 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 10

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

EXPLANATION

Mined

Length-normalized total mercury, 

Unmined

 wet-weight basis, brown trout,  as percentiles

Less than 25%

25 - 49%50 - 74%75 - 89%

Greater than or equal to 90%

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 10. Spatial distribution for percentiles of length-normalized total mercury concentrations in brown trout, 1998–2005.
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water 19

Bed Sediment

With the exception of sites in mined basins, many high 

THg concentrations in bed sediment were in the northeast; 

however, values in the top quartile of THg concentrations were 

scattered across the United States (fig. 11). Concentrations of 

THg in bed sediment (dry-weight basis) ranged from 0.84 to 

4,520 ng/g (table 3B). Concentrations were less than about 80 

ng/g THg at 75 percent of sites and less than about 250 ng/g at 

90 percent of sites (fig. 12A).

Table 3B. Summary statistics for mercury in U.S. streams, 1998–2005: Total and methylmercury and ancillary chemical characteristics 

of bed sediment.

[Mercury concentrations are on a dry-weight basis. Abbreviations: ng/g, nanograms per gram; μg/g, micrograms per gram; n, number of samples]

Parameter Site grouping Mean Median Std Dev Minimum Maximum n Units Comparison

Methylmercury All sites 1.65 0.510 2.54 0.01 15.6 344 ng/g No significant 

Sites in unmined basins 1.73 0.510 2.62 0.01 15.6 257 difference

Sites in mined basins 1.41 0.516 2.28 0.04 14.6 87

Total mercury All sites 110 31.8 343 0.84 4,520 345 ng/g Mined > Unmined 

Sites in unmined basins 88.7 30.3 243 0.90 2,480 259 (p<0.01)

Sites in mined basins 175 48.5 539 0.84 4,520 86

Methyl/Total mercury All sites 3.24 1.60 4.68 0.020 41.0 337 Percent Unmined > Mined 

Sites in unmined basins 3.26 1.72 4.58 0.020 41.0 253 (p<0.05)

Sites in mined basins 3.18 1.27 5.01 0.024 24.8 84

Loss-on-ignition 

(LOI)

All sites 7.38 4.26 8.14 0.11 43.5 327 Percent No significant 

Sites in unmined basins 8.12 4.50 8.78 0.11 43.5 254 difference

Sites in mined basins 4.78 3.51 4.52 0.50 27.7 73

Methylmercury/LOI All sites 0.227 0.137 0.300 0.0040 2.56 325 (ng/g)/ 

percent

Mined > Unmined 

Sites in unmined basins 0.195 0.125 0.255 0.0040 2.56 252 (p<0.001)

Sites in mined basins 0.338 0.201 0.402 0.0116 1.83 73

Total mercury/LOI All sites 25.3 6.61 129 0.15 1,940 325 (ng/g)/ 

percent 

Mined > Unmined 

Sites in unmined basins 10.1 5.91 14.5 0.15 122 253 (p<0.0001)

Sites in mined basins 78.6 10.5 267 <0.58 1,940 72

Acid-volatile sulfide All sites 84.9 5.34 235 <0.01 2,630 252 μg/g No significant 

Sites in unmined basins 89.9 5.03 258 <0.01 2,630 187 difference

Sites in mined basins 70.4 6.58 149 0.01 690 65

Concentrations of MeHg in bed sediment ranged from 

0.01 to 15.6 ng/g (table 3B). The highest MeHg values were 

from a group of New England coastal streams, including 

sites in mined as well as unmined basins (fig. 13). Some of 

these New England streams, such as the Sudbury River in 

Massachusetts, are unmined but known to have historical 

industrial contamination of Hg in the basin (Massachusetts 

Department of Environmental Protection, 1995; Flannagan 

and others, 1999; Waldron and others, 2000; Wiener and 

Shields, 2000; Chalmers, 2002). About 75 percent of all MeHg 

values were less than 2 ng/g, and 90 percent of concentrations 

were less than about 5 ng/g (fig.12B).
20 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 11

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined Unmined

0.84 to 11.111.2 to 31.731.8 to 81.681.7 to 231

Total mercury, bed sediment, in nanograms per gram dry weight

232 to 4520

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 11. Spatial distribution of total mercury concentrations in bed sediment, 1998–2005. [Percentiles shown: 0 to 24 (white), 25 to 49 (yellow), 50 to 74 (orange),

75 to 89 (red), and greater than or equal to 90 (purple).]
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water 21

A

B

0.10

1.00

10.00

100.00

1000.00

10000.00

0102030405060708090100

Unmined

Mined

Probable effect concentration = 1,060 ng/g

Threshold effect concentration = 180 ng/g

 TOTAL MERCURY IN BED SEDIMENT,IN NANOGRAMS PER GRAM DRY WEIGHT

0.01

0.10

1.00

10.00

100.00

0102030405060708090100

 METHYLMERCURY IN BED SEDIMENT,IN NANOGRAMS PER GRAM DRY WEIGHT

EXCEEDANCE FREQUENCY, IN PERCENT

Figure 12. Frequency distribution of mercury concentrations in bed sediment, 

1998–2005, showing the percentage of samples that equalled or exceeded benchmark 

or guideline concentrations; A, Total mercury; B, Methylmercury. [Probable Effect 

Concentration, consensus-based (MacDonald and others, 2000) = 1,060 ng/g, dry weight; 

Threshold Effect Concentration, consensus-based (MacDonald and others, 2000) = 180 

ng/g dry weight.]
22 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 13

0.01 to 0.130.14 to 0.500.51 to 2.022.03 to 5.03

Methylmercury, bed sediment,  in nanograms per gram dry weight

5.04 to 15.6

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined Unmined

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 13. Spatial distribution of methylmercury concentrations in bed sediment, 1998–2005. [Percentiles shown: 0 to 24 (white), 25 to 49 (yellow), 

50 to 74 (orange), 75 to 89 (red), and greater than or equal to 90 (purple).]
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water 23

Table 3C. Summary statistics for mercury in U.S. streams, 1998–2005: Total and methylmercury and ancillary water quality 

characteristics of unfiltered stream water.

[Values equal to 1/2 minimum reporting limits were substituted for censored values in computations. Abbreviations: DOC, dissolved organic carbon; UV, 

ultraviolet absorbance at 254 nm; SUVA, specific UV absorbance at 254 nm; nm, nanometers; (L/mg C)/m, liters per milligram carbon per meter; ng/L, 

nanograms per liter; mg/L, milligrams per liter; μS/cm, microsiemens per centimeter at 25 degrees Celsius; n, number of samples]

Parameter Site grouping Mean Median Std Dev Min Max n Units Comparison

Methylmercury All sites 0.19 0.11 0.35 <0.010 4.11 337 ng/L No significant 

Sites in unmined basins 0.20 0.11 0.37 <0.010 4.11 257 difference

Sites in mined basins 0.18 0.10 0.31 <0.010 2.02 80

Total mercury All sites 8.22 2.09 32.8 0.27 446 336 ng/L Mined > Unmined 

Sites in unmined basins 2.96 1.90 5.29 0.27 75.1 250 (p<0.0001)

Sites in mined basins 23.5 3.79 62.1 0.48 446 86

Methyl/Total mercury All sites 7.08 4.60 8.18 0.02 81.5 328 Percent Unmined > Mined 

Sites in unmined basins 7.46 5.35 6.72 0.19 46.8 249 (p<0.0001)

Sites in mined basins 5.87 2.37 11.6 0.02 81.5 79

Specific conductance All sites 389 247 493 15.6 6,080 349 μS/cm Mined > Unmined 

Sites in unmined basins 349 246 467 15.6 6,080 263 (p<0.001)

Sites in mined basins 513 252 551 34.1 2,350 86

pH All sites 7.48 7.50 0.73 3.30 10.1 352 Standard units Mined > Unmined 

Sites in unmined basins 7.38 7.42 0.72 5.50 10.1 264 (p<0.01)

Sites in mined basins 7.78 7.90 0.70 3.30 9.00 88

Suspended sediment All sites 75.4 7.00 501 0 6,170 177 mg/L No significant 

Sites in unmined basins 26.3 7.00 53.1 0 391 130 difference

Sites in mined basins 212 8.00 966 1 6,170 47

DOC All sites 5.09 3.80 6.49 0.34 76.9 349 mg/L Unmined > Mined 

Sites in unmined basins 5.82 4.38 7.29 0.34 76.9 261 (p<0.0001)

Sites in mined basins 2.90 2.61 1.77 0.40 11.6 88

UV All sites 0.15 0.11 0.17 0.003 1.2 138 Dimensionless Unmined > Mined 

Sites in unmined basins 0.18 0.13 0.18 0.005 1.2 107 (p<0.001)

Sites in mined basins 0.08 0.07 0.05 0.003 0.3 31

SUVA All sites 2.92 2.80 1.43 0.30 15.5 138 (L/mg C)/m No significant 

Sites in unmined basins 2.92 2.90 0.91 0.60 5.7 107 difference

Sites in mined basins 2.92 2.60 2.52 0.30 15.5 31

Sulfate All sites 45.9 10.9 123 0.09 954 343 mg/L Mined > Unmined 

Sites in unmined basins 28.3 9.95 73.7 0.09 954 263 (p<0.01)

Sites in mined basins 104 16.1 208 0.47 860 80

Stream Water

There was wide variation in concentrations of THg 

in unfiltered water across the United States, as one might 

expect for a dataset that included sites that were relatively 

pristine to sites in gold- or Hg-mined basins (table 3C; 

fig. 14). Concentrations of unfiltered THg ranged from 0.27 

to 446 ng/L, and the median value was 2.09 ng/L. THg 

concentrations were less than about 4 ng/L at 75 percent 

of sites and less than about 9 ng/L at 90 percent of sites 

(fig. 15A). 

Concentrations of MeHg in unfiltered water were 

somewhat less variable than for THg across sites (fig. 16). 

Values ranged from less than 0.01 to 4.11 ng/L, and the 

median MeHg concentration was 0.11 (table 3C). MeHg 

concentrations were less than about 0.2 ng/L at 75 percent of 

the sites and less than about 0.4 ng/L at 90 percent of sites 

(fig. 15B). Moreover, MeHg concentrations at 97 percent of 

the sites were less than 0.8 ng/L, which is consistent with 

findings of Krabbenhoft and others (2007), who reviewed 

the literature and found that most surface waters had MeHg 

concentrations in the range of approximately 0.04 to 0.8 ng/L 

(St. Louis and others, 1994; Hurley and others, 1995; Babiarz 

and others, 1998; Bodaly and others, 1998; Gilmour and 

others, 1998; Krabbenhoft and others, 1999).
24 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 14

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined

Total mercury, unfiltered water,  in nanograms per liter

Unmined

0.27 to 1.301.31 to 2.08

2.09 to 3.88

3.89 to 9.00

9.01 to 446

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 14. Spatial distribution of total mercury concentrations in unfiltered stream water,1998–2005. [Percentiles shown: 0 to 24 (white), 

25 to 49 (yellow), 50 to 74 (orange), 75 to 89 (red), and greater than or equal to 90 (purple).]
Spatial Distribution of Mercury in Fish, Bed Sediment, and Stream Water 25

Figure 15. Frequency distribution of mercury concentrations in unfiltered water, 1998–2005, 

showing the percentage of samples that equalled or exceeded benchmark or guideline 

concentrations; A, Total mercury; B, Methylmercury. [Great Lakes States 30-day standard for fisheating wildlife (U.S. Environmental Protection Agency,1997) = 1.3 ng/L.]

TOTAL MERCURY IN UNFILTERED WATER, IN NANOGRAMS PER LITER METHYMERCURY IN UNFILTERED WATER, IN NANOGRAMS PER LITER

EXCEEDANCE FREQUENCY, IN PERCENT

A

B

0.10

1.00

10.00

100.00

1,000.00

0102030405060708090100

Unmined

Mined

30-day standard for fish-eating wildlife = 1.3 ng/L

0.001

0.010

0.100

1.000

10.000

0102030405060708090100
26 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093_fig 16

0 250 500 MILES0 250 500 KILOMETERS

0 100 200 MILES

0 100 200 KILOMETERS

0 500 1,000 MILES

0 500 1,000 KILOMETERS

0 50 100 MILES

0 50 100 KILOMETERS

EXPLANATION

Mined

Methylmercury, unfiltered water,  in nanograms per liter

Unmined

< 0.010 to 0.043

0.044 to 0.1060.107 to 0.1930.194 to 0.395

0.396 to 4.11

100°

90°

80°

70°

110°

120°

30°

40°

40°

30°

75°

70°

45°

40°

155° 160°

22°19°

70° 130°150°170° 170°E

60°

50°

150° 140° 130° 160° 170° 180°

70°

60°

50°

Figure 16. Spatial distribution of methylmercury concentrations in unfiltered stream water, 1998–2005. [Percentiles shown: 0 to 24 (white), 25 to 49 (yellow), 

50 to 74 (orange), 75 to 89 (red), and greater than or equal to 90 (purple).]
Comparisons Among Fish, Bed Sediment, and Stream Water 27

Comparisons to Benchmarks and 

Guidelines

Hg concentrations in fish at most sites (71 percent, 208 of 

291 sites) exceeded the value of 0.1 μg/g THg (ww) that is of 

concern for the protection of fish-eating mammals, including 

mink and otters (fig. 6; Yeardley and others, 1998; Peterson 

and others, 2007). Concentrations at 27 percent of the sites 

(79 of 291) exceeded 0.3 μg/g THg ww in fish. As mentioned 

earlier, most of the Hg found in fish tissue is MeHg (Huckabee 

and others, 1979; Grieb and others, 1990; Bloom 1992), and 

a concentration of 0.3 μg/g MeHg ww in fish is the USEPA 

MeHg criterion for the protection of human health (U.S. 

Environmental Protection Agency, 2001, 2009). 

Two sediment-quality guidelines were used to evaluate 

THg concentrations in bed sediment in our study. These 

consensus-based concentrations of MacDonald and others 

(2000) are currently considered to be the best predictive 

guidelines. However, MacDonald and others (2000) noted 

that the consensus-based Threshold Effect Concentration 

(TEC) for THg correctly predicted toxicity only 34 percent 

of the time, whereas the consensus-based Probable Effect 

Concentration (PEC) correctly predicted toxicity 100 percent 

of the time although based on only 4 values. Because the 

primary toxic form of Hg is MeHg, THg-based toxicity 

estimates are not expected to be highly accurate; however, 

MeHg-based guidelines are unavailable at this time. In our 

study, concentrations of THg at 12 percent of sites (40 of 345 

sites) exceeded the TEC of 180 ng/g. Total Hg in bed sediment 

from six of the sites exceeded the PEC of 1,060 ng/g; these 

sites included two western sites in mined basins (South 

Fork Coeur d’Alene River and Carson River below Carson 

Diversion Dam) and four sites from the northeast (Mousam 

River in Maine; Aberjona, Assabet, and Neponset Rivers near 

Boston, Massachussetts). These results indicate the potential 

for toxic effects on benthic communities at some sites sampled 

as part of this study.

Because of the complicated nature of Hg methylation and 

bioaccumulation, there are currently no national guidelines 

for protection of wildlife from exposure to Hg in water. 

However, of 336 sites with data for THg in unfiltered water, 

THg at three-quarters of the sites exceeded 1.3 ng/L, the 

30-day standard derived by the USEPA for Great Lakes 

States fish-eating wildlife and slightly less than the value of 

1.8 ng/L derived for protection of eagles (U.S. Environmental 

Protection Agency, 1995a, 1995b, 1997; Wolfe and others, 

2007). Concentrations of unfiltered THg at 14 sites exceeded 

26 ng/L, the Interim Canadian Water Quality Guideline for the 

protection of freshwater life (Environment Canada, 2005). All 

but one site with unfiltered THg concentrations greater than 

26 ng/L were in the western United States, in basins where 

gold and (or) Hg mining took place in the past. The exception, 

Whitewood Creek above Lead, S.D., was within the highly 

mineralized area of the Black Hills of South Dakota (Norton, 

1975; Goddard, 1988). There are gold mines in the area that 

could have contributed to high Hg concentrations, but some 

sites in this geochemically rich region are likely to be naturally 

enriched in Hg. The unfiltered THg concentration above Lead 

was similar to that found downstream at Deadwood (75.1 and 

77.8 ng/L, respectively). In contrast to the sampling timing for 

the majority of our synoptic sites, the South Dakota sampling 

was intentionally timed to catch runoff with high-suspended 

sediment loads, when most of the Hg was in the particulate 

phase (Steve Sando, U.S. Geological Survey, oral commun., 

October 2007). 

Comparisons Among Fish, Bed 

Sediment, and Stream Water

Because of bioaccumulation and biomagnification, Hg 

concentrations in fish were several orders of magnitude higher 

than in stream water. Overall, results of our study agreed 

with results in the literature for lakes and other waterbody 

types that have described relatively large differences in 

mean concentrations among fish, bed sediment, and water 

(Wiener and Stokes, 1990; Wiener, 1995; U.S. Environmental 

Protection Agency, 1997; Mason and others, 2000). We found 

a high accumulation of Hg in top-predator fish compared to 

stream water and bed sediment. This accumulation resulted in 

Hg concentrations in top-predator fish that were more than six 

orders of magnitude higher than concentrations of Hg in the 

water that the fish inhabit (fig. 17). 

For all fish species and sites combined, the mean Biota 

Accumulation Factor (BAF, in log10; see equation 1, p. 8) for 

THg in fish relative to MeHg in water was 6.33 L/kg (range 

= 4.36 to 7.59) and for THg in fish relative to MeHg in bed 

sediment was 3.42 (range = 1.52 to 5.09) (table 4A). The 

BAF values determined in our studies were not significantly 

different at sites in mined basins when compared to sites in 

unmined basins. However, mean and median BAF values 

were lower for bed sediment than for water (tables 4B and 

4C). Our mean water BAF value of 6.33 L/kg was slightly 

lower than the national mean BAF value of 6.40 L/kg reported 

by the USEPA for Hg in riverine fish relative to water (U.S. 

Environmental Protection Agency, 2000). 
28 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093-c Mercury SIR_fig 17

x

x

x

xx

x

(337) Number of values

EXPLANATION 

Methylmercury, 

in unfiltered

water

Methylmercury,

in bed 

sediment (dw)

Total mercury,

in fish (ww)

10-9 101 10-1 10-3 10-5 10-7

MERCURY CONCENTRATION, IN PARTS PER MILLION

(337) (344) (291)

VERTICAL LINES —Lines from

rectangle extend to the last data 

point that is < 1.5 times the 

semiquartile range

75th PERCENTILE

MEDIAN

25th PERCENTILE

SEMIQUARTILE 

RANGE

x

o

OUTSIDE VALUE—Values are more 

 than 1.5 times the semiquartile

 range from the top or bottom of the 

 rectangle

FAR OUT VALUE—Values are more than 

 3.0 times the semiquartile range from 

 the top or bottom of the rectangle

Figure 17. Statistical distributions of mercury concentrations in fish, bed sediment, and water, 1998–2005. (dw, dry 

weight; ww, wet weight)

Table 4A. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish from U.S. streams, 1998–2005: BAFs for fish with 

respect to water and bed sediment, all species.

[Abbreviations: BAF, Biota Accumulation Factor; water BAF values are for THg in fish with respect to MeHg in filtered water, in log10 (liters per kilogram); 

sediment BAF values are for THg in fish with respect to MeHg in bed sediment, in log10 (grams per gram); Std Dev, standard deviation; n, number of samples]

Parameter Site grouping Mean Median Std Dev Minimum Maximum n

BAF (water) All sites 6.33 6.33 0.50 4.36 7.59 166

Sites in unmined basins 6.32 6.30 0.50 4.36 7.59 128

Sites in mined basins 6.36 6.35 0.48 5.46 7.47 38

BAF (sediment) All sites 3.42 3.43 0.76 1.52 5.09 229

Sites in unmined basins 3.45 3.43 0.80 1.52 5.09 175

Sites in mined basins 3.32 3.49 0.61 1.92 4.42 54
Comparisons to Benchmarks and Guidelines 29

Table 4B. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish from U.S. streams, 1998–2005: BAFs for fish with 

respect to water, individual species.

[Abbreviations: BAF, Biota Accumulation Factor; water BAF values are for THg in fish with respect to MeHg in filtered water, in log10 (liters per kilogram);

Std Dev, standard deviation; ND, no data; *, insufficient data to compute summary metric; n, number of samples]

Parameter Site grouping Mean Median Std Dev Minimum Maximum n

Largemouth bass All sites 6.61 6.61 0.46 5.22 7.59 38

Sites in unmined basins 6.58 6.60 0.47 5.22 7.59 33

Sites in mined basins 6.82 6.81 0.38 6.34 7.39 5

Smallmouth bass All sites 6.32 6.37 0.48 5.25 7.08 20

Sites in unmined basins 6.41 6.38 0.43 5.25 7.08 15

Sites in mined basins 6.02 5.93 0.53 5.46 6.70 5

Rock bass All sites 6.18 6.24 0.42 5.38 7.00 11

Sites in unmined basins 6.18 6.24 0.42 5.38 7.00 11

Sites in mined basins ND ND ND ND ND ND

Spotted bass All sites 6.59 6.52 0.35 6.09 7.32 12

Sites in unmined basins 6.52 6.40 0.38 6.09 7.32 8

Sites in mined basins 6.73 6.72 0.27 6.42 7.07 4

Pumpkinseed All sites ND ND ND ND ND ND

Sites in unmined basins ND ND ND ND ND ND

Sites in mined basins ND ND ND ND ND ND

Rainbow-cutthroat trout All sites 6.31 6.27 0.40 5.54 7.47 26

Sites in unmined basins 6.26 6.29 0.36 5.54 6.92 19

Sites in mined basins 6.43 6.26 0.51 5.92 7.47 7

Brown trout All sites 6.04 6.04 0.42 5.25 6.96 18

Sites in unmined basins 5.87 6.03 0.34 5.25 6.25 9

Sites in mined basins 6.21 6.34 0.44 5.63 6.96 9

Channel catfish All sites 6.12 6.02 0.36 5.56 6.76 11

Sites in unmined basins 6.08 6.00 0.36 5.56 6.76 9

Sites in mined basins * * * 5.84 6.02 2
30 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Table 4C. Summary statistics for mercury Biota Accumulation Factors (BAFs) for fish from U.S. streams, 1998–2005: BAFs for fish with 

respect to bed sediment, individual species.

[Abbreviations: BAF, Biota Accumulation Factor; sediment BAF values are for THg in fish with respect to MeHg in bed sediment, in log10 (grams per gram); 

Std Dev, standard deviation; ND, no data, *, insufficient data to compute summary metric; n, number of samples]

Parameter Site grouping Mean Median Std Dev Minimum Maximum n

Largemouth bass All sites 3.99 4.08 0.67 2.37 5.09 51

Sites in unmined basins 4.08 4.26 0.71 2.37 5.09 42

Sites in mined basins 3.59 3.57 0.23 3.12 3.91 9

Smallmouth bass All sites 3.43 3.55 0.63 1.73 4.96 44

Sites in unmined basins 3.41 3.40 0.65 1.73 4.96 36

Sites in mined basins 3.50 3.72 0.52 2.39 3.87 8

Rock bass All sites 3.24 3.20 0.71 2.09 4.61 14

Sites in unmined basins 3.24 3.20 0.71 2.09 4.61 14

Sites in mined basins ND ND ND ND ND ND

Spotted bass All sites 4.07 4.07 0.35 3.53 4.51 14

Sites in unmined basins 4.23 4.37 0.32 3.53 4.51 9

Sites in mined basins 3.76 3.78 0.14 3.54 3.90 5

Pumpkinseed All sites 1.91 2.04 0.26 1.52 2.16 5

Sites in unmined basins 1.91 2.04 0.26 1.52 2.16 5

Sites in mined basins ND ND ND ND ND ND

Rainbow-cutthroat trout All sites 3.16 3.13 0.51 2.20 4.10 26

Sites in unmined basins 3.18 3.15 0.47 2.20 3.98 19

Sites in mined basins 3.12 2.93 0.66 2.35 4.10 7

Brown trout All sites 3.03 2.97 0.63 1.92 4.25 17

Sites in unmined basins 3.01 2.75 0.52 2.51 3.82 8

Sites in mined basins 3.04 3.04 0.75 1.92 4.25 9

Channel catfish All sites 2.89 2.75 0.46 2.38 3.67 11

Sites in unmined basins 2.90 2.75 0.46 2.38 3.67 9

Sites in mined basins * * * 2.38 3.32 2

Comparisons Between Mined and 

Unmined Basins

All sites in Hg-mined basins and most sites in goldmined basins were in the western half of the United States 

(fig. 3). Across all sites, fish Hg, as wet weight (raw or lengthnormalized), was not significantly different between sites in 

unmined basins and mined basins, except for smallmouth bass. 

That exception was solely due to a single high outlier for the 

composite sample of smallmouth bass from the Carson River 

at Dayton, Nev., a mined basin. Concentrations of MeHg 

in bed sediment and unfiltered stream water from sites in 

unmined basins were not significantly different from those in 

mined basins; however, THg concentrations were significantly 

higher in bed sediment and stream water from sites in mined 

basins (tables 3B,C; fig.18).

It also should be noted that the percentages of MeHg 

(percent MeHg/THg) in bed sediment and unfiltered water 

were significantly higher in unmined basins (tables 3B, 3C). 

The percentage of MeHg is considered to be a useful 

estimate of methylation efficiency (Gilmour and others, 

1998). Although THg concentrations in unfiltered water 

were higher as a group from streams in mined basins, MeHg 

concentrations from many of these same streams were not 

high relative to those at other sampled sites. More importantly, 

water from many sites in unmined basins with relatively low 

THg was relatively high in MeHg. This finding emphasizes the 

importance of Hg methylation in these ecosystems. 

Examination of Hg relations to environmental 

characteristics for fish species from sites in mined basins 

was limited to largemouth bass and brown trout because of 

small sample sizes for other species. Concentrations of Hg 

in largemouth bass at these sites increased with increasing 

suspended sediment (rs

 = 0.98, p < 0.05, n = 5) and THg in 

unfiltered water (rs

 = 0.67, p < 0.05, n = 9). In contrast, Hg 

in brown trout at sites in mined basins increased significantly 

with increasing MeHg concentration in unfiltered water 

(rs = 0.93, p < 0.01, n = 7). 
Comparisons Between Mined and Unmined Basins 31

11-7093-c_fig 18

x

x

x

x

x

x

(86) (259) (87) (257)

MERCURY CONCENTRATION IN BED SEDIMENT, 

IN NANOGRAMS PER GRAM

10-2 10-1 100 101 102 103 104

Bed Sediment

Unfiltered Water x

x

x

xx

x

o

xx

x x

x

x

(86) (250) (80) (257)

Total mercury Total mercury Methylmercury Methylmercury

MERCURY CONCENTRATION IN UNFILTERED WATER,

 IN NANOGRAMS PER LITER

10-3 10-2 10-1 100 101 102 103

Unmined

Mined

Total mercury Total mercury Methylmercury Methylmercury

(86) Number of values

EXPLANATION 

VERTICAL LINES —Lines from

rectangle extend to the last data 

point that is < 1.5 times the 

semiquartile range

75th PERCENTILE

MEDIAN

25th PERCENTILE

SEMIQUARTILE 

RANGE

x

o

OUTSIDE VALUE—Values are more 

 than 1.5 times the semiquartile

 range from the top or bottom of the 

 rectangle

FAR OUT VALUE—Values are more than 

 3.0 times the semiquartile range from 

 the top or bottom of the rectangle

Figure 18. Statistical distributions of mercury concentrations in bed sediment and unfiltered water at stream 

sites in mined and unmined basins, 1998–2005.
32 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Factors Related to Mercury 

Bioaccumulation in Fish

The remainder of this report describes relations between 

environmental characteristics and length-normalized Hg 

concentrations (micrograms per gram per meter) in unmined 

basins for the fish species that were most commonly collected: 

largemouth bass, smallmouth bass, rainbow-cutthroat 

trout, brown trout, pumpkinseed, rock bass, spotted bass, 

and channel catfish. Data for sites in mined basins were 

removed from these analyses to allow for evaluation of 

factors other than mining that could be important in fish Hg 

bioaccumulation. Most of the 89 sites in mined basins were 

in just two LULC categories: undeveloped (61 sites) or mixed 

(21 sites), and for several fish species—especially brown 

trout—the land-use relation often became weak or nonexistent 

when sites in mined basins were included. 

Comparisons Among Land-Use/Land-Cover 

Categories

Significant differences among LULC categories were 

found for unmined basins (but not for mined basins) with 

respect to Hg. For unmined sites, largemouth bass from 

predominantly undeveloped or mixed-land-use basins were 

significantly higher in Hg than those from urban basins and 

were somewhat higher (p = 0.059) than those from agricultural 

basins (fig. 19); a similar difference was seen between 

undeveloped and urban basins for brown trout. Spotted bass 

from undeveloped basins were somewhat higher in Hg than 

those from agricultural basins (p = 0.051). In contrast to fish 

THg, bed sediment THg (whether normalized by LOI or not) 

and AVS were higher at urban sites compared to agricultural, 

undeveloped, or mixed-land-use sites. Although there were no 

significant differences among LULC categories for MeHg in 

bed sediment, the percentage of MeHg in bed sediment was 

higher at undeveloped sites than at urban sites. Undeveloped 

sites tended to have more wetland and forest cover in the 

basin. Differences among LULC categories were not found for 

THg or MeHg in unfiltered water.

TOTAL MERCURY IN LARGEMOUTH BASS, IN MICROGRAMS PER GRAM PER METER, WET-WEIGHT BASIS

 (8) (11) (10) (22)

Agriculture Urban Undeveloped Mixed

(8) Number of values

EXPLANATION 

100

10-1

101

VERTICAL LINES —Lines from

rectangle extend to the last data 

point that is < 1.5 times the 

semiquartile range

75th PERCENTILE

MEDIAN

25th PERCENTILE

SEMIQUARTILE 

RANGE

Figure 19. Statistical distributions of length-normalized mercury concentrations in largemouth bass for U.S. streams 

draining various land-use/land-cover categories, 1998–2005.
Factors Related to Mercury Bioaccumulation in Fish 33

For those fish species with enough data available to test 

subcategories within the undeveloped LULC category for 

unmined sites (largemouth bass, smallmouth bass, rock bass, 

and brown trout), only largemouth bass showed significant 

differences between two subcategories: Hg concentrations 

in largemouth bass from sites in forested areas with high 

percentages of wetland (>15 percent) were significantly 

higher than in largemouth bass from sites in forested areas 

with low percentages of wetland (<10 percent) (means ± 

standard deviations were 2.92 ± 0.79 (μg/g)/m and 1.28 ± 

0.05 (μg/g)/m, n = 6 and 3, respectively). The comparison 

should be viewed with caution due to the small sample sizes. 

Fish Species-Specific Relations with 

Environmental Characteristics 

Relations between fish Hg and environmental 

characteristics varied in their significance with the group of 

fish examined (table 5). Fish length correlated positively with 

Hg concentration for largemouth bass, rock bass, and rainbowcutthroat trout, so length-normalized Hg concentrations for all 

fish were used in comparisons to environmental characteristics 

(Boudou and Ribeyre, 1983; Ribeyre and Boudou, 1984; 

Goldstein and others, 1996, Brumbaugh and others, 2001). 

Perhaps because of differences in species spatial distribution, 

as well as feeding habits, many statistically significant 

relations to environmental characteristics were found for Hg in 

largemouth bass (n = 52, unmined), whereas none were found 

for smallmouth bass (n = 51, unmined). Sample numbers 

of other fish species were more limited (n < 20, unmined), 

and significant relations also were less common than for 

largemouth bass. The apparent absence of relations for these 

other fish species may have been due in part to small sample 

sizes. Most bass samples in our study were from the eastern 

and southern United States. Largemouth bass appeared to 

be a good indicator for Hg in top-predator fish on the basis 

of (1) its ability to accumulate Hg from a predominantly 

piscivorous diet; (2) relations between Hg in largemouth bass 

and LULC, and MeHg in water or bed sediment; and (3) its 

generally ubiquitous distribution and status as a game fish. 

Factors related to Hg bioaccumulation in largemouth bass 

from unmined basins were subsequently examined in greater 

detail.

Stepwise multiple-linear regression revealed that 

increasing length-normalized Hg concentrations in largemouth 

bass from unmined basins were primarily related to increasing 

basin percentages of evergreen forest and woody wetland, 

especially with increasing proximity of evergreen forest and 

woody wetland to the sampling site (adjusted r2 = 0.66):

LMB ef

ww

LMB

l n[Hg ] = -0.592 + 0.0319 arcsin [L ] 

+ 0.0194 arcsin [L ] ,

where

 Hg is the length-normalized THg concentration

 in largemouth bass, in micrograms per gram 

 

ef

ww

 per meter,

 L is the distance-weighted percentage of basin 

 LULC that is evergreen forest, and

 L is the distance-weighted percentage of basin

 LULC that is woody wetland.

(2)

This equation underscores the sensitivity of these two 

LULC types in comparison to other types with regard to 

Hg bioaccumulation in largemouth bass. Evergreen forest 

and woody wetland were positively correlated with each 

other (rs = 0.60) in the largemouth bass dataset even though 

these characteristics were uncorrelated in the larger dataset. 

Redundancy Analysis (RDA) confirmed the significance 

of these two characteristics and additionally indicated that 

increasing amounts of MeHg in unfiltered stream water and 

LOI normalized MeHg concentrations in bed sediment, and 

decreasing pH and dissolved sulfate, were important for 

explaining variability in fish-Hg concentrations (fig. 20). 

Normalizing MeHg in bed sediment by organic content (as 

measured by LOI) provided a way to account for differences 

in the Hg concentrations of bed sediment collected from zones 

of inorganic sediment as compared to zones of organic muck. 

The similar results from multiple regression and RDA confirm 

the importance of evergreen forest, woody wetland, and 

MeHg in bed sediment and stream water for predicting THg in 

largemouth bass. Details of these relations are provided below.

The strength and direction of relations to LULC varied 

with fish species examined. As mentioned above, as the 

percentage of evergreen forest and woody wetland in the 

basin increased, Hg concentrations in largemouth bass also 

increased (figs. 21A, B). When the percentages of woody 

wetland were distance-weighted, rs

 values for largemouth 

bass increased from 0.62 to 0.72 (table 5). This indicates that 

the closer woody wetland was to the sampling site, the higher 

the concentration of fish Hg. Spotted bass and brown trout 

Hg were also positively correlated with evergreen forest, 

including distance-weighted evergreen forest (fig. 21C, 21D). 

Hg in smallmouth bass did not correlate significantly with 

either forest or wetland. In general, positive relations were 

also seen between fish Hg and either total forest or total 

wetland in the basin; however, the relations were weaker than 

with evergreen forest or woody wetland.
34 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Table 5. Spearman rank correlation coefficients (rs) for relations between length-normalized total mercury 

in composite samples of fish and selected environmental characteristics for U.S. streams, 1998–2005.

[Definitions of variable abbreviations are listed in Appendix 1. Values are for sites in unmined basins only. Color coding of rs

based on p values, p < 0.001 (pink), p < 0.01 (orange), and p < 0.05 (yellow). Abbreviations: n, number of samples available for 

correlation;*, insufficient n or too many values less than the detection limit] Largemouth bass Smallmouth bass Rock bass Spotted bass

PumpkinseedRainbow - cutthroat troutBrown troutChannel catfish

Maximum n 52 51 17 9 16 19 13 10

Streamwater

pH -0.43 -0.03 -0.14 0.24 0.30 0.18 -0.25 -0.49

DOC 0.13 0.01 -0.61 -0.45 0.04 0.28 -0.60 0.15

Sulfate -0.54 -0.23 -0.04 -0.52 -0.41 0.65 -0.65 0.18

UMeHg 0.50 0.19 -0.04 -0.07 0.79 0.24 -0.26 -0.12

UTHg 0.37 0.09 -0.24 -0.17 -0.52 0.54 -0.35 0.21

UMeHg/UTHg 0.36 0.21 -0.42 0.45 0.86 -0.38 -0.52 -0.19

Bed sediment

SMeHg 0.07 -0.01 0.13 0.47 0.67 0.41 0.31 -0.20

STHg -0.09 -0.08 0.35 -0.10 -0.17 0.32 -0.26 -0.08

SMeHg/STHg 0.32 0.04 -0.04 0.73 0.74 0.16 0.85 0.12

SMeHg/LOI 0.35 0.01 -0.03 0.60 0.29 0.56 0.42 -0.27

STHg/LOI -0.03 -0.05 0.07 -0.23 -0.59 0.40 -0.77 0.03

Land use/land cover, percentage of basin area 

SUM_FOREST 0.56 0.25 0.05 0.68 0.19 * 0.62 0.47

EVR_FOREST 0.77 0.18 -0.25 0.72 0.44 * 0.82 0.39

EVR_FOREST_DW 0.77 0.16 -0.37 0.72 0.54 * 0.86 0.31

SUM_WETLAND 0.46 -0.19 -0.52 -0.12 0.25 0.15 -0.18 -0.21

WOODWETLAND 0.62 -0.28 -0.50 0.28 0.32 0.33 -0.19 -0.04

WOODWETLAND_DW 0.72 -0.25 -0.42 0.17 0.35 0.33 -0.25 -0.15

HERBWETLAND -0.01 -0.06 -0.51 -0.15 -0.14 -0.07 -0.38 -0.19

HERBWETLAND_DW 0.06 -0.03 -0.40 -0.15 -0.04 -0.06 -0.37 -0.13

SUM_UNDEVELOPED 0.58 0.22 -0.11 0.70 0.20 -0.60 0.67 0.31

SUM_URBAN -0.48 -0.20 0.13 -0.20 -0.16 * -0.58 0.25

POPDEN00 -0.50 -0.22 0.37 -0.60 -0.39 * -0.75 0.27

SUM_AGRICULTURE -0.14 -0.24 0.14 -0.72 0.24 * -0.78 -0.31

ROW_CROP 0.10 -0.31 0.05 -0.70 0.30 0.08 -0.65 -0.39

ROW_CROP_DW 0.11 -0.31 0.05 -0.70 0.22 * -0.66 -0.30

Other

AWET.PRE 0.28 -0.26 -0.01 0.53 -0.46 * -0.31 0.10

ATOT.SEI -0.16 0.02 0.76 * 0.09 -0.20 -0.32 0.12
Factors Related to Mercury Bioaccumulation in Fish 35

11-7093-c Mercury SIR_fig 20

-1.0 1.2

-1.0 1.0

Sulfate,

unfiltered water

Methylmercury, 

unfiltered water

Methylmercury/Loss on ignition,

bed sediment

 Woody wetland,

distance weighted

RDA Axis 2

RDA Axis 1

pH,

unfiltered water

Fish mercury, wet weight

Fish mercury/length, wet weight

 Evergreen forest, distance weighted

Figure 20. Redundancy Analysis (RDA) showing relative importance of selected environmental characteristics (blue arrows and 

labels) to concentrations of mercury in largemouth bass (green arrows and labels), 1998–2005. (Arrows extending in the same 

direction indicate a positive correlation, arrows in opposite directions indicate a negative correlation, and arrows at right angles 

indicate no correlation; arrow length indicates the relative importance of the variable in the relation.)

LULC data that correlated negatively with fish Hg 

included the percentage of urban developed land and Census 

2000 population density (fig. 21E, largemouth bass; fig 21F, 

brown trout), and percentage of row crops (brown trout only; 

table 5). Chalmers (2002) in the New England Coastal Basins 

regional study data included here, also found a negative 

correlation (rs

 = -0.72) between fish Hg and population 

density. Brumbaugh and others (2001) found a negative 

correlation with urban land and fish Hg, although most of 

the fish sampled from urban streams were largemouth or 

smallmouth bass. The above results underscore the importance 

of considering LULC and especially its proximity to the 

sampling site when interpreting fish-Hg concentrations.

Although fish Hg in largemouth bass, spotted bass, 

pumpkinseed, brown trout, and rainbow-cutthroat trout 

correlated with various measures of bed sediment Hg, fish 

Hg in smallmouth bass, rock bass, and channel catfish did not 

(table 5). Fish Hg correlated with LOI only for pumpkinseed 

(rs

 = 0.58, p < 0.05), whereas Hg in largemouth bass, spotted 

bass, and rainbow-cutthroat trout correlated positively with 

bed sediment MeHg as normalized by LOI (fig. 21G–21I), 

and, in general, these correlations were higher than with 

bed-sediment MeHg concentrations that were not normalized 

by LOI (table 5). An exception was found for pumpkinseed; 

fish Hg in pumpkinseed was more highly correlated with 

bed-sediment MeHg concentrations not normalized by LOI 

(fig. 21J). An estimate of Hg methylation potential, the 

percentage of MeHg in bed sediment also correlated positively 

with Hg in brown trout (fig. 21K), pumpkinseed (fig. 21L), 

and spotted bass, but only weakly for largemouth bass. 

Sediment-fish BAF values for several species decreased with 

increasing LOI percentages and with AVS for largemouth bass 

(fig. 22A–22F). 
36 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093-c_fig 21a-f

0.1

1

10

0 20 40 60 80

Largemouth bass

0.1

1

10

0 20 40 60 80

EVERGREEN FOREST, PERCENT OF BASIN AREA, 

DISTANCE-WEIGHTED

EVERGREEN FOREST, PERCENT OF BASIN AREA, 

DISTANCE-WEIGHTED

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

Unmined

Mined

r

s

= 0.77 

p < 0.001

WOODY WETLAND, PERCENT OF BASIN AREA, 

DISTANCE-WEIGHTED

EVERGREEN FOREST, PERCENT OF BASIN AREA, 

DISTANCE-WEIGHTED

p < 0.001

B

0.01

0.1

1

10

0 20 40 60 80

p < 0.001

Brown trout

D

0.1

1

10

0 20 40 60

p < 0.05

Spotted bass

C

0.1

1

10

0.1 1 10 100 1000 10000

POPULATION DENSITY, 

PEOPLE PER SQUARE KILOMETER 

POPULATION DENSITY, 

PEOPLE PER SQUARE KILOMETER 

p < 0.001

Largemouth bass

E

0.01

0.1

1

10

0 1 2 3 4 5 6 7 8 9 10

p < 0.01

Brown trout

F

A

Largemouth bass

r

s

= 0.72 

r

s

= -0.50 

r

s

= 0.72 

r

s

= 0.86 

r

s

= -0.75 

Figure 21. Correlations between length-normalized mercury concentrations in fish and selected environmental 

characteristics, 1998–2005. [Data for all sites shown, unmined and mined; however, Spearman rank correlation 

coefficients (rs

) are for unmined sites only.]
Factors Related to Mercury Bioaccumulation in Fish 37

11-7093-c_fig 21g-l

0.1

1

10

0.01 0.1 1

p = 0.10

Spotted bass

H

0.1

1

10

0 1 10 100

METHYLMERCURY IN BED SEDIMENT, 

NANOGRAMS PER GRAM

p < 0.01

J

Pumpkinseed

0.1

1

10

0.01 0.1 1

p < 0.05

Largemouth bass

G

0.01

0.1

1

10

0.01 0.1 1

p < 0.05

Rainbow-Cutthroat trout

I

0.1

1

10

0 1 10 100

p < 0.001

L

Pumpkinseed

0.01

0.1

1

10

0.01 0.1 1 10 100

METHYLMERCURY AS A PERCENTAGE 

OF TOTAL MERCURY IN BED SEDIMENT

METHYLMERCURY AS A PERCENTAGE 

OF TOTAL MERCURY IN BED SEDIMENT

p < 0.05

Brown trout

K

METHYLMERCURY IN BED SEDIMENT, NANOGRAMS 

PER GRAM, DIVIDED BY PERCENT LOSS ON IGNITION

METHYLMERCURY IN BED SEDIMENT, NANOGRAMS

 PER GRAM, DIVIDED BY PERCENT LOSS ON IGNITION

METHYLMERCURY IN BED SEDIMENT, NANOGRAMS 

PER GRAM, DIVIDED BY PERCENT LOSS ON IGNITION

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

Unmined

Mined

r

s

= 0.35 r

s

= 0.60 

r

s

= 0.67 

r

s

= 0.74

r

s

= 0.56

r

s

= 0.85

Figure 21.—Continued.
38 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

11-7093-c_fig 21m-r

0.1

1

10

0.01 0.1 1

Pumpkinseed

0.01

0.1

1

10

0.001 0.01 0.1 1 10

WHMI.5

DELR.26

N

Smallmouth bass

0.1

1

10

0.01 0.1 1 10

Largemouth bass

M

0.1

1

10

0.1 1 10 100

Largemouth bass

O

0.1

1

10

0.1 1 10

R

Pumpkinseed 0.01

0.1

1

10

0.1 1 10

Rainbow-Cutthroat trout

Q

P

Unmined

Mined

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

TOTAL MERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

TOTAL MERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

TOTAL MERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

r

s

= 0.50

r

s

= 0.79

r

s

= 0.54 r

s

= -0.52

r

s

= 0.37

r

s

= 0.19

p < 0.01 p > 0.10

p < 0.001 p < 0.01

p < 0.05 p < 0.05

Figure 21.—Continued.
Factors Related to Mercury Bioaccumulation in Fish 39

11-7093-c_fig 21s_x

0.01

0.1

1

10

1 10 100

DISSOLVED SULFATE IN UNFILTERED WATER, 

MILLIGRAMS PER LITER

Brown trout

T

0.1

1

10

0.1 1 10 100 1000

DISSOLVED SULFATE IN UNFILTERED WATER, 

MILLIGRAMS PER LITER

Largemouth bass

S

0.01

0.1

1

10

1 10 100

DISSOLVED ORGANIC CARBON IN UNFILTERED WATER,

MILLIGRAMS PER LITER

Brown trout

V

0.1

1

10

1 10

SPECIFIC ULTRAVIOLET ABSORBANCE OF UNFILTERED WATER 

AT 254 NANOMETERS, LITER PER MILLIGRAMS CARBON PER METER 

Largemouth bass

W

0.1

1

10

4 5 6 7 8 9 10

PH, UNFILTERED WATER 

Largemouth bass

U

0.1

1

10

1 10 100

TOTAL MERCURY IN ATMOSPHERIC DEPOSITION, 

SEIGNEUR-MODELED, WET AND DRY, MICROGRAMS PER SQUARE METER 

Rock bass

X

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

TOTAL MERCURY IN FISH,

MICROGRAMS PER GRAM PER METER

Unmined

Mined

p < 0.001

p < 0.01

r

s

= -0.54

r

s

= -0.43

r

s

= 0.71

r

s

= 0.76

r

s

= -0.60

r

s

= -0.60

p < 0.001

p < 0.05 p < 0.001

p < 0.001

Figure 21.—Continued.
40 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

For the 1998 National Mercury Pilot, Brumbaugh and 

others (2001) showed a highly significant correlation between 

length-normalized Hg in largemouth bass and MeHg in 

unfiltered water (rs = 0.71, p < 0.001). In our study, fish-Hg 

concentrations also correlated positively with unfiltered MeHg 

for largemouth bass (rs = 0.50; fig. 21M) and pumpkinseed 

(rs = 0.79; fig. 21O), but the relation was not significant for 

smallmouth bass (fig. 21N) or other fish species evaluated 

(table 5). Fish Hg appeared to be similarly correlated with 

filtered MeHg concentrations; however, some correlations 

with this parameter must be viewed with caution because 

filtered Hg data were available at far fewer sites than unfiltered 

Hg data, and concentrations at many of these sites were below 

detection limits. Fish Hg also correlated with THg in unfiltered 

water, but generally more weakly than to MeHg; this relation 

was positive for largemouth bass and rainbow-cutthroat 

trout, and was negative for pumpkinseed (figs. 21P–21R). 

Total Hg in filtered samples appeared to be a better predictor 

of spotted bass Hg concentrations than MeHg in unfiltered 

water, although it is MeHg in water that is accumulated in the 

aquatic food web eventually to fish. Noise in the correlations 

with MeHg in unfiltered water might be reduced with 

increased water sampling, such as was done by Chasar and 

others (2009). Multiple samples over a range of hydrologic 

conditions, and possibly lower detection limits, would be 

needed to improve correlations. 

In general, length-normalized Hg concentrations in 

fish correlated weakly to selected ancillary water chemistry 

characteristics. Fish Hg in largemouth bass and brown 

trout were negatively correlated with concentrations of 

dissolved sulfate in water (figs. 21S, 21T). Sulfate may 

exert concentration-dependent positive or negative effects 

on Hg methylation and, therefore, bioaccumulation by fish 

(Compeau and Bartha, 1983, 1987; Gilmour and others, 

1992, 1998; Benoit and others, 2003). A negative correlation 

with pH was found for Hg in largemouth bass only (rs

 = 

-0.43; fig. 21U). Lower pH waters (more acidic) tend to be 

associated with a greater partitioning of Hg to the dissolved 

phase, enhancing Hg methylation, and resulting in higher rates 

of Hg bioaccumulation (Watras and Bloom, 1992). Although 

DOC and fish Hg directly correlated only in rock bass (table 5) 

and brown trout (fig. 21V), water BAF values for largemouth 

bass and brown trout decreased with increasing concentrations 

of DOC in unfiltered water (figs. 22G, H). In contrast, Hg in 

largemouth bass positively correlated with SUVA of DOC 

(fig. 21W). This supports the importance of the indirect 

and positive effect of DOC and DOC complexity in fish Hg 

bioaccumulation, as also found by Chasar and others (2009) 

for DOC and SUVA for top-predator fish.

With the exception of rock bass, no relation was 

found between atmospheric THg deposition and fish-Hg 

concentrations when examined at sites across the United 

States (fig. 21X); however, variation in local environmental 

characteristics in stream basins may confound evidence of 

the potential effects of atmospheric deposition. The three 

bass species that are widespread in the eastern half of the 

United States (largemouth, smallmouth, and rock bass) were 

examined further for relations to atmospheric THg deposition 

by confining analyses to sites from mixed and undeveloped 

LULC; sites from mined, urban, and agricultural LULC were 

excluded to minimize confounding effects of nonatmospheric 

Hg sources and land-use disturbances. Length-normalized 

Hg in fish was compared to three estimates of Hg deposition: 

total combined [sum of precipitation-weighted wet THg 

deposition measured at MDN sites and modeled dry THg 

deposition (Seigneur and others, 2004)]; total modeled [sum 

of modeled wet and dry THg deposition from Seigneur and 

others (2004)]; and wet only [precipitation-weighted wet THg 

deposition measured at MDN sites]. In addition to the positive 

correlation mentioned earlier for total modeled Hg deposition 

with rock bass (fig. 21X), total combined deposition positively 

correlated with rock bass Hg (not shown). The positive 

relation for rock bass Hg with Hg deposition also remained 

significant in the multiple regression model that included 

evergreen forest and woody wetland abundance. Relations 

between largemouth bass Hg levels and either total combined 

or wet only Hg deposition were deemed not reliable because 

four influential samples were in Kansas and Nebraska, where 

the western U.S. average was used as an estimate of Hg 

deposition. Given the lack of wet deposition measurements 

in that part of the country we do not have confidence in the 

accuracy of this estimate for Kansas and Nebraska. When the 

four low-Hg deposition samples were excluded, there was 

no significant relation. Relations for smallmouth bass with 

atmospheric Hg were not significant. 

Hammerschmidt and Fitzgerald (2006) examined a large, 

historical data set for 25 States and found positive relations 

between statewide average Hg in largemouth bass and wet 

Hg deposition. Our site-based (rather than statewide) analysis 

provides limited support for positive relation between fish-Hg 

concentration and Hg deposition. One explanation for the 

limited connection between Hg in fish and deposition in our 

study is that variation in Hg methylation among ecosystems is 

greater than the variation in Hg deposition, particularly in the 

eastern United States, where most of our bass were sampled. 
Factors Related to Mercury Bioaccumulation in Fish 41

11-7093-c_fig 22a-f

0.01 0.1 1 10 100

LOSS ON IGNITION OF BED SEDIMENT, PERCENT LOSS ON IGNITION OF BED SEDIMENT, PERCENT

LOSS ON IGNITION OF BED SEDIMENT, PERCENT LOSS ON IGNITION OF BED SEDIMENT, PERCENT

LOSS ON IGNITION OF BED SEDIMENT, PERCENT

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

LOG SEDIMENT-FISH 

BIOTA ACCUMULATION FACTOR

Largemouth bass

A

0.1 1 10

Spotted bass

C

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

0.1 1 10 100

Rock bass

B

0.1 1 10 100

Brown trout

D

0.1 1 10 100

Rainbow-Cutthroat trout

E

0.001 0.01 0.1 1 10 100 1000

ACID VOLATILE SULFIDE IN BED SEDIMENT, 

MICROGRAMS PER GRAM DRY WEIGHT

Largemouth bass

F

Unmined

Mined

p < 0.0001 p < 0.01

r

s

= -0.63 

r

s

= -0.30

p> 0.10 

r

s

= -0.85 r

s

= -0.78

r

s

= -0.55

p > 0.10

r

s

= -0.63

p < 0.01 p < 0.001

Figure 22. Biota Accumulation Factors (BAF) for fish in relation to selected environmental characteristics, 

1998–2005. [Data for all sites are shown, unmined and mined; however, Spearman rank correlation coefficients 

(rs

) are for unmined only. BAF values are in Log10.]
42 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Bed-Sediment Relations with 

Environmental Characteristics 

Higher concentrations of MeHg in bed sediment at 

sites in unmined basins (n = 183) were significantly related 

to higher LOI, THg, and AVS of the sediment, as shown in 

equation 3 (adjusted r2 = 0.73):

BS

BS

BS

ln[MeHg ] = - 2.857 + 0.925 ln[LOI] 

+ 0.247 ln[THg ] 0.048 ln[AVS] ,

where

MeHg is the bed sediment MeHg concentration,

in nanograms per gram,

LOI is the loss-on-ignition of the bed sediment

in percent,

T

+

Hg is the bed sediment THg concentration, in BS

nanograms per gram, and

AVS is the acid-volatile sulfide concentration, 

in micrograms per gram.

(3)

 LOI was a strong predictor of MeHg in bed sediment 

(rs = 0.81, fig. 23A) and THg in bed sediment (rs=0.78; 

table 6). Although bed sediment MeHg was near or below 

detection at many sites, MeHg and THg were more highly 

related in bed sediment (rs = 0.72) (fig. 23B, table 6) than in 

unfiltered water (rs = 0.40). Krabbenhoft and others (1999) 

also found a high positive correlation between bed sediment 

MeHg and LOI, as well as with sediment organic carbon. 

Recent work by Marvin-DiPasquale and others (2009) found 

that MeHg in bed sediment from streams with predominantly 

atmospheric Hg inputs was a function of sediment organic 

content and the activity of Hg-methylating microbes. AVS 

correlated positively with bed sediment MeHg and THg in our 

study (fig. 23C) but contributed least to the predictive power 

of equation 3. Key LULC categories, such as forest cover, 

wetland, urban, and agriculture, were at most only weakly 

correlated with Hg concentrations in bed sediment (table 6). 

As atmospheric Hg concentrations increased, 

concentrations of THg in bed sediment increased, and the 

highest correlation (rs = 0.53) was found for Seigneur-modeled 

dry atmospheric deposition with bed sediment THg (fig. 23D; 

table 6); the correlation between THg and Seigneur-modeled 

total (wet + dry) atmospheric deposition was lower, but still 

significant (rs = 0.39). 

11-7093-c_fig 22g-h

4

5

6

7

8

9

0.1 1 10 100

DISSOLVED ORGANIC CARBON IN UNFILTERED WATER, 

MILLIGRAMS PER LITER 

LOG WATER-FISH BIOTA 

ACCUMULATION FACTOR

Brown trout

G H

Largemouth bass

4

5

6

7

8

9

0.1 1 10 100

DISSOLVED ORGANIC CARBON IN UNFILTERED WATER,

MILLIGRAMS PER LITER 

LOG WATER-FISH BIOTA 

ACCUMULATION FACTOR

rs= -0.58

p < 0.001

r

s

= -0.63

p < 0.01

Mined

Non-mined

Figure 22.—Continued
Bed-Sediment Relations with Environmental Characteristics 43

Figure 23. Correlations between mercury in bed sediment and selected environmental characteristics 

in unmined basins, 1998–2005. (rs

, Spearman rank correlation coefficient; modeled mercury is based on 

Seigneur and others, 2004.)

0.001

0.010

0.100

1.000

10.000

100.000

0.001 0.1 10 1000 100000

ACID-VOLATILE SULFIDE IN BED SEDIMENT, 

IN MICROGRAMS PER GRAM DRY WEIGHT 

C

rs = 0.46

p < 0.001

0.001

0.010

0.100

1.000

10.000

100.000

0.1 1 10 100

LOSS-ON-IGNITION OF BED SEDIMENT,

PERCENT

METHYLMERCURY IN BED SEDIMENT,

NANOGRAMS PER GRAM DRY WEIGHT

METHYLMERCURY IN BED SEDIMENT,

NANOGRAMS PER GRAM DRY WEIGHT

TOTAL MERCURY IN BED SEDIMENT,

NANOGRAMS PER GRAM DRY WEIGHT

METHYLMERCURY IN BED SEDIMENT,

NANOGRAMS PER GRAM DRY WEIGHT

rs = 0.81

p < 0.0001

A

0.001

0.010

0.100

1.000

10.000

100.000

0.1 1 10 100 1000 10000

TOTAL MERCURY IN BED SEDIMENT,

NANOGRAMS PER GRAM DRY WEIGHT

rs = 0.72

p < 0.0001

B

0.1

1

10

100

1000

10000

1 10 100

TOTAL MERCURY IN ATMOSPHERIC DEPOSITION,SEIGNEURMODELED, DRY ONLY, MICROGRAMS PER SQUARE METER

D

rs = 0.53

p< 0.001
44 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 6. Spearman rank correlation coefficients (rs) for relations between selected environmental characteristics from U.S. streams, 1998–2005. [Definitions of variable abbreviations are listed in Appendix 1. Values are for sites in unmined basins only. Color coding of rs based on p values, p < 0.001 (pink), p < 0.01 (orange), and p < 0.05 (yellow)] Parameter pH DOC UV SUVA Sulfate SS_ conc UMeHg UTHg UMeHg/ UTHg FMeHg FTHg PMeHg PTHg SMeHg/ LOI SMeHg STHg / LOI STHg SMeHg/ STHg LOI AVS Stream water pH 1.00 DOC -0.23 1.00 UV -0.24 0.92 1.00 SUVA -0.55 0.31 0.60 1.00 Sulfate 0.40 0.12 -0.16 -0.45 1.00 SS_conc 0.09 0.36 -0.22 0.05 0.27 1.00 UMeHg -0.39 0.59 0.67 0.47 -0.09 0.55 1.00 UTHg -0.23 0.43 0.31 0.28 0.14 0.62 0.54 1.00 UMeHg/UTHg -0.29 0.37 0.48 0.30 -0.26 0.13 0.72 -0.12 1.00 FMeHg -0.31 0.56 0.51 0.42 0.07 0.26 0.83 0.50 0.58 1.00 FTHg -0.31 0.49 0.31 0.31 0.03 0.27 0.61 0.79 0.04 0.67 1.00 PMeHg -0.07 0.31 0.03 -0.06 0.40 0.69 0.77 0.72 0.22 0.46 0.45 1.00 PTHg -0.08 0.15 0.04 -0.16 0.42 0.61 0.45 0.79 -0.29 0.19 0.36 0.72 1.00 Bed sediment SMeHg/LOI -0.20 0.03 -0.15 0.16 0.01 0.07 0.28 0.23 0.14 0.27 0.21 0.36 0.21 1.00 SMeHg -0.28 0.08 -0.06 0.28 -0.13 0.15 0.28 0.16 0.19 0.09 0.11 0.31 0.17 0.77 1.00 STHg/LOI -0.05 0.10 -0.21 -0.19 0.33 -0.01 -0.08 0.29 -0.33 0.13 0.26 0.14 0.34 0.26 0.08 1.00 STHg -0.25 0.16 -0.03 0.14 0.02 0.05 0.10 0.22 -0.08 0.02 0.17 0.17 0.27 0.39 0.72 0.51 1.00 SMeHg/STHg -0.08 -0.07 -0.04 0.19 -0.23 0.07 0.31 -0.03 0.39 0.09 -0.04 0.16 -0.12 0.63 0.59 -0.50 -0.06 1.00 LOI -0.28 0.13 0.12 0.31 -0.22 0.05 0.21 0.07 0.18 -0.02 0.00 0.12 0.03 0.29 0.81 -0.08 0.78 0.30 1.00 AVS -0.27 0.14 0.42 0.32 0.03 0.07 0.08 0.14 -0.03 0.09 0.16 0.14 0.04 0.31 0.46 0.17 0.40 0.13 0.42 1.00 Atmospheric deposition SULF.DEP -0.08 -0.03 -0.21 -0.03 0.32 -0.16 -0.08 -0.03 -0.12 0.35 0.19 0.18 0.20 0.24 0.17 0.44 0.28 -0.11 0.05 0.17 ADRY.SEI -0.20 0.10 -0.21 -0.09 0.29 -0.20 0.01 -0.01 -0.04 0.25 0.09 0.10 0.15 0.36 0.42 0.44 0.53 -0.03 0.35 0.26 ATOT.SEI -0.16 -0.06 -0.28 -0.15 0.22 -0.39 -0.12 -0.09 -0.12 0.06 -0.03 -0.11 -0.03 0.25 0.25 0.45 0.39 -0.12 0.19 0.12 AWET.MDN -0.04 0.07 0.13 0.23 0.17 -0.08 -0.10 0.00 -0.12 0.36 0.11 0.03 -0.00 -0.16 -0.37 0.21 -0.27 -0.24 -0.44 -0.13 AWET.PRE -0.07 0.13 0.18 0.27 0.20 0.03 -0.05 0.01 -0.06 0.37 0.12 0.12 0.03 -0.11 -0.26 0.18 -0.18 -0.18 -0.31 -0.09 PREC.PR -0.45 -0.04 0.12 0.33 -0.35 -0.49 -0.03 -0.05 0.03 0.13 0.09 -0.31 -0.22 0.05 0.02 0.22 0.15 -0.10 0.06 0.06 WET_DEP_AVE 0.24 -0.51 -0.50 -0.19 -0.18 -0.07 -0.27 -0.16 -0.20 -0.44 -0.26 -0.13 -0.09 -0.08 -0.02 -0.23 -0.10 0.10 0.02 -0.09

Other

POPDEN00 -0.11 0.28 0.23 0.04 0.42 -0.04 0.01 0.14 -0.14 0.13 0.08 0.10 0.34 0.11 0.15 0.47 0.40 -0.25 0.17 0.18

ELEV.AVG 0.54 -0.41 -0.52 -0.53 0.01 0.01 -0.31 -0.17 -0.24 -0.37 -0.15 -0.08 -0.08 -0.02 -0.05 -0.26 -0.21 0.15 -0.12 -0.14

HYDRIC SOILS -0.22 0.48 0.56 0.35 0.06 0.11 0.31 0.09 0.28 0.36 0.19 0.09 -0.06 0.04 0.01 0.13 0.05 -0.04 -0.01 0.04

PET -0.14 0.18 0.32 0.25 0.28 0.17 0.12 0.18 0.00 0.31 0.11 0.21 0.22 -0.26 -0.42 0.10 -0.30 -0.27 -0.40 -0.11

AET -0.25 0.18 0.28 0.34 0.18 0.04 0.10 0.12 0.04 0.37 0.16 0.12 0.10 -0.18 -0.32 0.17 -0.17 -0.25 -0.30 -0.10
Bed-Sediment Relations with Environmental Characteristics 

45

Parameter pH DOC UV SUVA Sulfate SS_ conc UMeHg UTHg UMeHg/ UTHg FMeHg FTHg PMeHg PTHg SMeHg/ LOI SMeHg STHg / LOI STHg SMeHg/ STHg LOI AVS

Land use / land cover

SUM_FOREST -0.26 -0.19 -0.30 0.11 -0.56 -0.41 -0.04 -0.15 0.10 0.03 0.15 -0.30 -0.41 0.18 0.30 -0.15 0.18 0.27 0.31 0.02

EVR_FOREST -0.32 -0.16 -0.10 0.23 -0.68 -0.30 0.03 -0.08 0.14 -0.04 0.09 -0.38 -0.47 0.04 0.05 -0.25 -0.07 0.23 0.08 -0.10

EVR_FOREST_DW -0.32 -0.16 -0.14 0.21 -0.68 -0.30 0.05 -0.08 0.17 -0.01 0.10 -0.35 -0.45 0.05 0.07 -0.29 -0.08 0.26 0.09 -0.12

SUM_WETLAND -0.45 0.49 0.66 0.55 -0.22 0.19 0.47 0.18 0.41 0.38 0.24 0.15 -0.05 0.09 0.17 -0.02 0.13 0.09 0.21 0.20

WOODWETLAND -0.50 0.47 0.58 0.58 -0.25 0.09 0.42 0.15 0.37 0.43 0.29 0.06 -0.12 0.10 0.17 0.05 0.17 0.07 0.21 0.20

WOODWETLAND_DW -0.51 0.45 0.55 0.57 -0.26 0.15 0.44 0.19 0.37 0.44 0.29 0.10 -0.09 0.08 0.14 0.02 0.14 0.07 0.20 0.19

HERBWETLAND -0.22 0.51 0.67 0.35 -0.06 0.19 0.39 0.14 0.37 0.21 0.10 0.17 0.02 0.12 0.25 -0.02 0.25 0.07 0.32 0.21

HERBWETLAND_DW -0.23 0.52 0.70 0.38 -0.06 0.21 0.39 0.15 0.36 0.22 0.11 0.18 0.01 0.11 0.23 0.00 0.24 0.05 0.29 0.24

SUM_UNDEVELOPED -0.16 -0.17 -0.13 0.13 -0.62 -0.19 0.07 -0.10 0.19 -0.05 0.09 -0.13 -0.38 0.12 0.17 -0.34 -0.03 0.32 0.19 -0.00SUM_URBAN -0.14 0.28 0.21 0.05 0.39 0.00 0.07 0.16 -0.11 0.18 0.11 0.16 0.36 0.15 0.16 0.45 0.38 -0.21 0.15 0.18

RES_L_URBAN -0.17 0.29 0.20 0.05 0.40 -0.02 0.08 0.18 -0.09 0.18 0.08 0.16 0.35 0.17 0.18 0.49 0.41 -0.22 0.17 0.19

RES_L_URBAN_DW -0.15 0.29 0.17 -0.02 0.40 -0.01 0.08 0.18 -0.09 0.19 0.10 0.17 0.36 0.19 0.20 0.52 0.42 -0.21 0.16 0.18

RES_H_URBAN -0.07 0.26 0.23 0.06 0.46 0.02 -0.05 0.18 -0.23 0.14 0.06 0.05 0.24 0.03 -0.02 0.45 0.21 -0.32 -0.02 0.10

RES_H_URBAN_DW -0.05 0.26 0.22 0.00 0.46 0.02 -0.05 0.18 -0.23 0.15 0.06 0.06 0.24 0.04 -0.00 0.46 0.22 -0.31 -0.02 0.09

COM_INDUSTR -0.12 0.33 0.27 0.09 0.40 0.12 0.11 0.20 -0.08 0.17 0.16 0.20 0.40 0.09 0.13 0.41 0.35 -0.22 0.15 0.16

COM_INDUSTR_DW -0.12 0.30 0.20 -0.01 0.39 0.11 0.10 0.18 -0.10 0.18 0.17 0.21 0.42 0.13 0.14 0.43 0.35 -0.21 0.13 0.12

SUM_AGRICULTURE 0.19 0.05 -0.08 -0.11 0.43 0.30 -0.02 0.07 -0.09 0.10 -0.02 0.25 0.32 -0.14 -0.21 0.06 -0.17 -0.09 -0.25 -0.14

ROW_CROP 0.01 0.15 -0.00 -0.00 0.29 0.32 0.14 0.14 0.06 0.18 0.02 0.29 0.29 0.01 -0.05 0.04 -0.09 0.05 -0.13 -0.13

ROW_CROP_DW 0.00 0.15 0.00 0.01 0.27 0.32 0.15 0.12 0.09 0.17 -0.00 0.27 0.27 0.04 -0.03 0.02 -0.08 0.09 -0.12 -0.12

PAST_HAY 0.20 -0.01 -0.17 -0.15 0.41 0.23 -0.11 0.07 -0.20 0.19 0.09 0.24 0.37 -0.19 -0.23 0.11 -0.13 -0.17 -0.23 -0.17

PAST_HAY_DW 0.23 -0.04 -0.16 -0.13 0.39 0.23 -0.12 0.05 -0.20 0.16 0.07 0.20 0.32 -0.18 -0.24 0.07 -0.17 -0.14 -0.26 -0.19

GRASSLAND 0.39 -0.05 0.12 -0.17 0.04 0.33 -0.07 0.02 -0.05 -0.27 -0.12 0.10 0.04 -0.30 -0.30 -0.34 -0.39 0.00 -0.23 -0.14

Table 6. Spearman rank correlation coefficients (rs) for relations between selected environmental characteristics from U.S. streams, 1998–2005.—Continued[Definitions of variable abbreviations are listed in Appendix 1. Values are for sites in unmined basins only. Color coding of rs based on p values, p < 0.001 (pink), p < 0.01 (orange), and p < 0.05 (yellow)]
46 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Stream-Water Relations with 

Environmental Characteristics 

Stepwise multiple-linear regression indicated that higher 

concentrations of MeHg in unfiltered water from sites in 

unmined basins (n = 223) were primarily related to higher 

DOC and THg of unfiltered stream water and, to a lesser 

extent, higher percentages of MeHg in bed sediment, higher 

percentages of total wetland (woody and herbaceous) in the 

basin, and lower pH values of the water (adjusted r2= 0.61):

water

water

BS

w

water

ln[MeHg ] = - 1.664 + 0.573 ln[DOC] 

 + 0.384 ln[THg ] 0.270 [pH] 

 + 0.268 ln[MeHg/THg ]

 + 0.015 arcsin[L ],

where

MeHg is the MeHg concentration in unfiltered

water, in nanograms per lit

−

BS

water

er,

DOC is the dissolved organic carbon

concentration in unfiltered water, in

milligrams per liter,

MeHg / THg is the percentage of MeHg in bed

sediment,

THg is the THg concentration in unfiltered

water, i

w

n nanograms per liter, pH is

the pH value in unfiltered water, and

L is the percentage of total wetland in the

basin.

(4)

MeHg concentrations in unfiltered water correlated 

positively with concentrations of DOC (rs = 0.59, p < 0.001) 

and UV absorbance (rs = 0.67, p < 0.001) (fig. 24A, 24B; 

table 6). UV absorbance has been suggested as an inexpensive 

surrogate measure for Hg concentration in water because it 

correlates highly with DOC and even more highly with the 

types of DOC thought to complex most strongly with Hg 

(George R. Aiken, U.S. Geological Survey, oral commun., 

2003). The correlation of unfiltered MeHg to SUVA (rs = 

0.466, p < 0.01) was not as strong. Similar but weaker 

correlations were found between filtered MeHg concentrations 

and DOC, UV absorbance, and SUVA. DOC, in turn, 

correlated positively with hydric soils, total wetness index, 

total wetlands, and precipitation-weighted atmospheric Hg 

deposition, and it correlated negatively with average basin 

elevation and average depth to the seasonally high water table. 

Spearman correlations between MeHg and THg in water 

ranged from rs

 = 0.54 in unfiltered water (fig. 24C) to rs = 0.72 

in particulate water samples (table 6). In addition, MeHg and 

THg in unfiltered and particulate samples increased in relation 

to total suspended-sediment concentration. A weak negative 

relation was found between MeHg and pH in unfiltered water 

(fig. 24D). The percentage of MeHg (percent MeHg/THg) in 

unfiltered water was positively correlated with percent MeHg 

in bed sediment (fig. 24E). 

MeHg concentrations in unfiltered water were higher 

at sites in basins with higher percentages of total wetland 

(fig. 24F) and with both woody wetland and herbaceous 

wetland (table 6). Increasing percentages of hydric soils were 

only weakly predictive of unfiltered MeHg. Other LULC and 

basin-level GIS measured characteristics were limited in their 

value for explaining Hg in water.

No correlation was found for modeled or actual Hg from 

atmospheric deposition with unfiltered MeHg; however, this 

is not surprising, given that water samples were collected only 

once at each site. The analysis was also hampered for filtered 

MeHg by many values below reporting limits and by sparse 

NADP-MDN wet-deposition data for Western States. 

Discussion of Findings and Comparison 

with Other Studies

Our results for total Hg in fish provide evidence that 

Hg concentrations in freshwater fish across the United 

States are often greater than levels specified in various 

criteria for protection of fish-eating wildlife and humans. 

However, the purpose of our study was to compare sites 

and explore factors related to fish Hg; it was not intended to 

be a thorough assessment of fish Hg with respect to fishconsumption-advisory levels. The results presented here 

paint a picture of Hg in streams across the United States for 

a broad range of regional and national gradients in Hg source 

strength and factors thought to influence Hg methylation and 

bioaccumulation. Sources included atmospheric deposition, 

urbanization, and gold or Hg mining; however, sampling 

focused primarily on sites where atmospheric deposition was 

the Hg source. Hg in fish, bed sediment, and stream water 

were assessed spatially and with regard to existing guidelines 

or criteria and possible relations to stream and basin attributes, 

including chemical and physical characteristics, as well as 

LULC. To date, there have been no other studies of this scale 

in the literature that include multimedia sampling of MeHg 

and THg and, currently, there is no national Hg monitoring 

network in the United States for fish, bed sediment, and water. 

A conceptual model for MeHg bioaccumulation is that 

as MeHg is formed within the ecosystem through methylation 

of inorganic Hg, some portion of the MeHg is transferred to 

stream water, and some portion of MeHg in water is taken 

up by the base of the aquatic food web through both sorption 

to detritus and uptake into living algal (periphyton) cells. 

MeHg is subsequently biomagnified in aquatic food webs 
Discussion of Findings and Comparison with Other Studies 47

11-7093-c_fig 24

0.001

0.01

0.1

1

10

0.1 1 10 100

DISSOLVED ORGANIC CARBON, 

MILLIGRAMS PER LITER

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER

rs = 0.59

p < 0.0001

A

0.001

0.01

0.1

1

10

0.1 1 10 100

TOTAL MERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

rs = 0.54

p < 0.001

rs = 0.39

p < 0.05

C

0.001

0.01

0.1

1

10

2 4 6 8 10 12

PH, UNFILTERED WATER

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER

rs = -0.39

p < 0.001

D

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER 

0.001

0.01

0.1

1

10

0 20 40 60 80

TOTAL WETLAND, PERCENT OF BASIN AREA

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER

rs = 0.46

p < 0.001

E F

0.001

0.01

0.1

1

10

0.001 0.01 0.1 1 10

ULTRAVIOLET ABSORBANCE OF WATER AT 254 

NANOMETERS, PER CENTIMETER

METHYLMERCURY IN UNFILTERED WATER, 

NANOGRAMS PER LITER

rs = 0.67

p < 0.001

B

0.1

1

10

100

0.01 0.1 1 10

METHYLMERCURY IN UNFILTERED 

WATER, AS PERCENT OF TOTAL MERCURY 

METHYLMERCURY IN STREAMBED SEDIMENT, 

AS PERCENT OF TOTAL MERCURY

100

Figure 24. Correlations between mercury in unfiltered water and selected environmental characteristics in 

unmined basins, 1998–2005. (rs

, Spearman rank correlation coefficients.)
48 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

to reach highest concentrations at the apex of the food web. 

One plausible inference from this conceptual model is that 

MeHg concentrations in organisms at the top of the aquatic 

food web are linearly related to concentrations at the base of 

the food web, which are in turn linearly related to aqueous 

MeHg concentrations. We examined relations between fish 

Hg, which is largely MeHg, to MeHg in water. Whereas fish 

accumulate MeHg over time, MeHg in water is highly variable 

over time, season, and hydrologic conditions. Our dataset 

does not capture this variability, so correlations between fish 

Hg and MeHg measured in this study are confounded by 

the fact that single, instantaneous (single synoptic) aqueous 

MeHg measurements are an uncertain estimator of longerterm mean MeHg concentrations in a stream (Paller and 

others, 2004; Brigham and others, 2009). Chasar and others 

(2009), using temporally extensive water sampling and more 

complete assessment of MeHg in aquatic food webs, support 

the conceptual model that MeHg concentrations in predator 

fish are related to mean aqueous MeHg concentrations and 

that trophic transfer (biomagnification) is relatively consistent 

among diverse stream ecosystems.

Concentrations of fish Hg from our study must be 

compared to those from other studies with caution, owing 

to influences of fish species, age, length, weight, sex, and 

sample cut or type (skin-off fillets, as were most samples in 

our study, compared to skin-on fillets or whole-body fish). In 

general, Hg increases with age and size in top-predator fish 

and can be lower in whole-body fish compared to muscle 

or fillet. However, the ratio of fillet to whole-body Hg may 

be relatively consistent for some fish species (Boudou and 

Ribeyre, 1983; Ribeyre and Boudou, 1984; Goldstein and 

others, 1996). Differences in Hg relations with feeding 

habitat, length, and weight have been noted in other largescale studies, including the historical NCBP (Schmitt and 

others, 1999), the USGS BEST study (Schmitt, 2002; Schmitt 

and others, 2004; Hinck and others, 2004a and 2004b, 2006, 

2007), and USEPA EMAP (Peterson and others, 2007). For 

example, Hinck and others (2004b) analyzed whole-body fish 

from historical stream sites in major river basins of the United 

States and found that piscivorous fish (bass and northern 

pikeminnow) in the BEST Columbia River Basin study had 

higher Hg concentrations than nonpiscivores and that Hg in 

these fish increased with size.

Fish in streams receiving higher amounts of Hg due to 

atmospheric load, gold or Hg mining, or urban contamination 

have been found generally to have higher concentrations of 

Hg. Hammerschmidt and Fitzgerald (2006) compared a large 

historical dataset for Hg in largemouth bass (30-40 cm total 

length) for 25 States with average annual wet atmospheric 

deposition of Hg from the MDN and the literature for various 

periods from the 1990s to early 2004. They excluded known 

point sources and found a positive correlation between 

statewide average concentrations of Hg in largemouth bass 

and average annual wet deposition of Hg. Based on USEPA 

EMAP results, Peterson and others (2007) suggested that 

atmospheric deposition of Hg was an important source of fish 

Hg in the western United States. However, at least one recent 

paper found that effects of atmospheric deposition on fish Hg 

were lessened by the structure and function of the particular 

aquatic ecosystem (Rypel and others, 2008). They compared 

largemouth bass in two river basins in the southeastern United 

States; atmospheric Hg was not correlated with fish Hg. In 

our study, we did not find any relation to atmospheric THg 

except for rock bass. In recent decades, industrial Hg use and 

atmospheric Hg deposition have decreased in parts of the 

United States (Engstrom and Swain, 1997). It is, therefore, 

likely that fish-Hg concentrations are not at a steady state 

but may be decreasing in the Nation’s waters. The response 

time for fish Hg with regard to source input, such as from 

atmospheric deposition, is unknown and is likely dependent on 

many factors that were incompletely described or unmeasured 

by this study. 

Gold and Hg mining played an important role in 

higher fish-Hg concentrations at selected sites in this 

study, overwhelming correlations with other site or basin 

characteristics. When sites in mined basins were excluded, 

higher unfiltered MeHg in streams correlated with higher 

unfiltered THg. Davis and others (2008) examined Hg in 

largemouth bass and other fish in streams of the SacramentoSan Joaquin Delta of California, an area affected by historical 

gold and Hg mining. They found that the median fish Hg 

for largemouth bass (0.53 μg/g ww) reflected this influence. 

Detailed and accurate data on Hg sources, such as atmospheric 

deposition, which is sparsely measured in the western 

United States, as well as gold or Hg mining or other sources 

of local Hg contamination, are critical to tease apart other 

environmental characteristics contributing to Hg methylation 

and fish Hg bioaccumulation.

In this study, the strongest correlations with 

environmental characteristics were found for largemouth bass, 

a top-predator/piscivorous fish, but significant correlations 

were also found for brown and rainbow-cutthroat trout, with 

selected environmental characteristics that were often different 

from those found for bass or other sunfish. In the USEPA 

EMAP study, fish were also grouped by genera or family for 

comparison to environmental factors (Peterson and others, 

2007). Fish Hg for rainbow trout, cutthroat trout, and brown 

trout genera, as well as for suckers, had the weakest relations, 

if any, with measured environmental characteristics, whereas 

top-predator/piscivorous genera, such as pikeminnow, had the 
Discussion of Findings and Comparison with Other Studies 49

strongest. The interspecies differences we observed between 

fish Hg correlations with environmental characteristics (for 

example, largemouth and smallmouth bass) suggest caution 

in generalizing beyond the species level. This concern has 

been held historically for different groups of biota and other 

environmental contaminants. 

Results of the current study indicate that, if sites in gold 

or Hg mined basins are excluded from statistical analysis, the 

most important environmental characteristics for predicting 

increasing concentrations of unfiltered MeHg in streams 

are higher concentrations of DOC, unfiltered THg, and 

bed-sediment MeHg, as well as higher basin percentages of 

wetland and lower pH. Increased bed-sediment MeHg was 

correlated with increasing LOI as a measure of sediment 

organic content, bed-sediment THg, and AVS. The best 

predictors of increasing fish Hg for largemouth bass were 

increasing basin percentages of forest and wetland, MeHg 

in unfiltered water and bed sediment, and decreasing pH and 

dissolved sulfate. Although less important than water and 

bed-sediment organic content (as measured by DOC and 

LOI, respectively), sulfate was a useful characteristic for 

understanding Hg in fish, bed sediment, and water. Dissolved 

sulfate concentration negatively correlated with fish Hg for 

largemouth bass and brown trout. Similarly, atmospheric 

sulfate deposition positively correlated with fish Hg in rock 

bass. The roles of pH and sulfate in Hg methylation have 

been documented in the literature; sulfate is important in Hg 

methylation by bacteria and, depending on concentration, can 

have either a positive or negative effect on Hg methylation 

(Compeau and Bartha, 1983, 1987; Gilmour and others, 1992, 

1998; Benoit and others, 2003). The complex nature of sulfate 

effects may help explain why it was not highly correlated 

with fish Hg across the broad range of concentrations and 

environmental conditions found in our study.

Increasing MeHg in water with increasing DOC, as found 

in our study over a broad range of environmental conditions, 

confirms similar results found in smaller scale studies with 

regard to the role of DOC in Hg methylation (St. Louis and 

others, 1994; Hurley and others, 1995). With the exception of 

a negative correlation for rock bass, DOC was not correlated 

with fish Hg, but unfiltered MeHg was found to be positively 

correlated with fish Hg for all fish species where data were 

sufficient for this examination. MeHg in unfiltered water was 

less than 1 ng/L at most sites and, although MeHg in unfiltered 

water was high for many sites in mined basins, both unfiltered 

MeHg and fish Hg were high at many other sites that also 

were high in DOC, such as coastal-plain streams along the 

eastern and southern United States. These observations 

underscore the importance of multiple factors that control Hg 

bioaccumulation. A large source of Hg input to an ecosystem, 

coupled with a modest capacity of the ecosystem to methylate 

inorganic Hg, can produce high levels of MeHg in water and 

fish. In contrast, a modest Hg source input to an ecosystem, 

such as in ecosystems where atmospheric deposition is thought 

to be the predominant source, coupled with a large capacity 

of an ecosystem to methylate inorganic Hg, also can produce 

high MeHg concentrations in water and fish.

High fish THg concentrations were found at sites that had 

high percentages of forest and wetland, especially evergreen 

forest and woody wetland more proximal to stream sites. 

MeHg in unfiltered water positively correlated with wetland 

abundance and, as for fish, MeHg relations to woody or 

herbaceous wetland strengthened when these LULC types 

were more proximal to stream sites. Wente (2000) showed 

that proximity-based (distance-weighted) LULC explained 

more variability in ecosystem integrity than more commonly 

used standard percentages of LULC, a finding also seen 

in this study. Other studies have found greater amounts of 

wetland to be correlated with higher water MeHg (St. Louis 

and others, 1994, 1996; Hurley and others, 1995; Krabbenhoft 

and others, 1999; Grigal, 2002; Brigham and others, 2009). 

Higher rates of Hg methylation in wetlands promote higher 

MeHg in streams, especially during years of high water yield 

(Krabbenhoft and others, 1995; Branfireun and others, 1996). 

Chumchal and others (2008) noted that Hg concentrations in 

largemouth bass were higher from forested-wetland habitat 

compared to open-water habitat. Our finding of higher 

potential methylation rates, based on the MeHg to THg 

ratio, at sites in basins with primarily undeveloped land in 

comparison to urban land, agrees with findings of Krabbenhoft 

and others (1999) who noted that forested and mixed forest/

agricultural basins had higher rates than streams in mining 

and urban basins. Horowitz and Stephens (2008) found that 

THg in bed sediment was higher at sites in forested basins 

(≥ 50 percent forested land use) than in basins in other LULC 

categories. They analyzed data for a suite of trace elements 

across 1,200 stream sites sampled as part of the NAWQA 

Program during 1991 to 1999. Evergreen forest canopies have 

greater effective surface areas than deciduous forest canopies 

or open (non-forested) land for filtering Hg from atmospheric 

deposition (Iverfeldt, 1991; Kolka and others, 1999). A study 

by St. Louis and others (2001) showed that the tree canopies 

of boreal forests receiving low atmospheric deposition are 

significant sources of both MeHg and THg via litter fall to the 

forest floor, wetlands, and potentially to downstream water 

bodies. This underscores the greater sensitivity and efficiency 

of these two LULC types with regard to Hg methylation.
50 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Summary and Conclusions

Hg in top-predator fish, bed sediment, and water was 

examined from streams in diverse settings across the United 

States during 1998–2005 by the USGS. Most studies of Hg 

in aquatic environments have focused on lakes, reservoirs, 

and wetlands because of the predominance of lakes with Hg 

concerns and the importance of wetlands in Hg methylation. 

Fewer studies have focused on Hg in streams or rivers. This 

report describes the occurrence and distribution of THg in 

stream fish in relation to regional and national gradients of Hg 

source strength (including atmospheric deposition, gold and 

Hg mining, urbanization) and other factors that are thought 

to affect Hg concentrations, including LULC. In addition, 

concentrations of THg and MeHg in bed sediment and stream 

water were evaluated in relation to these gradients and to 

identify ecosystem characteristics that favor the production 

and bioaccumulation of MeHg. 

Site selection targeted environmental settings thought 

to be important with regard to the source, concentration, 

or biogeochemical behavior of Hg in aquatic ecosystems. 

Agricultural, urban, undeveloped (forested, grassland, 

shrubland, and wetland land cover), and mined (for gold 

and Hg) settings were of particular interest. Each site was 

sampled one time during seasonal low flow. Predator fish 

were targeted for collection, and composited skin-off fillets 

were analyzed for THg, as most of the Hg found in fish tissue 

(95–99 percent) is MeHg. Bed sediment and stream water 

were analyzed for THg, MeHg, and characteristics thought 

to affect Hg methylation, such as LOI, AVS, pH, DOC, and 

dissolved sulfate. 

Key findings of this report are as follows:

• Hg concentrations in fish at more than two-thirds of 

the sites exceeded the value of 0.1 μg/g Hg ww that is 

of concern for the protection of fish-eating mammals, 

including mink and otters. Fish-Hg concentrations 

equaling or exceeding the 0.3 μg/g ww USEPA 

criterion for the protection of human health were found 

at 27 percent of the sites. The highest concentrations 

among all sampled sites occurred in fish from 

blackwater coastal-plain streams draining forested 

land or wetland in the eastern and southeastern United 

States, as well as from streams draining gold- or 

Hg-mined basins in the western United States.

• Across the United States, concentrations of MeHg in 

unfiltered water and in bed sediment were generally 

low (median values were 0.11 and 0.51 ng/g, 

respectively). 

• Concentrations of MeHg in unfiltered water from 

several blackwater coastal-plain streams were similar 

to those of streams in mined basins, although THg 

concentrations were significantly lower than in mined 

basins. This finding emphasizes the importance of the 

amount of Hg in an ecosystem in combination with the 

capacity of an ecosystem to methylate inorganic Hg. 

• Across all sites, fish Hg was not significantly different 

between sites in unmined basins compared to mined 

basins, except for smallmouth bass. This exception was 

driven by one high outlier from a mined basin.

• Largemouth bass from predominantly undeveloped or 

mixed-land-use basins were significantly higher in Hg 

than were largemouth bass from urban basins. 

• Length-normalized Hg concentrations in largemouth 

bass from unmined basins were primarily related 

to basin percentages of evergreen forest and woody 

wetland, especially with proximity of these land-cover 

types to the sampling site. This finding underscores 

the sensitivity of these land-cover types to Hg 

bioaccumulation.

• Length-normalized Hg concentrations in largemouth 

bass were highly correlated with stream water and bed 

sediment chemistry, and with LULC characteristics, 

but this was not true for smallmouth bass. This finding 

warns against interspecies conversions of fish-Hg 

concentrations because different fish species are 

influenced by different factors.

• In addition to basin percentages of evergreen forest and 

woody wetland, increasing concentrations of MeHg in 

unfiltered stream water, increasing bed sediment MeHg 

normalized by loss-on-ignition (LOI), and decreasing 

pH and dissolved sulfate also were important as 

explanatory variables for Hg concentrations in 

largemouth bass. 

• In contrast to the positive relation for fish Hg with 

evergreen forest and woody wetland LULC, bedsediment THg concentrations were higher in urban 

sites. Higher concentrations of MeHg in bed sediment 

were found with higher THg, LOI, and AVS; LOI was 

a strong predictor of bed-sediment THg and MeHg.

• Concentrations of MeHg in unfiltered water were 

higher with higher DOC and increased DOC 

complexity (as measured by SUVA), THg in water, 

percentage of MeHg in bed sediment, and percentage 

of wetland in the basin. 

It is difficult to directly compare fish-Hg concentrations 

across the Nation by using any compilation of existing fish-Hg 

data. Increased water sampling over the water cycle, such as 

was done by Brigham and others (2009), Chasar and others 

(2009), and Marvin-DiPasquale and others (2009), could 

increase identification and understanding of factors leading to 

high Hg bioaccumulation. 
References 51

Acknowledgments

This study was supported by the following USGS 

programs and disciplines: National Water-Quality Assessment, 

Toxic Substances Hydrology, and National Research 

Programs; Water, Biology, and Geology Disciplines. We 

thank many USGS scientists and field staff for assistance in 

site selection, technical input, and careful sample collection. 

We especially wish to thank the following USGS employees: 

Rod DeWeese, for assistance in initial planning of the study; 

George Aiken and Kenna Butler, for DOC sample planning 

and analyses; William Brumbaugh, for assistance with use of 

fish results from the 1998 National Mercury Pilot Study and 

constructive comments on earlier versions of this manuscript; 

Michelle Lutz and James Kennedy, for preparation of nationalscale maps, and Michelle for additional assistance in data 

and figure preparation; Kerie Hitt, Dave Wolock, and Naomi 

Nakagaki, for GIS data compilation and preparation; Douglas 

Causey and William Ferguson, for assistance with retrieval 

and interpretation of data from the MRDS and MAS-MILS 

mining databases; John DeWild, Shane Olund, Mark Olson 

of the Wisconsin Mercury Research Laboratory, for their 

expertise and guidance in multimedia Hg sampling; and 

Ann Chalmers (USGS) and Bruce Monson (Environmental 

Analysis and Outcomes Division, Minnesota Pollution Control 

Agency), for their technical reviews on an earlier version of 

this manuscript. 

References

Aiken, G.R., 1992, Chloride interference in the analysis of 

dissolved organic carbon in the wet oxidation method: 

Environmental Science and Technology, v. 26, p. 2435—

2439.

Allen, H.E., Fu, G., Boothman, W., DiToro, D.M., and 

Mahony, J.D., 1991, Draft analytical method for 

determination of acid volatile sulfide in sediment: U.S. 

Environmental Protection Agency, 18 p.

Atwell, Lisa, Hobson, K.A., and Welch, H.E., 1998, 

Biomagnification and bioaccumulation of mercury in an 

arctic marine food web—Insights from stable nitrogen 

isotope analysis: Canadian Journal of Fisheries and Aquatic 

Sciences, v. 55, no. 5, p. 1114–1121.

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

Andren, A.W., and Webb, D.A., 1998, Seasonal influences 

on partitioning and transport of total and methylmercury in 

rivers from contrasting watersheds: Biogeochemistry, v. 41, 

no. 3, p. 237–257.

Balogh, S.J., Meyer, M.L., and Johnson, D.K., 1998, 

Tramsport of mercury in three contrasting river basins: 

Environmental Science & Technology, v. 32, no. 4, 456–62.

Bates, A.L., Spiker, E.C., Orem, W.H., Burnett, W.C., 1993, 

Speciation and isotopic composition of sulfur in sediments 

from Jellyfish Lake, Palau: Chemical Geology, v. 106, p. 

63—76.

 Bauch, N.J., Chasar, L.C., Scudder, B.C., Moran, P.W., Hitt, 

K.J., Brigham, M.E., Lutz, M.A., and Wentz, D.A., 2009, 

Data on mercury in water, streambed sediment, and fish 

tissue from selected streams across the United States, 1998–

2005: U.S. Geological Survey Data Series 307, available at 

http://pubs.usgs.gov/ds/307/

Benoit, J.M., Gilmour, C.C., Heyes, A., Mason, R.P., and 

Miller, C.L., 2003, Geochemical and biological controls 

over methylmercury production and degradation in aquatic 

ecosystems, chap. 19 of Chai, Y., and Braids, O.C., eds., 

Biogeochemistry of environmentally important trace 

elements: Washington D.C., American Chemical Society 

Symposium Series 835, p. 262–297. 

Bloom, Nicholas, 1989, Determination of picogram levels of 

methylmercury by aqueous phase ethylation, followed by 

cryogenic gas chromatography with cold vapour atomic 

fluorescence detection: Canadian Journal of Fisheries and 

Aquatic Sciences, v. 46, no. 7, p. 1131–1140.

Bloom, N.S., 1992, On the chemical form of mercury in edible 

fish and marine invertebrate tissue: Canadian Journal of 

Fisheries and Aquatic Sciences, v. 49, no. 5, p. 1010–1017.

Bloom, N.S., Watras, C.J., and Hurley, J.P., 1991, Impact of 

acidification on the methylmercury cycle of remote seepage 

lakes: Water, Air, and Soil Pollution, v. 56, 477-491.

Bodaly, R.A., Rudd, J.W.M., and Flett, R.J., 1998, Effect 

of urban sewage treatment on total and methyl mercury 

concentrations in effluents: Biogeochemistry, v. 40, no. 2/3, 

p. 279–291.

Boudou, A., and Ribeyre, F., 1983, Contamination of aquatic 

biocenoses by mercury compounds—An experimental 

ecotoxicological approach, in Nriagu, J.O., ed., Aquatic 

toxicology: New York, John Wiley and Sons, p. 73–116.

Boudou, A., and Ribeyre, F., 1997, Mercury in the food 

web—Accumulation and transfer mechanisms, in Sigel, 

Astrid, and Sigel, Helmut, eds., Mercury and its effects on 

environment and biology: New York, Marcel Dekker, Metal 

Ions in Biological Systems, v. 34, p. 289–319.

Branfireun, B.A.; Heyes, Andrew; and Roulet, N.T., 1996, The 

hydrology and methylmercury dynamics of a Precambrian 

Shield headwater peatland: Water Resources Research, 

v. 32, no. 6, p. 1785–1794.
52 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Brenton, R.W., and Arnett, T.L., 1993, Methods of analysis 

by the U.S. Geological Survey National Water Quality 

Laboratory–Determination of dissolved organic carbon 

by UV-promoted persulfate oxidation and infrared 

spectrometry: U.S. Geological Survey Open-File 

Report 92–480, 12 p.

Briand, Frédéric, and Cohen, J.E., 1987, Environmental 

correlates of food chain length: Science, v. 238, no. 4829, 

p. 956–960.

Brigham, M.E., Wentz, D.A., Aiken, G.R., and Krabbenhoft, 

D.P., 2009, Mercury cycling in stream ecosystems; 1. Water 

column chemistry and transport: Environmental Science & 

Technology, v. 43, p. 2720-2725.

Brightbill, R.A.; Riva-Murray, Karen; Bilger, M.D.; and 

Byrnes, J.D., 2003, Total mercury and methylmercury in 

fish fillets, water, and bed sediment from selected streams 

in the Delaware River basin, New Jersey, New York, and 

Pennsylvania, 1998–2001: U.S. Geological Survey WaterResources Investigations Report 03–4183, 30 p., accessed 

February 12, 2007, at http://pubs.usgs.gov/wri/wri03-4183/

Brumbaugh, W.G., Krabbenhoft, D.P., Helsel, D.R., 

Wiener, J.G., and Echols, K.R., 2001, A national pilot 

study of mercury contamination of aquatic ecosystems 

along multiple gradients—Bioaccumulation in fish: U.S. 

Geological Survey Biological Science Report 2001–0009, 

25 p.

Chalmers, Ann, 2002, Trace elements and organic compounds 

in streambed sediment and fish tissue of coastal New 

England streams, 1998–99: U.S. Geological Survey WaterResources Investigations Report 02–4179, 30 p.

Chalmers, Ann, and Krabbenhoft, D.P., 2001, Distribution of 

total and methyl mercury in water, sediment, and fish tissue 

in New England streams [abs.]: American Geophysical 

Union (AGU), May 29–June 2, 2001, Boston, Mass., 

accessed February 12, 2007, at http://nh.water.usgs.gov/

projects/nawqa/sw_merc.htm

Chasar, L.C., Scudder, B.C., Stewart, A.R., Bell, A.H., and 

Aiken, G.R., 2009, Mercury cycling in stream ecosystems; 

3. Trophic dynamics and methylmercury bioaccumulation: 

Environmental Science & Technology, v. 43, p. 2733-2739.

Christensen, V.G., Wente, S.P., Sandheinrich, M.B., and 

Brigham, M.E., 2006, Spatial variation in fish-tissue 

mercury concentrations in the St. Croix River basin, 

Minnesota and Wisconsin, 2004: U.S. Geological Survey 

Scientific Investigations Report 2006–5063, 26 p., accessed 

March 19, 2007, at http://pubs.usgs.gov/sir/2006/5063/

Chumchal, M.M., Drenner, R.W., Fry, Brian, Hambright, K.D., 

and Newland, L.W., 2008, Habitat-specific differences in 

mercury concentrations in a top predator from a shallow 

lake: Transactions of the American Fisheries Society, v. 137, 

p. 195-208.

Compeau, Geoffrey, and Bartha, Richard, 1983, Effects of sea 

salt anions on the formation and stability of methylmercury: 

Bulletin of Environmental Contamination and Toxicology, 

v. 31, p. 486–493.

Compeau, G.C., and Bartha, Richard, 1987, Effect of salinity 

on mercury-methylating activity of sulfate-reducing 

bacteria in estuarine sediments: Applied and Environmental 

Microbiology, v. 53, no. 2, p. 261–265.

Daly, C., Neilson, R.P., and Phillips, D.L., 1994, A statisticaltopographic model for mapping climatological precipitation 

over mountainous terrain: Journal of Applied Meteorology, 

v. 33, no. 2, p. 140–158.

Daly, C., Taylor, G.H., and Gibson, W.P., 1997, The PRISM 

approach to mapping precipitation and temperature: 

Proceedings, American Meteorological Society 10th 

Conference on Applied Climatology, Reno, Nev., October 

20–23, 1997, p. 10–12. 

Data Description Inc., 1996, Data Desk, Version 6.1: Ithaca, 

N.Y., Data Description Inc.

Davis, J.A.; Greenfield, B.K.; Ichikawa, Gary; and 

Stephenson, Mark, 2008, Mercury in sport fish from the 

Sacramento-San Joaquin Delta region, California, USA: 

Science of the Total Environment, v. 391, no. 1, p. 66–75.

Dennis, I.F; Clair, T.A.; Driscoll, C.T.; Kamman, Neil; 

Chalmers, Ann; Shanley, Jamie; Norton, S.A., and Kahl, 

Steve, 2005, Distribution patterns of mercury in lakes and 

rivers of northeastern North America: Ecotoxicology, v. 14, 

nos. 1–2, p. 113–123.

DeWild, J.F., Olson, M.L., and Olund, S.D., 2002, 

Determination of methyl mercury by aqueous phase 

ethylation, followed by gas chromatographic separation 

with cold vapor atomic fluorescence detection: U.S. 

Geological Survey Open-File Report 01–445, 14 p., 

accessed March 16, 2007, at http://pubs.er.usgs.gov/

usgspubs/ofr/ofr2001445

DeWild, J.F., Olund, S.D., Olson, M.L, and Tate, M.T., 2004, 

Methods for the preparation and analysis of solids and 

suspended solids for methylmercury: U.S. Geological 

Survey Techniques and Methods, book 5, chap. A7, 

accessed March 16, 2007, at http://pubs.usgs.gov/tm/2005/

tm5A7/
References 53

Domagalski, Joseph, 1998, Occurrence and transport of total 

mercury and methyl mercury in the Sacramento River 

Basin, California: Journal of Geochemical Exploration, 

v. 64, nos. 1–3, p. 277–291.

Driscoll, C.T., Yan, Cheng, Schofield, C.L., Munson, Ron, 

Holsapple, John, 1994, The mercury cycle and fish in the 

Adirondack lakes: Environmental Science and Technology, 

v. 28, no. 3, p. 136-143.

Eisler, Ronald, 1987, Mercury hazards to fish, wildlife, and 

invertebrates—A synoptic review: Laurel, Md., U.S. Fish 

and Wildlife Service Biological Report 85(1.10), 63 p. 

Eisler, Ronald, 2004, Mercury hazards from gold mining to 

humans, plants, and animals: Review of Environmental 

Contamination and Toxicology, v. 181, p. 139–198.

Engstrom, D.R., and Swain, E.B., 1997, Recent declines in 

atmospheric mercury deposition in the upper Midwest: 

Environmental Science and Technology, v. 31, p. 960-967.

Environment Canada, 2005, Guidelines at a glance—Inorganic 

mercury and methylmercury: Ottawa, Ontario, National 

Guidelines and Standards Office, 2 p., accessed June 

18, 2008, at http://www.ec.gc.ca/ceqg-rcqe/English/Pdf/

GAAG_Mercury_WQG_e.pdf

Falcone, James; Stewart, Jana; Sobieszczyk, Steven; 

Dupree, Jean; McMahon, Gerard; and Buell, Gary, 2007, 

A comparison of natural and urban characteristics and 

the development of urban intensity indices across six 

geographic settings: U.S. Geological Survey Scientific 

Investigations Report 2007–5123, 43 p.

Fishman, M.J., and Friedman, L.C., 1989, Methods for 

determination of inorganic substances in water and fluvial 

sediments: U.S. Geological Survey Techniques of WaterResources Investigations, book 5, chap. A1, sec. 15, 

p. 465–498, accessed March 16, 2007, at http://pubs.usgs.

gov/twri/twri5-a1/

Fitzgerald, W.F., Engstrom, D.R., Mason, R.P., and 

Nater, E.A., 1998, The case for atmospheric mercury 

contamination in remote areas: Environmental Science & 

Technology, v. 32, no. 1, p. 1–7.

Flannagan, S.M., Nielsen, M.G., Robinson, K.W., and Coles, 

J.F., 1999, Water-quality assessment of the New England 

Coastal Basins in Maine, Massachusetts, New Hampshire, 

and Rhode Island—Environmental settings and implications 

for water quality and aquatic biota: U.S. Geological Survey 

Water-Resources Investigations Report 98–4249, 64 p.

Francesconi, K.A., and Lenanton, R.C.J., 1992, Mercury 

contamination in a semi-enclosed marine embayment—

Organic and inorganic mercury content of biota, and factors 

influencing mercury levels in fish: Marine Environmental 

Research, v. 33, no. 3, p. 189–212.

Gilliom, R.J., Alley, W.M., and Gurtz, M.E., 1995, Design 

of the National Water-Quality Assessment Program—

Occurrence and distribution of water-quality conditions: 

U.S. Geological Survey Circular 1112, 33 p.

Gilliom, R.J.; Barbash, J.E.; Crawford, C.G.; Hamilton, 

P.A.; Martin, J.D.; Nakagaki, Naomi; Nowell, L.H.; Scott, 

J.C.; Stackelberg, P.E.; Thelin, G.P.; and Wolock, D.M., 

2006, The quality of our Nation’s waters—Pesticides in 

the Nation’s streams and groundwater, 1992–2001: U.S. 

Geological Survey Circular 1291, 173 p.

Gilliom, R.J., Hamilton, P.A., and Miller, T.L., 2001, The 

National Water-Quality Assessment Program—Entering a 

new decade of investigations: U.S. Geological Survey Fact 

Sheet 071–01, 6 p.

Gilmour, C.C., Henry, E.A., and Mitchell, Ralph, 1992, 

Sulfate stimulation of mercury methylation in freshwater 

sediments: Environmental Science & Technology, v. 26, 

no. 11, p. 2281–2287.

Gilmour, C.C., Riedel, G.S., Ederington, M.C., Bell, 

J.T., Benoit, J.M., Gill, G.A., and Stordal, M.C., 1998, 

Methylmercury concentrations and production rates 

across a trophic gradient in the northern Everglades: 

Biogeochemistry, v. 40, no. 2/3, p. 327–345.

Goddard, K.E., 1988, Gold-mill-tailings contamination 

of the Cheyenne River system, Western South Dakota, 

chap. A of Mallard, G.E., ed., U.S. Geological Survey 

Toxic Substances Hydrology Program—Surface-water 

contamination: Proceedings of the Technical Meeting, 

Denver, Colo., February 2–4, 1987, p. 1–20.

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: Canadian Journal of Fisheries and Aquatic 

Sciences, v. 53, no. 2, p. 244–252.

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

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

mercury accumulation in fish in the upper Michigan 

peninsula: Environmental Toxicology and Chemistry, v. 9, 

no. 7, p. 919–930.

Grigal, D.F., 2002, Inputs and outputs of mercury from 

terrestrial watersheds—A review: Environmental Reviews, 

v. 10, no. 1, p. 1–39.

Hall, B.D., Bodaly, R.A., Fudge, R.J.P., Rudd, J.W.M., and 

Rosenberg, D.M., 1997, Food as the dominant pathway 

of methylmercury uptake by fish: Water, Air, and Soil 

Pollution, v. 100, p. 13–24.
54 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Hammerschmidt, C.R., and Fitzgerald, W.F., 2006, 

Methylmercury in freshwater fish linked to atmospheric 

mercury deposition: Environmental Science & Technology, 

v. 40, p. 7764–7770.

Heiri, Oliver, Lotter, A.F., and Lemcke, Gerry, 2001, Loss on 

ignition as a method for estimating organic and carbonate 

content in sediments–Reproducibility and comparability of 

results: Journal of Paleolimnology, v. 25, no. 1, p. 101–110.

Helsel, D.R., 1995, Design of a relational water-quality 

assessment program: Alexandria, Va., American Statistical 

Association, Proceedings of the Biometrics Section, 

p. 60–67.Hinck, J.E., Bartisch, T.M., Blazer, V.S., 

Denslow, N.D., Gross, T.S., Myers, M.S., Anderson, P.J., 

Orazio, C.E., and Tillit, D.E., 2004a, Biomonitoring of 

Environmental Status and Trends (BEST) program—

Environmental contaminants and their effrects on fish in 

the Yukon River Basin: U.S. Geological Survey Scientific 

Investigations Report 2004–5285, 87 p.

Hinck, J.E.; Blazer, V.S.; Denslow, N.D.; Echols, K.R.; 

Gale, R.W.; May, T.W.; Claunch, Rachael; Wieser, Carla; 

Anderson, P.J.; Coyle, J.J.; Gross, T.S.; and Tillitt, D.E., 

2007, Biomonitoring of Environmental Status and Trends 

(BEST) program—Environmental contaminants, health 

indicators, and reproductive biomarkers in fish from the 

Mobile, Apalachicola-Chattahoochee-Flint, Savannah, and 

Pee Dee River Basins: U.S. Geological Survey Scientific 

Investigations Report 2007–5176, 114 p.

Hinck, J.E., Blazer, V.S., Denslow, N.D., Gross, T.S., Echols, 

K.R., Davis, A.P., May, T.W., Orazio, C.E., Coyle, J.J., and 

Tillitt, D.E., 2006, Biomonitoring of Environmental Status 

and Trends (BEST) program—Environmental contaminants 

and their effects on fish in the Colorado River Basin: U.S. 

Geological Survey Scientific Investigations Report 2006–

5163, 119 p.

Hinck, J.E., Schmitt, C.J., Bartisch, T.M., Denslow, N.D., 

Blazer, V.S., Anderson, P.J., Coyle, J.J., Dethloff, G.M., and 

Tillit, D.E., 2004b, Biomonitoring of Environmental Status 

and Trends (BEST) program—Environmental contaminants 

and their effrects on fish in the Columbia River Basin: U.S. 

Geological Survey Scientific Investigations Report 2004–

5154, 125 p.

Horowitz, A.J., and Stephens, V.C., 2008, The effects of land 

use on fluvial sediment chemistry for the conterminous 

U.S.—Results from the first cycle of the NAWQA 

Program—Trace and major elements, phosphorus, carbon, 

and sulfur: Science of the Total Environment, v. 400, nos. 

1–3, p. 290–314.

Horvat, M., Liang, L., and Bloom, N.S., 1993, Comparison 

of distillation with other current isolation methods for the 

determination of methyl mercury compounds in low-level 

environmental samples—Part II. Water: Analytica Chimica 

Acta, v. 282, no. 1, p. 153–168.

Huckabee, J.W., Elwood, J.W., and Hildebrand, S.G., 1979, 

Accumulation of mercury in freshwater biota, in Nriagu, 

J.O., ed., Biogeochemistry of mercury in the environment: 

New York, Elsevier/North-Holland Biomedical Press, 

p. 277–302.

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

Andren, A.W.; Sullivan, J.R.; Hammond, Richard; and 

Webb, D.A., 1995, Influences of watershed characteristics 

on mercury levels in Wisconsin Rivers: Environmental 

Science & Technology, v. 29, no. 7, p. 1867–1875.

Insightful Corporation, 1998–2005, S-PLUS version 7.0 for 

Windows (computer software): Seattle, Wash.

Iverfeldt, Ake, 1991, Mercury in forest canopy throughfall 

water and its relation to atmospheric deposition: Water, Air, 

and Soil Pollution, v. 56, p. 553-564.

Jearld, A., Jr., 1983, Age determination, in Nielsen, L.A., and 

Johnson, D.L., eds., Fisheries techniques: Bethesda, Md., 

American Fisheries Society, p. 301–324.

Kamman, N.C.; Burgess, N.M.; Driscoll, C.T.; Simonin, 

H.A.; Goodale, Wing; Linehan, Janice; Estabrook, Robert; 

Hutcheson, Michael; Major, Andrew; Scheuhanmer, A.M.; 

and Scruton, D.A., 2005, Mercury in freshwater fish of 

northeast North America—A geographic perspective based 

on fish tissue monitoring databases: Ecotoxicology, v. 14, 

nos. 1–2, p. 163–180.

Kim, J.P., and Burggraaf, Shane, 1999, Mercury 

bioaccumulation in rainbow trout (Oncorhynchus mykiss) 

and the trout food web in lakes Okareka, Okaro, Tarawera, 

Rotomahana and Rotorua, New Zealand: Water, Air and 

Soil Pollution, v. 115, nos. 1–4, p. 535–546.

Kolka, R.K., Nater, E.A., Grigal, D.F., and Verry, E.S., 1999, 

Atmospheric inputs of mercury and organic carbon into 

a forested upland/bog watershed: Water, Air, and Soil 

Pollution, v. 113, p. 273-294.

Kotnik, Jože; Horvat, Milena; Fajon, Vesna; and Logar, 

Martina, 2002, Mercury in small freshwater lakes—A case 

study, Lake Velenje, Slovenia: Water Air and Soil Pollution, 

v. 134, nos. 1–4, p. 319–339.

Krabbenhoft, D.P., Benoit, J.M., Babiarz, C.L., Hurley, J.P., 

and Andren, A.W., 1995, Mercury cycling in the Allequash 

Creek watershed, Northern Wisconsin: Water, Air, and Soil 

Pollution, v. 80, nos. 1–4, p. 425–433.
References 55

Krabbenhoft, D.P., Engstrom, D., Gilmour, C., Harris, R., 

Hurley, J., and Mason, R., 2007, Monitoring and evaluating 

trends in sediment and water indicators, chap. 3 of Harris, 

R., Krabbenhoft, D.P., Mason, R., Murray, M.W., Reash, 

R., and Saltman, T., eds., Ecosystem responses to mercury 

contamination—Indicators of change: Boca Raton, Fla., 

CRC Press and Society of Environmental Toxicology and 

Chemistry, p. 47–86. 

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, in U.S. Geological Survey Toxic 

Substances Hydrology Program—Proceedings of the 

Technical Meeting, Charleston, S.C., March 8–12, 1999. 

Volume 2 of 3—Contamination of hydrologic systems 

and related ecosystems: U.S. Geological Survey WaterResources Investigations Report 99–4018B, p. 147–160.

Leahy, P.P., Rosenshein, J.S., and Knopman, D.S., 1990, 

Implementation plan for the National Water-Quality 

Assessment Program: U.S. Geological Survey Open-File 

Report 90–174, 10 p.

Lewis, M.E., and Brigham, M.E., 2004, Low level mercury: 

U.S. Geological Survey Techniques of Water-Resources 

Investigations, book 9, chap. A5, section 5.6.4.B, 26 p., 

accessed March 16, 2007, at http://water.usgs.gov/owq/

FieldManual/chapter5/pdf/5.6.4.B_v1.0.pdf

Lutz, M.A., Brigham, M.E., and Marvin-DiPasquale, M., 

2008, Procedures for collecting and processing streambed 

sediment and pore water for analysis of mercury as part 

of the National Water-Quality Assessment Program: U.S. 

Geological Survey Open-File Report 2008–1279, 68 p.

MacDonald, D.D., Ingersoll, C.G., and Berger, T.A. 2000, 

Development and evaluation of consensus-based sediment 

quality guidelines for freshwater ecosystems: Archives of 

Environmental Contamination and Toxicology, v. 39, no. 1, 

p. 20–31.

Marvin-DiPasquale, Mark, Lutz, M.A., Brigham, M.E., 

Krabbenhoft, D.P., Aiken, G.R., Orem, W.H., and Hall, 

B.D., 2009, Mercury cycling in stream ecosystems; 2. 

Benthic methylmercury production and bed sediment–pore 

water partitioning: Environmental Science & Technology, 

v. 43, p. 2726-2732.

Mason, R.P., Laporte, J.-M., and Andres, S., 2000, Factors 

controlling the bioaccumulation of mercury methylmercury, 

arsenic, selenium, and cadmium by freshwater invertebrates 

and fish: Archives of Environmental Contamination and 

Toxicology, v. 38, no. 3, p. 283–297.

Massachusetts Department of Environmental Protection, 

1995, Commonwealth of Massachusetts summary of water 

quality, 1995: North Grafton, Mass., Division of Water 

Pollution Control, 97 p.

Meili, Marcus, 1991, Mercury in forest lake ecosystems—

Bioavailability, bioaccumulation and biomagnifications, 

chap. 11 of Lindqvist, Oliver, and others, Mercury in 

the Swedish environment—Recent research on causes, 

consequences and corrective methods: Water Air and Soil 

Pollution, v. 55, nos. 1–2, p. 131–137.

Morel, F.M.M., Kraepiel, A.M.L., and Amyot, Marc, 1998. 

The chemical cycle and bioaccumulation of mercury: 

Annual Review of Ecology and Systematics, v. 29, 

p. 543-566.

Nakagaki, Naomi, and Wolock, D.M., 2005, Estimation of 

agricultural pesticide use in drainage basins using land 

cover maps and county pesticide data: U.S. Geological 

Survey Open-File Report 2005–1188, 46 p.

Norton, J.J., 1975, Mineral Resources—Introduction, in U.S. 

Geological Survey, Mineral and Water Resources of South 

Dakota: South Dakota Geological Survey Bulletin 16, 

p. 77–90. 

Olson, M.L., Cleckner, L.B., Hurley, J.P., Krabbenhoft, D.P., 

and Heelan, T.W., 1997, Resolution of matrix effects on 

analysis of total and methyl mercury in aqueous samples 

from the Florida Everglades: Fresenius’ Journal of 

Analytical Chemistry, v. 358, no. 3, p. 392–396. 

Olson, M.L., and DeWild, J.F., 1999, Techniques for the 

collection and species-specific analysis of low levels of 

mercury in water, sediment, and biota, in U.S. Geological 

Survey Toxic Substances Hydrology Program—Proceedings 

of the Technical Meeting, Charleston, South Carolina, 

March 8–12, 1999. Volume 2 of 3—Contamination of 

hydrologic systems and related ecosystems: U.S. Geological 

Survey Water-Resources Investigations Report 99–4018B, 

p. 191–199.

Olund, S.D., DeWild, J.F., Olson, M.L., and Tate, M.T., 2004, 

Methods for the preparation and analysis of solids and 

suspended solids for total mercury: U.S. Geological Survey 

Techniques of Water-Resources Investigations, book 5, 

chap. A8, accessed March 16, 2007, at http://pubs.usgs.gov/

tm/2005/tm5A8/

Paller, M.H., Jagoe, C.H., Bennett, H., Brant, H.A., and 

Bowers, J.A., 2004, Influence of methylmercury from 

tributary streams on mercury levels in Savannah River 

Asiatic clams: Science of the Total Environment, v. 325, 

p. 209-219.
56 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Peckenham, J.M., Kahl, J.S. and Mower, Barry, 2003, 

Background mercury concentrations in river water in Maine 

U.S.A.: Environmetnal Monitoring and Assessment, v. 89, 

no. 2, p. 129–152.

Peterson, S.A.; Van Sickle, John; Herlihy, A.T.; and Hughes, 

R.M., 2007, Mercury concentration in fish from streams and 

rivers throughout the western United States: Environmental 

Science & Technology, v. 41, no. 1, p. 58–65.

Pickhardt, P.C.; Folt, C.L.; Chen, C.Y.; Klaue, Bjoern; and 

Blum, J.D., 2002, Algal blooms reduce the uptake of toxic 

methylmercury in freshwater food webs: Proceedings of 

the National Academy of Sciences of the USA, v. 99, no. 7, 

p. 4419–4423.

Porak, W., Coleman, W.S., and Crawford, S., 1986, Age, 

growth, and mortality of Florida largemouth bass utilizing 

otoliths, in Proceedings of the annual conference of 

Southeastern Association of Fish and Wildlife Agencies, 

40th: Tallahassee, Fla., Southeastern Association of Fish 

and Wildlife Agencies, p. 206–215.

Ribeyre, F., and Boudou, A., 1984, Bioaccumulation et 

repartition tissulaire du mercure—HgCl et CH3HgCl—chez 

Salmo gairdneri après contamination par voie directe: 

Water, Air, and Soil Pollution, v. 23, no. 2, p. 169–186.

Ribeyre, F., and Boudou, A., 1994, Experimental study of 

inorganic and methylmercury bioaccumulation by four 

species of freshwater rooted macrophytes from water 

and sediment contamination sources: Ecotoxicology and 

Environmental Safety, v. 28, no. 3, p. 270–286.

Rumbold, D.G., Fink, L.E., Laine, K.A., Niemczyk, S.L., 

Chandrasekar, T., Wankel, S.D., Kendall, C., 2002, Levels 

of mercury in alligators (Alligator mississippiensis) 

collected along a transect through the Florida Everglades: 

Science of the Total Environment, v. 297, nos. 1–3, 

p. 239-252. 

Rypel, A.L., Arrington, D.A., and Findlay, R.H., 2008, 

Mercury in southeastern U.S. riverine fish populations 

linked to water body type: Environmental Science & 

Technology, v. 42, no. 14, p. 5118–5124.

St. Louis, V.L., Rudd, J.W.M., Kelly, 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: 

Canadian Journal of Fisheries and Aquatic Sciences, v. 51, 

no. 5, p. 1065–1076.

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

Flett, R.J., and Roulet, N.T.,1996, Production and loss 

of methylmercury and loss of total mercury from boreal 

forest catchments containing different types of wetlands: 

Environmental Science & Technology, v. 30, no. 9, 

p. 2719-2729.

St. Louis, V.L., Rudd, J.W.M., Kelly, C.A., Hall, B.D., 

Rolfhus, K.R., Scott, K.J., Lindberg, S.E., and Dong, 

Weijin, 2001, Importance of the forest canopy to fluxes of 

methyl mercury and total mercury to boreal ecosystems: 

Environmental Science & Technology, v. 35, no. 15, 

p. 3089–3098.

Schmitt, C.J., ed., 2002, Biomonitoring of Environmental 

Status and Trends (BEST) Program—Environmental 

contaminants and their effects on fish in the Mississippi 

River Basin: U.S Geological Survey Biological Science 

Report 2002–0004, 217 p., apps.

Schmitt, C.J., Dethloff, G.M., Hinck, J.E., Bartish, T.M., 

Blazer, V.S., Coyle, J.J., Denslow, N.D., and Tillitt, D.E., 

2004, Biomonitoring of Environmental Status and Trends 

(BEST) Program—Environmental contaminants and their 

effects on fish in the Rio Grande Basin: U.S. Geological 

Survey Scientific Investigations Report 2004–5108, 117 p.

Schmitt, C.J., Zajicek, J.L., May, T.W., and Cowman, D.F., 

1999, Organochlorine residues and elemental contaminants 

in U.S. freshwater fish, 1976–1986—National Contaminant 

Biomonitoring Program: Reviews of Environmental 

Contamination and Toxicology, v. 162, p. 43–104.

Scudder, B.C., Chasar, L.C., DeWeese, L.R., Brigham, M.E., 

Wentz, D.A., and Brumbaugh, W.G., 2008, Procedures for 

collecting and processing aquatic invertebrates and fish for 

analysis of mercury as part of the National Water-Quality 

Assessment Program: U.S. Geological Survey Open-File 

Report 2008–1208, 34 p. 

Seigneur, Christian; Vijayaraghavan, Krish; Lohman, Kristen; 

Karamchandani, Prakash; and Scott, Courtney, 2004, Global 

source attribution for mercury deposition in the United 

States: Environmental Science & Technology, v. 38, no. 2, 

p. 555–569.

Shelton, L.R., and Capel, P.D., 1994, Guidelines for collecting 

and processing samples of stream bed sediment for analysis 

of trace elements and organic contaminants for the National 

Water-Quality Assessment program: U.S. Geological 

Survey Open-File Report 94–458, 20 p.

Strahler, A.N., and Strahler, A.H., 1978, Modern physical 

geography: New York, John Wiley and Sons, 502 p.

Tchounwou, P.B.; Ayensu, W.K.; Ninashvili, Nannuli; and 

Sutton, Dwayne, 2003, Environmental exposure to mercury 

and its toxicopathologic implications for public health: 

Environmental Toxicology, v. 18, no. 3, p. 149–175.

ter Braak, C.J.F., and Šmilauer, Petr, 2002, CANOCO 

reference manual and CanoDraw for Windows User’s 

Guide—Software for Canonical Community Ordination 

(version 4.5): Ithaca, N.Y., Microcomputer Power, 500 p.
References 57

Trudel, Marc; Tremblay, Alain; Shchetagne, Roger; and 

Rasmussen, J.B., 2000, Estimating food consumption rates 

of fish using a mercury mass balance model: Canadian 

Journal of Fisheries and Aquatic Sciences, v. 57, no. 2, 

p. 414–428.

U.S. Department of Agriculture, 1994, State Soil Geographic 

(STATSGO) Data Base, data use information: U.S. 

Department of Agriculture, Natural Resources Conservation 

Service, National Soil Survey Center, Miscellaneous 

Publication 1492; available at http://www.nrcs.usda.gov/

technical/techtools/statsgo_db.pdf

U.S. Environmental Protection Agency (USEPA), 1995a, 

Great Lakes Water Quality Initiative technical support 

document for wildlife criteria: Washington, D.C., Office of 

Water, EPA 820–B95–009, 53 p.

U.S. Environmental Protection Agency (USEPA), 1995b, 

Great Lakes Water Quality Initiative technical support 

document for human health criteria and values: Washington, 

D.C., Office of Water, EPA 820–B95–007, 54 p. plus 

appendixes.

U.S. Environmental Protection Agency, 1996a, Method 

1669—Sampling ambient water for trace metals at EPA 

water quality criteria levels: Washington, D.C., Office of 

Water, Engineering and Analysis Division, 37 p., available 

at http://www.epa.gov/waterscience/methods/method/

inorganics/1669.pdf 

U.S. Environmental Protection Agency, 1996b, Method 

1631—Mercury in water by oxidation, purge and trap, and 

cold vapor atomic fluorescence (CVAS): Draft Methods 

EPA 821–R–96–012. 

U.S. Environmental Protection Agency, 1997, Mercury study 

report to Congress, Vol. 3—Fate and transport of mercury 

in the environment: Washington, D.C., Office of Air 

Quality Planning and Standards and Office of Research and 

Development, EPA–452/R–97–005, 376 p.

U.S. Environmental Protection Agency, 1998, Method 7473—

Mercury in solids and solutions by thermal decomposition, 

amalgamation, and atomic absorption spectrophotometry: 

Report SW–846, available at http://www.epa.gov/epawaste/

hazard/testmethods/sw846/online/7_series.htm

U.S. Environmental Protection Agency, 2000, Methodology 

for deriving ambient water quality criteria for the protection 

of human health: Washington, D.C., Office of Science 

and Technology/Office of Water, EPA–822–B–00–004 

[variously paged].

U.S. Environmental Protection Agency, 2001, Water quality 

criterion for protection of human health—Methylmercury: 

Washington, D.C., Technical Report EPA/823/R–01/001 

[variously paged]. 

U.S. Environmental Protection Agency, 2002, Method 1631 

Revision E—Mercury in water by oxidation, purge, and 

trap, and cold vapor atomic fluorescence spectrometry: 

EPA–821–R–02–019, 38 p., available at http://www.epa.

gov/waterscience/methods/1631e.pdf

U.S. Environmental Protection Agency, 2007, 2005/2006 

National listing of fish advisories: Washington D.C, Office 

of Water, Fact Sheet EPA–823–F–07–003, 7 p., available 

at http://www.epa.gov/waterscience/fish/advisories/2006/

index.html

U.S. Environmental Protection Agency, 2009, Guidance for 

implementing the January 2001 methylmercury water 

quality criterion: Washington D.C, Office of Water, EPA 

823–R–09–002, 201 p.

U.S. Geological Survey, 2002, Elevation Derivatives for 

National Applications (EDNA) [digital data], accessed 

January 2006, available at http://edna.usgs.gov/

U.S. Geological Survey, 2004, Mineral Resources Data 

System (MRDS) [digital data], available at http://tin.er.usgs.

gov/mrds/

Vogelmann, J.E.; Howard, S.M.; Yang, Limin; Larson, C.R.; 

Wylie, B.K.; and Van Driel, Nick, 2001, Completion of the 

1990’s national land cover dataset for the conterminous 

United States from Landsat Thematic Mapper data and 

ancillary data sources: Photogrammetric Engineering and 

Remote Sensing, v. 67, no. 6, p. 650–662.

Waldron, M.C., Colman, J.A., and Breault, R.F., 2000, 

Distribution, hydrologic transport, and cycling of total 

mercury and methyl mercury in a contaminated riverreservoir-wetland system (Sudbury River, eastern 

Massachussetts): Canadian Journal of Fisheries and Aquatic 

Sciences, v. 57, no. 5, p. 1080–1091. 

Watras, C.J., and Bloom, N.S., 1992, Mercury and 

methylmercury in individual zooplankton—Implications 

for bioaccumulation. Limnology and Oceanography, v. 37, 

no. 6, p. 1313–1318.

Weishaar, J.L., Aiken, G.R., Bergamaschi, B.A., Fram, M.S., 

Fujii, Roger, and Mopper, Kenneth, 2003, Evaluation 

of specific ultraviolet absorbance as an indicator of the 

chemical composition and reactivity of dissolved organic 

carbon: Environmental Science and Technology, v. 37, 

no. 20, p. 4702-4708.

Wente, S.P., 2000, Proximity-based measure of land use 

impacts to aquatic ecosystem integrity: Environmental 

Toxicology and Chemistry, v. 19, no. 4(2), p. 1148–1152.
58 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Wente, S.P., 2004, A statistical model and national data set 

for partitioning fish-tissue mercury concentration variation 

between spatiotemporal and sample characteristic effects: 

U.S. Geological Survey Science Investigations Report 

2004–5199, 15 p., available at http://pubs.usgs.gov/

sir/2004/5199/

Westcott, Kim, and Kalff, Jacob, 1996, Environmental factors 

affecting methyl mercury accumulation in zooplankton: 

Canadian Journal of Fisheries and Aquatic Sciences, v. 53, 

no. 10, p. 2221–2228.

Wiener, J.G., 1995, Bioaccumulation of mercury in fish, 

in Proceedings—National Forum on Mercury in Fish, 

September 27–29, 1994, New Orleans, La.: Washington, 

D.C., U.S. Environmental Protection Agency, Office of 

Water, EPA 823–R–95–002, p. 41–52.

Wiener, J.G., Krabbenhoft, D.P., Heinz, G.H., and 

Scheuhammer, A.M., 2003, Ecotoxicology of mercury, 

chap. 16 of Hoffman, D.J., Rattner, B.A., Burton, G.A., Jr., 

and Cairns, J., Jr., eds., Handbook of ecotoxicology (2d 

ed.): Boca Raton, Fla., Lewis Publishers, p. 409–463.

Wiener, J.G., and Shields, P.J., 2000, Mercury in the Sudbury 

River (Massachusetts, U.S.A.)—Pollution history and a 

synthesis of recent research: Canadian Journal of Fisheries 

and Aquatic Sciences, v. 57, no. 5, p. 1053–1061.

Wiener, J.G., and Spry, D.J., 1996, Toxicological 

significance of mercury in freshwater fish, in Beyer, 

W.N., Heinz, G.H., and Redmon-Norwood, A.W. , eds., 

Environmental contaminants in wildlife—Interpreting 

tissue concentrations: Boca Raton, Fla., Lewis Publishers, 

p. 297–339. 

Wiener, J.G., and Stokes, P.M., 1990, Enhanced 

bioaccumulation of mercury, cadmium, and lead in lowalkalinity waters—An emerging regional environmental 

problem: Environmental Toxicology and Chemistry, v. 9, 

p. 821–823.

Wolfe, M.F., Atkeson, T., Bowerman, W., Burger, J., Evers, 

D.C., Murray, M.W., and Zillioux, E., 2007, Wildlife 

indicators, chap. 5 of Harris, R., Krabbenhoft, D.P., Mason, 

R., Murray, M.W., Reash, R.J., and Saltman, T., eds., 

Ecosystem responses to mercury contamination: Pensacola, 

Fla., CRC Press and Society of Environmental Toxicology 

and Chemistry, p. 123–189.

Wolock, D.M., 1997, STATSGO soil characteristics for the 

conterminous United States: U.S., Geological Survey OpenFile Report 97–656 [digital data], available at http://water.

usgs.gov/GIS/metadata/usgswrd/XML/muid.xml

Wolock, D.M., 2003a, Base-flow index grid for the 

conterminous United States: U.S. Geological Survey OpenFile Report 03–263 [digital data], accessed December 6, 

2006, at http://water.usgs.gov/lookup/getspatial?bfi48grd

Wolock, D.M., 2003b, Flow characteristics at U.S. Geological 

Survey streamgages in the conterminous United States: 

U.S. Geological Survey Open-File Report 03-146 [digital 

data], accessed December 6, 2006, at http://water.usgs.gov/

lookup/getspatial?qsitesdd

Wolock, D.M., and McCabe, G.J., 2000, Differences 

in topographic characteristics computed from 100- 

and 1000-m resolution digital elevation model data: 

Hydrological Processes, v. 14, p. 987–1002.

Wong, A.H.K., McQueen, D.J., Williams, D.D., and Demers, 

Eric, 1997, Transfer of mercury from benthic invertebrates 

to fishes in lakes with contrasting fish community 

structures: Canadian Journal of Fisheries and Aquatic 

Sciences, v. 54, no. 6, p. 1320–1330.

Yeardley, R.B., Jr., Lazorchak, J.M., and Paulsen, S.G., 1998, 

Elemental fish tissue contamination in northeastern U.S. 

lakes—Evaluation of an approach to regional assessment: 

Environmental Toxicology and Chemistry, v. 17, no. 9, 

p. 1875–1884.

Yokoo, E.M.; Valente, J.G.; Granttan, Lynn; Schmidt, S.L.; 

Platt, Illeane; and Silbergeld, E.K., 2003, Low level 

methylmercury exposure affects neuropsychological 

function in adults: Environmental Health—A Global Access 

Science Source, v. 2, no. 8, p. 1–11.
Table 7

59

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

ACAD.1 Bogue Falaya at Covington, La. 07375170 30 29 59 -090 05 04 * No * * * * * * *

ACAD.2 Tangipahoa River at Robert, La. 07375500 30 30 24 -090 21 42 1,675 No 3.3 33.4 58.4 3.0 0.0 1.9 Mixed

ACAD.3 Blind River near Gramercy, La. 07380222 30 06 01 -090 44 07 141 No 6.5 40.5 3.8 46.6 0.0 2.5 Mixed

ACAD.4 Bayou Boeuf at Railroad Bridge 

at Amelia, La.

073814675 29 40 06 -091 05 59 3,171 No 4.8 37.7 3.6 52.4 0.1 1.5 Mixed

ACAD.5 Bayou Teche at Keystone Lock near St. 

Martinville, La.

07385700 30 04 16 -091 49 45 181 No 14.6 66.7 6.1 10.6 0.2 1.7 Mixed

ACAD.6 Mermentau River at Mermentau, La. 08012150 30 11 24 -092 35 26 3,576 No 3.2 63.7 20.9 10.0 0.9 1.2 Ag

ACAD.7 Bayou Lacassine near Lake Arthur, La. 08012470 30 04 12 -092 52 44 767 No 2.2 87.6 2.9 6.7 0.2 0.4 Ag

ACAD.8 Whiskey Chitto Creek near Oberlin, La. 08014500 30 41 56 -092 53 35 1,305 No 1.4 8.2 65.8 15.3 0.0 9.4 Undev

ACAD.9 Calcasieu River near Kinder, La. 08015500 30 30 09 -092 54 56 4,442 No 1.8 11.3 64.9 15.5 0.0 6.3 Undev

ACAD.10 Turtle Bayou near Bayou 

Penchant, La.

293524091041300 29 35 25 -091 04 13 * No * * * * * * *

ACAD.11 Bayou Segnette 4.6 mi South of Westwego, La. 294957090095300 29 49 58 -090 09 53 62 No 35.1 0.5 5.1 55.0 0.5 3.8 Urban

ACFB.1 New River near Sumatra, Fla. 02330400 30 02 20 -084 50 38 449 No 0.0 0.3 34.3 64.4 0.0 1.0 Undev

ACFB.2 Peachtree Creek at Atlanta, Ga. 02336300 33 49 10 -084 24 28 222 No 85.3 0.0 14.2 0.0 0.0 0.4 Urban

ACFB.3 Chattahoochee River near Whitesburg, Ga. 02338000 33 28 37 -084 54 03 6,251 Yes 19.2 10.2 66.0 0.7 0.0 3.8 Mixed

ACFB.4 Mulberry Creek at Mountain Hill Road, below 

Hamilton, Ga.

02341230 32 40 56 -085 00 30 421 No 1.1 7.2 84.6 1.8 0.0 5.2 Undev

ACFB.5 Flint River at Montezuma, Ga. 02349500 32 17 54 -084 02 38 7,575 Yes 4.8 18.4 65.3 7.8 0.0 3.8 Undev

ACFB.6 Cooleewahee Creek near 

Newton, Ga.

02352980 31 19 49 -084 19 50 400 No 4.5 38.3 33.2 20.1 0.0 3.9 Mixed

ACFB.7 Chickasawhatchee Creek at Elmodel, Ga. 02354500 31 21 02 -084 28 57 818 No 0.9 32.0 37.4 24.2 0.0 5.6 Mixed

ACFB.8 Spring Creek at US Hwy 84 at Brinson, Ga. 02357050 30 58 31 -084 44 44 1,394 No 0.9 52.0 29.9 12.9 0.0 4.3 Ag

ALBE.1 Nottoway River near Sebrell, Va. 02047000 36 46 14 -077 09 58 3,731 No 2.1 20.6 66.4 7.6 0.0 3.3 Undev

ALBE.2 Ahoskie Creek near Poortown, N.C. 02053490 36 17 19 -077 01 31 150 No 3.9 24.6 52.7 16.8 0.0 1.9 Mixed

ALBE.3 Falling River below Hat Creek 

near Brookneal, Va.

02065000 37 04 54 -078 56 07 575 No 3.0 27.6 65.8 0.8 0.0 2.8 Mixed

ALBE.4 Grindle Creek at US 264 at Pactolus, N.C. 0208412725 35 37 28 -077 13 16 192 No 1.3 38.8 34.7 22.0 0.0 3.2 Mixed

ALBE.5 Flat River at SR 1737 near Red Mountain, N.C. 0208539150 36 14 31 -078 54 21 265 No 4.9 29.8 64.0 0.6 0.0 0.7 Mixed

ALBE.6 Crabtree Creek at US 1 at Raleigh, N.C. 02087324 35 48 40 -078 36 39 315 No 33.7 6.2 55.2 2.1 0.0 2.8 Urban

ALBE.7 Walnut Creek at Sunnybrook Drive near Raleigh, 

N.C.

02087359 35 45 30 -078 34 59 77 No 61.8 3.2 26.0 2.4 0.0 6.5 Urban

ALBE.8 Contentnea Creek at Hookerton, N.C. 02091500 35 25 44 -077 34 57 1,909 No 4.3 41.9 33.4 19.4 0.0 1.0 Mixed

ALMN.1 Clarion River at Ridgway, Pa. 03029000 41 25 15 -078 44 09 791 No 2.8 6.9 89.0 0.2 0.0 1.1 Undev
60 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

ALMN.2 Allegheny River at New Kensington, Pa. 03049625 40 33 52 -079 46 21 29,728 No 2.5 20.8 74.0 1.0 0.0 1.8 UndevALMN.3 Dunkard Creek at Shannopin, Pa. 03072000 39 45 33 -079 58 14 588 No 0.7 20.3 78.2 0.1 0.0 0.8 UndevALMN.4 Tenmile Creek near Amity, Pa. 03072815 40 01 11 -080 12 19 134 No 2.3 44.2 53.4 0.0 0.0 * Mixed

ALMN.5 Youghiogheny River at Sutersville, Pa. 03083500 40 14 24 -079 48 23 4,429 No 3.6 26.4 67.2 0.7 0.0 2.0 Mixed

CACI.1 North Canadian River near Calumet, Okla. 07239450 35 37 01 -098 03 55 34,332 No 0.4 43.4 1.0 0.1 54.7 0.4 Mixed

CACI.2 North Canadian River at Britton Rd at OKC, Okla. 07241520 35 33 56 -097 22 02 35,478 No 1.2 43.6 1.1 0.1 53.5 0.5 Mixed

CAZB.1 Verde River above W. Clear Creek, near Camp 

Verde, Ariz.

09505570 34 30 20 -111 50 08 11,211 Yes 1.1 0.4 44.6 0.0 53.1 0.7 Undev

CAZB.2 West Clear Creek near Hwy 260, Ariz. 343104111461300 34 31 04 -111 46 16 665 No 0.0 0.0 86.6 0.0 13.4 * UndevCAZB.3 Wet Beaver Creek at Beaver Creek Campground, 

Ariz.

344010111424300 34 40 10 -111 42 46 299 No 0.0 0.0 79.4 0.0 20.6 * Undev

CAZB.4 Verde River above Perkinsville diversion, Ariz. 345338112124500 34 53 38 -112 12 48 7,587 Yes 0.8 0.3 34.3 0.0 63.7 0.9 Undev

CCYK.1 Crab Creek at Rocky Ford Road near Ritzville, 

Wash.

12464770 47 18 10 -118 22 09 1,188 No 1.2 66.6 4.0 0.3 27.4 0.4 Ag

CCYK.2 Umtanum Creek near mouth at Umtanum, Wash. 12484550 46 51 26 -120 29 50 137 No 0.0 2.7 6.4 0.0 90.8 0.1 UndevCCYK.3 S F Ahtanum Creek above Conrad Ranch near 

Tampico, Wash.

12500900 46 29 31 -120 57 27 48 No 0.0 0.0 79.0 0.0 16.7 4.3 Undev

CCYK.4 Satus Creek at gage at Satus, Wash. 12508620 46 16 25 -120 08 36 1,458 No 0.1 0.7 29.4 0.1 69.4 0.4 UndevCCYK.5 Yakima River at Kiona, Wash. 12510500 46 15 12 -119 28 41 14,536 Yes 2.1 15.0 36.2 0.2 41.9 4.7 MixedCCYK.6 Rock Creek below Cottonwood Creek near 

Revere, Wash.

13349700 47 06 16 -117 47 17 1,767 No 1.3 81.2 2.9 0.1 13.6 0.9 Ag

CCYK.7 Frenchmannhills at Road I, near George, Wash. 470012119410300 47 00 12 -119 41 03 297 No 2.8 80.8 0.1 0.6 15.2 0.5 Ag

CHEY.1 Moreau River near Whitehorse, S. Dak. 06360500 45 15 21 -100 50 35 12,657 No 0.1 18.1 0.3 0.7 79.5 1.3 Undev

CHEY.2 Cheyenne River near Hot Springs S. Dak. 06400500 43 18 19 -103 33 45 22,592 Yes 0.1 1.2 7.9 1.0 89.4 0.4 UndevCHEY.3 Cheyenne River at Redshirt, S. Dak. 06403700 43 40 23 -102 53 38 26,563 Yes 0.2 2.7 8.7 0.9 86.9 0.6 UndevCHEY.4 Cheyenne River near Wasta, S. Dak. 06423500 44 04 52 -102 24 05 32,865 Yes 0.5 3.9 12.9 0.9 80.4 1.4 UndevCHEY.5 Belle Fourche River at Belle Fourche, S. Dak. 06429000 44 40 30 -103 51 22 8,602 Yes 0.4 6.5 10.9 2.3 79.4 0.6 UndevCHEY.6 Belle Fourche River below Nisland, S. Dak. 06436100 44 40 12 -103 29 32 11,888 Yes 0.4 8.5 18.1 2.8 69.7 0.5 Undev

CHEY.7 Whitewood Creek above Lead, S. Dak. 06436150 44 18 07 -103 46 59 22 No 0.2 0.0 85.7 3.1 11.0 * Undev

CHEY.8 Whitewood Creek at Deadwood, S. Dak. 06436170 44 22 48 -103 43 27 105 Yes 3.3 0.0 78.6 1.6 13.9 2.6 UndevCHEY.9 Whitewood Creek above Whitewood, S. Dak. 06436180 44 26 32 -103 37 46 147 Yes 2.6 1.7 76.5 1.9 15.4 1.9 Undev

CHEY.10 Whitewood Creek above Vale, S. Dak. 06436198 44 37 04 -103 28 54 267 Yes 1.9 15.5 46.7 5.0 30.0 1.1 UndevCHEY.11 Belle Fourche River at Vale, S. Dak. 06436250 44 38 10 -103 25 39 12,787 Yes 0.4 8.6 17.8 2.9 69.5 0.7 UndevCHEY.12 Belle Fourche River near Sturgis, S. Dak. 06437000 44 30 47 -103 08 13 15,021 Yes 0.4 9.7 15.3 3.1 70.9 0.7 UndevCHEY.13 Belle Fourche River near Elm Springs, S. Dak. 06438000 44 22 11 -102 33 58 18,309 Yes 0.3 10.1 13.6 2.9 72.0 1.1 Undev
Table 7

61

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

CHEY.14 Cheyenne River near Plainview, S. Dak. 06438500 44 31 46 -101 55 49 55,527 Yes 0.4 6.7 12.6 1.6 77.4 1.3 Undev

CHEY.15 Cheyenne River at Cherry Creek, S. Dak. 06439300 44 35 59 -101 29 53 61,041 Yes 0.4 7.0 11.5 1.4 78.4 1.3 Undev

CHEY.16 Cheyenne River near Eagle Butte, S. Dak. 06439500 44 41 47 -101 13 03 62,787 Yes 0.4 7.2 11.2 1.4 78.6 1.3 Undev

CHEY.17 Yellow Creek at mouth, at Lead, S. Dak. 442023103451600 44 20 23 -103 45 18 55 Yes 1.7 0.0 82.3 2.0 11.7 2.3 Undev

CHEY.18 Whitetail Creek below Kirk Power Plant, at Lead, 

S. Dak.

442034103453100 44 20 34 -103 45 33 18 Yes 4.9 0.0 71.5 0.8 15.8 6.9 Undev

CHEY.19 West Strawberry Creek above Grizzly Gulch, near 

Lead, S. Dak.

442042103434600 44 20 42 -103 43 48 5 No 0.0 0.0 94.6 0.3 5.1 * Undev

CHEY.20 Deadwood Creek above Central City, S. Dak. 442148103471000 44 21 48 -103 47 12 9 Yes 0.0 0.0 87.2 1.3 11.4 0.1 Undev

CNBR.1 Dismal River near Thedford, Nebr. 06775900 41 46 43 -100 31 31 72 No 0.0 1.1 12.3 12.1 72.0 2.5 Undev

CNBR.2 Middle Loup River at St. Paul, Nebr. 06785000 41 12 13 -098 26 46 20,918 No 0.2 14.6 2.2 2.4 79.5 1.1 Mixed

CNBR.3 North Loup River at Taylor, Nebr. 06786000 41 46 37 -099 22 45 6,088 No 0.0 2.2 0.4 5.4 90.8 1.2 Undev

CNBR.4 Calamus River near Harrop, Nebr. 06787000 41 56 49 -099 23 10 1,794 No 0.0 1.5 0.2 8.0 88.3 2.1 Undev

CNBR.5 Cedar River near Spalding, Nebr. 06791500 41 42 41 -098 26 49 1,947 No 0.0 10.9 0.9 6.6 80.4 1.2 Undev

CNBR.6 Maple Creek near Nickerson, Nebr. 06800000 41 33 37 -096 32 27 954 No 0.4 96.7 1.0 0.2 1.4 0.3 Ag

CNBR.7 Elkhorn River at Waterloo, Nebr. 06800500 41 17 36 -096 17 02 17,989 No 0.8 67.8 1.7 7.3 21.6 0.9 Ag

CNBR.8 Salt Creek at Greenwood, Nebr. 06803555 40 57 56 -096 27 16 2,724 No 5.7 72.8 2.5 1.0 16.9 1.0 Mixed

CONN.1 Priest Brook near Winchendon, Mass. 01162500 42 40 57 -072 06 54 50 No 2.7 4.5 78.7 12.2 0.0 1.9 UndevCONN.2 Green River at Stewartville, Mass. 01170095 42 42 42 -072 40 07 107 No 0.3 6.1 90.7 2.3 0.0 0.6 Undev

CONN.3 Connecticut River at Thompsonville, Conn. 01184000 41 59 14 -072 36 19 25,049 Yes 5.0 8.4 78.7 4.6 0.2 3.1 Undev

CONN.4 Broad Brook at Broad Brook, Conn. 01184490 41 54 50 -072 33 00 38 No 13.1 39.0 41.8 5.2 0.0 0.9 Mixed

CONN.5 Pequabuck River at Forestville, Conn. 01189000 41 40 23 -072 54 02 116 No 34.6 7.9 49.8 5.0 0.0 2.7 Urban

CONN.6 Hockanum River near East Hartford, Conn. 01192500 41 46 59 -072 35 14 191 No 42.7 11.2 36.6 7.0 0.0 2.5 UrbanCONN.7 Konkapot River at Hartsville-Mill River Road, near 

Mill River, Mass.

01198158 42 07 46 -073 15 50 90 No 4.0 5.4 86.1 0.9 0.0 3.7 Undev

CONN.8 Norwalk River at South Wilton, Conn. 01209700 41 09 49 -073 25 09 85 No 50.2 2.8 39.8 5.8 0.0 1.4 Urban

COOK.1 South Fork Campbell Creek near Anchorage, Alaska 15274000 61 10 00 -149 46 22 76 No * * * * * * *

COOK.2 Chester Creek at Arctic Boulevard at Anchorage, 

Alaska

15275100 61 12 17 -149 53 51 71 No * * * * * * *

COOK.3 Deshka River near Willow, Alaska 15294100 61 46 03 -150 20 21 1,531 No * * * * * * *

COOK.4 Johnson River above Lateral Glacier near Tuxedni 

Bay, Alaska

15294700 60 05 39 -152 54 46 64 No * * * * * * *

COOK.5 Costello Creek near Colorado, Alaska 631018149323700 63 16 16 -149 32 45 60 Yes * * * * * * *

DELR.1 West Branch Delaware River at Walton, N.Y. 01423000 42 09 58 -075 08 24 860 No 1.3 23.1 75.2 0.1 0.0 0.2 Undev

DELR.2 Lackawaxen River at Hawley, Pa. 01431500 41 28 34 -075 10 20 749 No 1.6 18.7 74.1 2.7 0.0 3.0 Undev

DELR.3 Delaware River at Port Jervis, N.Y. 01434000 41 22 14 -074 41 51 7,968 No 1.9 10.6 83.5 1.4 0.0 2.5 Undev
62 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

DELR.4 Neversink River near Claryville, N.Y. 01435000 41 53 24 -074 35 24 172 No 0.3 0.5 99.1 0.0 0.0 0.1 Undev

DELR.5 Neversink River at Godeffroy, N.Y. 01437500 41 26 28 -074 36 07 794 No 4.9 2.9 87.7 1.4 0.0 3.0 Undev

DELR.6 Bush Kill at Shoemakers, Pa. 01439500 41 05 17 -075 02 16 306 No 3.7 0.4 84.1 9.4 0.0 2.4 Undev

DELR.7 Flat Brook near Flatbrookville, N.J. 01440000 41 06 22 -074 57 09 168 No 1.5 7.0 87.4 3.1 0.0 1.0 Undev

DELR.8 Brodhead Creek at Minisink Hills, Pa. 01442500 40 59 55 -075 08 34 675 No 8.5 7.2 79.6 3.0 0.0 1.6 Mixed

DELR.9 Little Lehigh Creek at East Texas, Pa. 01451425 40 32 34 -075 33 46 131 No 8.6 67.5 23.1 0.3 0.0 0.5 Mixed

DELR.10 Jordan Creek near Schnecksville, Pa. 01451800 40 39 42 -075 37 37 136 No 1.8 64.9 32.5 0.3 0.0 0.3 Ag

DELR.11 Lehigh River at Glendon, Pa. 01454700 40 40 09 -075 14 11 3,519 No 10.0 23.0 60.4 3.5 0.0 3.1 Mixed

DELR.12 Pidcock Creek near New Hope, Pa. 01462100 40 19 46 -074 56 13 36 No 0.6 38.6 58.8 1.7 0.0 0.3 Mixed

DELR.13 Delaware River at Trenton, N.J. 01463500 40 13 18 -074 46 41 17,580 No 5.3 16.4 73.0 2.5 0.0 2.8 Mixed

DELR.14 Shabakunk Creek near Lawrenceville, N.J. 01463810 40 15 19 -074 44 16 33 No 66.5 14.1 14.9 4.2 0.0 0.3 Urban

DELR.15 Pine Run at Chalfont, Pa. 01464710 40 17 20 -075 12 10 33 No 19.1 45.7 33.5 0.3 0.0 1.5 Mixed

DELR.16 Little Neshaminy Creek at Valley Road near 

Neshaminy, Pa.

01464907 40 13 45 -075 07 11 72 No 37.2 31.2 30.4 0.2 0.0 1.0 Mixed

DELR.17 Pennypack Creek at Paper Mill, Pa. 01467040 40 08 24 -075 04 27 61 No 81.9 4.0 13.0 0.4 0.0 0.6 Urban

DELR.18 South Branch Pennsauken Creek at Cherry Hil, N.J. 01467081 39 56 30 -075 00 04 23 No 72.7 12.1 9.5 5.3 0.0 0.4 Urban

DELR.19 Cooper River at Haddonfield, N.J. 01467150 39 54 11 -075 01 17 47 No 69.5 6.5 17.1 3.5 0.0 3.5 Urban

DELR.20 Tulpehocken Creek near Bernville, Pa. 01470779 40 24 48 -076 10 18 179 No 4.6 81.9 12.5 0.4 0.0 0.6 Ag

DELR.21 Wyomissing Creek at West Reading, Pa. 01471520 40 19 41 -075 56 40 42 No 38.2 23.3 37.8 0.3 0.0 0.4 Urban

DELR.22 Hay Creek near Birdsboro, Pa. 01471668 40 15 04 -075 48 49 57 No 0.7 21.2 75.4 1.1 0.0 1.6 Undev

DELR.23 Manatawny Creek near Pottstown, Pa. 01471980 40 16 22 -075 40 48 222 No 2.2 41.3 54.9 0.9 0.0 0.7 Mixed

DELR.24 Pigeon Creek near Parker Ford, Pa. 01472100 40 11 48 -075 35 12 37 No 6.0 45.0 48.8 0.1 0.0 0.1 Mixed

DELR.25 French Creek near Phoenixville, Pa. 01472157 40 09 05 -075 36 05 152 No 1.8 34.1 62.7 0.9 0.0 0.5 Mixed

DELR.26 Stony Creek at Sterigere Street at Norristown, Pa. 01473470 40 07 38 -075 20 42 49 No 46.6 27.7 24.4 0.2 0.0 1.1 Mixed

DELR.27 Wissahickon Creek at mouth, Philadelphia, Pa. 01474000 40 00 55 -075 12 25 165 No 61.8 9.9 26.8 0.4 0.0 1.1 Urban

DELR.28 Schuylkill River at Philadelphia, Pa. 01474500 39 58 04 -075 11 19 4,896 Yes 13.8 37.3 45.6 0.7 0.0 2.6 MixedDELR.29 Darby Creek at Foxcroft, Pa. 01475430 39 59 45 -075 21 21 41 No 64.3 10.9 24.5 0.2 0.0 0.1 Urban

DELR.30 Darby Creek near Darby, Pa. 01475510 39 55 44 -075 16 21 98 No 78.3 6.0 15.3 0.3 0.0 0.1 Urban

DELR.31 Crum Creek at Goshen Road near Whitehorse, Pa. 01475845 39 59 24 -075 26 15 33 No 33.3 19.5 46.9 0.3 0.0 * Urban

DELR.32 Ridley Creek near Media, Pa. 01476470 39 55 57 -075 24 42 71 No 21.0 27.4 51.3 0.1 0.0 0.2 Mixed

DELR.33 Raccoon Creek near Swedesboro, N.J. 01477120 39 44 26 -075 15 33 67 No 6.9 65.7 23.2 3.8 0.0 0.3 Mixed

DELR.34 East Branch Brandywine Creek near Dorlan, Pa. 01480665 40 03 08 -075 43 27 87 No 2.5 51.8 44.3 0.2 0.0 1.1 Ag

GAFL.1 St. Marys River at Boulogne, Fla. 02231220 30 46 36 -081 58 43 3,311 No 1.6 1.5 48.6 37.2 1.6 9.5 UndevGAFL.2 Little Wekiva River near Longwood, Fla. 02234998 28 42 13 -081 23 31 115 No 72.9 7.1 4.1 5.3 1.3 9.2 Urban

GAFL.3 Blackwater Creek near Cassia, Fla. 02235200 28 52 28 -081 29 23 298 No 3.0 18.6 34.4 28.1 5.7 10.2 Undev
Table 7

63

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

GAFL.4 Withlacoochee River at US 84, near Quitman, Ga. 02318500 30 47 35 -083 27 13 3,864 No 3.0 49.7 25.5 15.2 0.3 6.3 Mixed

GAFL.5 Santa Fe River near Fort White, Fla. 02322500 29 50 56 -082 42 54 2,592 No 2.8 14.6 47.0 18.1 10.6 6.9 Undev

GAFL.6 Steinhatchee River near Cross City, Fla. 02324000 29 47 12 -083 19 17 791 No 0.1 0.2 41.0 42.4 0.1 16.1 Undev

GAFL.7 Econfina River near Perry, Fla. 02326000 30 10 15 -083 49 26 556 No 0.3 3.1 35.1 47.6 3.3 10.5 Undev

GRSL.1 Cub River near Richmond, Utah 10102200 41 55 35 -111 51 13 577 No 1.0 33.9 21.7 0.7 42.3 0.4 Ag

GRSL.2 Weber River near Coalville, Utah 10130500 40 53 43 -111 24 07 1,108 Yes 1.2 5.1 60.7 0.0 31.2 1.8 Undev

GRSL.3 Jordan River at 1700 South at Salt Lake City, Utah 10171000 40 44 01 -111 55 24 9,096 Yes 6.0 7.3 41.7 0.5 39.4 5.1 Mixed

HDSN.1 Hudson River near Winebrook Hills, N.Y. 01311951 43 57 30 -074 05 38 224 No 0.2 0.1 94.8 1.8 0.0 3.0 Undev

HDSN.2 Hudson River near Newcomb, N.Y. 01312000 43 57 58 -074 07 51 495 No 0.3 0.1 92.1 3.3 0.0 4.2 Undev

KANS.1 Kill Creek at 95 St near Desoto, Kans. 06892360 38 57 24 -094 58 25 124 No 18.1 65.3 12.0 0.8 2.5 1.4 Mixed

KANS.2 Cedar Creek near Desoto, Kans. 06892495 38 58 41 -094 55 22 151 No 11.2 59.9 22.3 1.1 3.5 2.0 Mixed

KANS.3 Mill Creek at Johnson Drive, Shawnee, Kans. 06892513 39 01 45 -094 49 02 150 No 34.5 43.0 16.3 1.1 2.7 2.3 Mixed

KANS.4 Indian Creek at State Line Rd, Leawood, Kans. 06893390 38 56 18 -094 36 28 167 No 58.2 32.6 5.7 1.2 1.4 0.9 Mixed

LERI.1 Clinton River at Sterling Heights, Mich. 04161820 42 36 52 -083 01 36 803 No 29.0 26.7 25.4 10.8 0.0 8.2 Mixed

LERI.2 Cuyahoga River near Newburgh Heights, Ohio 04208504 41 27 45 -081 40 51 2,044 No 29.1 25.5 36.2 6.2 0.0 2.9 Mixed

LERI.3 Grand River at Harpersfield, Ohio 04211820 41 45 19 -080 56 54 1,431 No 1.2 41.6 40.4 15.7 0.0 1.1 Mixed

LINJ.1 Swan River at East Patchogue N.Y. 01305500 40 46 01 -072 59 37 21 No 79.1 1.2 18.8 0.6 0.0 0.3 Urban

LINJ.2 Passaic River near Millington, N.J. 01379000 40 40 48 -074 31 44 140 No 25.9 11.3 40.7 21.5 0.0 0.7 Urban

LINJ.3 Raritan River at Queens Bridge at Bound Brook, 

N.J.

01403300 40 33 34 -074 31 40 2,074 No 17.5 34.1 42.0 5.0 0.0 1.4 Mixed

LINJ.4 Bound Brook at Middlesex, N.J. 01403900 40 35 06 -074 30 28 126 No 74.9 1.0 18.2 5.6 0.0 0.3 Urban

LINJ.5 Great Egg Harbor River near Sicklerville, N.J. 01410784 39 44 01 -074 57 04 39 No 36.1 14.5 33.3 14.8 0.0 1.3 Urban

LINJ.6 Muddy Run at Centerton, N.J. 01411700 39 31 28 -075 10 08 98 No 4.4 65.8 22.1 6.4 0.0 1.3 Ag

MISE.1 Hatchie River at Bolivar, Tenn. 07029500 35 16 31 -088 58 36 3,837 No 1.3 27.6 64.3 4.8 0.0 2.0 Mixed

MISE.2 Wolf River at LaGrange, Tenn. 07030392 35 01 57 -089 14 48 543 No 0.3 31.9 57.8 8.7 0.0 1.3 Mixed

MN.1 St. Croix River near Danbury, Wis. 05333500 46 04 34 -092 14 49 4,092 No 0.4 6.7 76.7 8.7 0.4 7.1 Undev

MN.2 Rush Creek near Rush City, Minn. 05339720 45 39 19 -092 53 56 156 No 2.9 51.3 16.4 20.1 0.0 9.2 Ag

MN.3 Sunrise River at Sunrise, Minn. 05340195 45 32 48 -092 51 23 781 No 2.6 53.4 17.6 21.0 0.1 5.4 Ag

MN.4 St Croix River at Nevers Dam site, near Wolf 

Creek, Wis.

05340420 45 32 13 -092 43 28 15,737 No 0.8 22.2 52.9 19.0 0.5 4.6 Undev

MN.5 St Croix River at Franconia, Minn. 05340552 45 21 40 -092 42 05 16,026 No 0.8 23.0 52.4 18.7 0.5 4.6 Undev

MN.6 Apple River at County Road H near Balsam Lake, 

Wis.

05341111 45 26 16 -092 21 58 327 No 0.0 42.0 46.2 5.1 0.2 6.4 Mixed

MN.7 Apple River above 05341499 at Park in Somerset, 

Wis.

05341498 45 07 40 -092 40 31 1,346 No 0.7 62.4 28.1 3.4 0.2 5.3 Ag
64 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

MN.8 St. Croix River at Prescott, Wis. 05344490 44 44 57 -092 48 17 19,814 No 1.1 32.7 45.6 15.6 0.4 4.6 Mixed

MOBL.1 Coosa River near Rome, Ga. 02397000 34 12 01 -085 15 24 10,461 Yes 4.1 13.8 78.8 0.2 0.0 3.1 Undev

MOBL.2 Cahaba Valley Creek at Cross Creek Road at 

Pelham, Ala.

0242354750 33 18 48 -086 48 23 66 No 11.9 9.8 76.7 0.2 0.0 1.4 Mixed

MOBL.3 Shades Creek at Samford Univ at Homewood, Ala. 02423581 33 27 40 -086 47 36 56 No 53.3 3.6 40.8 0.3 0.0 2.0 Urban

MOBL.4 Alabama River at Claiborne, Ala. 02429500 31 32 49 -087 30 45 56,921 Yes 3.0 16.3 73.1 4.1 0.0 3.6 Undev

MOBL.5 Town Creek at Tupelo, Miss. 02434000 34 17 40 -088 42 33 283 No 1.0 51.3 45.9 0.3 0.0 1.5 Ag

MOBL.6 Tombigbee R below Coffeeville L&D near 

Coffeeville, Ala.

02469762 31 45 26 -088 07 30 47,833 No 2.2 22.0 63.6 8.0 0.0 4.2 Undev

MOBL.7 Satilpa Creek near Coffeeville, Ala. 02469800 31 44 40 -088 01 21 423 No 0.1 1.5 91.2 3.6 0.0 3.6 UndevMOBL.8 Chickasaw Creek near Kushla, Ala. 02471001 30 48 11 -088 08 36 324 No 1.3 9.6 81.4 3.5 0.0 4.3 Undev

NECB.1 Souadabscook Stream at Carmel, Maine 01037110 44 48 03 -069 03 10 56 No 2.8 10.5 71.0 11.3 0.1 4.3 UndevNECB.2 Marsh Stream near Monroe, Maine 01037230 44 36 01 -069 02 22 101 No 1.3 10.2 85.3 2.0 0.4 0.8 UndevNECB.3 Deer Meadow Brook near Newcastle, Maine 01038100 44 02 23 -069 35 10 17 No 0.4 5.4 88.0 5.2 0.0 1.0 UndevNECB.4 Fifteenmile Stream at East Benton, Maine 01049135 44 34 59 -069 27 54 171 No 1.2 19.3 71.4 6.7 0.0 1.3 UndevNECB.5 Kennebec River at North Sidney, Maine 01049265 44 28 20 -069 41 02 14,015 No 1.4 5.6 79.4 3.7 0.4 9.5 UndevNECB.6 Bond Brook at Augusta, Maine 01049318 44 19 22 -069 46 30 54 No 17.0 20.2 57.7 4.2 0.0 0.9 Mixed

NECB.7 Togus Stream at Togus, Maine 01049550 44 15 58 -069 41 53 88 No 4.3 11.6 73.7 3.5 0.0 6.9 Undev

NECB.8 Taylor Brook at Poland Rd near Auburn, Maine 01058710 44 04 47 -070 14 44 48 No 16.0 17.7 58.0 2.6 0.0 5.6 Mixed

NECB.9 Little River near Lisbon Falls, Maine 01059295 44 00 17 -070 02 02 59 No 1.0 15.8 81.3 1.3 0.0 0.5 Undev

NECB.10 Androscoggin River near Lisbon Falls, Maine 01059300 43 59 00 -070 02 28 8,849 Yes 1.9 5.3 83.5 3.4 0.2 5.7 Undev

NECB.11 Pleasant River at Popeville, Maine 01064110 43 47 12 -070 25 16 121 No 14.0 10.0 65.4 3.9 0.0 6.6 Mixed

NECB.12 Stoudwater River near South Gorham, Maine 01064154 43 39 22 -070 24 00 45 No 14.1 14.4 67.4 4.0 0.0 0.1 Mixed

NECB.13 Nonesuch River near Scarborough, Maine 01064195 43 36 58 -070 21 19 47 No 14.4 5.1 74.0 6.2 0.0 0.2 Mixed

NECB.14 Mousam River near Sanford, Maine 01068900 43 25 54 -070 45 40 112 No 17.9 5.9 65.7 3.3 0.0 7.2 Mixed

NECB.15 Little River near Lebanon, Maine 01072540 43 24 21 -070 51 03 46 Yes 2.4 8.6 84.7 3.8 0.0 0.4 Undev

NECB.16 Little River near Berwick, Maine 01072550 43 19 07 -070 51 53 133 Yes 2.1 6.6 84.1 7.0 0.0 0.2 Undev

NECB.17 Great Works River near North Berwick, Maine 01072650 43 19 03 -070 44 20 60 No 12.7 8.5 72.3 4.5 0.0 2.1 Mixed

NECB.18 Isinglass River, Batchelder Rd, near Ctr Strafford, 

N.H.

01072845 43 15 15 -071 06 10 59 No 4.8 3.9 73.9 8.8 0.0 8.6 Undev

NECB.19 Bellamy River at Bellamy Rd, near Dover, N.H. 01072904 43 10 49 -070 53 22 68 No 11.1 10.1 63.6 9.8 0.0 5.4 MixedNECB.20 Lamprey River below Cotton Road, near Deerfield 

Center, N.H.

01073260 43 05 00 -071 14 00 83 No 3.7 6.4 80.2 8.4 0.0 1.3 Undev

NECB.21 Pawtuckaway River at Folsum Mill Lane, near 

Epping, N.H.

01073392 43 02 36 -071 07 39 59 No 2.5 2.7 79.6 8.2 0.0 7.0 Undev
Table 7

65

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

NECB.22 North River at NH 152, near Nottingham, N.H. 01073458 43 05 53 -071 03 34 75 No 5.4 4.4 77.8 10.4 0.0 2.0 Mixed

NECB.23 Little River at Cartland Rd, at Lee, N.H. 010734833 43 07 07 -071 01 20 52 No 3.4 4.4 76.8 11.5 0.0 3.9 Undev

NECB.24 Little Suncook River at Black Hall Rd, at Epson, 

N.H.

01089743 43 13 26 -071 20 46 101 No 4.6 6.4 73.4 8.1 0.0 7.5 Undev

NECB.25 Black Brook at Dunbarton Road, near Manchester, 

N.H.

01090477 43 01 31 -071 30 17 54 No 2.0 11.3 77.7 6.0 0.0 3.0 Undev

NECB.26 Baboosic Brook at Bedford Road, near Merrimack, 

N.H.

01094005 42 53 36 -071 30 51 73 No 10.7 9.8 72.0 3.6 0.0 3.9 Mixed

NECB.27 Pennichuck Brook at US 3, near Nashua, N.H. 01094161 42 47 36 -071 28 14 66 No 21.2 8.1 59.0 7.7 0.0 4.0 Mixed

NECB.28 Stillwater River near Sterling, Mass. 01095220 42 24 39 -071 47 28 79 No 6.0 8.8 74.2 8.1 0.0 2.9 Mixed

NECB.29 Mulpus Brook at Hazen Road near Shirley, Mass. 01095917 42 34 26 -071 37 28 41 No 12.0 9.5 67.7 5.6 0.0 5.2 Mixed

NECB.30 Nissitissit River at Bond Street, at Brookline, N.H. 0109650060 42 43 59 -071 39 51 71 No 3.7 3.3 84.3 5.7 0.2 2.7 Undev

NECB.31 Stony Brook at School Street at Chelmsford, Mass. 01096544 42 37 04 -071 24 08 108 No 23.2 5.8 55.2 9.0 0.0 6.7 Mixed

NECB.32 Beaver Brook at North Pelham, N.H. 010965852 42 46 58 -071 21 13 122 No 38.5 7.2 49.2 2.7 0.0 2.4 Urban

NECB.33 Assabet River at Allen Street at Northborough, 

Mass.

01096710 42 19 46 -071 37 48 76 No 36.6 1.9 48.9 8.6 0.0 4.1 Urban

NECB.34 Elizabeth Brook off White Pond Road near Stow, 

Mass.

01096945 42 25 36 -071 29 07 49 No 12.2 10.9 70.5 3.9 0.0 2.4 Mixed

NECB.35 Fort Pond Brook at River Road near South Acton, 

Mass.

01097270 42 27 34 -071 26 34 54 No 23.0 5.2 63.3 5.8 0.0 2.8 Mixed

NECB.36 Sudbury River at Concord Street at Ashland, Mass. 01097476 42 15 45 -071 27 48 90 No 20.4 5.5 60.1 8.7 0.0 5.3 Mixed

NECB.37 Merrimack River below Concord River at Lowell, 

Mass.

01100000 42 38 45 -071 17 54 11,983 Yes 11.5 6.7 71.6 4.6 0.1 5.5 Mixed

NECB.38 Spicket River at Bridge Street, at Salem, N.H. 011005372 42 47 16 -071 11 59 123 No 20.8 6.4 64.4 3.5 0.0 4.9 MixedNECB.39 Shawsheen River near Tewksbury, Mass. 01100610 42 35 59 -071 11 34 145 No 64.6 0.3 25.7 7.6 0.0 1.7 UrbanNECB.40 Little River at Rt 121, at Westville, N.H. 01100684 42 49 04 -071 06 48 54 No 30.8 5.8 56.2 5.9 0.0 1.3 UrbanNECB.41 Powwow River at Whitehall Rd, at South Hampton, 

N.H.

01100842 42 52 21 -070 57 41 126 No 13.2 6.5 65.5 8.2 0.0 6.6 Mixed

NECB.42 Parker River at Byfield, Mass. 01101000 42 45 10 -070 56 44 55 No 15.2 4.7 64.4 12.4 0.2 3.1 MixedNECB.43 Ipswich River at South Middleton, Mass. 01101500 42 34 10 -071 01 37 115 No 45.5 0.6 34.9 16.2 0.0 2.8 Urban

NECB.44 Saugus River at Saugus Ironworks at Saugus, Mass. 01102345 42 28 10 -071 00 25 60 No 67.8 0.0 18.8 9.1 0.0 4.3 Urban

NECB.45 Aberjona River at Winchester, Mass. 01102500 42 26 50 -071 08 20 60 No 79.2 0.0 13.8 4.4 0.0 2.6 UrbanNECB.46 Charles River at Maple St. at North Bellingham, 

Mass.

011032058 42 07 11 -071 27 10 54 No 31.5 6.0 53.0 6.5 0.2 2.8 Urban

NECB.47 Charles River above Watertown Dam at Watertown, 

Mass.

01104615 42 21 53 -071 11 23 695 No 40.4 4.3 45.5 6.5 0.1 3.2 Urban
66 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

NECB.48 Neponset River at Norwood, Mass. 01105000 42 10 39 -071 12 03 85 No 41.3 2.3 45.2 9.6 0.0 1.5 Urban

NECB.49 East Branch Neponset River at Canton, Mass. 01105500 42 09 16 -071 08 45 73 No 52.0 0.2 36.4 7.4 0.0 4.0 Urban

NECB.50 Monatiquot River at River Street at Braintree, Mass. 01105581 42 13 12 -070 59 56 71 No 55.4 0.5 32.2 8.5 0.0 3.3 Urban

NECB.51 Matfield River at N. Central St. at E. Bridgewater, 

Mass.

01106468 42 02 01 -070 58 21 80 No 66.6 0.2 26.5 5.0 0.1 1.7 Urban

NECB.52 Wading River near Norton, Mass. 01109000 41 56 51 -071 10 36 113 No 25.6 4.2 59.3 8.9 0.1 1.9 Urban

NECB.53 Middle River off Sutton Lane at Worcester, Mass. 01109595 42 14 19 -071 49 28 125 No 32.5 5.9 48.3 6.8 0.1 6.3 Urban

NECB.54 Quinsigamond River at North Grafton, Mass. 01110000 42 13 49 -071 42 39 66 No 53.9 0.7 30.7 7.7 0.3 6.7 Urban

NECB.55 Mill River at Summer Street near Blackstone, 

Mass.

01112262 42 02 27 -071 30 56 74 No 13.6 9.4 66.8 7.4 0.1 2.8 Mixed

NECB.56 Blackstone River at Manville, R.I. 01112900 41 58 16 -071 28 12 1,115 No 22.7 6.3 60.1 6.8 0.2 4.0 MixedNROK.1 Clark Fork at Turah Bridge near Bonner, Mont. 12334550 46 49 34 -113 48 51 9,521 Yes 0.6 5.1 51.7 0.8 40.3 1.4 Undev

NROK.2 Clark Fork at St. Regis, Mont. 12354500 47 18 07 -115 05 14 27,820 Yes 0.6 5.2 63.2 0.7 27.5 2.9 Undev

NROK.3 Middle Fork Flathead River near West Glacier, 

Mont.

12358500 48 29 43 -114 00 36 2,939 No 0.2 0.1 75.9 0.3 14.3 9.3 Undev

NROK.4 Flathead River at Perma, Mont. 12388700 47 22 03 -114 35 06 21,787 Yes 0.5 7.0 65.6 0.4 18.6 8.0 Undev

NROK.5 South Fork Coeur d'Alene River near Pinehurst, 

Idaho

12413470 47 33 07 -116 14 11 738 Yes 2.4 0.1 83.2 0.1 12.7 1.4 Undev

NVBR.1 East Fork Carson River below Markleeville Creek 

near Markleeville, Calif.

10308200 38 42 53 -119 45 54 716 Yes 0.0 0.0 58.0 0.0 37.0 4.9 Undev

NVBR.2 East Fork Carson River near Dresslerville, Nev. 10309010 38 52 42 -119 41 22 970 Yes 0.0 0.0 52.7 0.0 43.4 3.8 Undev

NVBR.3 West Fork Carson River at Woodfords, Calif. 10310000 38 46 11 -119 50 02 169 Yes 0.0 0.0 60.1 0.0 37.7 2.2 Undev

NVBR.4 Carson River at Deer Run Road near Carson City, 

Nev.

10311400 39 10 53 -119 41 42 24,83 Yes 2.4 6.0 34.0 0.2 55.1 2.3 Undev

NVBR.5 Carson River at Dayton, Nev. 10311700 39 14 16 -119 35 16 28,00 Yes 2.2 5.4 33.5 0.2 56.6 2.3 Undev

NVBR.6 Carson River near Fort Churchill, Nev. 10312000 39 17 30 -119 18 40 3,801 Yes 1.7 4.3 26.2 0.1 65.4 2.3 Undev

NVBR.7 Carson River below Carson Diversion Dam near 

Fallon, Nev.

10312158 39 29 33 -118 59 31 4,669 Yes 1.5 3.8 21.3 0.3 69.3 3.8 Undev

NVBR.8 Carson River at Tarzyn Road near Fallon, Nev. 10312275 39 33 32 -118 43 34 * Yes * * * * * * *

NVBR.9 Truckee River below Viking Plant near Verdi, Nev. 10347335 39 31 18 -119 58 29 2,576 Yes 4.0 0.0 57.6 0.1 16.5 21.7 Undev

NVBR.10 Truckee River near Sparks, Nev. 10348200 39 31 03 -119 44 30 2,763 Yes 5.0 0.1 54.8 0.1 19.7 20.3 Mixed

NVBR.11 Truckee River at Clark, Nev. 10350500 39 33 56 -119 29 10 4,310 Yes 5.9 1.2 39.0 0.1 40.2 13.5 Mixed

OAHU.1 Waikele Stream at Waipahu, Oahu, Hawaii 16213000 21 23 00 -158 00 39 118 No * * * * * * *

OAHU.2 Kawainui Canal at Kailua, Oahu, Hawaii 16264800 21 24 26 -157 45 22 28 No * * * * * * *

PODL.1 Christina River at Coochs Bridge, Del. 01478000 39 38 15 -075 43 40 54 No 37.2 34.0 27.2 1.0 0.0 0.7 Mixed

PODL.2 Nassawango Creek near Snow Hill, Md. 01485500 38 13 44 -075 28 17 142 No 2.5 23.2 54.3 16.9 0.0 3.2 Undev
Table 7

67

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

PODL.3 Nanticoke River near Bridgeville, Del. 01487000 38 43 42 -075 33 43 187 No 4.4 54.7 27.1 13.7 0.0 0.1 Ag

PODL.4 Deep Creek at Old Furnace, Del. 01487100 38 39 59 -075 30 52 88 No 2.5 36.2 47.2 14.0 0.0 0.1 Mixed

PODL.5 Marshyhope Creek near Adamsville, Del. 01488500 38 50 59 -075 40 23 125 No 0.9 59.2 27.8 12.0 0.0 0.1 Ag

PODL.6 Chesterville Branch near Crumpton, Md. 01493112 39 15 25 -075 56 25 17 No 0.4 90.8 4.5 3.8 0.0 0.6 Ag

PODL.7 South Fork South Branch Potomac River near 

Moorefield, W. Va.

01608000 39 00 44 -078 57 22 718 No 0.2 9.9 88.9 0.1 0.0 0.8 Undev

PODL.8 Rock Creek at Joyce Rd Washington, D.C. 01648010 38 57 37 -077 02 30 169 No 61.3 18.0 18.3 1.6 0.0 0.8 Urban

PUGT.1 North Fork Skokomish River below Staircase 

Rapids near Hoodsport, Wash.

12056500 47 30 51 -123 19 48 147 No 0.0 0.0 89.7 0.0 5.0 5.2 Undev

PUGT.2 Big Soos Creek above Hatchery near Auburn, Wash. 12112600 47 18 44 -122 09 55 173 No 39.0 3.4 46.6 0.8 6.0 4.2 Urban

PUGT.3 Taylor Creek near Selleck, Wash. 12117000 47 23 11 -121 50 46 45 No 0.1 0.0 94.6 0.0 0.3 5.0 Undev

PUGT.4 Mercer Creek near Bellevue, Wash. 12120000 47 36 10 -122 10 51 38 No 80.5 0.2 14.4 0.3 3.8 0.9 Urban

PUGT.5 North Creek below Penny Creek near Bothell, 

Wash.

12125900 47 49 12 -122 12 46 31 No 68.0 1.0 23.9 1.3 5.0 0.8 Urban

PUGT.6 Thornton Creek near Seattle, Wash. 12128000 47 41 44 -122 16 34 29 No 94.4 0.0 3.6 0.2 1.6 0.1 Urban

RIOG.1 Saguache Creek near Saguache, Colo. 08227000 38 09 48 -106 17 26 1,327 Yes 0.0 0.8 51.5 0.0 44.2 3.5 Undev

RIOG.2 Rio Chama near La Puente, N. Mex. 08284100 36 39 46 -106 38 00 1,222 Yes 0.4 3.9 52.9 0.1 41.8 0.9 Undev

SACR.1 Cottonwood Creek near Cottonwood, Calif. 11376000 40 23 14 -122 14 19 2,313 Yes 0.3 2.5 48.0 0.0 48.0 1.2 Undev

SACR.2 Colusa Basin Drain at Road 99E near Knights 

Landing, Calif.

11390890 38 48 45 -121 46 27 4,238 Yes 1.0 56.5 6.9 1.7 32.9 1.0 Ag

SACR.3 Sacramento Slough near Knights Landing, Calif. 11391100 38 46 45 -121 38 19 3,329 Yes 3.5 60.7 15.1 4.1 15.3 1.3 Ag

SACR.4 Sacramento River at Freeport, Calif. 11447650 38 27 22 -121 30 05 61,693 Yes 2.1 13.1 52.2 0.8 29.7 2.2 Mixed

SACR.5 Putah Creek below Road 95A near Davis, Calif. 383213121505701 38 32 13 -121 51 01 1,668 Yes 0.5 3.7 50.0 0.1 42.0 3.7 Undev

SACR.6 Miners Ravine near Roseville, Calif. 384537121145801 38 45 37 -121 14 58 50 Yes 12.5 34.5 27.3 0.0 25.1 0.5 Mixed

SACR.7 Secret Ravine near Roseville, Calif. 384544121151201 38 45 44 -121 15 12 50 Yes 9.8 37.7 18.0 0.0 33.9 0.6 Mixed

SACR.8 Coon Creek near Auburn, Calif. 385824121122501 38 58 24 -121 12 25 86 Yes 6.9 18.1 51.6 0.0 22.9 0.5 Mixed

SACR.9 Bear River at Hwy 70 near Rio Oso, Calif. 385821121323201 38 58 21 -121 32 36 1,096 Yes 5.0 10.0 59.5 0.2 23.8 1.5 Mixed

SANJ.1 Salt Slough at Hwy 165 near Stevinson, Calif. 11261100 37 14 52 -120 51 08 1,,274 No 1.8 75.1 0.1 10.2 10.9 2.0 Ag

SANJ.2 Merced River at River Road Bridge near Newman, 

Calif.

11273500 37 21 04 -120 57 43 3621 Yes 1.2 13.7 47.8 0.2 33.0 4.1 Ag

SANJ.3 San Joaquin River at Patterson Br near Patterson, 

Calif.

11274570 37 29 51 -121 04 59 9,801 Yes 2.0 31.4 22.6 2.3 39.0 2.7 Mixed

SANJ.4 Tuolumne River at Hickman near Waterford, Calif. 11289800 37 38 08 -120 45 18 4,052 Yes 1.9 0.6 56.4 0.0 28.6 12.3 Undev

SANJ.5 San Joaquin River near Vernalis, Calif. 11303500 37 40 34 -121 15 59 19,030 Yes 2.7 22.5 33.7 1.3 34.8 5.1 Mixed

SANJ.6 Cosumnes River at Michigan Bar, Calif. 11335000 38 30 01 -121 02 43 1,389 Yes 0.9 3.2 76.1 0.0 19.2 0.5 Undev
68 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

SANJ.7 Merced River at Mcconnell State Park near 

Livingston, Calif.

372450120423300 37 24 50 -120 42 37 3,214 Yes 0.6 5.0 53.8 0.2 35.7 4.6 Undev

SANJ.8 Stanislaus River at Riverbank, Calif. 374419120570701 37 44 19 -120 57 11 2,704 Yes 1.7 2.4 66.4 0.0 23.2 6.3 UndevSANT.1 Saluda River near Silverstreet, S.C. 02167500 34 10 58 -081 43 36 4,214 Yes 10.1 18.0 67.6 0.5 0.0 3.8 MixedSANT.2 South Fork Edisto River at Springfield, S.C. on 

SC39

02172654 33 28 42 -081 18 49 1,389 No 1.6 31.3 49.7 7.8 0.0 9.6 Mixed

SANT.3 South Fork Edisto River near Canaan, S.C. on 

SSR39

02173052 33 18 51 -080 57 51 2,197 No 1.5 35.9 43.4 11.0 0.0 8.2 Mixed

SANT.4 North Fork Edisto River near Fairview Crossroads, 

S.C.

02173180 33 43 03 -081 21 25 371 No 2.1 25.4 58.8 7.6 0.0 6.2 Mixed

SANT.5 North Fork Edisto River near Branchville, S.C. 02173700 33 17 21 -080 52 51 1,968 No 3.0 29.7 51.7 9.2 0.0 6.3 Mixed

SANT.6 Edisto River near Cottageville, S.C. 02174175 33 03 17 -080 26 57 5,347 No 1.9 30.8 47.3 13.5 0.0 6.5 MixedSANT.7 Edisto River near Givhans, S.C. 02175000 33 01 41 -080 23 29 7,077 No 2.0 31.8 44.8 15.5 0.0 5.9 MixedSOCA.1 Santa Ana River at MWD Crossing, Calif. 11066460 33 58 07 -117 26 54 2,136 Yes 20.0 4.6 27.4 0.1 45.6 2.4 Urban

SOCA.2 Santa Ana River below Prado Dam, Calif. 11074000 33 53 00 -117 38 43 3,727 Yes 25.4 8.6 19.1 0.4 44.0 2.5 Urban

SOCA.3 Santa Ana River at Hamner Rd near Norco, Calif. 335645117332701 33 56 45 -117 33 30 2,510 Yes 23.0 6.1 24.1 0.2 44.3 2.3 Mixed

SOCA.4 Mill Creek at Chino Corona Rd near Norco, Calif. 335645117365301 33 56 45 -117 36 56 225 No 42.7 18.4 7.6 0.0 28.8 2.5 Urban

SOCA.5 South Fork Santa Ana River near SF Campground 

near Angelus Oaks, Calif.

341014116494801 34 10 14 -116 49 51 19 No 0.7 0.0 75.0 0.3 17.1 7.0 Undev

SOFL.1 Kissimmee River at S-65E near Okeechobee, Fla. 02273000 27 13 33 -080 57 45 5,876 No 10.7 18.3 10.0 29.1 20.9 11.0 MixedSOFL.2 Cypress Creek Canal near Rock Island Road., near 

Margate, Fla.

261345080131700 26 13 46 -080 13 16 6 No 93.4 0.8 0.1 3.1 0.0 2.6 Urban

SOFL.3 Hillsborough Canal near Powerline Road., near 

Deerfield Beach, Fla.

261937080091200 26 19 38 -080 09 11 6 No 85.9 2.1 0.9 4.7 0.0 6.5 Urban

SOFL.4 Boynton Canal near I-95, near Boynton Beach, Fla. 263218080032800 26 32 19 -080 03 27 18 No 72.8 5.4 2.0 6.8 1.8 11.2 Urban

SPLT.1 Clear Creek above Johnson Gulch near Idaho 

Springs, Colo.

06718300 39 44 47 -105 26 10 693 Yes 1.3 0.0 57.6 0.0 13.3 27.8 Undev

SPLT.2 North St. Vrain Creek near Allens Park, Colo. 06721500 40 13 08 -105 31 42 84 No 0.1 0.0 48.5 0.0 6.3 45.1 UndevSPLT.3 St. Vrain Creek at Lyons, Colo. 06724000 40 13 05 -105 15 36 560 Yes 1.2 0.5 63.2 0.0 17.1 18.1 UndevSPLT.4 Big Thompson River at Estes Park, Colo. 06733000 40 22 42 -105 30 50 355 No 2.2 1.2 55.1 0.0 9.7 31.7 UndevSPLT.5 Cache La Poudre River at mo of cn, near Ft Collins, 

Colo.

06752000 40 39 52 -105 13 28 2,731 Yes 0.4 0.9 61.8 0.0 31.0 5.9 Undev

SPLT.6 South Platte River at North Platte, Nebr. 06765500 41 07 05 -100 46 24 63,678 Yes 3.4 26.1 14.7 0.3 52.7 2.8 MixedSPLT.7 James Creek near Jamestown, Colo. 400630105215801 40 06 30 -105 21 58 44 Yes 1.2 0.9 77.9 0.0 19.8 0.2 UndevSPLT.8 Big Thompson below Moraine Park near Estes 

Park, Colo.

402114105350101 40 21 14 -105 35 03 103 No 0.1 2.1 45.9 0.0 5.8 46.2 Undev
Table 7

69

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

TENN.1 Sequatchie River near Whitwell, Tenn. 03571000 35 12 24 -085 29 50 1,001 No 2.2 20.1 77.1 0.2 0.0 0.3 Undev

TENN.2 Indian Creek near Madison, Ala. 03575830 34 41 50 -086 42 00 127 No 4.5 57.7 37.0 0.7 0.0 0.2 Ag

TENN.3 Buffalo River near Flat Woods, Tenn. 03604000 35 29 45 -087 49 58 1,163 No 2.1 22.3 71.2 0.8 0.0 3.6 Undev

TRIN.1 Clear Creek near Sanger, Tex. 08051500 33 20 10 -097 10 46 763 No 0.2 37.9 15.2 0.0 45.8 0.9 Mixed

TRIN.2 White Rock Creek at Greenville Ave., Dallas, Tex. 08057200 32 53 21 -096 45 24 173 No 61.2 29.2 5.2 0.0 4.1 0.4 Mixed

TRIN.3 Trinity River below Dallas, Tex. 08057410 32 42 27 -096 44 09 16,227 No 12.0 38.3 13.5 0.7 31.4 4.2 Mixed

TRIN.4 East Fork Trinity River at McKinney, Tex. 08058900 33 14 38 -096 36 32 435 No 1.5 66.3 16.5 0.0 14.6 1.0 Ag

TRIN.5 Chambers Creek near Rice, Tex. 08064100 32 11 55 -096 31 13 2,136 No 2.6 77.1 12.3 0.1 5.5 2.5 Ag

TRIN.6 Upper Keechi Creek near Oakwood, Tex. 08065200 31 34 12 -095 53 18 391 No 1.9 59.2 35.5 2.7 0.0 0.7 AgTRIN.7 Trinity River near Crockett, Tex. 08065350 31 20 19 -095 39 23 35,967 No 8.2 50.6 18.8 1.9 16.1 4.4 Mixed

TRIN.8 Bedias Creek near Madisonville, Tex. 08065800 30 53 05 -095 46 40 856 No 1.8 75.8 12.4 9.5 0.0 0.5 Ag

TRIN.9 Menard Creek near Rye, Tex. 08066300 30 28 53 -094 46 47 384 No 1.8 9.4 85.2 1.8 0.0 1.9 Undev

UCOL.1 Colorado River below Baker Gulch near Grand 

Lake, Colo.

09010500 40 19 33 -105 51 24 163 Yes 0.3 0.0 63.7 0.0 9.8 26.1 Undev

UCOL.2 French Gulch at Breckenridge, Colo. 09046530 39 29 35 -106 02 41 29 Yes 5.7 0.0 63.1 0.0 6.5 24.7 Mixed

UCOL.3 Dry Creek at Begonia Road, near Delta, Colo. 09149480 38 38 45 -108 02 56 448 No 0.0 12.5 34.1 0.0 53.2 0.1 AgUCOL.4 Red Mountain Creek above Crystal Lake near 

Ironton, Colo.

375732107394000 37 57 32 -107 39 42 47 Yes 0.0 0.1 38.1 0.0 17.9 43.9 Undev

UCOL.5 Snake River below mouth of Peru Creek, Colo. 393557105530000 39 35 57 -105 53 02 84 Yes 0.0 0.0 27.6 0.0 14.2 58.2 Undev

UIRB.1 Pitner Ditch near La Crosse, Ind. 05517120 41 19 02 -086 50 55 113 No 1.2 92.2 4.4 0.3 1.8 0.1 Ag

UIRB.2 Des Plaines River at Russell, Ill. 05527800 42 29 21 -087 55 35 318 No 5.8 77.7 10.4 1.6 3.2 1.1 Mixed

UIRB.3 Salt Creek at Western Springs, Ill. 05531500 41 49 33 -087 54 01 291 No 81.5 2.2 8.0 2.5 3.6 2.2 Urban

UIRB.4 Mukwonago River at Mukwonago, Wis. 05544200 42 51 24 -088 19 40 191 No 7.7 56.6 24.8 5.0 2.1 3.8 Mixed

UIRB.5 Nippersink Creek above Wonder Lake, Ill. 05548105 42 23 07 -088 22 10 219 No 5.6 86.2 5.2 1.4 0.8 0.7 Mixed

UMIS.1 Shingle Creek at Queen Ave in Minneapolis, Minn. 05288705 45 03 00 -093 18 37 73 No 70.1 2.6 6.1 11.0 0.0 10.1 Urban

UMIS.2 Nine Mile Creek nearJames Circle at Bloomington, 

Minn.

05330902 44 48 26 -093 18 06 116 No 79.6 0.0 6.9 7.6 0.0 5.9 Urban

UMIS.3 St. Croix River near Woodland Corner, Wis. 05331775 46 07 00 -092 07 54 1,121 No 0.4 2.6 80.5 7.3 0.3 9.0 Undev

UMIS.4 Namekagon River at Leonards, Wis. 05331833 46 10 17 -091 19 46 333 No 0.2 4.3 71.7 16.2 0.4 7.2 Undev

UMIS.5 Kettle River below Sandstone, Minn. 05336700 46 06 20 -092 51 51 2,252 No 1.0 19.1 41.8 35.1 0.3 2.8 Undev

UMIS.6 Wood River at State Highway 70 at Grantsburg, 

Wis.

05338975 45 46 22 -092 42 30 414 No 0.7 44.2 36.9 7.5 5.0 5.7 Mixed

UMIS.7 Kinnickinnic River near River Falls, Wis. 05342000 44 49 50 -092 44 00 449 No 2.1 86.9 10.1 0.3 0.3 0.2 AgWHMI.1 Little Miami River at Milford, Ohio 03245500 39 10 17 -084 17 53 3,115 No 11.6 71.6 15.6 0.2 0.0 1.0 Mixed
70 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005 Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued

[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2

)

Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

WHMI.2 East Fork Little Miami River near Williamsburg, 

Ohio

03246400 39 03 32 -084 03 05 607 No 2.5 84.2 12.6 0.1 0.0 0.5 Ag

WHMI.3 Fall Creek at Millersville, Ind. 03352500 39 51 07 -086 05 15 772 No 12.0 79.1 6.8 0.8 0.0 1.4 Mixed

WHMI.4 White River near Centerton, Ind. 03354000 39 29 51 -086 24 02 6,325 No 16.6 75.7 5.8 0.8 0.0 1.1 Mixed

WHMI.5 Big Walnut Creek near Roachdale, Ind. 03357330 39 48 58 -086 45 12 340 No 1.0 95.0 3.7 0.3 0.0 * Mixed

WHMI.6 Sugar Creek at New Palestine, Ind. 03361650 39 42 51 -085 53 08 246 No 3.5 91.0 4.6 0.7 0.0 0.2 Ag

WHMI.7 Clifty Creek at Hartsville, Ind. 03364500 39 16 29 -085 42 06 228 No 0.6 94.8 4.1 0.5 0.0 0.1 Ag

WHMI.8 Muscatatuck River near Deputy, Ind. 03366500 38 48 15 -085 40 26 755 No 3.4 53.1 37.1 3.0 0.0 3.4 Ag

WHMI.9 Beaver Creek at Squirt Run near Shoals, Ind. 383915086474901 38 39 15 -086 47 49 186 No 3.6 21.1 74.5 0.2 0.0 0.6 Undev

WHMI.10 South Fork Salt Creek at Maumee Road near 

Robinson Cem, Ind.

390219086164901 39 02 19 -086 16 49 256 No 0.5 25.4 73.5 0.2 0.0 0.4 Mixed

WHMI.11 Great Miami River below Hamilton, Ohio 392246084340100 39 22 46 -084 34 01 9,404 No 9.8 79.0 10.1 0.3 0.0 0.8 Mixed

WHMI.12 Whitewater River near Nulltown, Ind. 393259085101200 39 32 59 -085 10 12 1,369 No 2.9 86.7 9.4 0.9 0.0 0.2 Ag

WHMI.13 Holes Creek in Huffman Park at Kettering, Ohio 393944084120700 39 39 44 -084 12 07 52 No 65.4 27.4 6.5 0.3 0.0 0.4 Mixed

WHMI.14 Stillwater River on Old Springfield Road near 

Union, Ohio

395433084175300 39 54 33 -084 17 53 1,672 No 2.8 90.6 6.0 0.3 0.0 0.2 Ag

WHMI.15 Great Miami River near Tipp City, Ohio 395534084091400 39 55 34 -084 09 14 2,958 No 4.3 85.5 8.6 0.4 0.0 1.1 Ag

WHMI.16 Mad River near Hwy. 41 near Springfield, Ohio 395650083504400 39 56 50 -083 50 44 802 No 4.8 80.2 14.5 0.3 0.0 0.3 Ag

WILL.1 Middle Fork Willamette River near Oakridge, Oreg. 14144800 43 35 49 -122 27 24 669 No 0.0 0.0 88.4 0.3 4.8 6.5 Undev

WILL.2 Row River above Pitcher Creek near Dorena, Oreg. 14154500 43 44 09 -122 52 24 547 Yes 0.6 0.1 94.2 0.0 3.2 2.0 Undev

WILL.3 Lookout Creek near Blue River, Oreg. 14161500 44 12 34 -122 15 24 62 No 0.0 0.0 97.0 0.0 2.3 0.7 Undev

WILL.4 East Fork Dairy Creek near Meacham Corner, Oreg. 14205400 45 40 50 -123 04 16 88 No 0.0 0.8 91.9 0.0 0.2 7.0 Undev

WILL.5 Beaverton Creek at SW 216th Ave, near Orenco, 

Oreg.

14206435 45 31 14 -122 53 58 96 No 67.8 10.5 16.2 0.2 4.7 0.6 Urban

WILL.6 Fanno Creek at Durham, Oreg. 14206950 45 24 12 -122 45 17 81 No 75.7 6.2 12.1 0.4 4.8 0.9 UrbanWILL.7 Johnson Creek at Milwaukie, Oreg. 14211550 45 27 10 -122 38 35 137 No 59.3 18.3 18.2 0.1 3.7 0.4 UrbanWILL.8 Calapooya Creek near Nonpareil, Oreg. 432454123124801 43 24 53 -123 12 52 255 Yes 0.5 2.6 89.4 0.0 6.8 0.7 Undev

WILL.9 Coast Fork Willamette River near London, Oreg. 433855123045401 43 38 54 -123 04 58 195 Yes 0.7 1.7 88.0 0.0 7.5 2.0 Undev

WILL.10 Horse Creek below Foley Springs at McKenzie 

Bridge, Oreg.

440944122091401 44 09 43 -122 09 18 388 No 0.0 0.0 91.9 0.3 2.6 5.2 Undev

WILL.11 Quartz Creek near Blue River, Oreg. 441120122195001 44 11 19 -122 19 54 9 Yes 0.0 0.0 93.9 0.0 4.3 1.7 Undev

WILL.12 North Santiam River near Marion Forks, Oreg. 443003122000801 44 30 02 -122 00 12 55 No 0.0 0.0 86.1 0.9 7.7 5.4 Undev

WILL.13 Canal Creek near Cascadia, Oreg. 443516122204701 44 35 15 -122 20 51 61 Yes 0.0 0.0 92.9 0.0 4.5 2.6 Undev

WILL.14 Breitenbush River below Breitenbush Hot Springs 

near Detroit, Oreg.

444649121594701 44 46 48 -121 59 51 161 No 0.0 0.0 87.7 0.2 5.6 6.5 Undev
Table 7

71

Table 7. Land-use/land-cover characterization of U.S. streams sampled for mercury, 1998–2005.—Continued[Land-use/land-cover category: “other” includes water, bare rock, quarry/mine, transitional, tundra, and ice/snow. Abbreviations: USGS, U.S. Geological Survey; DMS, degrees-minutes-seconds; km2, square 

kilometers; NAD 83, North American Datum 83; *, not determined]

Site 

number Site name USGS station identifier Latitude (DMS) NAD 83 Longitude (DMS) NAD 83 Drainage area (km2) Mined 

Land use/land cover (percent of basin area)

Land-use/ 

land-cover 

category Urban Agri- culture

Undeveloped

Other

Forest Wetland Shrub/ grassland

WILL.15 Upper Clackamas River at Two Rivers C.G., 

Oreg.

450156122033100 45 01 55 -122 03 35 408 No 0.0 0.0 88.3 0.1 3.7 7.9 Undev

WILL.16 Oak Grove Fork at Rainbow Campground, Oreg. 450448122023000 45 04 47 -122 02 34 365 Yes 0.1 0.0 87.1 0.5 3.0 9.4 Undev

WMIC.1 Pine River near Tipler, Wis. 04063660 45 53 37 -088 33 31 543 No 0.1 1.9 58.6 35.3 0.4 3.7 Undev

WMIC.2 Popple River near Fence, Wis. 04063700 45 45 49 -088 27 49 363 No 0.1 3.4 57.5 37.5 0.6 0.9 Undev

WMIC.3 South Branch Oconto River near Breed, Wis. 04070720 45 03 40 -088 31 24 370 No 0.0 4.3 77.3 14.2 1.6 2.6 Undev

WMIC.4 Evergreen River below Evergreen Falls near 

Langlade, Wis.

04075365 45 03 57 -088 40 34 167 No 0.2 11.3 75.7 9.1 3.4 0.4 Undev

WMIC.5 Milwaukee River at Milwaukee, Wis. 04087000 43 06 00 -087 54 32 1,805 No 10.8 65.2 16.4 5.3 0.8 1.5 Mixed

WMIC.6 Oak Creek at South Milwaukee, Wis. 04087204 42 55 30 -087 52 12 67 No 51.0 34.6 9.9 1.3 2.7 0.3 Mixed

WMIC.7 Root River near Franklin, Wis. 04087220 42 52 25 -087 59 45 128 No 62.0 20.6 13.4 1.1 1.2 1.7 UrbanWMIC.8 Poplar Creek near Waukesha, Wis. 05543796 43 02 39 -088 09 59 64 No 47.1 27.4 18.2 2.6 2.9 1.7 Mixed

YELL.1 Bighorn River at Kane, Wyo. 06279500 44 45 31 -108 10 53 40,825 Yes 0.2 3.8 9.2 0.7 80.6 5.5 Mixed

YELL.2 Tongue River at State Line near Decker, Mont. 06306300 45 00 32 -106 50 10 3763 Yes 0.8 9.1 28.3 2.0 58.2 1.6 Undev

YELL.3 Yellowstone River near Sidney, Mont. 06329500 47 40 42 -104 09 24 17,7139 Yes 0.2 8.4 14.0 0.6 72.4 4.4 Mixed

YELL.4 Shoshone River at mouth, near Kane, Wyo. 445221108122601 44 52 21 -108 12 28 7,711 Yes 0.3 7.2 28.3 0.6 56.0 7.5 Mixed
72 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

Appendix 1. Definitions for variable abbreviations used in tables 5 and 6.

[Acronyms: MDN, Mercury Deposition Network; PRISM, Parameter-elevation Regressions on Independent Slopes Model]

Abbreviation Description

Stream water

DOC Dissolved organic carbon concentration

UV Ultraviolet absorbance at 254 nm

SUVA Specific UV absorbance at 254 nm, divided by the DOC concentration

SS_conc Suspended sediment concentration

UMeHg Unfiltered water, methylmercury concentration

UTHg Unfiltered water, total mercury concentration

UMeHg/UTHg Unfiltered water, ratio of methylmercury concentration to total mercury concentration

FMeHg Filtered water, methylmercury concentration

FTHg Filtered water, total mercury concentration

PMeHg Particulate fraction, water, methylmercury concentration

PTHg Particulate fraction, water, total mercury concentration

Bed sediment

SMeHg/LOI Bed sediment, methylmercury concentration normalized by loss-on-ignition

SMeHg Bed sediment, methylmercury concentration

STHg/LOI Bed sediment, total mercury concentration normalized by loss-on-ignition

STHg Bed sediment, total mercury concentration

SMeHg/STHg Bed sediment, ratio of methylmercury concentration to total mercury concentration

LOI Loss-on-ignition

AVS Acid volatile sulfide concentration

Atmospheric deposition

SULF.DEP Atmospheric deposition, sulfate

ADRY.SEI Atmospheric deposition, dry, modeled Hg concentration

ATOT.SEI Atmospheric deposition, wet + dry, modeled Hg concentration

AWET.MDN Atmospheric deposition, wet, measured mercury concentration, MDN data

AWET.PRE Atmospheric deposition, wet, precipitation-weighted from PRISM

PREC.PR Mean annual precipitation (1961–90) from PRISM

WTDEPAVE Average depth to seasonally high water table

Other

POPDEN00 Population density, 2000 U.S. Census

ELEV.AVG Mean basin elevation

HYDRIC SOILS Hydric soils

PET Potential evapotranspiration, mean annual

AET Actual evapotranspiration, mean annual
Appendix 1 73

Appendix 1. Definitions for variable abbreviations used in tables 5 and 6.—Continued

[MDN, Mercury Deposition Network; PRISM, Parameter-elevation Regressions on Independent Slopes Model]

Abbreviation Description

Land use/land cover

SUM_FOREST Sum forest land in basin: evergreen, deciduous, mixed

EVR_FOREST Evergreen forest land, percent of basin area

EVR_FOREST_DW Distance weighted evergreen forest land in basin

SUM_WETLAND Sum wetland in basin: woody and herbaceous

WOODWETLAND Woody wetlands, percent of basin area

WOODWETLAND_DW Distance weighted woody wetlands in basin

HERBWETLAND Herbaceous wetlands, percent of basin area

HERBWETLAND_DW Distance weighted herbaceous wetlands in basin

SUM_UNDEVELOPED Sum undeveloped land in basin: forest, grassland, shrubland, tundra, wetland

SUM_URBAN Sum urban land in basin: residential, commercial/industrial

RES_L_URBAN Low intensity residential land, percent of basin area

RES_L_URBAN_DW Distance weighted low intensity residential land in basin

RES_H_URBAN High intensity residential land, percent of basin area

RES_H_URBAN_DW Distance weighted high intensity residential land in basin

COM_INDUSTR Commercial/industrial/transportation land, percent of basin area

COM_INDUSTR_DW Distance weighted commercial/industrial/transportation land in basin

SUM_AGRICULTURE Sum agricultural land in basin: row crop, small grains, fallow, pasture/hay, orchards/vineyards

ROW_CROP Row crop land, percent of basin area

ROW_CROP_DW Distance weighted row crop land in basin

PAST_HAY Pasture/hay land, percent of basin area

PAST_HAY_DW Distance weighted pasture/hay land in basin

GRASSLAND Grasslands (herbaceous) land, percent of basin area
74 Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005

This page intentionally left blank.
Publishing support provided by the U.S. Geological Survey

Publishing Network, Columbus and Tacoma Publishing Service Centers

For more information concerning the research in this report, contact the

 Director, Wisconsin Water Science Center

U.S. Geological Survey

8505 Research Way

Middleton, Wisconsin 53562

http://wi.water.usgs.gov
2

Report Title

Scudder and others— Mercury in Fish, Bed Sediment, and Water from Streams Across the United States, 1998–2005—Scientific Investigations Report 2009–5109