United States
Environmental Protection
Agency
EPA-452/R-97-008
December 1997
Air
Mercury Study
Report to Congress
Volume VI:
An Ecological Assessment for
Anthropogenic Mercury
Emissions in the United States
Office of Air Quality Planning & Standards
and
Office of Research and Development
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MERCURY STUDY REPORT TO CONGRESS
VOLUME VI:
AN ECOLOGICAL ASSESSMENT FOR ANTHROPOGENIC
MERCURY EMISSIONS IN THE UNITED STATES
December 1997
Office of Air Quality Planning and Standards
and
Office of Research and Development
U.S. Environmental Protection Agency
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TABLE OF CONTENTS
age
U.S. EPA AUTHORS iv
SCIENTIFIC PEER REVIEWERS v
WORK GROUP AND U.S. EPA/ORD REVIEWERS viii
LIST OF TABLES ix
LIST OF FIGURES x
LIST OF SYMBOLS, UNITS AND ACRONYMS xi
EXECUTIVE SUMMARY ES-1
1. INTRODUCTION 1-1
2. PROBLEM FORMULATION 2-1
2.1 Stressor Characteristics: Mercury Speciation and Cycling 2-1
2.1.1 Mercury in Air 2-3
2.1.2 Mercury in Surface Water 2-4
2.1.3 Mercury in Soil 2-5
2.2 Potential Exposure Pathways 2-5
2.2.1 Exposure Pathways in Aquatic Systems 2-5
2.2.2 Exposure Pathways in Terrestrial Systems 2-9
2.2.3 Summary of Aquatic and Terrestrial Exposure Pathways 2-10
2.3 Ecological Effects 2-11
2.3.1 Bioaccumulation of Mercury 2-11
2.3.2 Individual Effects 2-26
2.3.3 Population Effects 2-30
2.3.4 Communities and Ecosystems 2-36
2.3.5 Conclusions 2-37
2.4 Ecosystems Potentially at Risk 2-37
2.4.1 Highly Exposed Areas 2-38
2.4.2 Lakes and Streams Impacted by Acid Deposition 2-38
2.4.3 Dissolved Organic Carbon 2-39
2.4.4 Factors in Addition to pH and DOC that Contribute to Increased
Bioaccumulation of Mercury in Aquatic Biota 2-39
2.4.5 Sensitive Species 2-39
2.5 Endpoint Selection 2-39
2.6 Conceptual Model for Mercury Fate and Effects in the Environment 2-40
2.7 Analysis Plan 2-41
3. EXPOSURE OF PISCIVOROUS AVIAN AND MAMMALIAN WILDLIFE TO
AIRBORNE MERCURY 3-1
3.1 Objectives and Approach 3-1
3.2 Description of Computer Models 3-1
3.3 Current Exposure of Piscivorous Wildlife to Mercury 3-3
3.4 Regional-Scale Exposure Estimates 3-5
3.4.1 Predicted Current Mercury Exposure Across the Continental U.S 3-6
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3.4.2 Locations of Socially Valued Environmental Resources 3-6
3.4.3 Airborne Deposition Overlay with Threatened and Endangered Plants 3-10
3.4.4 Regions of High Mercury Deposition 3-10
3.4.5 Regions of High Mercury Deposition Overlay with the Distribution of
Acid Surface Waters 3-10
3.4.6 Regions of High Mercury Deposition Overlays with Wildlife Species
Distribution Maps 3-10
3.5 Modeling Exposures Near Mercury Emissions Sources 3-16
3.5.1 Estimates of Background Mercury 3-22
3.5.2 Hypothetical Wildlife Exposure Scenarios 3-22
3.5.3 Predicted Mercury Exposure Around Emissions Sources 3-23
3.5.4 Results of Hypothetical Exposure Scenarios 3-25
3.5.5 Issues Related to Combining Models to Assess Environmental Fate of
Mercury and Exposures to Wildlife 3-25
4. EFFECTS OF MERCURY ON AVIAN AND MAMMALIAN WILDLIFE 4-1
4.1 Mechanism of Toxicity 4-1
4.2 Toxicity Tests with Avian Wildlife Species 4-2
4.3 Toxicity Tests with Mammalian Wildlife Species 4-2
4.4 Tissue Mercury Residues Corresponding to Adverse Effects 4-4
4.5 Factors Relevant to the Interpretation and Use of Mercury Toxicity Data 4-4
4.6 Combined Effects of Mercury and Other Chemical Stressors 4-6
5. ASSESSMENT OF THE RISK POSED BY AIRBORNE MERCURY EMISSIONS TO
PISCIVOROUS AVIAN AND MAMMALIAN WILDLIFE 5-1
5.1 Scope of the Assessment 5-1
5.2 Summary of Relevant Risk Assessment Methodologies 5-2
5.3 Review of Published Efforts to Estimate the Risk of Mercury to Wildlife 5-3
5.3.1 Risk of Mercury to Bald Eagles in the Great Lakes Region 5-3
5.3.2 Risk of Mercury to Bald Eagles in Michigan 5-3
5.3.3 Risk of Mercury to Loons in Central Ontario 5-3
5.3.4 Risk of Mercury to Mink in Georgia, North Carolina, and South Carolina ... 5-4
5.3.5 Risk of Mercury to Mink in Michigan 5-4
5.3.6 Risk of Mercury to Great Egrets in south Florida 5-4
5.4 Calculation of a Criterion Value for Protection of Piscivorous Wildlife 5-4
5.4.1 Procedure Used to Develop Criterion Values for Wildlife in the Water
Quality Guidance for the Great Lakes System 5-4
5.4.2 Bioaccumulation Factors (BAFs) for Magnification of Methylmercury in
Aquatic Food Chains 5-7
5.4.3 Exposure Parameters 5-11
5.4.4 Summary of Health Endpoints for Avian and Mammalian Wildlife 5-11
5.4.5 Calculation of Wildlife Criterion Values 5-12
5.4.6 Calculation of Mercury Residues in Fish Corresponding to the Wildlife
Criterion Value 5-14
5.4.7 Calculation of the Wildlife Criterion Value for Total Mercury in Water . . . 5-14
5.4.8 Calculation of a Wildlife Criterion for the Florida Panther 5-15
5.4.9 Comparison of GLWQI Criteria with WC Derived in this Report 5-15
5.4.10 Uncertainty Analysis 5-17
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5.4.11 Sensitivity Analysis 5-17
5.4.12 Uncertainties Associated with the Wildlife Criteria Methodology 5-18
5.5 Risk of Mercury from Airborne Emissions to Piscivorous Avian and Mammalian
Wildlife 5-27
5.5.1 Lines of Evidence 5-27
5.5.2 Risk Statements 5-28
6. CONCLUSIONS 6-1
7. RESEARCH NEEDS 7-1
7.1 Process-based Research 7-1
7.2 Wildlife Toxicity Data 7-1
7.3 Improved Analytical Methods 7-2
7.4 Complexity of Aquatic Food Webs 7-2
7.5 Accumulation in Trophic Levels 1 and 2 7-2
7.6 Field Residue Data 7-2
7.7 Natural History Data 7-3
8. REFERENCES 8-1
in
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U.S. EPA AUTHORS
Principal Author:
John W.Nichols, Ph.D.
Mid-Continent Ecology Division
Office of Research and Development
Duluth, MN
Contributing Authors:
Robert B. Ambrose, Jr., P.E.
Ecosystems Research Division
National Exposure Research Laboratory
Athens, GA
Chris Cubbison, Ph.D.
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Anne Fairbrother, Ph.D., D.V.M.
Environmental Research Laboratory-Corvallis
Corvallis, OR
currently with:
Ecological Planning and Toxicology, Inc.
5010 S.W. Hout St.
Corvallis, OR 97333
Martha H. Keating
Office of Air Quality Planning and Standards
Research Triangle Park, NC
Kathryn R. Mahaffey, Ph.D.
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Debdas Mukerjee, Ph.D.
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Glenn E. Rice
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
David J. Reisman
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Rita Schoeny, Ph.D.
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Jeff Swartout
National Center for Environmental Assessment-
Cincinnati
Office of Research and Development
Cincinnati, OH
Michael Troyer
Office of Science, Planning and Regulatory
Evaluation
Cincinnati, OH
IV
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SCIENTIFIC PEER REVIEWERS
Dr. William J. Adams*
Kennecott Utah Corporation
Dr. Brian J. Alice
Harza Northwest, Incorporated
Dr. Thomas D. Atkeson
Florida Department of Environmental Protection
Dr. Donald G. Barnes*
U.S. EPA Science Advisory Board
Dr. Steven M. Bartell
SENES Oak Ridge, Inc.
Dr. David Bellinger*
Children's Hospital, Boston
Dr. Nicolas Bloom*
Frontier Geosciences, Inc.
Dr. Mike Bolger
U.S. Food and Drug Administration
Dr. Peter Botros
U.S. Department of Energy
Federal Energy Technology Center
Thomas D. Brown
U.S. Department of Energy
Federal Energy Technology Center
Dr. Dallas Burtraw*
Resources for the Future
Dr. Thomas Burbacher*
University of Washington
Seattle
Dr. James P. Butler
University of Chicago
Argonne National Laboratory
Elizabeth Campbell
U.S. Department of Energy
Policy Office, Washington D.C.
Dr. Rick Canady
Agency for Toxic Substances and Disease
Registry
Dr. Rufus Chaney
U.S. Department of Agriculture
Dr. Joan Daisey*
Lawrence Berkeley National Laboratory
Dr. John A. Dellinger*
Medical College of Wisconsin
Dr. Kim N. Dietrich*
University of Cincinnati
Dr. Tim Eder
Great Lakes Natural Resource Center
National Wildlife Federation for the
States of Michigan and Ohio
Dr. Katherine Flegal
National Center for Health Statitistics
Dr. Lawrence J. Fischer*
Michigan State University
Dr. William F. Fitzgerald
University of Connecticut
Avery Point
A. Robert Flaak*
U.S. EPA Science Advisory Board
Dr. Bruce A. Fowler*
University of Maryland at Baltimore
Dr. Steven G. Gilbert*
Biosupport, Inc.
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SCIENTIFIC PEER REVIEWERS (continued)
Dr. Cynthia C. Gilmour*
The Academy of Natural Sciences
Dr. Robert Goyer
National Institute of Environmental Health
Sciences
Dr. George Gray
Harvard School of Public Health
Dr. Terry Haines
National Biological Service
Dr. Gary Heinz*
Patuxent Wildlife Research Center
Joann L. Held
New Jersey Department of Environmental
Protection & Energy
Dr. Robert E. Hueter*
Mote Marine Laboratory
Dr. Harold E. B. Humphrey*
Michigan Department of Community Health
Dr. James P. Hurley*
University of Wisconsin
Madison
Dr. Joseph L. Jacobson*
Wayne State University
Dr. Gerald J. Keeler
University of Michigan
Ann Arbor
Dr. Ronald J. Kendall*
Clemson University
Dr. Lynda P. Knobeloch*
Wisconsin Division of Health
Dr. Leonard Levin
Electric Power Research Institute
Dr. Steven E. Lindberg*
Oak Ridge National Laboratory
Dr. Genevieve M. Matanoski*
The Johns Hopkins University
Dr. Thomas McKone*
University of California
Berkeley
Dr. Malcolm Meaburn
National Oceanic and Atmospheric
Administration
U.S. Department of Commerce
Dr. Michael W. Meyer*
Wisconsin Department of Natural Resources
Dr. Maria Morandi*
University of Texas Science Center at Houston
Dr. Paul Mushak
PB Associates
Harvey Ness
U.S. Department of Energy
Federal Energy Technology Center
Dr. Christopher Newland*
Auburn University
Dr. Jerome O. Nriagu*
The University of Michigan
Ann Arbor
William O'Dowd
U.S. Department of Energy
Federal Energy Technology Center
Dr. W. Steven Otwell*
University of Florida
Gainesville
Dr. Jozef M. Pacyna
Norwegian Institute for Air Research
VI
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SCIENTIFIC PEER REVIEWERS (continued)
Dr. Ruth Patterson
Cancer Prevention Research Program
Fred Gutchinson Cancer Research Center
Dr. Donald Porcella
Electric Power Research Institute
Dr. Deborah C. Rice*
Toxicology Research Center
Samuel R. Rondberg*
U.S. EPA Science Advisory Board
Charles Schmidt
U.S. Department of Energy
Dr. Pamela Shubat
Minnesota Department of Health
Dr. Ellen K. Silbergeld*
University of Maryland
Baltimore
Dr. Howard A. Simonin*
NYSDEC Aquatic Toxicant Research Unit
Dennis Smith
U.S. Department of Energy
Federal Energy Technology Center
Dr. Ann Spacie*
Purdue University
Dr. Alan H. Stern
New Jersey Department of Environmental
Protection & Energy
Dr. David G. Strimaitis*
Earth Tech
Dr. Edward B. Swain
Minnesota Pollution Control Agency
Dr. Valerie Thomas*
Princeton University
Dr. M. Anthony Verity
University of California
Los Angeles
*With EPA's Science Advisory Board, Mercury Review Subcommitte
vn
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WORK GROUP AND U.S. EPA/ORD REVIEWERS
Core Work Group Reviewers:
DanAxelrad, U.S. EPA
Office of Policy, Planning and Evaluation
Angela Bandemehr, U.S. EPA
Region 5
Jim Darr, U.S. EPA
Office of Pollution Prevention and Toxic
Substances
Thomas Gentile, State of New York
Department of Environmental Conservation
Arnie Kuzmack, U.S. EPA
Office of Water
David Layland, U.S. EPA
Office of Solid Waste and Emergency Response
Karen Levy, U.S. EPA
Office of Policy Analysis and Review
Steve Levy, U.S. EPA
Office of Solid Waste and Emergency Response
Lorraine Randecker, U.S. EPA
Office of Pollution Prevention and Toxic
Substances
Joy Taylor, State of Michigan
Department of Natural Resources
U.S. EPA/ORD Reviewers:
Robert Beliles, Ph.D., D.A.B.T.
National Center for Environmental Assessment
Washington, DC
Eletha Brady-Roberts
National Center for Environmental Assessment
Cincinnati, OH
Annie M. Jarabek
National Center for Environmental Assessment
Research Triangle Park, NC
Matthew Lorber
National Center for Environmental Assessment
Washington, DC
Susan Braen Norton
National Center for Environmental Assessment
Washington, DC
Terry Harvey, D.V.M.
National Center for Environmental Assessment
Cincinnati, OH
Vlll
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LIST OF TABLES
age
ES-1 Percent of Species Range Overlapping with Regions of High Mercury Deposition ES-3
ES-2 Percentiles of the Methylmercury Bioaccumulation Factor ES-5
ES-3 Wildlife Criteria for Mercury ES-7
2-1 Examples of Effects of Contaminants on Ecosystem Components 2-12
2-2 Nationwide Average of Mercury Residues in Fish 2-17
2-3 Mercury Residues in Tissues of Piscivorous Birds 2-19
2-4 Mercury Residues in Tissues of Piscivorous Mammals 2-23
2-5 Toxicity Values for Aquatic Plants 2-26
2-6 Mercury Toxicity Increases With Temperature 2-27
2-7 Toxicity Values for Fish and Aquatic Invertebrates 2-29
2-8 Examples of Assessment and Measurement Endpoints 2-41
3-1 Models Used to Predict Mercury Air Concentrations, Deposition Fluxes and
Environmental Concentrations 3-2
3-2 Percentiles of the Methylmercury Bioaccumulation Factor 3-3
3-3 Exposure Parameters for Mink, Otter, Kingfisher, Osprey, and Eagle 3-4
3-4 Summary of Sample Calculations of Wildlife Species Methylmercury Exposure from
Fish Ingestion, Based on Average Fish Residue Values 3-5
3-5 Inputs to IEM-2M Model for the Two Time Periods Modeled 3-22
3-6 Process Parameters for the Model Plants Considered in the Local Impact Analysis 3-24
3-7 Predicted MHg Exposure to Ecological Receptors for the Eastern Site 3-26
3-8 Predicted MHg Exposure to Ecological Receptors for the Western Site 3-28
5-1 Summary of Methylmercury Bioaccumulation Factors for Trophic Levels 3 and 4 5-9
5-2 Exposure Parameters for Mink, Otter, Kingfisher, Osprey, and Eagle 5-11
5-3 Species-specific Wildlife Criteria Calculated in the Great Lakes Water Quality Initiative
and in the Mercury Study Report to Congress 5-16
5-4 Analysis of LOAEL-to-NOAEL Uncertainty Factor 5-20
IX
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LIST OF FIGURES
Page
2-1 Cycling of Mercury in Freshwater Lakes 2-2
2-2 Possible Routes of Exposure to Mercury 2-6
2-3 Distribution of Mercury in a Water Body 2-7
2-4 Example Aquatic Food Web 2-8
2-5 Example Terrestrial Food Web 2-10
3-1 Total Anthropogenic Mercury Deposition 3-7
3-2 Major Rivers and Lakes 3-8
3-3 National Resource Lands 3-9
3-4 Threatened and Endangered Plant Species and Anthropogenic Mercury Deposition 3-11
3-5 Regions of High Mercury Deposition 3-12
3-6 Regions of High Mercury Deposition and the Distribution of Acid Surface Waters 3-13
3-7 Kingfisher Range and Regions of High Mercury Deposition 3-14
3-8 Bald Eagle Range and Regions of High Mercury Deposition 3-15
3-9 Osprey Range and Regions of High Mercury Deposition 3-17
3-10 Common Loon Range and Regions of High Mercury Deposition 3-18
3-11 Florida Panther Range and Regions of High Mercury Deposition 3-19
3-12 Mink Range and Regions of High Mercury Deposition 3-20
3-13 River Otter Range and Regions of High Mercury Deposition 3-21
3-14 Configuration of Hypothetical Water Body and Wastershed Relative to Local Source 3-23
5-1 LOAEL-to-NOAEL Ratio Distribution 5-22
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LIST OF SYMBOLS, UNITS AND ACRONYMS
BAF Bioaccumulation factor
BAF3 Aquatic life bioaccumulation factor for trophic level 3
BAF4 Aquatic life bioaccumulation factor for trophic level 4
BCF Bioconcentration factor
BSAF Biota-sediment accumulation factor
BMP Biomagnification factor
bw Body weight
CAA Clean Air Act as Amended in 1990
d Day
DDE p,p-Dichlorodiphenyldichloroethylene
DDT 4,4-Dichlorodiphenyltrichloroethane
DOC Dissolved organic carbon
FA Average daily amount of food consumed
FCM Food chain multiplier
FD3 Fraction of the diet derived from trophic level 3
FD4 Fraction of the diet derived from trophic level 4
GAS-ISC3 Short range air dispersion model for mercury
GLWQI Great Lakes Water Quality Initiative
ha Hectare
Hg° Elemental mercury
Hg22+ Mercurous ion
Hg2+ Mercury II
IEM-2M Indirect exposure model for mercury
IJC International Joint Commission
kg Kilogram
L Liter
LC50 Lethal concentration (for fifty percent of population)
LD50 Lethal dose (for fifty percent of population)
LCUB Large coal-fired utility boiler
LOAEL Lowest-observed-adverse-effect level
m Meter
m3 Cubic meter
MCM Mercury cycling model
MDNR Michigan Department of Natural Resources
mg Milligram
MHg Methlymercury
MWC Municipal waste combustor
MWI Medical waste incinerator
ng Nanogram
nM Nanomole
NCBP National Contaminant Biomonitoring Program
NOAEL No-observed-adverse-effect level
PCBs Polychlorinated biphenyls
pg Picogram
pH Logarithm of the reciprocal of the hydrogen ion concentration. A measure of acidity
PPF Predator-prey factor
XI
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LIST OF SYMBOLS, UNITS AND ACRONYMS (continued)
PPF4 The observed ratio of the concentration at trophic level 4, divided by the
concentration at trophic level 3
ppm parts per million
RELMAP Regional Lagrangian Model of Air Pollution
SAB Science Advisory Board
sp. Species
UFA Uncertainty factor for species extrapolation
UFS Uncertainty factor for use of less than lifetime study
UFL Uncertainty factor for use of a lowest adverse effect level
U.S. EPA U.S. Environmental Protection Agency
//g Microgram
//M Micromole
WA Average daily volume of water consumed
WC Wildlife criterion level
WCf Final wildlife criterion level
WCj Intermediate wildlife criterion level
WCS Species-specific wildlife criterion level
WtA Average species weight
xn
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EXECUTIVE SUMMARY
Section 112(n)(l)(B) of the Clean Air Act (CAA), as amended in 1990, directs the U.S.
Environmental Protection Agency (U.S. EPA) to submit to Congress a comprehensive study on emissions
of mercury to the air. Volume VI, which addresses the ecological exposure and effects assessment for
mercury and mercury compounds, is part of an eight-volume report developed by U.S. EPA in response
to this directive.
Volume VI is an ecological risk assessment for anthropogenic mercury emissions. It follows the
format of the U.S. EPA Framework for Ecological Risk Assessment (U.S. EPA, 1992a), with minor
changes as suggested in the draft Proposed Guidelines for Ecological Risk Assessment (U.S. EPA, 1996).
The first step in the Framework is the problem formulation phase, wherein the potential ecological
impacts of mercury are reviewed. This is followed by the presentation of a conceptual model describing
how airborne mercury accumulates in aquatic biota, biomagnifies in aquatic food chains and is consumed
by wildlife that eat contaminated fish. Subsequent steps in the assessment include exposure and effects
assessments. Exposure and effects information are then considered together in an effort to develop
qualitative statements about the risk of airborne mercury emissions to piscivorous avian and mammalian
wildlife. An outcome of this effort is a recalculation of the wildlife criterion (WC) value for mercury in
aquatic systems. A characterization of the risks to wildlife from anthropogenic mercury emissions is
provided in Volume VII of this Report to Congress.
Scope of the Assessment
The scope of this assessment was limited solely to anthropogenic mercury that is emitted directly
to the atmosphere. The origins and extent of these emissions are reviewed in Volume II of this Report.
This analysis did not address mercury originating from direct wastewater discharge to water bodies,
mining waste or the application of mercurial pesticides. In a number of instances, these and other "point"
sources have been related to unacceptably high mercury levels in fish, triggering site-specific fish
consumption advisories. Clearly, where such point sources exist, there is a need to address the combined
impacts of mercury originating from all sources, including air emissions.
Mercury in the Environment
Wet deposition is thought to be the primary mechanism by which mercury emitted to the
atmosphere is transported to surface waters and land, although dry deposition may also contribute
substantially. Once deposited, mercury enters aquatic and terrestrial food chains. Mercury
concentrations increase at successively higher trophic levels as a result of bioconcentration,
bioaccumulation and biomagnification. Of the various forms of mercury in the environment,
methylmercury has the highest potential for bioaccumulation and biomagnification. Predators at the top
of these food chains are potentially at risk from consumption of methylmercury in contaminated prey.
Based on a review of available information, it was concluded that piscivorous (fish-eating) birds and
mammals are particularly at risk from mercury emissions. This risk is likely to be greatest in areas that
receive high levels of mercury deposition, although local and regional factors can substantially impact
the amount of total mercury that is translocated from watersheds to waterbodies and undergoes chemical
transformation to the methylated species.
ES-1
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The assessment endpoint for this ecological risk assessment is the maintenance of self-sustaining
wildlife populations. Measurement endpoints include the growth and survival of individual animals,
reproductive success, and behavior.
Exposure of Piscivorous Wildlife to Mercury
Exposure was characterized in a progressive manner, with varying reliance on computer models
for mercury deposition and fate. The objective of this analysis was to characterize the extent to which
piscivorous wildlife are exposed to mercury originating from airborne emissions. Details on exposure
assessment inputs, methods and results can be found in Volumes III and IV of this Report. Three general
approaches were used, which are described as follows.
1. Estimation of current average exposure to piscivorous wildlife on a nationwide basis.
The first analysis was conducted without computer models. Estimates of current mercury
exposure to selected piscivorous wildlife species were calculated as the product of the fish consumption
rate and measured mercury concentrations in fish. This analysis was not intended to be a site-specific
analysis, but rather to provide national exposure estimates for piscivorous wildlife. This analysis used
mean total mercury measurements from two nationwide studies offish residues and published fish
consumption data for the selected wildlife species. The relative ranking of exposure in //g/kg bw/d of
selected wildlife species was as follows: kingfisher > river otter > loon =osprey = mink > bald eagle.
2. Estimation of mercury deposition on a regional scale (40 km grid) and comparison of these
deposition data with species distribution information.
The second type of analysis was carried out on a regional scale. A long-range atmospheric
transport model (RELMAP) was used in conjunction with the mercury emissions inventory provided in
Volume II of this Report to generate predictions of mercury deposition across the continental U.S.
Ecosystems subject to high levels of mercury deposition will be more exposed to mercury than
ecosystems with lower levels of mercury deposition. The pattern of mercury deposition nationwide,
therefore, will influence which ecoregions and ecosystems might be exposed to hazardous levels of
mercury. Thus, predictions of mercury deposition were compared with the locations of major lakes and
rivers, national resource lands, threatened and endangered plant species and the distributions of selected
piscivorous wildlife species. Additionally, mercury deposition data were superimposed onto a map of
surface waters impacted by acid deposition, because it has been shown that low pH values are often
correlated with high levels of mercury in fish. The extent of overlap of selected species distributions
with areas receiving high rates of deposition (>5 (ig/m2) was characterized.
Avian wildlife considered in this analysis included species that are widely distributed
(kingfishers) and narrowly distributed (bald eagles, ospreys, and loons). All the birds selected were
piscivores that feed at or near the top of aquatic food chains and are therefore at risk from biomagnified
mercury. Two of the mammals selected for this analysis (mink and river otters) are piscivorous and
widely distributed. The other mammal selected, the Florida panther, is not widely distributed but is listed
as an endangered species. The Florida panther lives in an environment known to be contaminated with
mercury and preys upon small mammals (such as raccoons), which may contain high tissue burdens of
mercury. Results for each avian and mammalian species are summarized in Table ES-1.
ES-2
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Table ES-1
Percent of Species Range Overlapping
with Regions of High Mercury Deposition
Species
Kingfisher
Bald Eagle
Osprey
Common Loon
Florida Panther
Mink
River Otter
Percent of Range
Impacted
29%
34%
20%
40%
100%
35%
38%
Approximately 29% of the
kingfisher's range occurs within regions
of high mercury deposition. On a
nationwide basis, mercury does not
appear to be a threat to this species.
However, kingfishers consume more
mercury on a body weight basis than
any other wildlife species examined.
Although a recovery in the
population of bald eagles has resulted in
a status upgrade from "endangered" to
"threatened" in five states (Michigan,
Minnesota, Oregon, Washington and
Wisconsin), bald eagle populations are
still depleted throughout much of their
historical range. Bald eagles can be
found seasonally in large numbers in
several geographic locations, but most
of these individuals are transient, and
the overall population is still small.
Historically, eagle populations in the lower 48 states have been adversely impacted by the effects of
bioaccumulative contaminants (primarily DDT and perhaps also PCBs). Approximately 34% of the bald
eagle's range overlaps regions of high mercury deposition. Areas of particular concern include the Great
Lakes region, the northeastern Atlantic states and south Florida.
Nationwide, approximately 20% of the osprey's total range overlaps regions of high mercury
deposition; however, a much larger fraction of the osprey's eastern population occurs within these
regions. The osprey diet consists almost exclusively offish. Osprey populations underwent severe
declines during the 1950s through the 1970s due to widespread use of DDT and related compounds.
Nearly 40% of the loon's range is located in regions of high mercury deposition. Limited data
from a study of a mercury point source showed that loon reproductive success was negatively correlated
with exposure to mercury in a significant dose-response relationship. In some cases, mercury residues in
fish collected from lakes used as loon breeding areas may exceed levels that, on the basis of this point
source study, are associated with reproductive impairment. Loons frequently breed in areas that have
been adversely impacted by acid deposition. An assessment of mercury's effects on loon populations is
complicated by the fact that decreases in surface water pH have been associated with both increased
mercury residues in fish and declines in the available forage base.
All (100%) of the panther's range falls within an area of high mercury deposition. Mercury
levels found in tissues obtained from dead panthers are similar to levels that have been associated with
frank toxic effects in other feline species. The State of Florida has taken measures to reduce the risk to
panthers posed by mercury. Existing plans include measures to increase the number of deer available as
prey in order to reduce the reliance of panthers on raccoons. Raccoons frequently feed at or near the top
of aquatic food webs and can accumulate substantial tissue burdens of mercury. An evaluation of the
risk posed by mercury to the Florida panther is complicated by the possible impacts of other chemical
stressors, habitat loss, and inbreeding.
ES-3
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Approximately 35% of the range of mink habitat coincides with regions of high mercury
deposition nationwide. Mink occupy a large geographic area and are common throughout the U.S.
Given the opportunity, mink will prey on small mammals and birds. Many subpopulations, however,
prey almost exclusively on fish and other aquatic biota. Due to allometric considerations, mink may be
exposed to more mercury on a body weight basis than larger piscivorous mammals feeding at higher
trophic levels. In several cases, mercury residues in wild-caught mink have been shown to be equal to or
greater than levels associated with toxic effects in the laboratory.
River otter habitat overlaps regions of high mercury deposition for about 14% of the range for
this species. River otters occupy large areas of the U.S., but their population numbers are thought to be
declining in both the midwestern and southeastern states. The river otter's diet is almost exclusively of
aquatic origins and includes fish (primarily), crayfish, amphibians and aquatic insects. The consumption
of large, piscivorous fish puts the river otter at risk from bioaccumulative contaminants including
mercury. Like the mink, mercury residues in some wild-caught otters have been shown to be close to,
and in some cases greater than, concentrations associated with frank toxic effects.
3. Estimation of mercury exposure on a local scale in areas near emissions point sources.
A final analysis was conducted using a local-scale atmospheric fate model (GAS-ISC3), in
addition to the long-range transport data and an indirect exposure methodology, to predict mercury
concentrations in water and fish under a variety of hypothetical emissions scenarios. GAS-ISC3
simulated mercury deposition originating from model plants representing a range of mercury emissions
source classes. The four source categories were selected based on their estimated annual mercury
emissions or their potential to be localized point sources of concern. The categories selected were these:
municipal waste combustors (MWCs), medical waste incinerators (MWIs), utility boilers, and chlor-
alkali plants. To account for the long-range transport of emitted mercury, the 50th percentile RELMAP
atmospheric concentrations and deposition rates were included in the estimates from the local air
dispersion model. To account for other sources of mercury, estimates of background concentrations of
mercury were also included in this exposure assessment.
These data were used to estimate the contributions of different emission source types to mercury
exposure of selected wildlife species. It was concluded from this analysis that local emissions sources
have the potential to increase significantly the exposure of piscivorous birds and mammals to mercury.
Important factors related to local source impacts include quantity of mercury emitted by the source,
species and physical form of mercury emitted, and effective stack height. The extent of this local
contribution also depends upon watershed characteristics, facility type, local meteorology, and terrain.
The exposure of a given wildlife species is also highly dependent upon the fish bioaccumulation factor,
the trophic level(s) at which it feeds and the amount offish consumed per day.
Although the accumulation of methylmercury in fish tissues appears to be highly variable across
bodies of water, field data were determined to be sufficient to calculate representative means for different
trophic levels. The variability can be seen in the distribution of the methylmercury bioaccumulation
factors (BAF) for fish in trophic levels 3 and 4. These values, summarized in Table ES-2, are believed to
be better estimates of mercury bioaccumulation in natural systems than values derived from laboratory
studies.
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Table ES-2
Percentiles of the Methylmercury Bioaccumulation Factor
Parameter
Trophic 3 BAF
Trophic 4 BAF
Percentile of Distribution
5th
4.6 xlO5
3.3xl06
25th
9.5 xlO5
5.0xl06
50th
1.6 xlO6
6.8xl06
75th
2.6xl06
9.2xl06
95th
5.4xl06
1.4xl07
Effects Assessment for Mercury
Due to the broad range and extent of mercury emissions throughout the United States, many
potential ecological effects could have been considered. Neither the available data nor existing
methodology supported evaluation of all possible effects.
The ecosystem effects of mercury are incompletely understood. No applicable studies of the
effects of mercury on intact ecosystems were found. The ecological risk assessment for mercury did not,
therefore, address effects of mercury on ecosystems, plant and animal communities or species diversity.
Effects of methylmercury on fish and other aquatic biota were also not characterized, although there is
evidence of adverse impacts on these organisms following point source releases of mercury and in
aquatic environments affected by urban runoff.
Data on methylmercury effects in wildlife suitable for dose-response assessment are limited to
what are termed "individual effects" in the U.S. EPA Framework for Ecological Risk Assessment (U.S.
EPA, 1992a). A reference dose (RfD), defined as the chronic NOAEL, was derived for avian species
from studies by Heinz (1975, 1976a,b, 1979) in which three generations of mallard ducks (Anas
platyrhychos) were dosed with methylmercury dicyandiamide. The lowest dose, 0.5 ppm (78 (ig/kg
bw/d), resulted in adverse effects on reproduction and behavior and was designated as a chronic LOAEL.
A chronic NOAEL was estimated by dividing the chronic LOAEL by a LOAEL-to-NOAEL uncertainty
factor of 3. Calculated in this manner, the RfD for avian wildlife species is 26 (ig/kg bw/d.
The RfD for mammalian species was derived from studies involving subchronic exposures with
mink (Wobeser, 1973, 1976a,b), in which animals were dosed with mercury in the form of mercury-
contaminated fish. The dose of 0.33 ppm (55 (ig/kg bw/d) was selected as the NOAEL for subchronic
exposure. As this was less than a lifetime exposure, the subchronic NOAEL was divided by a
subchronic-to-chronic uncertainty factor of 3. Calculated in this manner, the RfD for mammalian
wildlife species is 18 (ig/kg bw/d.
Risk Assessment for Mercury
Ecological risk assessment methods relevant to chemical effects on wildlife are reviewed. The
data needs of these methods vary widely and dictate, to a considerable degree, which methods can be
applied to a given situation. Guidance is provided on the risk assessment methods that may be most
applicable to airborne mercury emissions, given the nature and extent of currently existing information.
Additional guidance is provided by reviewing published assessments for piscivorous species living in the
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Great Lakes region, south Florida, central Ontario, and coastal regions of Georgia, South Carolina and
North Carolina.
The scope of the present Report was intended to be national in scale. It was determined,
therefore, that any effort to assess the risk of mercury to a given species living in a defined location
would be inappropriate. Instead, an effort was made to compare mercury exposure and effects in a
general way using data collected from throughout the country and, in so doing, to develop qualitative
statements about risk.
Consistent with this broader-scale approach, an effort was made to derive a wildlife criterion
(WC) value for mercury that is protective of piscivorous wildlife. This WC is defined as the
concentration of mercury in water that, if not exceeded, protects avian and mammalian wildlife
populations from adverse effects resulting from ingestion of surface waters and from ingestion of aquatic
life taken from these surface waters. The health of wildlife populations may, therefore, be considered the
assessment endpoint of concern. Although not generally derived for the purpose of ecological risk
assessment, WC values incorporate the same type of exposure and effects information used in more
standard approaches. Such calculations also provide for a simple assessment of risk in any given
situation; that is, by determining whether the concentration of mercury in water exceeds the criterion
value.
The principal factors used to select wildlife species for WC development were: (1) exposure to
bioaccumulative contaminants; (2) species distributions; (3) availability of information with which to
calculate criterion values; and (4) evidence for bioaccumulation and/or adverse effects. All of the species
selected feed on or near the top of aquatic food webs. The avian species selected were the bald eagle
(Haliaeetus leucocephalus), osprey (Pandion haliaetus), common loon (Gavia immer) and belted
kingfisher (Ceryle alcyon). The mammalian species selected were the mink (Mustela vison) and river
otter (Lutra canadensis).
Because this assessment depends to a large extent on the assignment of BAFs for mercury in fish
at trophic levels 3 and 4, an effort was made to review published field data from which these BAFs could
be estimated. A Monte Carlo analysis was then performed to characterize the variability around these
estimates. The results of this effort are reported in Appendix D of Volume III and are summarized in
Table ES-2.
A WC value for mercury was estimated as the ratio of an RfD, defined as the chronic NOAEL (in
(ig/kg bw/d), to an estimated mercury consumption rate, referenced to water concentration using a BAF.
Individual wildlife criteria are provided in Table ES-3. This approach is similar to that used in non-
cancer human health risk assessment and was employed previously to estimate a WC for mercury in the
Water Quality Guidance for the Great Lakes System (GLWQI). The present effort differs, however,
from that of the GLWQI in that the entire analysis was conducted on a methylmercury basis. Additional
differences resulted from the availability of new data, including measured residue levels in fish and
water, and a re-evaluation of the toxicity data from which RfD estimates were derived. In this Report, a
more sensitive endpoint was selected for mammalian species, with the goal of assessing the full range of
effects of mercury. These changes reflect the amount of discretion allowed under Agency Risk
Assessment Guidelines.
Species-specific WC values for methylmercury were estimated for selected avian and
mammalian wildlife (identified above). A final WC was then calculated as the lowest mean of WC
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values for each of the two taxonomic classes (birds and mammals). The final WC for methylmercury
was based on
Table ES-3
Wildlife Criteria for Methylmercury
Organism
Mink
River otter
Kingfisher
Loon
Osprey
Bald eagle
Wildlife Criterion
(pg/L)
57
42
33
82
82
100
individual WC values calculated for mammalian species, and was estimated to be 50 picograms (pg)
methylmercury/L water.
The WC for methylmercury can be expressed as a corresponding mercury residue in fish though
the use of appropriate BAFs. Using the BAFs presented in Table ES-2 (50th percentile), a WC of 50
pg/L corresponds to methylmercury concentrations in fish of 0.077 (ig/g and 0.346 (ig/g for trophic levels
3 and 4, respectively. In addition, a WC for total mercury can be calculated using an estimate of
methylmercury as a proportion of total mercury in water. Based upon a survey of speciation data, the
best current estimate of dissolved methylmercury as a proportion of total dissolved mercury was
determined to be 0.078. Using this value, a methylmercury WC of 50 pg/L corresponds to a total
dissolved mercury WC of 641 pg/L. An additional correction is needed if the WC is to be expressed as
the amount of total mercury in unfiltered water. The available data, although highly variable, suggest
that on average total dissolved mercury comprises about 70 percent of that contained in unfiltered water.
Making this final correction results in a WC of 910 pg/L (unfiltered, total mercury), which is
approximately 70 percent of the value published previously in the GLWQI.
Conclusions
The following conclusions are presented in approximate order of degree of certainty in the
conclusion, based on the quality of the underlying database. The conclusions progress from those
with greater certainty to those with lesser certainty.
• Mercury emitted to the atmosphere deposits on watersheds and is translocated to waterbodies. A
variable proportion of this mercury is transformed by abiotic and biotic chemical reactions to
organic derivatives, including methylmercury. Methylmercury bioaccumulates in individual
organisms, biomagnifies in aquatic food chains and is the most toxic form of mercury to which
wildlife are exposed.
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The proportion of total mercury in aquatic biota that exists as methylmercury tends to increase
with trophic level. Greater than 90% of the mercury contained in freshwater fish exists as
methylmercury. Methylmercury accumulates in fish throughout their lifetime, although changes
in concentration as a function of time may be complicated by growth dilution and changing
dietary habits.
Piscivorous avian and mammalian wildlife are exposed to mercury primarily through
consumption of contaminated fish and accumulate mercury to levels above those in prey items.
Toxic effects on piscivorous avian and mammalian wildlife due to the consumption of
contaminated fish have been observed in association with point source releases of mercury to the
environment.
Concentrations of mercury in the tissues of wildlife species have been reported at levels
associated with adverse health effects in laboratory studies with the same species.
Piscivorous birds and mammals receive a greater exposure to mercury than any other known
receptors.
BAFs for mercury in fish vary widely; however, field data are sufficient to calculate
representative means for different trophic levels. These means are believed to be better estimates
of mercury bioaccumulation in natural systems than values derived from laboratory studies. The
recommended methylmercury BAFs for tropic levels 3 and 4 are 1,600,000 and 6,800,000,
respectively (dissolved basis).
Based upon knowledge of mercury bioaccumulation in fish, and of feeding rates and the identity
of prey items consumed by piscivorous wildlife, it is possible to rank the relative exposure of
different piscivorous wildlife species. Of the six wildlife species selected for detailed analysis,
the relative ranking of exposure to mercury is this: kingfisher > otter > loon = osprey = mink >
bald eagle. Existing data are insufficient to estimate the exposure of the Florida panther relative
to that of the selected species.
Local emissions sources (<50 km from receptors) have the potential to increase the exposure of
piscivorous wildlife well above that due to sources located more than 50 km from the receptors
(i.e., "remote" sources).
Field data are insufficient to conclude whether the mink, otter or other piscivorous mammals
have suffered adverse effects due to airborne mercury emissions.
Field data are insufficient to conclude whether the loon, wood stork, great egret, or other
piscivorous wading birds have suffered adverse effects due to airborne mercury emissions.
Field data are suggestive of adverse toxicological effects in the Florida panther due to mercury.
Unfortunately, the interpretation of these data is complicated by the co-occurrence of several
other potentially toxic compounds, habitat degradation, and loss of genetic diversity. Field data
suggest that bald eagles have not suffered adverse toxic effects due to airborne mercury
emissions.
ES-8
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• Reference doses (RfDs) for methylmercury, defined as chronic NOAELs, were determined for
avian and mammalian wildlife. Each RfD was calculated as the toxic dose (TD) from laboratory
toxicity studies, divided by appropriate uncertainty factors. The RfD for avian species is 21
(ig/kg bw/d (mercury basis). The RfD for mammalian wildlife is 18 (ig/kg bw/d (mercury basis).
• Based upon knowledge of mercury exposure to wildlife and its toxicity in long-term feeding
studies, WC values can be calculated for the protection of piscivorous avian and mammalian
wildlife. A WC value is defined as the concentration of total mercury in water which, if not
exceeded, protects avian and mammalian wildlife populations from adverse effects resulting
from ingestion of surface waters and from ingestion of aquatic life taken from these surface
waters.
• The methylmercury WC for protection of piscivorous avian wildlife is 61 pg/L (mercury basis).
• The methylmercury criterion for protection of piscivorous mammalian wildlife is 50 pg/L
(mercury basis).
• The final methylmercury criterion for protection of piscivorous wildlife species is 50 pg/L. This
value corresponds to a total mercury concentration in the water column of 641 pg/L, and
methylmercury concentrations in fish of 0.077 ppm (trophic level 3) and 0.346 ppm (trophic
level 4).
• Modeled estimates of mercury concentration in fish around hypothetical mercury emissions
sources predict exposures within a factor of two of the WC. The WC, like the human RfD, is
predicted to be a safe dose over a lifetime. It should be noted, however, that the wildlife effects
used as the basis for the WC are gross clinical manifestations. Expression of subtle adverse
effects at these doses cannot be excluded.
• The adverse effect level (population impacts on piscivorous wildlife) for methylmercury in fish
that occupy trophic level 3 lies between 0.077 and 0.3 ppm. A comparison of this range of
values with published residue levels in fish suggests that it is probable that individuals of some
highly exposed wildlife subpopulations are experiencing adverse toxic effects due to airborne
mercury emissions.
There are many uncertainties associated with this analysis, due to an incomplete understanding of
the biogeochemistry and toxicity of mercury and mercury compounds. The sources of uncertainty
include the following:
• Variability in the calculated BAFs is a source of uncertainty. BAFs given in this Report relate
methylmercury in fish to dissolved methylmercury levels in the water column. Methods for the
speciation of mercury in environmental samples are rapidly improving but remain difficult to
perform. Questions also remain concerning the bioavailability of methylmercury associated with
suspended particulates and dissolved organic material. Local biogeochemical factors that
determine net methylation rates are not fully understood. The food webs through which mercury
moves are poorly defined in many ecosystems and may not be adequately represented by a four-
tiered food chain model.
• The representativeness of field data used in establishing the BAFs is a source of uncertainty.
The degree to which the analysis is skewed by the existing data set is unknown. A
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disproportionate amount of data is from north-central and northeastern lakes. The uncertainty
associated with applying these data to a national-scale assessment is unknown.
Limitations of the toxicity database present a source of uncertainty. Few controlled studies of
quantifiable effects of mercury exposure in wildlife are available. These are characterized by
limited numbers of dosage levels, making it difficult to establish NOAEL and LOAEL values.
The toxic endpoints reported in most studies can be considered severe, raising questions as to the
degree of protection against subtle effects offered by RfD and WC values. Use of less than
lifetime studies for prediction of effects from lifetime exposure is also a source of uncertainty.
Concerns exist regarding the possibility of toxic effects in species other than the piscivorous
birds and mammals evaluated in this Report. Uncertainty is associated with mercury effects in
birds and mammals that prey upon aquatic invertebrates and with possible effects on amphibians
and aquatic reptiles. Uncertainty is also associated with mercury effects in fish. Toxicity to
terrestrial ecosystems, in particular soil communities, is another source of uncertainty.
Lack of knowledge of wildlife feeding habits is a source of uncertainty. Existing information
frequently is anecdotal or confined to evaluations of a particular locality; the extent to which this
information can be generalized is open to question. In some instances, the feeding habits are
relatively well characterized (e.g., Florida panther), whereas the extent of mercury contamination
of prey is poorly known (e.g., in raccoons).
While the methods used to assess toxicity focus on individual-level effects, the stated goal of the
assessment is to characterize the potential for adverse effects in wildlife populations. Factors
that contribute to uncertainty in population-based assessments include: variability in the
relationship between individuals and populations; lack of data on carrying capacity; and
relationships of one population, of the same or different species, to another population.
A focus on populations may not always be appropriate. This could be true for endangered
species, which may be highly dependent for the survival of the species on the health of a few
individuals. This may also be true for some regional or local populations of widespread species;
the local population may be "endangered" and, thus, dependent on the survival of individuals.
Multiple stressor interactions involving chemical effects are, in general, poorly known. Even
less well known are the possible impacts of land and water use practices on water quality and
large-scale ecosystem attributes (e.g., community structure and biodiversity).
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1. INTRODUCTION
Section 112(n)(l)(B) of the Clean Air Act (CAA), as amended in 1990, requires the U.S.
Environmental Protection Agency (U.S. EPA) to submit a study on atmospheric mercury emissions to
Congress. The sources of emissions that must be studied include electric utility steam generating units,
municipal waste combustion units and other sources, including area sources. Congress directed that the
Mercury Study evaluate the rate and mass of mercury emissions, health and environmental effects,
technologies to control such emissions and the costs of such controls.
In response to this mandate, U.S. EPA has prepared an eight-volume Mercury Study Report to
Congress. The eight volumes are as follows:
I. Executive Summary
II. An Inventory of Anthropogenic Mercury Emissions in the United States
III. Fate and Transport of Mercury in the Environment
IV. An Assessment of Exposure to Mercury in the United States
V. Health Effects of Mercury and Mercury Compounds
VI. An Ecological Assessment for Anthropogenic Mercury Emissions in the United States
VII. Characterization of Human Health and Wildlife Risks from Mercury Exposure in the
United States
VIII. An Evaluation of Mercury Control Technologies and Costs
This volume (Volume VI) is an ecological assessment of airborne mercury emissions. It provides
an overview of the ecological effects of mercury, uses published data on fish residues as well as
modeling predictions from Volume III to assess potential ecological exposures, and reviews available
toxicity and bioaccumulation data for the purpose of developing qualitative statements about the risk of
airborne mercury emissions to piscivorous avian and mammalian wildlife. In addition, these data are
used to calculate a criterion value for the protection of piscivorous wildlife species, using the same
general methodology employed in the Great Lakes Water Quality Initiative (U.S. EPA 1993b, 1993c,
1995b).
Volume VI is organized according to the format provided by U.S. EPA's Framework for
Ecological Risk Assessment (U.S. EPA, 1992a). Chapter 2 corresponds to the problem formulation
phase of the assessment and reviews the potential ecological impacts of mercury. Based upon this
information, it is concluded that piscivorous avian and mammalian wildlife are potentially at risk due to
airborne mercury emissions. A conceptual model is presented to describe how airborne mercury
becomes concentrated in aquatic biota, which serve as the primary food source for piscivorous wildlife.
An exposure analysis is presented in Chapter 3, and effects are analyzed in Chapter 4. Effects and
exposure information are considered together in Chapter 5 as a means of assessing the risk of airborne
mercury emissions to piscivorous avian and mammalian wildlife. Chapter 6 lists the main conclusions of
this report, while Chapter 7 presents a list of critical research needs. References are provided at the end
of this Volume in Chapter 8. An ecological risk characterization for mercury is presented separately in
Volume VII of this Report.
The scope of this assessment is limited to consideration of only mercury that is emitted directly
to the atmosphere. The origins and extent of these emissions are reviewed in Volume II of this Report.
This analysis does not address mercury originating from mine leachate, the manufacturing and disposal
of batteries, dental amalgam (in municipal wastewater), or the application of mercurial pesticides. In a
number of instances, these and other "point" sources have been related to unacceptably high mercury
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levels in fish, triggering site-specific fish consumption advisories. Clearly, where such point sources
exist, there is a need to address the combined impacts of mercury originating from all sources, including
air emissions.
The exposure analysis for piscivorous wildlife was designed to address the following questions:
• What is the current degree of exposure of piscivorous avian and mammalian wildlife?
• In what broad geographical areas of the continental United States is there a high
probability for co-occurrence of high mercury deposition rates and wildlife species of
concern?
• What is the relative increase in exposure that can be anticipated for wildlife species that
live in proximity to mercury emissions sources?
The first of these questions was addressed by defining what piscivorous wildlife eat and then
characterizing the mercury content of these food items. The second question was addressed by
superimposing the results of a long-range transport analysis onto wildlife distribution information. The
last question was addressed by using the results of a local-scale air dispersion model, combined with an
indirect exposure methodology, to generate hypothetical exposure scenarios for wildlife. This short-
range analysis is similar to that used in the human health exposure assessment (Volume IV). Descriptions
of the long- and short-range air dispersion models and the indirect exposure methodology are provided in
Volume III.
The primary goal of the effects analysis was to identify and review toxicity studies with wildlife
species that could be used to estimate chronic NOAEL values for avian and mammalian wildlife. In
addition, field data were reviewed as a means of comparing mercury residues in wild animals with those
shown to associated with toxic effects in laboratory or other studies.
Finally, exposure and effects information are reviewed in an effort to develop qualitative
statements about the risk of mercury emissions to piscivorous avian and mammalian wildlife. This
assessment includes a review of previously published efforts to assess the risk of mercury to several
wildlife species living in restricted geographical locals. Exposure and effects information are also used
to calculate a water-based wildlife criterion value for mercury, which, if not exceeded, would be
protective of piscivorous avian and mammalian wildlife. The general method used to calculate this
criterion value is similar to that used previously to estimate criterion values for mercury in the Great
Lakes Water Quality Initiative (U.S. EPA 1993b, 1993c, 1995b). An effort was made to calculate fish
residue concentrations corresponding to this criterion value. These residue values were then compared
with measured values obtained in environmental sampling efforts. Owing to its importance for both the
ecological and human health assessments, published data for fish and other aquatic biota were evaluated
to calculate bioaccumulation factors (BAFs) for methylmercury and to characterize the uncertainties
associated with these estimates. The data and methods used to derive these BAFs are presented in
Appendix D of Volume III. A summary of this material is provided in Chapter 5 of the present Volume.
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2. PROBLEM FORMULATION
U.S. EPA defines ecological risk assessment as "a process that evaluates the likelihood that
adverse ecological effects may occur or are occurring as a result of exposure to one or more stressors"
(U.S. EPA, 1992a, 1996). A "stressor" is defined as any chemical, biological, or physical entity that can
induce an adverse response of ecological components, i.e., individuals, populations, communities, or
ecosystems. Although ecological risk assessment follows the same basic risk paradigm as human health
risk assessment, there are three key differences between the two types.
• Ecological risk assessment can consider effects on populations, communities and
ecosystems in addition to effects on individuals of a single species.
• No single set of ecological values to be protected is applicable in all cases; instead, they
must be selected for each assessment based on both scientific and societal merit.
• Nonchemical stressors (e.g., physical disturbances) often need to be evaluated as well as
chemical stressors.
The problem formulation phase of an environmental risk assessment consists of four main
components: (1) integrating available information on the stressors, potential exposure pathways,
ecosystems potentially at risk, and ecological effects; (2) selecting assessment endpoints (the ecological
values to be protected); (3) developing a conceptual model of the problem; and (4) formulating an
analysis plan for the exposure and effects characterization phases of the assessment.
Section 2.1 reviews the characteristics of mercury in the environment, including its various
chemical forms (speciation), chemical transformations and movement within and between the air, surface
water, and soil compartments of the environment (cycling). Section 2.2 identifies the pathways by which
plants and animals can be exposed to mercury in both aquatic and terrestrial ecosystems. Section 2.3
provides an overview of what is known about the effects of mercury on organisms, populations,
communities and ecosystems. Section 2.4 identifies ecosystems and ecosystem components that are
thought to be most at risk from mercury in the environment. Section 2.5 describes the selection of
assessment and measurement endpoints for the ecological risk assessment. A conceptual model of
mercury fate and effects in the environment is presented in Section 2.6. An analysis plan for the
exposure and effects characterizations is provided in Section 2.7.
It should be noted that this review of mercury fate and effects is limited to consideration of only
terrestrial and freshwater aquatic ecosystems. It is recognized that mercury that deposits in coastal areas
can be translocated to estuarine environments, and that biota which inhabit these and nearby marine
systems have the potential to be adversely impacted. Presently, however, uncertainties regarding
mercury deposition, cycling, and effects in such environments are so great as to preclude even a
qualitative risk assessment.
2.1 Stressor Characteristics: Mercury Speciation and Cycling
Mercury in the environment can occur in various physical and chemical forms. Physically,
mercury may exist as a gas or liquid, or it may be associated with solid particulates. Chemically,
mercury can exist in three oxidation states:
(1) Hg° - elemental mercury, also called metallic mercury;
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(2) Hg22+ - mercurous ion (monovalent mercury, mercury I); or
(3) Kg2* - mercury II (mercuric ion, divalent mercury).
Mercury also reacts with other chemicals to form inorganic compounds (e.g., HgCl2 - mercuric chloride)
and organic compounds (e.g., CH3Hg+ - monomethylmercury, (CH3)2Hg - dimethylmercury, C6H5HgCl -
phenyl mercuric chloride). Figure 2-1 illustrates the major transformations between these different forms
in the environment. Dimethylmercury is highly volatile and dissociates to monomethylmercury at neutral
or acid pH (pH < 8) (Huckabee et al., 1979). In contrast, monomethylmercury is stable and tends to
accumulate in living organisms (Bloom, 1992). Throughout this volume, monomethylmercury is referred
to simply as methylmercury.
Figure 2-1
Cycling of Mercury in Freshwater Lakes (adapted from Winfrey and Rudd, 1990)
CH3HgCH3
x , , ^Organic & Inorganic. , ,
, , , , Complexes / ,
As discussed in the box below, methylation is an important step in the mercury cycle that strongly
influences the ecological fate and effects of mercury. Methylmercury is readily accumulated by fish due to
efficient uptake from dietary sources and to low rates of elimination (Bloom, 1992). It is also the most
toxic form of mercury to wildlife (Eisler, 1987).
Mercury cycling and partitioning in the environment are complex phenomena and are influenced
by numerous environmental factors. The following sections provide a brief overview of mercury
speciation and partitioning in the atmosphere, surface water and soil, including information from specific
case studies. For a detailed review, see Volume HI of this Report.
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FOCUS ON METHYLMERCURY
Methylmercury is the form of mercury of particular concern in ecosystems for three reasons.
(1) All forms of mercury can be converted to methylmercury by natural processes in the environment.
(2) Methylmercury bioaccumulates and biomagnifies in aquatic food webs.
(3) Methylmercury is the most toxic form of mercury.
In the 1960s, researchers found methylmercury in fish in Swedish lakes, although no discharge of
methylmercury had occurred in those lakes (Bakir et al., 1973). Later research determined that the methylation of
mercury in sediments by anaerobic sulfur-reducing bacteria was a major source of methylmercury in many aquatic
environments (Gilmour and Henry, 1991; Zillioux et al., 1993). Aerobic bacteria and fungi, including yeasts that grow
best in acid conditions, also can methylate mercury (Eisler, 1987; Yannai et al., 1991; Fischer et al., 1995). In addition,
fulvic and humic material may abiotically methylate mercury (Nagase et al., 1984; Lee et al., 1985; Weber, 1993). The
major site of methylation in aquatic systems is the sediment, but methylation also occurs in the water column (Wright
and Hamilton, 1982; Xun et al., 1987; Parks et al., 1989; Bloom and Effler, 1990; Winfrey and Rudd, 1990; Bloom et
al., 1991; Gilmour and Henry, 1991; Miskimmin et al., 1992). Wetlands may be particularly active sites of methylation
(St. Louis et al., 1994; Hurley et al., 1995). The rate of mercury methylation varies with microbial activity, mercury
loadings, suspended sediment load, DOC, nutrient content, pH, redox conditions, temperature, and other variables.
Demethylation occurs via biotic and abiotic mechanisms, including photodegradation (Sellers et al., 1996). The net rate
of mercury methylation is determined by competing rates of methylation and demethylation.
Methylmercury bioaccumulates and biomagnifies in aquatic food webs at higher rates and to a greater extent
than any other form of mercury (Watras and Bloom, 1992). "Bioaccumulation" refers to the net uptake of a contaminant
from the environment into biological tissue via all pathways. It includes the accumulation that may occur by direct
contact of skin or gills with mercury-contaminated water as well as ingestion of mercury-contaminated food.
"Biomagnification" refers to the increase in chemical concentration in organisms at successively higher trophic levels in
a food chain as a result of the ingestion of contaminated organisms at lower trophic levels. Methylmercury can comprise
from 10 percent to over 90 percent of the total mercury in phytoplankton and zooplankton (trophic levels 1 and 2) (May
et al., 1987; Watras and Bloom, 1992), but generally comprises over 90 percent of the total mercury in fish (trophic
levels 3 and 4) (Huckabee et al., 1979; Grieb et al., 1990; Bloom, 1992; Watras and Bloom, 1992). Fish absorb
methylmercury efficiently from dietary sources and store this material in organs and tissues. The biological half-life of
methylmercury in fish is difficult to determine but is generally thought to range from months to years.
Methylmercury is the most toxic form of mercury to birds, mammals, and aquatic organisms due to its strong
affinity for sulfur-containing organic compounds (e.g., proteins). Biological membranes, including the blood-brain
barrier and the placenta, that tend to discriminate against other forms of mercury allow relatively easy passage of
methylmercury and dissolved mercury vapor (Eisler, 1987). Methylmercury can cause death, neurological disorders,
organ damage, impaired immune response, impaired growth and development and reduced reproductive success
(Klaassen, 1986). In mammals, fetuses are particularly sensitive to mercury, experiencing deleterious developmental
effects when the mothers appear to be unaffected (Clarkson, 1990).
2.1.1 Mercury in Air
In the atmosphere, most mercury (95 to over 99 percent) exists as gaseous Hg°; the remainder
generally is comprised of gaseous divalent (Hg2+) mercury and mercury associated with particulates
(Lindqvist, 1991; MDNR, 1993). Gaseous methylmercury may also may exist in air at measurable
concentrations, especially near mercury emissions sources. Mercury associated with particulates in air
includes Hg2+, which is thought to occur primarily as mercuric chloride (MDNR, 1993).
The form of mercury in air affects both the rate and mechanism by which it deposits to earth.
Oxidized and particulate mercury are more likely to be deposited than Hg° because they are more soluble
in water and are scavenged by precipitation more easily. They are also thought to be dry deposited more
easily. As a result, oxidized and particulate forms of mercury are thought to comprise the majority of
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deposited mercury, even though they comprise only a few percent of the total amount of mercury in the
atmosphere (Lindqvist, 1991).
Wet deposition is thought to be the primary mechanism for transporting mercury from the
atmosphere to surface waters and land (Lindqvist, 1991). In the Great Lakes area, for example, wet
deposition is believed to account for 60 to 70 percent of total mercury deposition. Hg2+ is the
predominant form in precipitation (MDNR, 1993).
2.1.2 Mercury in Surface Water
Mercury can enter surface water as Hg°, Hg2+, or methylmercury. Once in aquatic systems,
mercury can exist in dissolved or particulate forms and can undergo the following transformations (see
Figure 2-1) (Lindqvist et al., 1991; Winfrey and Rudd, 1990).
• Hg° in surface waters can be oxidized to Hg2+ or volatilized to the atmosphere.
• Hg2+ can be methylated in sediments and the water column to form methylmercury.
• Methylmercury can be alkylated to form dimethylmercury.
• Hg2+ and methylmercury can form organic and inorganic complexes with sediment and
suspended particulate matter.
Each of these reactions can also occur in the reverse direction. The net rate of production of each
mercury species is determined by the balance between forward and reverse reactions.
Estimates of the percent of total mercury in surface waters that exists as methylmercury vary.
Generally, methylmercury makes up less than 20 percent of the total mercury in the water column (Kudo
et al., 1982; Parks et al., 1989; Bloom and Effler, 1990; Watras et al., 1995a). In lakes without point
source discharges, methylmercury frequently comprises ten percent or less of total mercury in the water
column (Lee and Hultberg, 1990; Lindqvist, 1991; Porcella et al., 1991; Watras and Bloom, 1992;
Driscoll et al., 1994, 1995; Watras et al., 1995b). A review of speciation data collected to date suggests
that methylmercury as a percent of total averages just under 8 percent (see Volume III, Appendix D of
this Report).
Contaminated sediments can serve as an important mercury reservoir, with sediment-bound
mercury recycling back into the aquatic ecosystem for decades or longer. Biological processes affect this
recycling process. For example, sulfate-reducing bacteria may mediate mercury methylation (Gilmour
and Henry, 1991). Benthic invertebrates may take up mercury from sediments, making it available to
other aquatic animals through the food chain and to vertebrates that consume emergent aquatic insects
(Hildebrand et al., 1980; Wren and Stephenson, 1991; Dukerschein et al., 1992; Saouter et al., 1993;
Tremblay et al., 1996; Suchanek et al., 1997). Chemical factors, such as reduced pH, may stimulate
methylmercury production at the sediment/water interface and thus may accelerate the rate of mercury
methylation resulting in increased accumulation by aquatic organisms (Winfrey and Rudd, 1990).
Attributes of the sediment, including organic carbon and sulfur content, can influence mercury
bioavailability (Tremblay et al., 1995). DOC appears to be important in the transport of mercury to lake
systems but, at high concentrations, may limit bioavailability (Driscoll et al., 1994, 1995).
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2.1.3 Mercury in Soil
Mercury deposited from the air forms stable complexes with soil particles of high organic or
sulfur content and with humic and fulvic acids (Andersson, 1979; WHO, 1989; Johansson et al., 1991;
Yin et al., 1996). These chemical bonds limit mercury's mobility in soils and its availability for uptake
by living organisms. In general, the distribution of mercury in soil is likely to follow the distribution of
organic matter. Mercury has a long retention time in soils. As a result, mercury that has accumulated in
soils may continue to be released to surface waters for long periods of time, possibly hundreds of years
(Johansson et al., 1991)
Hg2+ in soils can be transformed to other mercury species. Bacteria and organic substances can
reduce Hg2+ to Hg°, releasing volatile elemental mercury to the atmosphere. Alternatively, bacteria and
organic substances can methylate mercury, and subsequently demethylate it, depending on environmental
conditions (Allard and Arsenic, 1991; Gilmour and Henry, 1991).
Recent measurements of volatile exchange between air and soil indicate that soil emissions could
be similar in magnitude to atmospheric deposition, suggesting that the total sink capacity of soils is less
than previously thought (Kim et al., 1995). Similarly, measurements of canopy emissions indicate that
forest ecosystems may not act as efficient sinks for atmospheric mercury (Lindberg, 1996). It is
uncertain at present how much these loss processes affect the retention of mercury in upper level soils.
2.2 Potential Exposure Pathways
Plants and animals can be exposed to mercury by direct contact with contaminated environmental
media or ingestion of mercury-contaminated water and food (see Figure 2-2). Mercury deposited in soil
can be a source of direct exposure from physical contact (e.g., earthworms and terrestrial plants).
Animals also can ingest mercury in soil, either purposefully (e.g., earthworms) or incidentally (e.g.,
grazers). Mercury in the air can be taken up directly by terrestrial or aquatic emergent plants or inhaled
by terrestrial animals. Mercury in water can be a source of direct exposure to aquatic plants (e.g., algae
and seagrasses) and animals (e.g., zooplankton and fish) and can be ingested by terrestrial animals in
drinking water. Finally, both aquatic and terrestrial animals can be exposed to mercury in contaminated
food sources.
Not all of these potential exposure pathways are equally important, however. The remainder of
this section evaluates the likely importance of different routes of exposure consequent to mercury release
to air. Section 2.2.1 discusses the fate and bioavailability of mercury in aquatic systems and the
pathways by which aquatic plants and animals can be exposed to mercury directly in contaminated water
or indirectly through aquatic food webs. Section 2.2.2 provides information on the fate and
bioavailability of mercury in terrestrial ecosystems and the pathways by which terrestrial plants and
animals can be exposed. Bioaccumulation of mercury in aquatic and terrestrial organisms is discussed
further in Section 2.3.1.
2.2.1 Exposure Pathways in Aquatic Systems
Figure 2-3 illustrates the potential distribution of mercury in a water body. As shown, mercury
can be present in surface waters in various forms: (1) dissolved in the water; (2) concentrated in the
surface
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microlayer (the uppermost layer of a surface water); (3) attached to seston1; (4) in the bottom sediments;
and (5) in biota (e.g., fish and macroinvertebrates2).
Figure 2-2
Possible Routes of Exposure to Mercury
Mercury Transported
• o . ° 11111111 ITT^^^^n
! I! 11 I I ! 11 ! ' //'
i i i i i i i 1111
I I I. I I I I I II >
Atmospheric Deposition of Mercury
Drinking
Water
Intakes
Mercury Transferred
Up Aquatic Food Web
Uptake by Uptake by
Bentnic Animals Aquate Plants
C54054-1-1
The form and location of mercury in a water body determines its bioavailability. For example,
dissolved mercury is available for direct uptake by aquatic plants, fish and invertebrates. Mercury that
concentrates in the surface microlayer is available to organisms that live, reproduce, or feed on the surface
of water bodies (i.e., neuston). Mercury attached to seston can be ingested by aquatic animals that feed on
plankton. Additionally, mercury that has accumulated in the sediments may be available to benthic plants
and animals.
Seston is suspended paniculate matter, including detritus (dead organic matter) and plankton (i.e., living
plants and animals that passively float or weakly swim in the water column such as algae, water fleas, and copepods).
2Macroinvertebrates are invertebrates (i.e., animals without backbones) that are visible to the naked eye,
such as worms, clams, snails, insects and insect larvae, and crayfish.
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Figure 2-3
Distribution of Mercury in a Water Body
Dissolves (available to
plants and animals)
Accumulates in fish and
invertebrates (available in
the food web to higher
trophic levels)
•O-
Attaches to seston (plankton and
suspended detritus); some settles
to bottom sediments (available
to bottom-dwellers), some eaten
(available in the food web to
higher trophic levels)
Concentrates in
surface microlayer
(concentrated levels
available to plants
and animals)
Methylated by bacteria
in sediments (methylmercury -
highly toxic to animals - becomes
available to biota)
C54054-1-2
Aquatic plants may take up mercury from air, water or sediments (Crowder, 1991; Ribeyre and
Boudou, 1994). Planktonic plants (i.e., phytoplankton such as algae) are not rooted; therefore, their only
route of exposure is uptake from water. Both submerged aquatic vegetation and wetland emergent plants
are rooted and can be exposed to mercury in sediments. In locations with mercury-contaminated
sediments, mercury levels in aquatic macrophytes3 have been measured at 0.01 ^g/g, indicating that these
plants do not strongly accumulate mercury from sediments (Wells et al., 1980; Crowder et al., 1988). The
ratio between inorganic and organic mercury varies in plants (Crowder, 1991).
For aquatic animals, the primary exposure routes of concern are direct contact with mercury-
contaminated water and sediments and ingestion of mercury-contaminated food. Fish can absorb mercury
through the gills, skin and gastrointestinal tract (Wiener and Spry, 1995). The proportion of mercury taken
up by any given route varies with fish size, and perhaps also with seasonal factors such as water
temperature, diet and prey availability (Post et al., 1996). These fish then become a source of mercury for
piscivorous birds and mammals. Emergent aquatic insects represent another potential source of mercury
for insectivorous birds and mammals (Dukerschein et al., 1992; Saouter et al., 1993).
3Macrophytes are aquatic plants that are large enough to be visible to the naked eye.
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Mercury in aquatic biota tends to occur at higher concentrations in higher trophic levels (discussed
in more detail in Section 2.3 of this Volume). An example aquatic food web is shown in Figure 2-4. At
the top trophic levels are piscivores, such as humans, bald eagles, cormorants, herring gulls, loons,
kingfishers, mergansers, herons, egrets, ospreys, bald eagles, river otters, mink, alligators, snapping turtles
and water snakes. The largest of these species (e.g., bald eagle and otter) can prey on fish that occupy high
trophic levels, such as trout and salmon, which in turn feed on smaller "forage" fish, such as smelt, alewife,
minnow, chub, and sculpin. Smaller piscivorous wildlife (e.g., kingfishers, ospreys, and terns) tend to feed
on the smaller forage fish, which in turn feed on zooplankton or benthic invertebrates. Zooplankton (e.g.,
copepods and water fleas) feed on phytoplankton (i.e., microscopic algae), and the smaller benthic
Figure 2-4
Example Aquatic Food Web
Submerged
Aquatic Vegetation
Bacteria
and Fungi
Dead Plants
and Animals
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invertebrates tend to feed on algae and detritus. Thus, mercury can be transferred and accumulated
through three or four trophic levels to reach the prey of piscivorous wildlife species. Studies with lake
trout suggest that differences in food web structure can substantially impact mercury accumulation by
large predatory fish (Cabana and Rasmussen, 1994; Cabana et al., 1994; Putter, 1994).
2.2.2 Exposure Pathways in Terrestrial Systems
Several exposure pathways are possible for both plants and animals in terrestrial systems. The
two main pathways by which terrestrial plants can be exposed to mercury are uptake from soils into the
roots and absorption directly from the air. Potential exposure routes for terrestrial animals include the
following: (1) ingestion of mercury-contaminated food; (2) direct contact with contaminated soil; (3)
ingestion of mercury-contaminated drinking water; and (4) inhalation. Food ingestion is of primary
concern for vertebrate carnivores (including humans). Once mercury enters a terrestrial food web, like
that shown in Figure 2-5, it can be transferred in increasing concentrations to higher trophic levels
(Talmage and Walton, 1993). A special case exists when terrestrial carnivores consume prey that have
accumulated mercury originating from aquatic sources. Perhaps the best known example is that of the
Florida panther, which consumes raccoons that have accumulated mercury through consumption of
contaminated fish and shellfish (Roelke et al., 1991).
2.2.2.1 Terrestrial Plants
Uptake by plants plays a major role in the entry of metals to terrestrial food webs. Mercury
uptake by terrestrial vascular plants4 can occur through the roots or through the leaves, by way of
stomata5 (Mosbaek et al., 1988; Crowder, 1991; Maserti and Ferrara, 1991). A vascular plant's uptake of
mercury from the soil depends on soil type, with uptake decreasing as organic matter, which binds
mercury, increases (WHO, 1989). Uptake of mercury through leaves is considered to be a negligible
source of mercury for beech and spruce (Schmidt, 1987) but is an important route for pines and
herbaceous plants (Mosbaek et al., 1988; Maserti and Ferrara, 1991). Bryophytes and lichens have no
roots and take up metals only from air or water (WHO, 1989; Crowder, 1991). Some species of
bryophytes and lichens can bioconcentrate mercury to relatively high levels (e.g., up to 1200 //g/g in
Sphagnum sp.) (Siegal et al., 1985). Some woody plants (e.g., Pinus sp.) also bioconcentrate mercury
(Siegal et al., 1987).
2.2.2.2 Terrestrial Animals
Dietary exposure is the primary route of mercury uptake for vertebrate members of terrestrial
food webs. Figure 2-5 illustrates a terrestrial food web. Plants are eaten by a wide diversity of
herbivorous animals (e.g., grasshoppers, caterpillars, mice, voles, rabbits, and deer). Insects, earthworms
and other soil macroinvertebrates can accumulate mercury to levels well above those of the soil in which
they reside (Siegel et al., 1975; Helmke et al., 1979; Beyer et al., 1985), and are themselves consumed by
many species of birds, shrews, snakes, and amphibians. Small mammals, birds, reptiles and amphibians
are consumed by larger predators, such as owls, hawks, eagles, mink, and wolves. Thus, mercury can be
transferred and accumulated through two or three trophic levels to reach the prey of top carnivores in
terrestrial systems.
4Plants with roots, stems, and leaves, such as ferns and seed plants.
5 Stomata (plural of stoma) are the minute openings in the epidermis of leaves, stems, or other plant organs
that allow gas to diffuse in and out.
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Figure 2-5
Example Terrestrial Food Web
For these terrestrial animals, exposure to mercury depends largely on the animal's feeding strategy.
For example, generalist herbivores (plant-eaters) may be less exposed to mercury than species that are
specialized in or restricted to feeding on highly exposed plant species (e.g., reindeer foraging mostly on
lichens and bryophytes).
2.2.3 Summary of Aquatic and Terrestrial Exposure Pathways
Food chain transfers of mercury are thought to be the most important exposure pathway in both
aquatic and terrestrial ecosystems. Mercury, however, tends to bioaccumulate and biomagnify more
strongly in aquatic than in terrestrial ecosystems. There are several possible explanations for this
observation. First, the transfer of metals to higher trophic levels depends to some extent on where the
metals are stored within prey organisms. Birds and mammals accumulate mercury in their feathers and fur,
which are not eaten or are poorly digested. In contrast, most of the mercury in fish is contained in muscle
tissue, which is consumed and digested by piscivorous wildlife. In addition, mercury in terrestrial food
webs frequently exists in an inorganic form, rather than as methylmercury. Inorganic mercury accumulates
to only a limited extent in plants and soil organisms and does not biomagnify in the organisms that feed on
them. Finally, aquatic food chains often include more trophic levels than terrestrial food chains. A typical
food chain in aquatic systems would consist of: phytoplankton/algae/detritus - zooplankton/benthic
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invertebrates -> small forage fish -> larger piscivorous fish. Piscivorous birds and mammals would
represent the fifth step in the chain. In some cases a sixth step exists, as when a bald eagle consumes a
piscivorous herring gull. A typical food chain in terrestrial systems might be: plants -> small herbivorous
mammals -> predatory birds and mammals. Another typical terrestrial food chain would be: plants ->
herbivorous insects -> small birds -> birds of prey. In these examples, the top predators represent the third
and fourth step in the chain (although additional steps are possible), instead of the fifth or sixth level as
can be the case for aquatic systems.
2.3 Ecological Effects
This section provides an overview of potential effects of mercury on ecosystems and components
of ecosystems. Contaminants such as mercury can affect individual organisms, populations,
communities, or ecosystems (see Table 2-1). Effects on individuals can be lethal or sublethal, including
behavioral, reproductive and developmental effects. Additionally, effects can be immediate, due to acute
(short-term) exposures or may be manifested only after chronic (long-term) exposures.
In animals, toxic effects caused by mercury exposure vary depending on a number of factors,
including but not limited to these:
• delivered dose (i.e., amount and duration of exposure);
• the form of mercury to which an organism is exposed;
• physical and chemical parameters of the environment (e.g., pH, temperature, and DOC);
• the extent to which an organism is exposed to other chemical or non-chemical stressors;
• the life stage, age, sex, species, and physiological condition of the exposed organism;
and
• the extent to which the organism can detoxify or eliminate absorbed mercury.
The remainder of this section provides an overview of potential adverse ecological effects of mercury.
Section 2.3.1 discusses the bioaccumulation and biomagnification of mercury in food chains, Section
2.3.2 reviews individual-level effects, Section 2.3.3 reviews population-level effects, and Section 2.3.4
reviews effects on communities and ecosystems.
2.3.1 Bioaccumulation of Mercury
As discussed previously, plants and animals may absorb mercury from direct exposure to
contaminated media. In addition, animals can acquire mercury through ingestion of mercury-
contaminated food. These pathways determine how much mercury an organism is exposed to from
outside sources. An additional factor that determines the effect of mercury on ecological systems is how
much mercury is accumulated by organisms. Mercury accumulation can result in concentrations in
exposed plants and animals that are higher than those in surrounding media or in ingested food. This
section outlines the basic processes by which mercury accumulates and introduces the different ways that
chemical accumulation in biological systems is measured and expressed.
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Table 2-1
Examples of Effects of Contaminants on Ecosystem Components
Component
Examples of Effects
Individual
Change in respiration
Change in behavior (e.g., migration, predator-prey interactions)
Inhibition or induction of enzymes
Increased susceptibility to pathogens
Decreased growth
Decreased reproduction
Death
Population
Decreased genotypic and phenotypic diversity
Decreased biomass
Increased mortality rate
Decreased fecundity rate
Decreased recruitment of juveniles
Increased frequency of disease
Decreased yield
Change in age/size class structure
Extinction
Community
Decreased species diversity
Change in species composition
Decreased food web diversity
Decreased productivity
Increased algal blooms
Ecosystem
Decreased diversity of communities
Altered nutrient cycling
Decreased resilience
Three terms are commonly used to describe the mechanism by which a contaminant accumulates
in living tissues. The term "bioconcentration" refers to the accumulation of a chemical that occurs as a
result of direct contact of an organism with its surrounding medium (e.g., uptake by a fish from water
through the gills and epithelial tissue or uptake by earthworms from soil through the skin) and does not
include the ingestion of contaminated food. The term "bioaccumulation" refers to the net uptake of a
contaminant from all possible pathways and includes the accumulation that may occur by direct exposure
to contaminated media as well as uptake from food. The term "biomagnification" refers to the increase in
chemical concentration in organisms at successively higher trophic levels as a result of the ingestion of
contaminated organisms at lower trophic levels. Mercury is known to bioconcentrate, bioaccumulate and
biomagnify. In fact, mercury is one of the few metals that is known to biomagnify in aquatic food webs.
Different numerical factors are used to estimate the extent to which a contaminant
bioconcentrates, bioaccumulates and biomagnifies.
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• The bioconcentration factor (BCF) is the ratio of a substance's concentration in tissues
(generally expressed on a whole-body basis) to its concentration in the surrounding
medium (e.g., water or soil) in situations where an organism is exposed through direct
contact with the medium.
• The bioaccumulation factor (BAF) is the ratio of a substance's concentration in tissue to
its concentration in the surrounding medium (e.g., water or soil) in situations where the
organism is exposed both directly and through dietary sources.
• The biota-sediment accumulation factor (BSAF) is a specialized form of the BAF that
refers to the chemical concentration in an aquatic organism divided by that in surficial
(aquatic) sediments. To date it has been applied only to bioaccumulative organic
compounds, but in principal it could be applied to mercury also. When applied to
organic compounds, chemical concentrations in tissues and sediment are generally
normalized for lipid content and organic carbon content, respectively.
• The predator-prey factor (PPF, also known as the biomagnification factor, or BMP) is the
factor by which a substance's concentration in the organisms at one trophic level exceeds
the concentration in the next lower trophic level. For example, the PPF for mercury at
trophic level 4 equals the observed mercury concentration in trophic level 4 organisms
divided by mercury concentration in trophic level 3 organisms.
• The food chain multiplier (FCM) is the factor by which the BAF of a substance at
trophic level 2 or higher exceeds the BCF at trophic level 1. Implied by this definition is
the assumption that organisms at trophic level 1 are at or near chemical equilibrium with
their environment.
Although generally developed for individual organisms, BAF, BSAF, PPF and FCM values can
also be viewed as trophic-level specific. Depending on environmental levels of mercury, sufficient
mercury may accumulate in organisms at one or more trophic levels to produce adverse effects at the
individual, population, community or ecosystem level.
Mercury accumulates in an organism when the rate of uptake exceeds the rate of elimination. All
forms of mercury can accumulate to some degree; however, methylmercury generally accumulates to a
greater extent than other forms. Methylmercury is absorbed into tissues quickly and becomes
sequestered due to covalent reactions with sulfhydryl groups in proteins and other macromolecules (see
Section 4 of this Volume for more detail). Inorganic mercury can also be absorbed but is usually taken
up at a slower rate and with lower efficiency than methylmercury. Elimination of methylmercury takes
place very slowly resulting in tissue half-lives (the time required for half of the mercury in the tissue to
be eliminated) ranging from months to years (Westermark et al., 1975). Elimination of methylmercury
from fish is so slow that long-term reductions of mercury concentrations in fish are often due mainly to
growth of the fish. In comparison, other mercury compounds are eliminated relatively quickly, resulting
in reduced levels of accumulation (Eisler, 1987).
Methylmercury and total mercury concentrations both tend to increase in aquatic organisms as
the trophic level in aquatic food webs increases. In addition, the proportion of total mercury that exists
as methylmercury generally increases with trophic level (May et al., 1987; Watras and Bloom, 1992;
Becker and Bigham, 1995; Hill et al., 1996; Tremblay et al., 1996; Mason and Sullivan, 1997).
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Accordingly, mercury exposure and accumulation is of particular concern for animals at the highest
trophic levels in aquatic food webs and for animals that feed on these organisms.
2.3.1.1 Field-derived BAFs, B SAFs, and PPFs
In this section, BCFs for organisms that occupy the base of aquatic food chains are reviewed,
along with BSAFs for fish and PPFs for avian and mammalian piscivores. BSAFs for earthworms and
benthic invertebrates are also presented because both represent possible vectors for mobilization of
sediment-associated mercury and subsequent translocation to wildlife. Median BAFs for fish occupying
trophic levels 3 and 4 are derived in Volume III, Appendix D. A summary of these calculations is
presented in Chapter 5 of this Volume.
Recent studies with marine phytoplankton suggest that mercury accumulation at the lowest levels
of aquatic food webs is controlled largely by the availability of neutral mercury complexes (primarily
HgCl2 and CH3HgCl) (Mason et al., 1996). Factors that can alter the concentration of these neutral
species include pH, chloride concentration, and the amount of dissolved organic material. Additionally,
it was found that most (63%) of the methylmercury that diffuses into phytoplankton becomes localized in
the cytoplasm. Copepods assimilated almost all of this cytoplasmic mercury when they were fed
contaminated phytoplankton. In contrast, inorganic mercury was concentrated predominantly (91%) in
cell membranes and was poorly (15%) assimilated. Research on a Lake Michigan food web suggests that
similar mechanisms may be responsible for controlling mercury uptake by freshwater phytoplankton
(Mason and Sullivan, 1997). Such studies are extremely important, since mercury uptake at the lowest
trophic levels is likely to be the single most important determinant of levels achieved by fish and
piscivorous wildlife.
Data published by Becker and Bigham (1995) can be used to calculate a methylmercury BCF of
107,000 for phytoplankton in Onondaga Lake. Corrected for the (assumed) percentage of methylmercury
in lake water (8%) and phytoplankton (24%), these data give a total mercury BCF of approximately
36,000. Using total mercury data reported by Mason and Sullivan (1997), and assuming that dry weight
is 10% of wet weight, a BCF of about 7,000 can be calculated for phytoplankton in Lake Michigan.
BCFs (total mercury basis, approximated from Hg2+ data) ranging from about 2,000 to 40,000 were
reported for periphyton collected from two streams in eastern Tennessee (Hill et al., 1996). A total
mercury BCF of approximately 20,000 was reported for phytoplankton in a northern Wisconsin lake
(reference basin; Watras and Bloom, 1992). Expressed on a methylmercury basis, the BCF for
phytoplankton in the same Wisconsin lake was approximately 90,000.
BAFs for zooplankton, expressed as ratios of total mercury, can be calculated from data
presented by Sorenson et al. (1990), Lindqvist (1991) and Mason and Sullivan (1997). Respectively, the
calculated values are 35,600, 285,000, and 3,100. A BAF of approximately 56,200 was reported for
zooplankton by Watras and Bloom (1992; reference basin). Expressed on a methylmercury basis, the
BAF measured by Watras and Bloom (1992) was about 1,000,000. Total mercury BAFs estimated for
zooplankton in 12 northern Wisconsin lakes ranged from about 4,800 to 270,000 (Back and Watras,
1995). BAFs expressed on a methylmercury basis for the same 12 lakes ranged from about 11,000 to
12,600,000. Much of this variability appeared to be correlated (inversely) with lakewater DOC content.
Work conducted by Slotten et al. (1995) and Suchanek et al. (1997) suggests that mercury
bioaccumulation by zooplankton may vary seasonally, although in both of these studies data
interpretation was complicated by the presence of mercury point sources. Becker and Bigham (1995)
reported a methylmercury BAF of approximately 87,000 for zooplankton in Onondaga Lake, which has
also received substantial mercury inputs from local point sources.
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To date, BSAFs for mercury in aquatic biota have been estimated by only a few authors (e.g.,
Tremblay et al., 1996); however, a substantial amount of data exists that allows such calculations to be
made. Hildebrand et al. (1980) observed a linear relationship between total mercury in sediment and that
in benthic invertebrates. A BSAF of approximately 0.4 is obtained from the slope of this relationship
(after expressing benthos data on a dry weight basis). The relationship between total mercury in fish
(rock bass and hog suckers) and that in sediments was reported by Hildebrand et al. (1980) to be
logarithmic. Taking as an average a fish tissue value of 4.0 //g/g (dry weight; converted from 1.0 //g/g
wet weight) and solving for the sediment concentration yields a value of 2.78 //g/g. The BSAF is equal
to the ratio offish and sediment values, or approximately 1.4. Total mercury data presented by Sorenson
et al. (1990) yield BSAFs (dry weight basis) of approximately 2.0 and 10.1 for zooplankton and northern
pike, respectively. Data presented by Wren and MacCrimmon (1986) allow BSAFs to be calculated for
two Ontario lakes that differed considerably with respect to total mercury residues in biota. In both lakes
BSAFs (dry weight basis) were very similar, ranging from approximately 5.1 (clams) to 24.0 (northern
pike) in the less contaminated of the two lakes, and 3.4 (clams) to 27.1 (pike) in the other system. Using
the mid-range of values reported by Lindqvist (1991), BSAFs (dry weight basis) of approximately 2.2,
17.2, 17.7, and 45.7 are obtained for zooplankton, macroinvertebrates, yellow perch (small and large),
and northern pike (large and small), respectively. Boyer (1982) reported total mercury concentrations in
fish and sediments from several locations on the upper Mississippi River. Expressed on a dry weight
basis, these data yield BSAFs ranging from 2.5 to greater than 50. Using "canal median" total mercury
data from Stober et al. (1995), a BSAF (wet weight basis) of about 0.6 can be calculated for mosquitofish
in the Florida Everglades region. This value would increase somewhat if expressed on a dry weight
basis. Saouter et al. (1993) exposed mayflies for 10 days to methylmercury in sediment and obtained a
BSAF (wet weight basis) of 4.0. A BSAF for zooplankton of about 1.4 (dry weight basis) can be
calculated from mean total mercury data obtained in a survey of 73 Canadian lakes (Tremblay et al.,
1995). Tremblay et al. (1996) reported the BSAF (dry weight basis) for aquatic insects to be about 3.0
when calculated using total mercury data, and from 6.0 to 22.0 when expressed on a methylmercury
basis.
In summary, BSAFs calculated for total mercury in aquatic biota ranged from 0.4 to about 50
and, within a given system, appeared to increase with trophic level. In terms of both magnitude and the
increase with trophic level, BSAFs for mercury are similar to BSAFs reported for hydrophobic organic
compounds (lipid/carbon normalized). It could be hypothesized, therefore, that similar processes are at
work. This is unlikely, however, since bioaccumulation of organic compounds is largely a partitioning
process, while for mercury the chemical interactions tend to more specific, often involving the formation
of covalent bonds. Because mercury does not partition into lipid, normalization for lipid content makes
little sense. The existence of strong relationships between mercury and organic carbon content (see for
example Wiener et al., 1982; Lindqvist, 1991) suggests, however, that some type of sediment carbon
normalization may be appropriate. A single study by Tremblay et al. (1996) suggests that within a given
system BSAFs expressed on a methylmercury basis will exceed values calculated using total mercury
data. While likely at higher trophic levels, additional data at lower trophic levels are needed to determine
the extent to which this observation may be generalized.
Limited data are available that allow calculation of BSAFs for earthworms. The concentration of
mercury in earthworms collected from an uncontaminated field site was 27.1 times that of soil and 6.9
times that of decaying vegetation (dry weight basis) (Siegel et al., 1975). In a 12 week laboratory
exposure, earthworms accumulated an average of 21.3 times the mercury concentration of the soil to
which they were exposed (including control and treatment groups) (Beyer et al., 1985).
2-15
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PPFs for piscivorous birds and mammals are difficult to determine accurately because residue
data cannot be attributed with any specificity to residues in a particular prey item; feeding observations
for the species in question are rarely reported in these studies. Where possible, PPFs were estimated by
constructing rough averages of residue values in prey items occupying similar trophic levels. For this
analysis, mink, mergansers, and loons were assumed to feed exclusively at trophic level 3. River otters
were assumed to feed at trophic levels 3 (80%) and 4 (20%).
PPFs calculated for piscivorous birds from breast muscle mercury levels ranged from 1.7 for the
hooded merganser (Vermeer et al., 1973) to 7.7 for the herring gull (Wren et al., 1983). Intermediate
values were calculated for the common merganser (2.5) (Vermeer et al., 1973) and loon (6.8) (Wren et
al., 1983). Data collected by Wren et al. (1996) from Muskota, Ontario, permit PPFs to be calculated for
mink and otter. Calculated from liver residues, these data yield PPFs of 6.2 and 4.7, respectively.
Muscle tissue data reported in the same study yield PPFs of 8.1 and 1.7 for mink and otter, respectively.
A PPF of 3.0 (muscle tissue basis) can be calculated for otters from Tadenac Lake, Ontario (Wren et al.,
1993). Averaged across sampling locations and assuming consumption of the fish species analyzed,
PPFs of 2.7 (muscle basis) and 5.7 (liver basis) may be estimated for otters in Georgia (Halbrook et al.,
1994).
In a study designed specifically to assess the degree of mercury biomagnification in piscivorous
mammals, liver residues were paired by location with residue levels in fish (Foley et al., 1988). These
data yield PPFs of 3.9 and 3.4 for mink and otter, respectively. Kucera (1983) reported that the ratio of
mercury concentrations in mink and otter to that in predatory fish in the same region was about 10. A
similar conclusion was reached by Francis and Bennett (1994) for otters in northern Michigan, based
upon an analysis of liver tissues. Thus, it can be shown that mercury biomagnifies in piscivorous
wildlife, although the extent of this biomagnification is less than that typically reported for persistent
organic compounds. For example, data reported by Braune and Norstrom (1989) suggest that the PPF for
PCBs in piscivorous birds can approach 100. These observations have led to the suggestion that mercury
is eliminated by piscivorous wildlife in feathers and fur, and perhaps also via a demethylation pathway
(Wren et al., 1986); however, extensive elimination would be expected to result in PPFs of 1 or less.
2.3.1.2 Mercury Residues in Fish
Consistent with a need to characterize the exposure of piscivorous avian and mammalian wildlife
to mercury, an effort was made to estimate "national average" values for mercury in fish at trophic levels
3 and 4. The calculation of true "national average" values would require the collection of a large number
of samples from randomly selected lakes and rivers. Instead, the published literature contains a number
of papers in which mercury concentrations are given for relatively small numbers offish from restricted
geographical regions. Many of these studies were initiated due to known or suspected problems with
mercury in the region of interest. Thus, a sample developed from a compilation of these data could be
biased toward the high-end of the distribution of mercury concentrations nationwide.
A survey of the literature revealed only three nationwide fish collection efforts that used
consistent sampling and mercury measurement techniques. In a study conducted by U.S. EPA, samples
were obtained from 374 sites across the U.S. (U.S. EPA, 1992b; Bahnick et al., 1994). Site selection was
based partly on proximity to suspected point and non-point pollution sources, and a majority of sites were
located on streams and rivers. Additionally, fish were collected from 35 "remote" sites that were thought
to provide background pollutant concentrations in fish. Whole-body mercury levels were determined for
bottom feeders, and mercury levels in fillets were analyzed for game fish. The maximum mercury level
detected was 1.80 //g/g wet weight, and the mean across all fish and sites was 0.26 //g/g (see Table 2-2).
2-16
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The highest values were detected in piscivorous game fish (trophic level 4), including walleye, bass and
northern pike. Lower levels were found in herbivores (e.g., carp and sucker), omnivores (e.g., catfish),
and species that prey extensively on insects (e.g., trout and crappie). In general, this sampling effort did
not address fish that occupy trophic level 3 (forage fish).
Table 2-2
Nationwide Average of Mercury Residues in Fish
Fish Species
Carp
Sucker (White, Redhorse and Spotted)
Catfish (Channel and Flathead)
Bass (Largemouth, Smallmouth and White)
Walleye pike
Northern pike
Crappie
Brown Trout
Mean of All Fish Sampled
Mercury Concentration Averaged Across
Sampling Sites (//g/g wet weight)
0.11
0.17
0.16
0.38
0.52
0.31
0.22
0.14
0.26
Source: Bahnick et. al., 1994.
Mercury levels in fish were measured at over 100 sites as part of the National Contaminant
Biomonitoring Program (NCBP) administered by the U.S. Fish and Wildlife Service. Two compilations
of NCBP mercury data have been published. The first summarizes data collected from 1978-1981 (Lowe
et al., 1985). The second reports on data collected from 1984-1985 and draws comparisons with the
results
of the earlier study (Schmitt and Brumbaugh, 1990). As with the Bahnick et al. (1994) study, most of the
sampling sites were located on streams and rivers, many of which receive municipal and other waste. In
addition, similar species were collected, with an emphasis on large piscivores, herbivores and omnivores.
A review of these data suggests that piscivores accumulate more mercury than other fish species. Thus,
lake trout (mean concentration of 0.17 (ig/g) and largemouth bass (0.14 (ig/g) contained more mercury
than co-collected non-piscivorous species (0.07 and 0.09 (ig/g, respectively). The maximum mercury
concentration reported was 1.09 (ig/g, and the mean across all fish and sites was 0.11 (ig/g. Of
importance for calculating a "national average" mercury concentration in fish, Schmitt and Brumbaugh
(1990) reported that mercury levels in fish did not change between 1976 and 1984. Attention was
focused, therefore, on the Lowe et al. (1985) study because it comprised a larger number of individual
samples and because fish length and weight were also reported.
2-17
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An average mercury concentration in piscivorous fish analyzed by Bahnick et al. (1994) was calculated
from data presented by these authors (Table 3 in their report). For this Report, the following species were
classified as trophic level 4 piscivores: largemouth bass, smallmouth bass, walleye, brown trout, white bass, and
northern pike. The mean (± SD) of concentration data presented for these six species is 0.35 ± 0.13 (ig/g.
An average value for piscivores analyzed by Lowe et al. (1985) was estimated using data presented by
these authors (Appendix A in their report). Each value reported for a site and species represented a composite of
three to five fish. The criteria established for using a reported value were: (1) the species is a recognized
piscivore; (2) the average size of specimens comprising a sample was > 0.5 kg; and (3) the sampling site was
located in the contiguous 48 states. For this Report, the species identified as trophic level 4 piscivores were:
largemouth bass, smallmouth bass, striped bass, white bass, rock bass, northern pike, walleye, sauger, lake trout,
brown trout, rainbow trout, and northern squawfish. The mean (± SD) of all data presented for these twelve
species was 0.18 ± 0.19 (^g/g (N = 119), or just over one-half the concentration calculated using the Bahnick et al.
(1994) data.
A "national average" mercury concentration for trophic level 4 fish was estimated as the average of mean
values calculated using data from Bahnick et al. (1994) and Lowe et al. (1985). This value is 0.26 (ig/g. As
indicated above, neither of these nationwide sampling efforts adequately characterized mercury concentrations in
fish at trophic level 3. A "national average" for trophic level 3 was therefore estimated by dividing the average
mercury concentration in piscivorous fish by an appropriate predator-prey factor (PPF). A PPF for trophic level
4 (PPF4) can be estimated from existing field data. This calculation was made in Appendix D, Volume III of this
Report, resulting in a mean PPF4 of 4.9. Dividing this value into the average residue for trophic level 4 fish
yields a value for trophic level 3 of 0.052 //g/g.
The extent to which these "national average" estimates reflect the true population means at each trophic
level is unknown. A comparison of these values with published residues from a large number of studies suggests,
however, that they are "reasonable" and can be used in exposure assessments for piscivorous avian and
mammalian wildlife.
2.3.1.3 Mercury Residues in Avian and Mammalian Wildlife
A large volume of mercury residue data exists for both avian and mammalian wildlife that cannot be
directly related to mercury concentrations in water or sediment. Nevertheless, these data are of considerable
value because they indicate the range of mercury concentrations that can be expected in animals inhabiting both
contaminated and uncontaminated environments. A comparison of these residues with those obtained from
laboratory dose-response studies provides additional information, including the extent of difference between
"natural background" residues and those that are associated with toxic effects. Emphasis is placed on piscivorous
birds and mammals living in association with freshwater ecosystems. Data are also provided for the tree swallow
due to its link to aquatic sediments through consumption of emergent insects.
Mercury residues in tissues from birds are given in Table 2-3. The birds represented in this table include
animals taken from polluted environments and individuals collected from environments for which there were no
known point sources. This table is not intended to be an exhaustive compilation of measured residues, but
instead illustrates the range of values encountered in environmental sampling efforts. Residues that, in the
opinion of the cited author, were associated with toxic effects are noted.
Factors contributing to the accumulation of mercury in wild birds are reviewed by Scheuhammer (1987,
1991). The interpretation of residue data is complicated by the likelihood that mercury distribution in tissues
varies among species, and perhaps also among individuals of a single species, depending upon age, sex, diet, and
other factors. Nevertheless, several generalizations can be attempted. Mercury levels in feathers of birds
experimentally dosed with methylmercury generally exceed levels in muscle, liver and kidney by a factor of four
or more (Heinz, 1976a; Stickel et al., 1977; Finley and Stendell, 1978), and it has been suggested that in free-
living birds greater than 50% of the total body burden of mercury may be
2-18
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Table 2-3
Mercury Residues in Tissues of Piscivorous Birds
Species
Bald eagle
Bald eagle
Bald eagle
Bald eagle
Common loon
Common loon
Common loon
Common loon
Wood stork
Bald eagle
Bald eagle
Common loon
Common loon
Common tern
Herring gull
Mercury
(ug/g fresh weight)
13.0-21.0
3.7-20.0
0.1-34.7
0.8-14.3
8.7
2.7
11.0-18.0
2.0-5.0
1.9
0.15-0.29
0.07-0.41
0.40-1.10
2.0-3.0
3.6
2.3-15.8
Tissue
feathers
feathers
feathers
feathers
feathers
feathers
feathers
feathers
feathers
eggs
eggs
eggs
eggs
eggs
eggs
Sampling Location
Great Lakes region
Great Lakes region
N. Central Florida
N. Central Florida
Minnesota lakes
Minnesota lakes
Wisconsin lakes
Wisconsin lakes
South Florida
British Columbia
15 States (USA)
Wisconsin lakes
Northwestern Ontario
Northwestern Ontario
Clay Lake, Ontario
Comments
adults
nestlings
adults
nestlings
adults
juveniles
adults
juveniles
juveniles
polluted by point
source; LOAEL -
reproduction
polluted by point
source; LOAEL -
reproduction
polluted by point
source, no adverse
effects
Reference
1
1
2
2
3
3
4
4
5
6
7
4
8
9
10
2-19
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Table 2-3 (continued)
Mercury Residues in Tissues of Piscivorous Birds
Species
Wood stork
Tree swallow
Common loon
Common loon
Common loon
Great White Heron
Great Blue Heron
Great Blue Heron
Common loon
Common goldeneye
Common merganser
Hooded merganser
Herring sull
Mercury
(ug/g fresh weight)
0.7
0.04 - 0.08
1.6-47.7
9.5-90.0
5.6
0.6-59.4
0.2-7.3
0.1 -74.5
0.2-6.9
0.9-19.4
4.4-13.1
3.9-17.6
0.7-4.0
Tissue
eggs
eggs
liver
liver
liver
liver
liver
liver
breast muscle
breast muscle
breast muscle
breast muscle
breast muscle
Sampling Location
South Florida
Lower Great Lakes
Northwestern Ontario
Wisconsin lakes
Minnesota lakes
South Florida
South Florida
South Florida
Northwestern Ontario
Clay Lake, Ontario
Clay Lake, Ontario
Clay Lake, Ontario
Tadenac Lake, Ontario
Comments
consume emergent
aquatic insects
LOAEL -
reproduction
adults found dead
adults found injured
mixed age birds
found dead
nestlings
fledglings/young
adults
polluted by point
source
polluted by point
source
polluted by point
source
polluted by point
source
Reference
11
12
8
4
o
J
13
14
14
8
10
10
10
15
2-20
-------
Table 2-3 (continued)
Mercury Residues in Tissues of Piscivorous Birds
Species
Common loon
Mercury
(ug/g fresh weight)
1.5
Tissue
breast muscle
Sampling Location
Tadenac Lake, Ontario
Comments
Reference
15
References:
1. Bowerman et al., 1994; range of means across sampling locations.
2. Wood et al., 1996; range of contour feathers recovered at nest sites. Means for nestlings and adults were 3.2 and 6.0, respectively.
3. Ensoretal., 1992; mean of birds caught by nightlighting.
4. Belant and Anderson, 1990; range of individual values. Means for feathers (adult and juvenile), eggs and liver were 14.8,4.0, 0.64 and 40.9, respectively.
5. Burger et al., 1993; mean value.
6. Elliott et al., 1996; range of means across sampling locations
7. Wiemeyer et al., 1993; range of means across sampling locations (collected after failure to hatch).
8. Barr, 1986; range of individual values. Means for liver and muscle were 13.0 and 2.3, respectively.
9. Fimreite, 1974.
10. Vermeer et al., 1973; range of individual values. Means for goldeneye, common merganser and hooded merganser were 7.8, 6.8 and 12.3, respectively.
11. Fleming et al., 1984; mean value.
12. Bishop et al., 1995; range of individual values, mean = 0.07.
13. Spalding et al., 1994; range of individual values. Means for birds that died of acute and chronic causes were 1.8 and 9.8, respectively.
14. Sundlof et al., 1994; range of individual values. Means for small nestlings, large nestlings and adults were 0.3,1.5 and 6.6, respectively.
15. Wren et al., 1983; gull data are reported as the range of individual values, mean = 1.7.
2-21
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present in the plumage (Braune and Gaskin, 1987). Natural background levels of mercury in feathers of non-
piscivorous raptorial birds are thought to range from 1-5 //g/g (dry weight); however, this may vary within and
among species depending upon the type of feather sampled, molting frequency and time to last molt. Changes in
feather mercury levels that accompany growth and development suggest that in seabirds molting may be an
efficient means of eliminating mercury (Becker et al., 1994; Burger et al, 1994). Comparable studies have not
yet been conducted with birds that live in freshwater ecosystems.
Tissue levels of mercury associated with toxic effects in birds appear to exceed those in birds inhabiting
relatively uncontaminated environments by a factor often or less (see Sections 2.3.2 and 2.3.3 for additional
details). This observation is consistent with data for other environmental media (e.g., water, sediments, and fish),
which evidence similar differences between natural "background" levels of mercury and those which cause
significant environmental damage. Owing to their ease of collection, the analysis of bird feathers and eggs has
been suggested as a means of identifying species that are at risk due to mercury. This suggestion has particular
merit in view of the natural variation in mercury levels in the fish upon which these animals prey. Mercury
residues in tissues also tend to integrate variations in mercury uptake and elimination due to changes in dietary
habits, migration, egg production, etc.
The abundance of mercury residue information for mammals reflects the availability of specimens as a
byproduct of commercial trapping. Thus, residue data are available for wild muskrat, beaver, fox, weasel,
bobcat, marten, fisher, wolf, raccoon, opossum, mink and river otter. Data are also available for a number of
game species, including squirrels, rabbits, caribou, moose, deer, elk, mountain goat and bear. An extensive
compilation of these data is provided by Wren (1986), along with a review of tissue levels in both wild and
laboratory animals that have been associated with toxic effects. Some of the data from this compilation are
presented in Table 2-4, as well as more recent information. Emphasis was placed on piscivorous species due to
the exposure of these animals from consumption of contaminated fish. Data from beaver and muskrat have also
been included, both to provide a general comparison of aquatic-based species and because, in several studies,
data were available for piscivores and herbivores from the same waterbody. Emphasis was also placed on
residues in fur and liver. This was done for two reasons: (1) high residues have been found in the liver and
kidney; however, there are more reported values for liver and (2) fur, like feathers, has been suggested as a way
of non-invasively determining the residue status of wild animals and of identifying areas where animals may be at
risk due to mercury intoxication. Finally, data from raccoons are included in Table 2-4 because they are
suspected of contributing to mercury exposure in the Florida panther.
In general, the rank order of mercury residues in tissues from wild mink and otter is: liver = kidney >
muscle > brain. Levels in fur relative to those in other tissues are variable but, in most cases, are higher than
those in liver. Comparisons between residues in wild animals with those in animals experimentally dosed with
mercury appear to be complicated by kinetics-based differences in disposition. Thus, Wobeser et al. (1976b)
reported that mercury levels in the fur of experimentally dosed mink were low (1.5 //g/g) relative to
concentrations in liver (24.3 //g/g), kidney (23.1 //g/g), muscle (16.0 //g/g) or brain (11.9 //g/g). A similar pattern
of distribution was reported for mink by Aulerich et al. (1974). In contrast, mercury levels in the fur of an
individual mink found dying of mercury poisoning were higher than concentrations in any other tissue (see Table
2-4) (Wobeser and Swift, 1976). Apparently, the length of time over which a dose is obtained dictates its
distribution, with redistribution from well-perfused organs (liver and kidney) to storage tissues (fur and muscle)
slowly taking place during lifetime exposures. These observations suggest that comparisons between mercury
residues in wild and experimental animals should be limited to consideration of well-perfused tissues. More
valid comparisons can be made between apparently unaffected wild animals and wild animals that have died from
mercury poisoning.
2-22
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Table 2-4
Mercury Residues in Tissues of Piscivorous Mammals
Species
Otter
Otter
Otter
Mink
Mink
Mink
Raccoon
Muskrat
Beaver
Otter
Otter
Otter
Otter
Otter
Mercury
(ug/g fresh weight)
6.5 (max. = 63.2)
47.0
15.2-25.6
10.7 (max. = 17.3)
7.6 (max. = 41.2)
34.9
4.4
0.06
0.03
5.1-9.2
1.7-3.4
2.4-4.5
0.3-3.0
0.9-3.5
Tissue
fur
fur
fur
fur
fur
fur
fur
fur
fur
liver
liver
liver
liver
liver
Sampling Location
Wisconsin
Clay Lake, Ontario
Georgia
Georgia
Wisconsin
Saskatchewan
S. Florida
Wisconsin
Wisconsin
Georgia
Manitoba
Winnipeg R.
Louisiana
Ontario
Comments
polluted by point
source; death due to
poisoning
polluted by point
source; death due to
poisoning
males and females
males and females;
polluted by point
source
residues correlated
with acidity
Reference
1
2
3
4
1
5
6
1
1
3
7
7
8
9
2-23
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Table 2-4 (continued)
Mercury Residues in Tissues of Piscivorous Mammals
Species
Otter
Otter
Otter
Otter
Mink
Mink
Mink
Mink
Mink
Raccoon
Raccoon
Muskrat
Beaver
Mercury
(ug/g fresh weight)
0.8-3.2
1.3-2.3
96.0
3.3 (max. = 23.6)
0.4- 1.7
2.1 (max. = 17.4)
0.1-2.6
58.2
0.9-2.9
2.0
1.5-24.0
<0.02
0.04
Tissue
liver
liver
liver
liver
liver
liver
liver
liver
liver
liver
liver
liver
liver
Sampling Location
N. Michigan
New York
Clay Lake, Ontario
Wisconsin
Manitoba
Wisconsin
Ontario
Saskatchewan
New York
Wisconsin
S. Florida
Wisconsin
Wisconsin
Comments
polluted by point
source; death due to
poisoning
residues correlated
with acidity
polluted by point
source; death due to
poisoning
Reference
10
11
5
1
7
1
9
5
11
1
12
1
1
References:
1. Sheffy and St. Amant, 1982; mean value.
2. Wren, 1985; one individual.
3. Halbrook et al., 1994; range of means across sampling locations.
2-24
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Table 2-4 (continued)
Mercury Residues in Tissues of Piscivorous Mammals
4. Cumbie, 1975; mean value.
5. Wobeser and Swift, 1976; one individual.
6. Bigler et al, 1975; mean value.
7. Kucera, 1983; Manitoba data are reported as the range of means across sampling locations. Data from the Winnipeg river are reported as a mean value.
8. Beck, 1977; range of means across sampling locations.
9. Wren et al., 1986; range of means across sampling locations.
10. Francis and Bennett, 1994; range of individual values.
11. Foley etal., 1988; range of means across sampling locations.
12. Roelke et al., 1991; range of means across sampling locations.
2-25
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An examination of Table 2-4 suggests that mercury residues in tissues from mink and otters from
Wisconsin (Sheffy and St. Amant, 1982) approached, and in several cases even exceeded, those of the "naturally"
poisoned animals. High mercury residues in fur were also reported for river otters trapped in several locations
across Georgia (Halbrook, 1994). The livers of raccoons captured in South Florida are also notably high in
mercury content (Roelke et al., 1991).
2.3.2 Individual Effects
Exposure to mercury can cause adverse effects in a wide variety of organisms, including plants, fish,
aquatic invertebrates, birds and mammals. In this section, we review information on exposure levels that can
cause adverse effects in these groups.
2.3.2.1 Individual Effects on Plants
Effects of mercury on aquatic plants include death and sublethal effects. Sublethal effects include plant
senescence, growth inhibition, decreased chlorophyll content, decreased protein and RNA content, inhibited
catalase and protease activities, inhibited and abnormal mitotic activity, increased free amino acid content,
discoloration of floating leaves, and leaf and root necrosis (Boney, 1971; Stanley, 1974; Muramoto and Oki,
1984; Mhatre and Chaphekar, 1985; Sarkar and Jana, 1986). The level of mercury that results in toxic effects
varies greatly among aquatic plants, as illustrated in Table 2-5.
Table 2-5
Toxicity Values for Aquatic Plants
Water Type
Fresh Water
Salt Water
Hg2+(HgClorHgN03)
(Mg/L)
Low End
53 (alga)
10 (alga)
High End
3,400 (submerged
aquatic vegetation)
160 (seaweed)
Methylmercury
(Mg/L)
Low End
0.8 (alga)
Not available
High End
6.0 (alga)
Not available
Source: U.S. EPA, 1985.
Mercury can also cause death and sublethal effects in terrestrial plants. Sublethal effects on terrestrial
plants include decreased growth, leaf injury, root damage, inhibited root growth and function, hampered nutrient
uptake, chlorophyll decline and reduced photosynthesis (Schlegel et al., 1987; Lindqvist, 1991; Godbold, 1991).
Methylmercury is more toxic to terrestrial plants than Hg2+. One to ten nM (nanomolar) mercuric
chloride or methyl mercuric chloride (provided in a nutrient solution) can inhibit root elongation in spruce
seedlings. However, methyl mercuric chloride has a greater effect than mercuric chloride at the same
concentration (Godbold, 1991). Sublethal effects, including decreased transpiration, decreased chlorophyll
concentration, partial stomatal closure, and reduced photosynthesis, occurred at nutrient solution concentrations
of 10 nM methyl mercuric chloride (Schlegel et al., 1987).
2-26
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2.3.2.2 Individual Effects on Fish and Aquatic Invertebrates
The toxicity of mercury to fish has been reviewed by Eisler (1987) and more recently by Wiener and
Spry (1995). The highest mercury concentrations in fish generally occur in the blood, spleen, kidney and liver,
and may exceed those in muscle by a factor of 2-10 (McKim et al., 1976; Olson et al, 1978; Ribeyre and
Boudou, 1984; Boudou and Ribeyre, 1985; Harrison et al., 1990; Niimi and Kissoon, 1994). Owing to the size of
these organs relative to that of other tissues, however, most of the mercury contained in a fish at any given time
is associated with muscle tissue.
The toxicity of mercury varies, depending on the fish's characteristics (e.g., species, life stage, age, and
size), environmental factors (e.g., temperature, salinity, dissolved oxygen content, hardness, and the presence of
other chemicals), and the form of mercury available. In particular, early life stages (especially of salmonids)
exhibit greater sensitivity to elevated metal concentrations than later life stages. The toxicity of Hg2+ compounds
to salmonids and catfish tends to increase with temperature (see Table 2-6). Organomercury compounds, such as
methylmercury, generally are much more acutely toxic than Hg2+ to aquatic organisms.
Table 2-6
Mercury Toxicity Increases With Temperature
Temperature (°C)
LC50 (Mg/l)
Rainbow Trout with HgCl
5
10
15
400
280
220
Juvenile Catfish with Phenylmercuric Acetate
10
16.5
24
1,960
1,360
233
Source: U.S. EPA, 1985.
Effects of mercury on fish include death, reduced reproduction, impaired growth and development,
behavioral abnormalities, altered blood chemistry, impaired osmoregulation, reduced feeding rates and predatory
success, and effects on oxygen exchange. LC50 values for fish range from 30 //g/L for guppies to 1,000 //g/L for
the Mozambique tilapia (U.S. EPA, 1985). Symptoms of acute mercury poisoning in fish include increased
secretion of mucous, flaring of gill opercula, increased respiration rate, loss of equilibrium and sluggishness.
Signs of chronic poisoning include emaciation, brain lesions, cataracts, inability to capture food, abnormal motor
coordination and various erratic behaviors (e.g., altered feeding behavior) (Weis and Weis, 1989, 1995).
It is generally thought that toxic effects are unlikely to occur in fish in the environment, except in the
case of point source pollution discharges. An accumulating body of evidence, however, suggests that histological
changes and effects on behavior, reproduction, and development can occur at water concentrations as low as 0.1
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//g/L (Wiener and Spry, 1995), or about two orders of magnitude higher than those generally associated with
unpolluted systems. In a recent study, juvenile walleye were exposed to methylmercury in the diet at
concentrations of 0.1 and 1.0 (ig/g (Friedmann et al., 1996). Growth, development and hormonal status were
impacted at the high dose level. No effects were seen at the lower dose level or in controls. The high dose level
used in this study is within a factor of 10 of values reported for macroinvertebrates and forage fish from mercury-
impacted "pristine" lakes (i.e., no known point source) in both Canada and the U.S. (Allard and Stokes, 1989;
Sorenson et al., 1990; Watras and Bloom, 1992).
Levels of mercury that induce toxic effects in aquatic invertebrate species vary. For Hg2+, acute values
(LC50) for invertebrates range from 2.2 //g/L for the cladoceran Daphniapulex to 2,000 //g/L for the larval forms
of three insects (U.S. EPA, 1985). Examples of some specific toxicity values for fish and aquatic invertebrates
are provided in Table 2-7.
2.3.2.3 Individual Effects on Birds
Methylmercury has been shown to be more toxic to birds than inorganic mercury. Mercury poisoning in
birds is characterized by muscular incoordination, falling, slowness, fluffed feathers, calmness, withdrawal,
hyperactivity, hypoactivity and eyelid drooping (reviewed by Eisler, 1987; Fimreite, 1979; Scheuhammer, 1987,
1991). Acute oral toxicity studies using methylmercury yielded LD50 values ranging from 2.2 to 23.5 //g/g for
mallards (Anas platyrhynchos}, 11.0 to 27.0 //g/g for quail (Coturnix) and 28.3 //g/g for northern bobwhite
(Colinus virginianus). Some bird kills have occurred, generally due to ingestion of mercury-based fungicides
applied to grain. Whole-body residues of mercury in acutely poisoned birds usually exceed 20 //g/g fresh weight
and have been found up to 126 //g/g. Mercury levels observed in such cases are generally highest in the brain,
followed by the liver, kidney, muscle and carcass.
Sublethal effects of mercury on birds include liver damage, kidney damage, neurobehavioral effects,
reduced food consumption, weight loss, spinal cord damage, effects on enzyme systems, reduced cardiovascular
function, impaired immune response, reduced muscular coordination, impaired growth and development, altered
blood and serum chemistry, and reproductive effects (Eisler, 1987; Scheuhammer, 1987, 1991; MDNR, 1993).
Reproductive and behavioral effects are the primary concern, however, and can occur at dietary concentrations
well below those that cause overt toxicity.
Scheuhammer (1991) concluded that on the basis of laboratory dose-response studies (Heinz, 1976a;
Finley and Stendell, 1978), piscivorous birds consuming diets containing >1 //g/g (dry weight) methylmercury in
their diet (approximately 0.25 //g/g wet weight) will accumulate >20 //g/g (dry weight) in their feathers. Similar
levels in both spiked diets (Heinz, 1974, 1976a,b, 1979) and natural prey sources (Barr, 1986) have been shown
to be toxic to birds. Thus, it appears that mercury levels in feathers exceeding 20 //g/g should be interpreted as
evidence for possible toxic effects. Eisler (1987) recommended that 5.0 //g/g fresh weight in feathers be used as
a criterion for the protection of birds.
Tissue mercury concentrations that are associated with toxicity in birds are remarkably similar despite
differences in species, dietary exposure level and length of time necessary to produce the effect (Scheuhammer,
1991). Frank neurological signs are generally associated with brain mercury concentrations of 15 //g/g (wet
weight) or higher and 30 //g/g or more in liver and kidney. Liver mercury concentrations of 2-12 //g/g (wet
weight) were associated with reproductive impairment in adult pheasants and mallard ducks (Fimreite, 1971;
Heinz, 1976a,b). Mortality was observed in newly hatched ducklings
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Table 2-7
Toxicity Values for Fish and Aquatic Invertebrates
Organism
Hg2+(HgClorHgNCg(,ag/L)
Methylmercury (/zg/L)
ACUTE (LC50)
Fresh water
invertebrates
Fresh water fish
Rainbow trout
Fresh water AWQCa
Salt water
invertebrates
Salt water fish
Salt water A WQCa
2.2 (cladoceran) to 2,000 (insect larvae)
30 (guppy) to 1,000 (tilapia)
155 to 420
Not available
Not available
24 to 84
2.4 (total mercury)
3.5 (mysid) to 400 (soft clam)b
36 (juvenile spot) to 1,678 (flounder)0
Not available
51.1 (mummichog)
2.1 (total mercury)
CHRONIC
Fresh water
invertebrates
Fresh water fish
Fresh water AWQCa
Salt water
invertebrates
Salt water AWQCa
0.96 (cladoceran) to 1.287 (cladoceran)
< 0.23 (minnow) to < 0.26 (minnow)
< 0.04 (cladoceran)
0.29 (brook trout) to 0.93 (brook trout)
0.012 (total mercury)
1.131 (mysid)
Not available
0.025 (total mercury)
a AWQCs are designed to be protective of the aquatic community as a whole.
b As cited in U.S. EPA, 1985, LC50s of 10,000 and 8,700 /zg/L for Atlantic clams (Rangia cuneata) were reported by Olson and Harrell
(1973), but Dillon (1977) reported LC50 values of 58 and 122 //g/L for the same clam species.
c As cited in U.S. EPA, 1985, an LC50 of 2,000 //g/L for mummichogs was reported by Klaunig et al. (1975), but Dorfman (1977) and
Eisler and Hennekey (1977) reported LC 50 values of 800 /zg/L or less for the same fish species.
Source: U.S. EPA, 1985 except where otherwise noted.
with brain mercury concentrations of 3-7 //g/g (wet weight), while levels four times these values are required to
cause mortality in adults (Stoewsand et al., 1974; Finley et al., 1979; Scheuhammer, 1988).
Reproductive impairment has been observed in laboratory studies when mercury concentrations in eggs
exceed 0.5 //g/g (Fimreite, 1971; Heinz, 1974, 1976a,b, 1979). Field studies tend to confirm these results.
Reproductive impairment in the loon was associated with mercury levels in eggs ranging from 2-3 //g/g (Barr,
1986). Adverse effects on hatching and fledging were observed when mercury concentrations in the eggs of
common terns exceeded 3.6 //g/g (Fimreite, 1974). Mercury appeared to be a contributing factor to reduced
reproductive success in raptors at some locations (Odsjo, 1982; Evans, 1986). In one study, however, hatching in
herring gulls appeared to be unaffected, despite the fact that eggs contained upwards of 10 //g/g of mercury
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(Vermeer et al., 1973). Lowest-observed-adverse-effect level (LOAEL) and no-observed-adverse-effect level
(NOAEL) values for effects of methylmercury on avian wildlife are derived in Section 4.2.2 of this Volume.
Possible effects on populations of selected avian species are discussed in Section 2.3.3 of this Volume.
2.3.2.4 Individual Effects on Mammals
Extensive research on the toxicity of mercury to mammals indicates that effects vary depending on the
form of mercury ingested or inhaled. Inorganic mercury is corrosive, and acute exposure to humans and other
mammals may cause burning, irritation, salivation, vomiting, bloody diarrhea, upper gastrointestinal tract edema,
abdominal pain, and hemorrhaging (Goyer, 1993). Ingestion of mercurial salts in large doses may cause kidney
damage (Zalups and Lash, 1994). The main toxic effects due to ingestion of organic mercurials are neurological
effects such as paresthesia, visual disturbances, mental disturbances, hallucinations, ataxia, hearing defects, and
stupor (Clarkson et al., 1972).
Differences between the toxicity of different forms of mercury were demonstrated in a study by Aulerich
et al.(1974) using mink (Mustela visori) fed either 5 ppm methylmercury or 10 ppm mercuric chloride. Mink
treated with methylmercury died within 30 days, while those treated with mercuric chloride suffered no ill
effects. Methylmercury attacks the central nervous systems in mammalian wildlife as well as in humans. The
nervous system of the developing fetus may be particularly vulnerable (Bakir et al., 1973), and concern for these
effects tends to drive human health risk assessments for mercury (Clarkson, 1990; reviewed in Volume V of this
Report). Methylmercury ingestion can also cause reduced food intake, weight loss, muscular atrophy and
damage to an animal's heart, lungs, liver, kidneys and stomach (Goyer, 1993; MDNR, 1993).
Levels of exposure that induce mercury poisoning in mammals vary among species. Death occurs in
sensitive mammal species at 0.1-0.5 //g/g bw/d, or 1.0-5.0 //g/g in the diet. Smaller animals (e.g., minks and
monkeys) are generally more susceptible to mercury poisoning than are larger animals (e.g., mule deer and harp
seals), perhaps because of differences in elimination rates. Also, smaller mammals eat more per unit body weight
than larger mammals and, thus, may be exposed to larger amounts of mercury on a body weight basis. LOAEL
and NOAEL values for effects of methylmercury on mammalian wildlife are derived in Section 4 of this Volume.
2.3.3 Population Effects
Mercury contamination has been documented in endangered species, such as the Florida panther and the
wood stork, as well as in populations of loons, eagles and furbearers such as mink and otters. These species
experience high exposures because they either are piscivores or eat piscivores.
2.3.3.1 Loon Populations
It has been suggested by several researchers that loons are at risk from mercury contamination in aquatic
food chains. Loons are primarily piscivorous but also consume benthic macroinvertebrates, such as crayfish
(Barr, 1973). Mercury levels in crayfish approach and may even exceed those of forage fish from the same lakes
(Barr, 1986; Allard and Stokes, 1989). Much of the loon's summer breeding range receives substantial mercury
inputs from airborne deposition. In addition, many of these areas are known to be susceptible to acid deposition.
As noted previously, a negative correlation often exists between lake water pH and mercury concentrations in
fish.
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A comprehensive study of mercury toxicity in wild loons was conducted by Barr (1986). Loons were
collected from three habitats within the Wabigoon River watershed (Ontario, Canada) both above and below a
chlor-alkali plant that discharged mercury into the river. The first habitat (designated Cl) consisted of the lakes
and river directly downstream of the plant. Habitat C2 did not receive mercury discharges but was accessible to
mercury-contaminated fish that originated in Cl. Habitat C3 was upstream from the chlor-alkali plant and
received no appreciable mercury from other sources. Contaminated fish were prevented from entering C3 by a
waterfall. A nearby habitat (C4), not connected to the other three habitats, received no mercury contamination
and served as a control. Human disturbances in all habitats were determined to be minimal, and concentrations
of organochlorine contaminants were low (less than 0.02 ppm total for all pesticides, including all DDT
metabolites, and 0.04 ppm for PCBs).
Barr (1986) found a strong negative correlation between mercury levels in water and reproductive
success in loons as far as 160 km downstream from the mercury source. Mercury in prey fish and invertebrates
declined with increasing distance from the mercury source, but contaminated fish were able to migrate into the
uncontaminated C2 habitat. Mercury levels in loon tissues (eggs, liver, muscle and brain in both adults and
chicks) were highest in the Cl habitat but were also elevated in the C2 habitat, presumably because loons were
feeding on contaminated prey which migrated from Cl. Mercury levels in loons from habitat C3 (upstream from
mercury source and inaccessible to contaminated fish) were comparable with levels from the uncontaminated
control habitat, C4. Most of the mercury in loon tissues, with the exception of the liver, was in the form of
methylmercury. Mercury in the liver appeared to be inorganic, suggesting the existence of a demethylation
pathway. Dose-response relationships appeared to exist between mercury in prey and reproductive success as
well as mercury in various tissues and reproductive success. For example, reductions in egg laying and in nest
site and territorial fidelity were associated with prey containing mean mercury concentrations in the range of
0.3-0.4 //g/g. Reproductive success was also reduced in loons with brain or egg levels of 2-3 //g/g and in loons
with liver residues above 13 /ug/g. No loons reproduced successfully where prey species contained mercury at
levels greater than 0.4 /ug/g.
Ensor et al. (1992) captured 93 loons and collected 128 dead or dying loons from 18 northern and central
counties in Minnesota. Feathers were collected from live loons. Feathers and liver tissue were collected from
the dead loons. In 22 percent of the liver samples, mercury concentrations exceeded 13 /ug/g, the level associated
with impaired reproduction by Barr (1986). Adult loons contained greater concentrations of mercury than
juvenile loons in feathers (8.7 vs. 2.7 //g/g wet weight) and in the liver (6.6 vs. 1.1 /ug/g wet weight), as expected
for a contaminant which bioaccumulates. The mercury in the juvenile loons was considered to be representative
of local mercury contamination since all of their food would have been obtained from lakes within Minnesota.
Mercury in adult loons was thought to represent contributions from both the summering grounds (Minnesota) and
wintering grounds (Gulf of Mexico).
Ensor et al. (1992) concluded that juvenile loons that died of disease had significantly higher mercury
levels in feathers than juvenile loons that died from injury or were caught alive. Emaciated loons also had
significant (significance level not reported) elevations of mercury in both feathers and liver. It was not clear
whether elevated mercury in emaciated loons resulted from concentration of existing mercury stores while body
fat and protein were catabolized or whether mercury contributed to the emaciation. The authors concluded that
the evidence of adverse impacts on the Minnesota loon population was sufficient to recommend monitoring
mercury levels in loon populations.
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Working in north central Wisconsin, Belant and Anderson (1990) collected both live and dead loons and
addled eggs from abandoned nests. Residues of mercury and 14 organochlorine pesticides were measured in
feathers (live and dead loons) and brain, muscle, and liver (dead loons). The conclusions reported in this study
were similar to those reached by Ensor et al. (1992). Pesticide concentrations in dead loons were relatively low.
In contrast, mercury levels in liver (mean concentration of 40.9 //g/kg wet weight) exceeded those associated
with reproductive dysfunction as reported by Barr (1986).
Scheuhammer and Blancher (1994) reported on mercury levels in fish sampled from lakes throughout
Ontario, Canada in areas without known point sources of mercury. Up to 30% of the lakes contained fish with
mercury levels that exceeded 0.3 //g/kg (wet weight), the level associated with reproductive impairment in loons
as reported by Barr (1986). The lack of any identified point source of mercury contamination was considered by
the authors to be indirect evidence of airborne deposition of mercury over large portions of Ontario.
Preliminary results from an ongoing study of loons in northern Wisconsin were reported by Meyer et al.
(1996). A significant negative correlation was found between mercury levels in blood from chicks and lake pH.
Chick mortality was also greater on low pH lakes. It was not clear; however, whether these effects can be
attributed to mercury or to a general reduction in the prey base of acidic lakes. Previously, it had been shown
that mercury levels in blood and feathers of adult loons were negatively correlated with lake pH (Meyer et al.,
1995).
The viability of loon populations within their traditional habitats in the United States is unclear. None of
the studies reviewed was able to demonstrate clear population declines on a regional or national basis. Several
studies have found that substantial numbers of loons contain mercury at or above levels associated with reduced
reproductive success as reported by Barr (1986) . It has also been suggested (but not clearly demonstrated) that
sublethal effects of mercury exposure may produce greater susceptibility to environmental stresses, including
other contaminants. Mercury also may make loons more susceptible to secondary infections, especially during
stressful activities such as molting and migration. Investigations in response to a die-off of over 2,500 loons in
the Gulf of Mexico in 1983 found that elevated levels of mercury were associated with abnormally high
infestations of parasites (Barr, 1986).
2.3.3.2 Eagle Populations
Bald eagles are distributed throughout the United States. Many migrate into the lower forty-eight states
only during the winter months; others are resident throughout the year. Bald eagles, like several other avian
species, were adversely impacted by DDT and its metabolites during the 1950s, 60s, and 70s. Due to their status
as a federally listed "threatened" species, the potential threat of mercury exposure to eagle survival and recovery
is a concern.
Researchers have measured mercury residues in bald eagle feathers (U.S. FWS, 1993; Welch, 1994;
Bowerman, 1994; Wood et al., 1996), eggs (Grier, 1974; Wiemeyer et al., 1984, 1993; Grubb et al., 1990;
Anthony et al., 1993; Elliott et al., 1996) and blood (Anthony et al., 1993; U.S. FWS, 1993; Welch, 1994; Wood
et al., 1996). Several of these studies have also reported on levels of other contaminants that might threaten eagle
reproduction.
Wiemeyer et al. (1984) sampled bald eagle eggs that had failed to hatch from nests located in 14 states
between 1969 and 1979; eggs were tested for organochlorine residues and mercury. The highest levels of
mercury were detected in eggs from Maine. Eight organic contaminants were negatively correlated with eggshell
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thinning, a trait often linked with reproductive failure in birds. When mercury levels were compared with the
mean 5-year production rate for eagle nests, a weak negative correlation was found, suggesting an adverse effect
of mercury. The analysis was confounded, however, by the co-occurrence of DDE in many of the eggs with the
highest mercury levels. The authors concluded that mercury contamination appears to have the potential for
adverse effects on eagle production in only a few of the breeding areas sampled, primarily in Maine.
Continuing the work begun earlier, Wiemeyer et al. (1993) collected eggs that had failed to hatch from
nests in 15 states between 1980 and 1984 and analyzed them for organochlorine pesticides, polychlorinated
biphenyls (PCBs) and mercury. These data were then combined with the data collected previously (Wiemeyer et
al., 1984). As before, DDE was the contaminant most significantly (negatively) correlated with eggshell
thinning, with ODD, DDT and PCBs significantly, but less strongly, correlated. The highest levels of DDE,
PCBs and mercury occurred in eggs collected in Maine. Mercury levels in eagle eggs, at or above 0.28 //g/g
(wet weight), were significantly correlated with a reduction in mean 5-year production rate for eagle nests. This
value is comparable to the negative effect value of 0.5 //g/g derived earlier (Wiemeyer et al., 1984). The authors
noted, however, that only three egg samples (all from Maine) contained mercury levels greater than 0.5 //g/g and
that these eggs also contained levels of DDE known to reduce eagle productivity (>6 //g/g). Wiemeyer et al.
(1993) concluded that recent data provide even less evidence than previously indicated (Wiemeyer et al., 1984)
that contaminants other that DDE are adversely impacting bald eagle productivity. Grubb et al. (1990), Grier
(1974), and Anthony et al. (1993) reached similar conclusions on the lack of evidence for an association between
mercury levels and reproductive failure in bald eagles.
Bowerman and co-workers (Bowerman, 1993; Bowerman et al. 1994) examined the productivity of bald
eagles in six geographic regions, including Lakes Superior, Michigan, Huron, and Erie and the states of Michigan
and Minnesota. Significant negative correlations existed between plasma levels of PCB and p,p'-DDE and
reproductive success. Mercury levels in feathers ranged from 9.0 to 23.4 //g/g but were not correlated with
reproductive success.
Welch (1994) sampled eggs, blood and feathers from Maine bald eagles and analyzed them for
organochlorine pesticides, PCBs, TCDD equivalents (TCDD-eq), and mercury. Mercury levels in inland eagles
were higher than concentrations in eagles inhabiting the coastline. In general, these elevated mercury levels
appeared to be related to mercury residues in fish from the two areas. Productivity was also lower for inland
eagle nests; however, the correlation of mercury levels in blood and feathers with mean productivity (5 and 15
years) was not significant.
Mercury concentrations in eagle eggs from British Columbia approached and in some instances exceeded
the level (0.28 //g/g) associated with long-term declines in eagle populations as reported by Wiemeyer et al.
(1993). However, populations in this region appeared at the time of the study to be increasing. Mercury residues
in feathers, blood and livers from eagles in central Florida were lower than those determined for most other wild
eagle populations (Wood et al., 1996).
One of the difficulties in evaluating the effect of mercury on the bald eagle is the co-occurrence of
organochlorine compounds such as PCBs, DDE and TCDDs at levels that may have adverse effects on
reproduction. Bowerman (1993) hypothesized that the effect of the organochlorine contaminants may be
masking the effect of mercury. The U.S. Fish and Wildlife Service (1993) also suggested that, while mercury
was not found in Florida bald eagles at lethal levels, sublethal levels may be adversely affecting eagle
reproduction. Historical data suggest that eagle populations in the Great Lakes Basin are still well below the
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region's carrying capacity. In contrast, eagle populations on many inland waters appear to be doing well
(Colborn, 1991; Bowerman, 1993; Bowerman et al., 1994).
2.3.3.3 Wood Stork Populations
Mercury has been detected in feathers of the endangered wood stork, although the levels found
apparently have not caused toxic effects. Young wood storks in Florida had mercury levels of 1.87 //g/g dry
weight; higher mercury levels would be expected for adults from the same area (Burger et al., 1993). Fleming et
al. (1984) reported mercury levels of 0.66 //g/g wet weight in wood stork eggs, which is somewhat less than
Eisler's (1987) recommended criterion of <0.90-2.0 //g/g wet weight in eggs.
2.3.3.4 Other Wading Birds
The wading bird population in Florida has declined substantially since the 1940's (Ogden, 1994). While
a variety of factors have been implicated, cause-and-effect relationships remain difficult to establish. The
possible effect of mercury on wading birds was investigated by Spalding et al. (1994) and Sundlof et al. (1994).
In general, there is a positive relationship between mercury residues in wading birds and the trophic level at
which they feed (Sundlof et al., 1994). Mercury levels in livers of birds that feed on fish (e.g., Great Blue Heron,
Great White Heron, and Great Egret) exceeded, in several instances, those associated by other authors with
neurologic signs in birds (30 //g/g wet weight) (Scheuhammer, 1991).
2.3.3.5 Furbearer Populations
In one Ontario incident, an eagle was found scavenging on a mercury-poisoned dead otter at Clay Lake
(Wren, 1985). Mercury levels in the otter (liver - 96 //g/g; kidneys - 58 //g/g; brain - 30 //g/g) were well above
those known to be toxic to otters in laboratory exposures. The primary source of the mercury was a chlor-alkali
plant that discharged mercury directly into the river.
In a separate incident, a mink exhibiting unnatural behavior was collected near the mercury-contaminated
Saskatchewan River (Wobeser and Swift, 1976). Subsequent determination of mercury levels in the liver (58
//g/g), kidney (32.9 //g/g), muscle (15.2 //g/g), brain (13.4 //g/g) and fur (34.9 //g/g), combined with clinical and
pathologic findings, were deemed sufficient by the authors to conclude that the animal had been poisoned by
mercury. Residue levels found in this animal exceeded those determined in laboratory studies to be associated
with toxicity. The origins of mercury in this case could not be determined; however, it was observed that fish
from the Saskatchewan River contain mercury at concentrations higher than those known to cause toxicity to
mink in laboratory studies.
In a study of furbearers obtained from trappers in the Wisconsin River watershed (1972-1975), otters
contained the highest tissue mercury levels, followed by minks, raccoons, foxes, muskrats and beavers (Sheffy
and St. Amant, 1982). Liver mercury concentrations reported by Halbrook et al. (1994) for otters collected from
the coastal plain of Georgia (5.1-9.2 //g/g) were approximately one-third the levels reported for otters and mink
that died in experimental dosing studies (Aulerich et al., 1974; Wobeser et al., 1976; O'Conner and Nielson,
1981), and it was speculated by these authors that sublethal behavioral and reproductive impacts could result in
population level effects.
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Mink populations, like those of the otter, have declined substantially in the Southeastern coastal states,
particularly in the coastal plain. Mercury concentrations in mink from the coastal plain were found to be higher
than those in mink from inland areas, and were in the range (3.5 //g/g in kidney) of those known to be associated
with reproductive and behavioral effects in laboratory studies (Osowski et al., 1995). Liver PCB levels were also
found to be significantly elevated. In this regard, it is of interest to note studies with mink which suggest that
mercury and PCBs can act synergistically to reduce reproductive success (Wren et al., 1987). Giesy et al. (1994)
determined that PCBs and mercury do not pose a threat to mink on three Michigan rivers. As with most
assessments of this type, however, combined impacts were not considered.
2.3.3.6 Florida Panther Populations
Mercury is suspected of contributing to the death of one and possibly more endangered Florida panthers.
The Florida Panther Interagency Committee (FPIC) reported that approximately 100 ppm of mercury was
detected in the liver and 130 ppm in the hair of a 4-year-old female panther (FPIC, 1989). The panther, No. 27,
had been radio-instrumented since 1988 and was found dead in the eastern part of the Florida Everglades
National Park (FPIC, 1989). Relatively high levels of mercury (0.005-20.0 ppm) were detected in archived liver
samples from six dead panthers, and levels ranging from 0.02-130.0 ppm have been measured in the hair samples
from ten live individuals. The FPIC concluded that panther No. 27 died of mercury poisoning; however, the
cause of death of the six archived animals was not mentioned in their report.
The most probable source of mercury contamination in Florida panthers is via the food chain. The diet of
the Florida panther includes both raccoons and white-tailed deer but varies greatly depending on prey
availability. Mercury contamination in raccoons has been found to occur in a distributional pattern that coincides
with the species range of Florida panthers (Roelke et al., 1991). The accumulation of mercury in raccoons is due
to consumption of contaminated aquatic life, including invertebrates, fish and amphibians. The panthers most at
risk, therefore, appear to be those that consume mercury-contaminated raccoons. Panthers that prey on deer are
less exposed to mercury because deer are herbivores and accumulate less mercury. Based upon the findings of
the FPIC, habitat modifications have been implemented in the Florida Everglades to increase local deer herds.
In addition to mortality, mercury contamination could decrease reproductive success in the Florida
panther. Methylmercury ingested by a pregnant mammal passes through the placenta to the developing fetus,
potentially causing abortions, stillbirths, congenital defects and behavioral modifications that result in the death
of neonates. Roelke et al. (1991) found a significant inverse correlation between mercury concentrations in
mother panthers and survivorship of the young. Because so few Florida panthers remain (only 30 to 50 in the
wild) (Jordan, 1990), the possibility exists that mercury contamination could contribute to the extinction of this
endangered species (Roelke et al., 1991). However, mercury is but one of several stressors that may be affecting
the panther. Habitat fragmentation, inbreeding (Roelke et al., 1993), and feminization by endocrine disrupting
compounds (Facemire et al., 1995) have all been implicated as causative factors in the decline of this species.
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2.3.4 Communities and Ecosystems
2.3.4.1 Aquatic Communities and Ecosystems
Effects of contaminants on aquatic communities have been investigated by examining functional and
structural responses of natural assemblages in laboratory settings to toxic substances added singly or in
combination. The species diversity of freshwater and brackish-water microbial communities was reduced by
exposure to 40 //g/L of mercuric chloride (Singleton and Guthrie, 1977). Carbon fixation was reduced by 50
percent in freshwater phytoplankton communities exposed to 0.4 //g/L of mercuric chloride, but this effect was
mitigated by the presence of humus or sediment (Hongve et al., 1980). Mercuric chloride (0.5 //g/L)
administered to a marine aquatic community inhibited phytoplankton growth, killed or retarded development in
copepods, and increased the number of viable bacteria (Kuiper, 1981). The species composition of the
phytoplankton also changed, possibly due to selective reduction of predation by the copepods. Bacterial
populations may have increased due to increased food supply in the form of dead phytoplankton (Kuiper, 1981).
In general, mercury concentrations (as Hg+2) required to elicit toxic effects on natural aquatic
communities exceed those commonly measured in surface waters by two or more orders of magnitude (low ng/L
in waters not impacted by point source discharge) (Spry and Wiener, 1991; Wiener and Spry, 1995). Studies of
the effects of methylmercury on aquatic assemblages were not found, however, and it can be reasonably
anticipated that the toxicity of methylmercury to these communities would exceed that of mercuric chloride.
Effects of mercury or any other substance at this level of biological organization could potentially have far-
reaching impacts on the entire food chain by changing both nutrient and energy fluxes.
Field studies of mercury occurrence and effects at the community level are not available. Moreover,
interpreting field studies can be difficult because more than one stressor is often present. Elevated concentrations
of mercury have been found in several species of piscivorous wildlife that have experienced reproductive failure
in the Great Lakes region (e.g., Caspian terns, herring gulls, double-crested cormorants, and mink) (Peakall,
1988; Colborn, 1991; Environment Canada, 1991; Gilbertson et al., 1991). However, other bioaccumulative
contaminants, such as PCBs, dioxins and DDT/DDE, have been implicated as the most likely causative agents
(Colborn, 1991; Gilbertson etal., 1991).
2.3.4.2 Terrestrial Communities and Ecosystems
As noted previously, atmospherically deposited heavy metals such as mercury tend to accumulate in top
soils. This results in particularly high exposures in decomposer communities, which play a crucial role within
the natural nutrient cycles of terrestrial ecosystems. Mercury forms stable complexes with organic substances of
high molecular weight (humic acids) and exhibits limited mobility within soils. Processes that may be affected
by heavy metals in top soil include litter decomposition, carbon mineralization, nitrogen transformation and
enzyme activity. Mercury effects on soil microorganisms vary depending on soil type (Zelles et al., 1986).
Mercury generally inhibits heat production, respiration and iron reduction by soil microorganisms in sandy soils
and, to a lesser extent, in clay. At some intermediate concentrations, however, mercury may stimulate microbial
activity in peat (Zelles et al., 1986).
It is difficult to estimate specific toxic levels for microbial-mediated processes in decomposer
communities due to widely differing soil properties and methodological discrepancies in the literature. In a
report on mercury in the Swedish environment, Lindqvist (1991) cites a study in which soil microbial activity
was significantly reduced at mercury concentrations ranging from 0.06-0.08 //g/g dry weight of humus. The
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concentration of mercury in forest soils in Sweden is in the range 0.01-0.09 //g/g. In a second cited study,
however, the mercury concentration in soil required to reduce soil microbial activity was 50 //g/g. A common
effect of metal contamination on soil animal groups is a decrease in species diversity. In some species,
susceptibility to metals may be a secondary effect due to differences in food availability rather than metal toxicity
per se.
2.3.5 Conclusions
Of the pathways by which ecosystems and components of ecosystems might be exposed to atmospheric
mercury, exposure of high trophic level wildlife to mercury in food is particularly important. The trophic level
and feeding habits of an animal influence the degree to which it is exposed to mercury. Mercury biomagnifies in
aquatic food chains resulting in increasing tissue concentrations of mercury as trophic level increases. Predatory
animals primarily associated with aquatic food chains accumulate more mercury than those associated with
terrestrial food chains. Thus, piscivores and other carnivores that prey on piscivores generally have the highest
exposure to mercury. In a study of furbearing mammals in Wisconsin, the species with the highest tissue levels
of mercury were otter and mink, which are top mammalian predators on aquatic food chains (Sheffy and St.
Amant, 1982). Top avian predators of aquatic-based food chains include raptors, such as the osprey and bald
eagle. Smaller birds feeding at lower levels in aquatic food chains also may be exposed to substantial amounts of
mercury due to their high food consumption rate (consumption/kg bw/d) relative to larger birds.
Although clear causal links have not been established, mercury originating from airborne deposition may
be a contributing factor to population effects on several wading birds, loons, river otters, mink, and the Florida
panther. Effects of mercury originating from point sources on restricted wildlife populations have been
conclusively demonstrated and provide a tissue residue basis for evaluation of risk to other populations. Based
upon reviews of both laboratory and field data, mercury levels that exceed the following values (in //g/g fresh
weight) have been suggested as evidence for possible adverse impacts on avian populations: feathers - 20 //g/g
(Scheuhammer, 1991); eggs - 2.0 //g/g (after conversion from dry weight) (Scheuhammer, 1991); liver - 5 //g/g
(Zillioux et al., 1993). Such criteria must be used with caution, however, as residue thresholds both above and
below these values have been reported. Field data for mammals are not as extensive as those for birds. Mercury
residues in mink and otter that were thought to have been poisoned by mercury originating from a point source
exceeded those seen in dead laboratory animals by a factor of two or more (see Section 2.3.2.4) (Wren, 1991).
The reason for this variation is presently unknown. Additional information is needed before tissue-residue-based
criteria for piscivorous mammals can be developed. Criterion values for fish and water that are designed to be
protective of piscivorous wildlife are calculated in Section 5 of this Volume.
2.4 Ecosystems Potentially at Risk
The information presented in Sections 2.1 through 2.3 suggests that the ecosystems most at risk from
mercury releases to air exhibit one or more of the following characteristics:
• they are located in areas that experience high levels of atmospheric deposition;
• they include surface waters already impacted by acid deposition;
• they possess characteristics other than low pH that result in high levels of mercury
bioaccumulation in aquatic biota;
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• they include species that experience high levels of exposure (e.g., piscivorous birds and
mammals).
2.4.1 Highly Exposed Areas
Ecosystems subjected to high levels of mercury deposition (e.g., near sources of mercury emissions or in
areas with high deposition rates) will be more exposed to mercury than ecosystems with lower levels of mercury
deposition. The pattern of mercury deposition nationwide, therefore, will influence which ecoregions and
ecosystems might be exposed to hazardous levels of mercury.
2.4.2 Lakes and Streams Impacted by Acid Deposition
In many aquatic systems, the tendency for mercury to bioaccumulate in fish is inversely correlated with
pH and alkalinity (or acid neutralizing capacity) (reviewed by Spry and Wiener, 1991). Thus, fish in acidic lakes
(pH 6.0 to 6.5 or less) often have higher body or tissue burdens of mercury than fish in nearby lakes with higher
pH. This relationship has been found for a variety offish species and water bodies, including the following:
• various fish species in 14 lakes and 31 streams in Florida (FDER, 1990);
• yellow perch from lakes in the Upper Michigan peninsula (Grieb et al., 1990);
• yellow perch from seepage lakes in Northern Wisconsin (Cope et al., 1990);
• yellow perch from an experimentally acidified lake in Northern Wisconsin (Wiener et
al., 1990);
• yellow perch from Southern Ontario lakes (Suns and Hitchin, 1990);
• yellow perch from 12 Adirondack lakes (Simonin et al., 1994);
• walleyes from Wisconsin lakes (Lathrop et al., 1991);
• largemouth bass from 53 lakes in Florida (Lange et al., 1993);
• northern pike from 80 Minnesota lakes (Sorensen et al., 1990); and
• smallmouth bass from Ontario lakes (McMurtry et al., 1989).
The increased accumulation of mercury in low pH lakes appears to be due largely to increased microbial
production of methylmercury (Xun et al, 1987; Bloom et al., 1991; Miskimmin et al., 1992), although
biogeochemical processes that release mercury from sediments have also been implicated (Rada et al., 1993).
The bioavailability of methylmercury is probably also enhanced by decreased levels of calcium, as is typical of
such lakes. There are, however, exceptions to the general relationship between pH and bioaccumulation of
mercury (Fjeld and Rognerud, 1993), and it has been suggested that clear correlations between pH and mercury
bioaccumulation are likely to occur only when mercury deposits onto seepage lakes (Richardson et al., 1995).
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2.4.3 Dissolved Organic Carbon
DOC appears to be an important determinant of mercury translocation from watersheds to waterbodies
and, in many systems, may be a better predictor offish mercury residues than pH (McMurtry et al., 1989; Nilsson
and Hakanson, 1992; Fjeld and Rognerud, 1993; Driscoll et al., 1994,1995; Watras et al., 1995b,c). However,
high concentrations of DOC may also complex methylmercury, diminishing its bioavailability (Driscoll et al.,
1994,1995; Hintelmann et al., 1995). Methylmercury uptake across the gills of the Sacramento blackfish was
measured directly by Choi et al. (1997). The addition of moderate amounts of DOC to the exposure water
dramatically reduced this uptake. DOC has been shown to reduce the bioavailability of neutral organic
compounds to freshwater invertebrates (Landrum et al., 1985). Studies of this type have not yet been conducted
with mercury.
2.4.4 Factors in Addition to pH and DOC that Contribute to Increased Bioaccumulation of Mercury in Aquatic
Biota
Numerous factors in addition to pH and DOC can influence the bioaccumulation of mercury in aquatic
biota. These include the length of the aquatic food chain (Cabana and Rasmussen, 1994; Cabana et al., 1994;
Putter, 1994) and water temperature (Bodaly et al., 1993). Physical and chemical characteristics of a watershed
affect the amount of mercury that is translocated from soils to water bodies (McMurtry et al., 1989, Johnston et
al., 1991; St. Louis et al., 1994; Joslin, 1994; Hurley et al., 1995). Interrelationships between these factors are
poorly understood, however, and there is no single factor that has been correlated with mercury bioaccumulation
in all cases examined.
2.4.5 Sensitive Species
For the purposes of this discussion, sensitive species are defined as those species that are more likely
than others to experience adverse effects due to mercury contamination. Such species may or may not be
inherently more sensitive on an absorbed dose basis. Sensitive species also may be at risk because they receive
high methylmercury exposures due to their position in the food chain or because their populations are already
stressed. In the first category are top-level predators of aquatic-based food webs exposed to high concentrations
of mercury in their prey. Examples include piscivorous raptors (e.g., bald eagles and ospreys), waterbirds (e.g.,
herons, gulls, kingfishers, and cormorants), and mammals (e.g., mink and otter). The second category includes
threatened and endangered species, which are species that have already experienced severe population declines
and are at risk of further population declines or extinction (e.g., Florida panther).
2.5 Endpoint Selection
U.S. EPA distinguishes two types of endpoints for ecological risk assessment purposes: assessment
endpoints and measurement endpoints (see text box). Assessment endpoints are explicit expressions of the actual
environmental value that is to be protected. Often, the assessment endpoint cannot be measured directly, so a risk
assessor selects one or more measurement endpoints that can be related, either quantitatively or qualitatively, to
the assessment endpoint (U.S. EPA, 1992a). In its draft guidance on risk assessment procedures, U.S. EPA
(1996) suggested that the term "measurement endpoint" be replaced by the term "measure of effect." It was
deemed prudent for this Report, however, to utilize established terminology until the draft guidelines are
finalized.
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A goal of the problem formulation phase in an
assessment is to select assessment endpoints that are
relevant to decisions to be made. Factors relevant to the
selection of these endpoints include: (1) ecological
relevance; (2) susceptibility to known or potential
stressors; and (3) representation of management goals
(U.S. EPA, 1992a, 1996).
Endpoints for Ecological Risk Assessment
Assessment endpoint - an explicit expression of the
environmental value that is to be protected (U.S. EPA,
1992a).
Measurement endpoint - a measurable ecological
characteristic that is related to the valued characteristic
chosen as the assessment endpoint. (U.S. EPA, 1992a).
Table 2-8 provides examples of ecological ^^^^^^^^^^^^^^^^^^^^^^^^^^^
assessment and measurement endpoints at various levels
of biological organization. In current practice, the most tractable endpoints are at the individual or population
level and include mortality, growth, development and reproduction.
Based on the information provided in Sections 2.1 through 2.4, the ecological components that appear to
be most at risk from atmospheric mercury are piscivorous mammals and birds that feed at or near the top of
aquatic food chains. This is particularly true of threatened or endangered species that already have suffered
population declines due to one or more causes. An appropriate assessment endpoint, therefore, would be
maintenance of self-sustaining populations of these species. Appropriate measurement endpoints for exposed
wildlife species would include growth and survival of adults or other life-stages, reproductive success, and
behavioral impacts. Alternatively, when such data are difficult to collect, it may be necessary to infer adverse
effects on wildlife from laboratory toxicity studies.
2.6 Conceptual Model for Mercury Fate and Effects in the Environment
An important product of the problem formulation phase in ecological risk assessment is a conceptual
model of how the stressor may affect ecological components of the natural environment (U.S. EPA, 1992a,1996).
The conceptual model identifies the ecosystem(s) potentially at risk, exposure pathways between sources and
receptors, and the relationship(s) between measurement and assessment endpoints. A preliminary analysis of the
ecosystem, stressor characteristics, and ecological effects helps to define possible exposure scenarios (i.e.,
qualitative descriptions of how the stressors co-occur with or contact the various ecological components).
A conceptual model of the ecological effects of airborne mercury emissions can be visualized using
Figures 2-1 through 2-5. Mercury is emitted to the atmosphere primarily as the elemental form or as an inorganic
ion. Inorganic mercury returns to earth in wet deposition due to its relatively high solubility in water and because
it adsorbs to airborne particulates. Elemental mercury has a long half-life in the atmosphere and tends to stay
aloft but may react with other chemicals to form inorganic mercury species. Wet deposition containing mercury
falls onto watersheds or directly on water bodies. Mercury deposited onto watersheds is rapidly bound to organic
matter and tends to accumulate over time. A portion of this mercury is released, however, and is transported in
runoff and groundwater to receiving waters such as lakes, streams and wetlands. Biotic and abiotic chemical
reactions transform mercury in water and associated sediments to organic derivatives (primarily methylmercury).
Organomercurial compounds then accumulate in aquatic food chains due both to their tendency to become
sequestered in tissues and to the efficiency with which they are transferred from one trophic level to another.
Eventually, mercury in fish is consumed by piscivorous wildlife, with the resulting potential for adverse
toxicological effects. Uptake
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Table 2-8
Examples of Assessment and Measurement Endpoints
Level of Organization
Ecoregiona
Ecosystem
Community
Population
Individual
Abiotic
Assessment Endpoints
Biodiversity
Regional production
Landscape aesthetics
Productive capability
Nutrient balance
Soil balance
Recreational quality
Change to less useful/desired type
Market/sport value
Extinction
Abundance
Yield/production
Frequent gross morbidity
Massive mortality
Range
Survival
Growth and development
Reproduction
Good physical condition
Habitat quality
Measurement Endpoints
Habitat area
Regional production
Other landscape descriptors
Habitat area
Biomass
Productivity
Nutrient export
Species number
Species evenness
Species diversity
Market/sport value
Saprobic index
Occurrence
Numbers/density
Age structure
Fecundity
Yield/production
Frequency of gross morbidity
Mortality rate
Longevity
Growth and development
Fecundity
Overt symptomology
Biomarkers
Temperature
Water flow
Soil characteristics
Sediment characteristics
a An ecoregion is an area (region) of relative homogeneity in ecological systems (based on elevation, soils, latitude,
precipitation).
Source: Adapted from U.S. EPA, 1989.
pathways other than consumption of contaminated prey (e.g., inhalation and drinking of contaminated water) are
considered to be of little consequence for piscivorous birds and mammals.
2.7 Analysis Plan
The final goal of the problem formulation phase of an assessment is to develop a plan for subsequent
analyses of exposure and effect (U.S. EPA, 1996). In Chapter 3 of this Volume, an attempt is made to
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characterize the exposure of piscivorous avian and mammalian wildlife to airborne mercury and to link these
exposures with information pertaining to specific emissions categories. A stepwise approach was taken, with
each step representing an increased level of complexity and uncertainty. Field residue data were used to the
maximum extent possible for characterization of mercury bioaccumulation and biomagnification in fish. These
data are believed to be better suited for this purpose than laboratory bioconcentration and bioaccumulation data.
Using a previously derived "national average" mercury concentration in fish, exposures to selected wildlife
species were estimated using published exposure factors. Air dispersion models were employed in this analysis,
progressing from the use of a long-range transport model to estimate mercury deposition on a regional basis to
the combined use of both local-scale and long-range models. Mercury deposition estimates on a regional scale
were compared with the distributions of sensitive wildlife species. Finally, an effort was made to determine
whether wildlife living in close proximity to a mercury emissions source experience particularly high exposures
leading potentially to adverse impacts within relatively small geographical regions.
An effects assessment is conducted in Chapter 4 of this Volume by reviewing pertinent toxicology testing
data, with priority given to long-term dietary exposures with wildlife species. A review of data on mercury
elimination suggested the need to evaluate species differences in mercury toxicokinetics and the ameliorative
effects of selenium supplementation. The primary goals of this assessment were: (1) to estimate toxic dose
levels for piscivorous wildlife and (2) to provide guidance on the rational use of uncertainty factors for
subsequent analyses of risk and the development of protective exposure criteria.
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3. EXPOSURE OF PISCIVOROUS AVIAN AND MAMMALIAN WILDLIFE TO
AIRBORNE MERCURY
3.1 Objectives and Approach
The objective of this analysis was to characterize the extent to which piscivorous wildlife are exposed
to mercury originating from airborne emissions. Three general approaches were used, which may be described as
follows.
1. Estimation of current average exposure to piscivorous wildlife on a nationwide basis (Section 3.2).
Estimates of current mercury exposure to selected piscivorous wildlife species were calculated as
the product of the fish consumption rate and measured mercury concentrations in fish. This was not intended to
be a site-specific analysis, but was instead intended to provide national exposure estimates for piscivorous
wildlife based on typical mercury concentrations in fish. This analysis utilized mean total mercury measurements
from two nationwide studies offish residues and published fish consumption data for the selected wildlife
species.
2. Estimation of mercury deposition on a regional scale (40 km grid) and comparison of these data with
species distribution information (Section 3.3).
A long-range atmospheric transport model (RELMAP) was used in conjunction with a mercury emissions
inventory to generate predictions of mercury deposition across the continental U.S. This information was then
compared with wildlife species distributions to characterize the potential for co-occurrence of high mercury
deposition rates and the presence of wildlife species of concern.
3. Estimation of mercury deposition on a local scale in areas near emissions point sources (Section 3.4).
A local-scale atmospheric transport model (GAS-ISC3) was used to simulate mercury deposition
originating from four different mercury emissions source classes. The analysis was conducted for two
hypothetical lakes located in the western and eastern U.S. The proximity of these lakes to the source was varied
to examine the effect of this parameter on model predictions. To account for the long-range transport of emitted
mercury, the 50th percentile RELMAP atmospheric concentrations and deposition rates were included in the
estimates from the local air dispersion model. To account for other sources of mercury, estimates of background
concentrations of mercury were also included in this exposure assessment.
3.2 Description of Computer Models
The models used for the wildlife exposure assessment are identical to those used for the human exposure
assessment (see Volume IV of this Report) and are described in detail in Volume III of this Report. Atmospheric
transport models were used to simulate the deposition of mercury at two different geographical scales (see
Table 3-1). A regional-scale analysis was conducted using the Regional
Lagrangian Model of Air Pollution (RELMAP). RELMAP calculates annual mean air concentrations and annual
mean deposition rates for each cell in a 40 km grid. This analysis covered the 48 contiguous states and was based
upon a recent inventory of mercury emissions sources (see Volume II of this Report).
3-1
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Table 3-1
Models Used to Predict Mercury Air Concentrations,
Deposition Fluxes and Environmental Concentrations
Model
RELMAP
GAS-ISC3
IEM-2M
Description
Predicts average annual atmospheric mercury concentration and wet and dry
deposition flux for each 40 km2 grid in the U.S. due to all anthropocentric sources of
mercury in the U.S. and a natural background atmospheric mercury concentration.
Predicts average concentration and deposition fluxes within 50 km of emission
source.
Predicts environmental concentrations based on air concentrations and deposition
rates to watershed and water body.
The local-scale exposure analysis was conducted using both RELMAP and a local air transport model,
GAS-ISC3, to generate hypothetical exposure scenarios for four mercury emission source classes. GAS-ISC3
uses hourly meteorological data to estimate hourly air concentrations and deposition fluxes within 50 km of a
point source. For each hour, general plume characteristics are estimated based on the source parameters (gas exit
velocity, temperature, stack diameter, stack height, wind speed at stack top, and atmospheric stability conditions)
for that hour. GAS-ISC3 was run using one year of actual meteorological data (1989, the same meteorologic year
as was utilized in the RELMAP modeling). The average annual predicted values for air concentration and
deposition rates were then used as inputs to the IEM-2M model. Finally, the IEM-2M model was used to
simulate the result of deposition over a 30 year period, which is the assumed typical lifetime of a facility.
The IEM-2M model was used to translate both regional and local-scale mercury deposition estimates into
mercury levels in soil, water and biota. Mercury levels in fish were calculated from average water concentrations
using estimated BAFs for fish occupying trophic levels 3 and 4. It was assumed throughout the wildlife exposure
analysis that 100% of mercury contained in fish exists as methylmercury.
IEM-2M is composed of two integrated modules that simulate mercury fate using mass balance equations
describing watershed soils and a shallow lake. IEM-2M simulates three chemical components ~ elemental
mercury (Hg°), divalent mercury (Hg2+), and methylmercury (MHg). The mass balances are performed for each
mercury component, with internal transformation rates linking Hg°, Hg2+, and MHg. Sources include wetfall and
dryfall loadings of each component to watershed soils and to the water body. An additional source is diffusion of
atmospheric Hg° vapor to watershed soils and the water body. Sinks include leaching of each component from
watershed soils, burial of each component in lake sediments, volatilization of Hg° and MHg from the soil and
water column, and advection of each component out of the lake.
At the core of IEM-2M are nine differential equations describing the mass balance of each mercury
component in the surficial soil layer, in the water column, and in the surficial benthic sediments. The equations
are solved for a specified interval of time, and predicted concentrations output at fixed intervals. For each
calculational time step, IEM-2M first performs a terrestrial mass balance to obtain mercury concentrations in
watershed soils. Soil concentrations are used along with vapor concentrations and deposition rates to calculate
concentrations in various food plants. These are used, in turn, to calculate concentrations in animals. IEM-2M
simultaneously performs an aquatic mass balance driven by direct atmospheric deposition along with runoff and
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erosion loads from watershed soils. MHg concentrations in fish are derived from dissolved MHg water
concentrations using bioaccumulation factors (BAFs).
Mercury residues in fish were estimated by making the simplifying assumption that aquatic food chains
can be adequately represented using four trophic levels. Respectively, these trophic levels are the following:
level 1 - phytoplankton (algal producers); level 2 - zooplankton (primary herbivorous consumers); level 3 - small
forage fish (secondary consumers); and level 4 - larger, piscivorous fish (tertiary consumers). This type of food
chain typifies the pelagic assemblages found in large freshwater lakes and has been used extensively to model
bioaccumulation of hydrophobic organic compounds (see for example Thomann, 1989; Clark, 1990; and Gobas,
1993). It is recognized, however, that food chain structure can vary considerably among aquatic systems
resulting in large differences in bioaccumulation in a given species offish (Putter, 1994; Cabana et al., 1994a,b).
In addition, this simplified structure ignores several important groupings of organisms, including benthic
detritivores, macroinvertebrates, and herbivorous fishes. The second simplifying assumption utilized in this effort
was that methylmercury concentrations in fish are directly proportional to dissolved methylmercury
concentrations in the water column. It is recognized that this relationship can vary widely among both physically
similar and dissimilar water bodies.
Methylmercury concentrations in fish were derived from predicted water column concentrations of
dissolved methylmercury by using BAFs for trophic levels 3 and 4 (see Table 3-2). The BAFs selected for these
calculations were estimated from existing field data. Respectively, these BAFs (dissolved methylmercury basis)
are 6.8 x 106 and 1.6 x 106. Methylmercury was estimated to constitute 7.8% of the total dissolved mercury in the
water column. The technical basis for these estimates is presented in Volume III, Appendix D.
The variability around these predicted fish residue values is highlighted in Table 3-2. Percentile
information for the BAF estimates developed in Appendix D of Volume III are presented. This table
demonstrates the large variability in fish residues that may occur at a given methylmercury water concentration.
This variability is largely due to the variability in field-derived BAF values.
Table 3-2
Percentiles of the Methylmercury Bioaccumulation Factor
Parameter
Trophic 3 BAF
Trophic 4 BAF
Percentile of Distribution
5th
4.6 xlO5
3.3xl06
25th
9.5 xlO5
5.0xl06
50th
1.6 xlO6
6.8xl06
75th
2.6xl06
9.2xl06
95th
5.4xl06
1.4xl07
3.3 Current Exposure of Piscivorous Wildlife to Mercury
Four avian species (eagle, common loon, kingfisher and osprey) and two mammalian species (otter and
mink) were assumed to be exposed to methylmercury through the ingestion of contaminated fish. Fish
consumption is thought to be the dominant mercury exposure pathway for piscivores (see Chapter 2 of this
Volume). Consequently, an analysis of these ecological receptors' methylmercury contact rate based on the daily
ingestion rate offish is reasonable and appropriate.
3-3
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The piscivorous bird's or mammal's methylmercury contact rate from fish consumption can be estimated
as the product of methylmercury levels in the fish and the daily amount offish eaten. The trophic level at which
piscivores feed significantly impacts their exposure to methylmercury. Those piscivores consuming a diet
primarily consisting of trophic level 3 fish are expected to ingest approximately five times less methylmercury
per gram offish eaten than those eating trophic level 4 fish from the same site. Animals consuming a mixture of
trophic level 3 and 4 fish would experience (on a per gram offish basis) an intermediate level of exposure.
Finally, many top level predators consume a mixture of both aquatic and terrestrially-derived prey. In general,
mercury levels in the tissues of terrestrial animals are much lower than those offish. A special case exists,
however, when a terrestrial animal (e.g., a raccoon) feeds on aquatic biota and is itself preyed upon by a larger
terrestrial animal (e.g., the Florida panther). A similar situation exists when a piscivorous bird (e.g., the herring
gull) is consumed by a larger bird (e.g., the bald eagle). In these situations, the potential exists for the top
predator to obtain a higher mercury dose than it would otherwise receive from a strictly fish-based diet. The
extent of this increase depends, in turn, upon the proportion of the diet composed of these mammalian and avian
prey items and the extent to which the prey items accumulate mercury in excess of levels found at trophic levels 3
and 4.
Exposure factors for the present analysis were obtained from two recent compilations of wildlife dietary
habits (U.S. EPA, 1993a, 1995a) and are shown in Table 3-3. Bald eagles were assumed to eat fish derived from
trophic levels 3 and 4, as well as prey derived from other sources. Expressed as percentages, these prey items
were assumed to contribute 74, 18 and 8% of the daily dietary intake. For this Report, dietary items other than
fish were assumed to contain no mercury. Eagles are, therefore, expected to experience a greater methylmercury
exposure per gram offish consumed than ospreys, loons, and kingfishers, which were assumed to consume only
trophic level 3 fish. Part of this increase, however, is offset by the contribution of uncontaminated prey
consumed by eagles. Among the mammals, otters, which were assumed to consume an 80/20 mix of trophic level
3 and 4 fish, are expected to have a greater methylmercury exposure per gram offish consumed than mink, which
were assumed to eat only trophic level 3 fish. In addition, 10% of the mink diet was assumed to consist of
uncontaminated prey items.
Table 3-3
Exposure Parameters for Mink, Otter, Kingfisher, Loon, Osprey, and Eagle
Species
Mink
Otter
Kingfisher
Loon
Osprey
Eagle
Body Wt.
(WtA)
kg
0.80
7.40
0.15
4.0
1.50
4.60
Ingestion Rate
(FA)
kg/d
0.178
1.220
0.075
0.8
0.300
0.500
Drinking Rate
(WA)
L/d
0.081
0.600
0.017
0.14
0.077
0.160
Trophic Level of
Wildlife Food
Source
3
3,4
3
3
3
3,4
% Diet at
Each
Trophic
Level
90
80,20
100
100
100
74,18,8
3-4
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The ratio of grams fish consumed per day to piscivore body weight is also significant in estimating
mercury exposure on a (ig/kg bw/d basis. The greater this ratio, the higher the resulting mercury exposure,
assuming that methylmercury concentrations in fish remain constant. For example, osprey, loons, and kingfishers
each consume trophic level 3 fish only. Kingfishers consume an amount offish equivalent to about 50% of their
body weight each day, while osprey and loons consume roughly 20% of their body weights in fish per day. The
resulting average daily intake of methylmercury in //g/kg body weight will, therefore, be higher in kingfishers.
Residue data used to calculate national averages for mercury concentration in fish were obtained from two
studies. The first, entitled "A National Study of Chemical Residues in Fish," was conducted by U.S. EPA
(1992b) and also reported in Bahnick et al. (1994). The second study, entitled "National Contaminant
Biomonitoring Program: Concentrations of Seven Elements in Freshwater Fish, 1978-1981," was published by
Lowe et al. (1985). These data are described in Section 2.3.1.2 of this Volume. Based upon these values,
national average methylmercury concentrations in fish tissue were determined to be 0.052 (ig/g and 0.26 (ig/g for
fish occupying trophic levels 3 and 4, respectively. Eagles consume approximately 500 g of food per day (U.S.
EPA, 1993a, 1995a), 74% of which (370 g/d) consists of trophic level 3 fish, and 18% of which (90 g/d) consists
of trophic level 4 fish. Multiplying these consumption rates by the methylmercury concentrations at trophic
levels 3 and 4 and dividing by the average weight of an adult eagle (4.6 kg) (U.S. EPA, 1993a, 1995a) yields an
average daily exposure of approximately 14 //g methylmercury/kg bw/d. Similar calculations were made for
other piscivores in this hypothetical exposure scenario allowing comparisons to be made among species (see
Table 3-4).
Table 3-4
Summary of Sample Calculations of
Wildlife Species Methylmercury Exposure
From Fish Ingestion, Based
on Average Fish Residue Values
From a modeling standpoint, methylmercury
levels in trophic level 3 fish and the mercury
concentration in water are irrelevant to a ranking of
predator exposure; only the relationship between the
methylmercury concentrations in trophic levels 3 and 4 is
critical. As noted previously, fish consumption rate
expressed per gram of body weight has a large effect on
these exposure calculations. Thus, despite consuming a
comparatively small amount of the trophic level 3 fish, the
kingfisher ranks well above any other birds (or mammals)
in this estimated amount of mercury ingested per kg/bw.
3.4 Regional-Scale Exposure Estimates
There are many stationary, anthropogenic
mercury sources in the U.S., and the impact of these
emissions may not be limited to the local area around the
facility. To account for impacts of mercury emitted from
these non-local sources, the long-range transport of
mercury was simulated using the RELMAP model. The
RELMAP model was used to predict the average annual
atmospheric mercury concentration and the wet and dry
deposition flux for each 40 km2 grid in the continental
U.S. The emission, transport and fate of airborne mercury over the continental U.S. were modeled using
meteorologic data for the year of 1989. This year was assumed to be a typical year from an atmospheric
dispersion perspective. Inputs to the RELMAP model were obtained from the mercury emissions inventory
presented as Volume II of this Report. In all, over 10,000 mercury emitting cells within the U.S. were addressed.
A detailed description of the RELMAP model is provided in Section 4 of Volume III.
Species
Kingfisher
Otter
Loon
Osprey
Mink
Eagle
Sample Estimated
Methylmercury Exposure from
Fish Ingestion (jttg/kg bw/d)
25
15
10
10
10
9
3-5
-------
3.4.1 Predicted Current Mercury Exposure Across the Continental U.S.
In the first stage of analysis, estimated total mercury deposition data were used with ARC/INFO
cartography software to generate U.S. map overlays. The overlays can be applied to similar scale maps of natural
resources and species distributions or combined with additional data, such as acid deposition or pH of surface
waters. Figure 3-1 shows RELMAP projections for total (including wet and dry) anthropogenic mercury
deposition. Nearly all the land area east of the Mississippi River is projected to receive mercury deposition
greater than 5 //g/m2. Highly industrialized northeastern states and south Florida are projected to receive more
than 20 //g/m2. RELMAP results are projections that may differ quantitatively from actual sampling data for a
given locale. It is anticipated, however, that additional sampling data will confirm the prediction that mercury is
deposited in significant quantities over large geographic areas.
Limitations on data precluded a quantitative, nation-wide analysis of the exposure of piscivorous wildlife
to mercury. Existing data are sufficient, however, to permit a qualitative analysis. In the case of plant life, the
analysis was limited to plotting the location of federally threatened or endangered species, thereby indicating
where threatened populations coincide with estimated high mercury deposition.
Avian wildlife selected for this analysis included species that are widely distributed (kingfishers) and
narrowly distributed (bald eagles, ospreys, and loons). All the birds selected were piscivores that feed at or near
the top of aquatic food chains and are therefore at risk from biomagnified mercury.
Two of the mammals selected for this analysis (mink and river otters) are piscivorous and widely
distributed. The other mammal selected, the Florida panther, is not widely distributed but is listed as an
endangered species. The Florida panther lives in an environment known to be contaminated with mercury and
preys upon small mammals (e.g., raccoons) that may contain high tissue burdens of mercury.
The maps and map overlays that follow were used to examine in a qualitative fashion the potential for
anthropogenic mercury to impact representative piscivorous species in a variety of ecosystems. Animal
distribution information was obtained from the Nature Conservancy (1994).
3.4.2 Locations of Socially Valued Environmental Resources
Major freshwater lakes and river systems potentially affected by high levels of atmospheric mercury
deposition are illustrated in Figure 3-2. Most of the freshwater located in the lower 48 states occurs in areas
where mercury deposition is predicted to be high. Because mercury accumulates in sediments, it is anticipated
that significant mercury inputs to surface waters will continue for a long period of time even if atmospheric
deposition is substantially reduced. The Great Lakes are particularly vulnerable due to the length of time
necessary to replenish contaminated freshwater with clean freshwater.
Figure 3-3 shows the location of national resource lands, which include national parks and monuments,
national forests, wildlife refuges and Native American reservation lands. The area of national resource lands that
are predicted to have high mercury deposition is relatively small when compared with the total area of national
resource lands, most of which are located in the western states. The small size of eastern resources makes them
especially vulnerable to the effects of mercury because depleted wildlife populations cannot easily be
repopulated from less-impacted adjoining regions. Increasingly, natural areas
3-6
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Figure 3-2
Major Rivers and Lakes
(Detail: Eastern U.S.)
Deposition 1-5 ug/m2
Deposition 5-10 ug/m2
Deposition > 10 ug/mZ
3-8
-------
Figure 3-3
National Resource Lands
I " ° ^q. ^f^3
^j e\, fl C^s-y i
I U^5^-^-:/---
•^ i. . -t> 4-7 <
National Part, Monument, Lakeshore, Parkway, BatU«fleld, Recreation area
National forest or grassland
National wildlife refuge, game preserve, fish hatchery
National scenic waterways or wilderness area
Native American reservation lands
Military reservation
3-9
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may become "islands" surrounded by development. The loss of biodiversity is an important problem that could
be exacerbated by the added stress of mercury toxicity.
3.4.3 Airborne Deposition Overlay with Threatened and Endangered Plants
Figure 3-4 shows the geographic locations of populations of threatened and endangered plant species
overlaid with RELMAP's predicted mercury deposition. Large concentrations of endangered plant populations
exposed to high levels of deposition occur in central and southern Florida, along the northeastern coastal region,
and scattered throughout the midwest.
3.4.4 Regions of High Mercury Deposition
Predicted mercury deposition rates in excess of 5 (ig/m2 are shown in Figure 3-5. These data are used
below to estimate the extent of overlap of wildlife species ranges with regions receiving high levels of mercury
deposition. It should not be inferred from this analysis that wildlife living in areas that receive relatively low
levels of mercury deposition are not at risk. For example, much of northern Wisconsin receives only moderate
amounts of mercury, yet the occurrence of high mercury levels in fish is a well-documented problem.
Nevertheless, it is of interest to define deposition patterns on a broad geographical scale. These data can then be
interpreted in the context of regional and watershed-specific factors that contribute to mercury translocation,
methylation, and bioaccumulation.
3.4.5 Regions of High Mercury Deposition Overlay with the Distribution of Acid Surface Waters
Figure 3-6 shows the co-occurrence of acidified surface waters (NAPAP, 1990) and regions receiving
high levels of mercury deposition. While it is recognized that a variety of factors impact the methylation of
mercury and its subsequent accumulation in aquatic biota (see Chapter 2 of this Volume), mercury residues in
fish have been positively correlated with low pH in ecosystems of widely varying type, including both northern
oligotrophic lakes and the lakes and wetlands of central Florida. Poorly buffered surface waters receiving high
levels of mercury deposition are located in central Florida, throughout the Chesapeake Bay region, and in the
northeastern U.S., including the Adirondack region of New York.
3.4.6 Regions of High Mercury Deposition Overlays with Wildlife Species Distribution Maps
Figure 3-7 shows the range of kingfisher habitat and areas where this habitat overlaps with regions of
high mercury deposition. Kingfishers consume fish primarily from trophic level 3. Approximately 29% of the
kingfisher's range overlaps with areas of high mercury deposition. On a nationwide basis, mercury does not
appear to be a threat to the species. However, as indicated by the exposure assessment in Section 3.3, kingfishers
consume more mercury on a body weight basis than any of the other wildlife species examined.
Figure 3-8 overlays the range of bald eagle habitat onto regions that receive high levels of mercury
deposition. Although a recovery in the population of bald eagles in the lower 48 states has resulted in a status
upgrade from "endangered" to "threatened," bald eagle populations are still depleted throughout much of their
historical range. Bald eagles can be found seasonally in large numbers in several geographic locations, but most
of these individuals are transient, and the overall population is still small. Historically, eagle populations in the
lower 48 states have been adversely impacted by the effects of bioaccumulative contaminants (primarily DDT
and perhaps also PCBs). Approximately 34% of the bald eagle's range overlaps with regions of high mercury
deposition. Areas of particular concern include the Great Lakes region, the northeastern Atlantic states, and
south Florida.
3-10
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Figure 3-4
Threatened and Endangered Plant Species and Anthropogenic Mercury Deposition
Threatened or Endangered Plant
Deposition 1-5 ugM)2
Deposition 5-10 ug/mz
Deposition > 10 ug/mz
3-11
-------
-------
Figure 3-6
Regions of High Mercury Deposition and the Distribution of Acid Surface Waters
NORTHEAST
WEST
6-20% pH < » 5.5, Deposition 6-10 ug/m2
6-20% pH < = 6.6, Deposition > 10 ug/m2
> 20% pH < - 6.6, Deposition 6-10 ug/m2
> 20% pH < = 6.6, Deposition > 10 ug/m2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
3-13
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Figure 3-7
Kingfisher Range and Regions of High Mercury Deposition
NORTHEAST
WEST
Ring* for tfite • pactot
D«po«Hlon 6-10 ug/m2
D*po«ltlon > 10 ug/m2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
3-14
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Figure 3-8
Bald Eagle Range and Regions of High Mercury Deposition
NORTHEAST
WEST
Rang* for thli «pedet
Deposition 6-10 ug/m2
Dapotttlon > 10 ug/nr>2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
3-15
-------
Figure 3-9 indicates where the range of osprey coincides with regions of high mercury deposition.
Nationwide, approximately 20% of the osprey's range overlaps these regions; however, a much larger fraction of
the osprey's eastern population occurs within these regions. The osprey diet consists almost exclusively offish.
Osprey populations underwent severe declines during the 1950s through the 1970s due to widespread use of DDT
and related compounds.
Figure 3-10 depicts areas where the range of the common loon coincides with regions of concern. Nearly
40% of the loon's range is located in regions of high mercury deposition. Limited data from a study of a mercury
point source showed that the reproductive success of loons was negatively correlated with exposure to mercury in
a significant dose-response relationship (see Section 2.3.3 of this Volume). Mercury residues in fish collected
from lakes used as loon breeding areas may, in some cases, exceed levels that, on the basis of the point source
study, are associated with reproductive impairment. Loons frequently breed in areas that have been adversely
impacted by acid deposition. An assessment of mercury's effects on loon populations is complicated by the fact
that decreases in surface water pH have been associated with both increased mercury residues in fish and a
decline in the available forage base.
Figure 3-11 shows the Florida panther's range. All (100%) of the panther's range falls within an area of
high mercury deposition. Mercury levels found in tissues obtained from dead panthers are similar to levels that
have been associated with frank toxic in other feline species. The State of Florida has taken measures to reduce
the risk to panthers posed by mercury. Existing plans include measures to increase the number of deer available
as prey in order to reduce the reliance of panthers on raccoons. As indicated previously, raccoons frequently feed
at or near the top of aquatic food webs and can accumulate substantial tissue burdens of mercury. An evaluation
of the risk posed by mercury to the Florida panther is complicated by the possible impacts of other chemical
stressors, habitat loss and inbreeding.
Figure 3-12 shows where mink habitat coincides with regions of high mercury deposition (approximately
35% nationwide). Mink occupy a large geographic area and are common throughout this range, although rarely
observed due to their nocturnal habits. Mink are extremely aggressive carnivores and, given the opportunity, will
prey on small mammals and birds. Many subpopulations, however, prey almost exclusively on fish and other
aquatic biota. Due to allometric considerations, the mink may be exposed to more mercury on a body weight
basis than larger piscivorous mammals feeding at higher trophic levels. In several cases, mercury residues in
wild-caught mink have been shown to be equal to or greater than levels associated with toxic effects in the
laboratory.
Figure 3-13 shows where the range of the river otter coincides with areas of high mercury deposition
(approximately 38% nationwide). River otters occupy large areas of the United States, but their population
numbers are thought to be declining in both the midwestern and southeastern states. The river otter's diet is
almost exclusively of aquatic origins and includes fish (primarily), crayfish, amphibians and aquatic insects. The
consumption of large, piscivorous fish puts the river otter at risk from bioaccumulative contaminants such as
mercury. Like the mink, mercury residues in some wild-caught otters have been shown to be close to, and in
some cases greater than, concentrations associated with frank toxic effects.
3.5 Modeling Exposures Near Mercury Emissions Sources
In this section, computer models are used to predict exposures of piscivorous wildlife to mercury
resulting from hypothetical local source emissions. Modeling assumptions related to the presence of
"background" mercury as well as mercury transported from other regions of the U.S. are also discussed.
3-16
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Figure 3-9
Osprey Range and Regions of High Mercury Deposition
(Detail: Eastern U.S.)
Range for this specie*
Deposition 5-10 ug/m2
Deposition > 10 ug/m2
3-17
-------
Figure 3-10
Common Loon Range and Regions of High Mercury Deposition
NORTHEAST
WEST
FUnga for thli tpeotof
D«potltlon 5-10 ug/m2
Dapotitlon > 10 ug/m2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
. .»*
3-18
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Figure 3-11
Florida Panther Range and Regions of High Mercury Deposition
(Detail: Eastern U.S.)
Range for thl> •pectot
Deposition 5-10 ug/m2
Deposition > 10 ug/m2
3-19
-------
Figure 3-12
Mink Range and Regions of High Mercury Deposition
NORTHEAST
WEST
FUnge for thl* tpaotot
Deposition 5-10 ug/m2
Deposition > 10 ug/m2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
3-20
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Figure 3-13
River Otter Range and Regions of High Mercury Deposition
NORTHEAST
WEST
FUnga for thl« tpadai
Deposition 5-10 ug/m2
Deposition > 10ufl/m2
MID-ATLANTIC
COASTAL PLAIN
FLORIDA
3-21
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3.5.1 Estimates of Background Mercury
In Volume III of this Report, it was noted that mercury is a constituent of the environment and has always
been present on the planet. Estimates of atmospheric mercury concentrations and deposition rates from periods
pre-dating large-scale anthropogenic emissions ("pre-anthropogenic"), as well as levels due to current sources,
were determined for hypothetical eastern and western sites. These estimates were used as inputs to the IEM-2M
model. The IEM-2M model was run until equilibrium was achieved for both the eastern and western sites and for
both the pre-anthropogenic and current time periods. Chemical equilibrium is defined here as "a steady state, in
which opposing chemical reactions occur at equal rates" (Pauling, 1963). When modeling the pre-anthropogenic
period, the initial conditions of all model compartments, except the atmosphere, were set to a mercury
concentration of 0. The results of running the pre-anthropogenic conditions to equilibrium in IEM-2M were used
as the initial conditions for estimating the current mercury concentrations. Table 3-5 lists the estimated mercury
air concentrations and deposition rates used at both hypothetical sites and for both time periods.
Table 3-5
Inputs to IEM-2M Model for the Two Time Periods Modeled
Time Period
Pre-
Anthropogenic
Current
Eastern Site
Air Concentration
ng/m3
0.5
1.6
Annual
Deposition Rate
(ig/m2/yr
3
10
Western Site
Air Concentration
ng/m3
0.5
1.6
Annual
Deposition Rate
(ig/m2/yr
1
2
3.5.2 Hypothetical Wildlife Exposure Scenarios
The exposure of piscivorous wildlife to mercury originating from hypothetical point sources was
characterized using the same approach as that used to characterize human exposure to mercury from consumption
of contaminated fish (see Volumes III and IV). A benefit of this approach is that it facilitates comparisons
between exposure levels to human and wildlife receptors.
Mercury exposure was assessed for piscivorous wildlife hypothetically located at two generic lacustrine
sites: (1) a humid site east of 90 degrees west longitude and (2) a more arid site west of 90 degrees west longitude
(see Volume III for site descriptions). Both sites were assumed to be located in relatively flat terrain. Exposure at
each site was assessed for piscivorous wildlife living around one of three lakes located at 2.5, 10, or 25 km from
the emissions source, as shown in Figure 3-14. The primary physical differences between the two hypothetical
sites as parameterized included the assumed average annual precipitation rate, the assumed erosion
3-22
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Figure 3-14
Configuration of Hypothetical Water Body and Watershed Relative to Local Source
^--"""""^ ^^^\^ Watershed
/^ x.
Local /
Source / Lake
1
*r = 0.9 km
/ \
Center of lake at / \
2.5 km,
10km, or
25km
Prevailing Downwind Direction
characteristics for the watershed, and the amount of dilution flow from the water body. The eastern site had
generally steeper terrain in the watershed than was assumed for the western site. The drainage lakes were
assumed to be circular with a diameter of 1.78 km and average depth of 5 m, with a 2 cm benthic sediment depth.
The watershed area was 37.3 km2. In each case, deposition information was used to estimate mercury
concentrations in water, averaged over the entire lake.
3.5.3 Predicted Mercury Exposure Around Emissions Sources
The goal of the local scale analysis was to evaluate the extent to which mercury emissions sources have
the potential to create locally elevated mercury exposures for piscivorous wildlife receptors. Air concentrations
and deposition rates due to a single local source were predicted using the GAS-ISC3 atmospheric dispersion and
deposition model. For the purposes of this study, hypothetical sources were assumed to contribute mercury in
addition to that simulated by RELMAP. Details of the local-scale modeling exercise are presented in Volume III
of this Report. Additionally, current background concentrations of mercury in various media were estimated and
used as inputs to the modeling (see Volume III for description).
Model plants (hypothetical anthropogenic mercury emissions sources) representing four source classes
were developed to represent a range of mercury emissions sources. The source categories were selected for the
indirect exposure analysis based on their estimated annual mercury emissions or their potential to be localized
point sources of concern. The categories selected were: municipal waste combustors (MWCs), medical waste
incinerators (MWIs), utility boilers, and chlor-alkali plants. Table 3-6 shows the process parameters assumed for
each of these facilities. The characteristics of the facilities were derived based on typical rather than extreme
representations; the facilities are known as model plants (see Volume II).
3-23
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Table 3-6
Process Parameters for the Model Plants Considered in the Local Impact Analysis
Model Plant
Large Municipal Waste
Combustors
Small Municipal Waste
Combustors
Large Commercial HMI
Waste Incinerator
(Wetscrubber)
Large Hospital HMI
Waste Incinerators
(Good Combustion)
Small Hospital HMI
Waste Incinerators
(1/4 sec Combustion)
Large Hospital HMI
Waste Incinerators
(Wet Scrubber)
Small Hospital HMI
Waste Incinerators (Wet
Scrubber)
Large Coal-fired Utility
Boiler
Medium Coal-fired
Utility Boiler
Small Coal-fired Utility
Boiler
Medium Oil-fired Utility
Boiler
Chlor-alkali plant
Plant Size
2,250 tons/day
200 tons/day
1500 Ib/hr capacity
(1000 Ib/hr actual)
1000 Ib/hr capacity
(667 Ib/hr actual)
100 Ib/hr capacity
(67 Ib/hr actual)
1000 Ib/hr capacity
(667 Ib/hr actual)
100 Ib/hr capacity
(67 Ib/hr actual)
975 Megawatts
375 Megawatts
100 Megawatts
285 Megawatts
300 tons
chlorine/day
Capacity
(% of year)
90%
90%
88%
39%
27%
39%
27%
65%
65%
65%
65%
90%
Stack
Height
(ft)
230
140
40
40
40
40
40
732
465
266
290
10
Stack
Diameter
(ft)
9.5
5
2.7
2.3
0.9
2.3
0.9
27
18
12
14
0.5
Hg Emission
Rate
(kg/yr)
220
20
4.58
23.9
1.34
0.84
0.05
230
90
10
2
380
Speciation
Percent
(Hg0/Hg2+/Hgp)
60/30/10
60/30/10
33/50/17
2/73/25
2/73/27
33/50/17
33/50/17
50/30/20
50/30/20
50/30/20
50/30/20
70/30/0
Exit
Velocity
(m/sec)
21.9
21.9
9.4
16
10.4
9.0
5.6
31.1
26.7
6.6
20.7
0.1
Exit
Temperature
(°F)
285
375
175
1500
1500
175
175
273
275
295
322
Ambient
" Hg° = Elemental Mercury
b Hg2+ = Divalent Vapor Phase Mercury
0 Hgp = Particle-Bound Mercury
3-24
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GAS-ISC3 was employed to estimate deposition originating from local point sources (<50 km from the
receptor). The IEM-2M model was then utilized to estimate the fate of mercury in the watershed and water body.
The estimated concentrations of dissolved methylmercury in the water column were used to predict
methylmercury concentrations in fish that occupy trophic levels 3 and 4. This was accomplished by multiplying
the predicted methylmercury dissolved water concentration by the BAF at each trophic level. Wildlife receptors
were assumed to ingest the fish at rates given previously (Table 3-3).
3.5.4 Results of Hypothetical Exposure Scenarios
High rates of mercury deposition were associated with proximity to industrial sources emitting
substantial levels of divalent mercury (see Tables 3-7 and 3-8). Additional factors that contributed to high local
deposition rates include low stack height and slow stack exit gas velocities. In general, predicted dissolved
methylmercury concentrations in lake waters located 2.5 km from the source were higher than levels predicted at
10 or 25 km. This was due primarily to the dilution of the mercury emissions in the atmosphere. Mercury
concentrations in fish (hence the mercury exposure to piscivores) were proportional to dissolved methylmercury
levels in the local waters. When the two hypothetical locations were compared (western and eastern), higher
mercury concentrations were predicted to occur in the environmental media at the eastern location. This was due
primarily to higher levels of precipitation at the eastern site, which tends to remove mercury from the
atmosphere. Also, the assumptions of background mercury are higher for the eastern than the western site. On a
per kilogram of body weight per day basis, the species predicted to be most exposed were the kingfisher and the
otter.
3.5.5 Issues Related to Combining Models to Assess Environmental Fate of Mercury and Exposures to
Wildlife
In modeling the environmental fate and subsequent exposure of piscivorous wildlife to mercury emitted
from a number of different sources, many simplifying assumptions have been made. Each simplifying assumption
is associated with some degree of uncertainty; the accumulation of these uncertainties results in uncertainty in the
exposure levels predicted by the models. Many of the input parameters to the models may also be quite variable
across time and location. This variability leads to uncertainty in the modeling results. While no effort is made
here to quantify these variabilities and uncertainties, this section will attempt to describe those deemed most
significant to this element of the assessment.
There is no consensus approach for developing exposure scenarios for pollutants such as mercury, which
have always been environmental constituents (i.e., how to incorporate background concentrations into
environmental fate modeling). The approach developed for this document is clearly not the only approach that
could have been taken to account for environmental background concentrations; however, each potential
alternative approach evaluated also presented associated uncertainty. If the error in estimate of background
results in an overestimation of concentrations in environmental media from these sources, the presented impacts
of anthropogenic sources will be underestimated, and vice versa.
Combining the outputs of the different environmental fate models, while deemed necessary for this
pollutant, clearly compounds the uncertainty relating to individual model assumptions and input parameter
uncertainties. The chemical properties associated with elemental mercury and divalent mercury species in the
atmosphere are assumed to be very dissimilar. This necessitates an atmospheric modeling approach that can
account for long range atmospheric transport of anthropogenic emissions as well as local transport from a given
source. The primary impacts of environmental mercury result from bioaccumulation and biomagnification in the
aquatic food chain. This necessitates the use of a model such as IEM-2M that
3-25
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Table 3-7
Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Percentile)
Variant b: Large Municipal
Waste Combustor
Variant b: Small Municipal
Waste Combustor
Large Commercial HMI
Large Hospital HMI
Small Hospital HMI
Large Hospital HMI (wet
scrubber)
Small Hospital HMI (wet
scrubber)
Large Coal-fired Utility
Boiler
Medium Coal-fired Utility
Boiler
Small Coal-fired Utility
Boiler
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
MHg Dissolved
Concentration (ng/L)
1.7E-01
1.1E-01
8.9E-02
9.5E-02
8.2E-02
7.9E-02
9.6E-02
8.0E-02
7.8E-02
1.9E-01
9.4E-02
8.1E-02
8.5E-02
7.8E-02
7.8E-02
8.1E-02
7.8E-02
7.7E-02
7.8E-02
7.7E-02
7.7E-02
1.3E-01
8.6E-02
8.0E-02
l.OE-01
8.3E-02
8.0E-02
8.3E-02
7.9E-02
7.8E-02
MHg Concentration (ug/g) Predicted MHg Exposure from Ingestion of Fish (mg/kg/day)
Tier3 Tier4 Background RELMAP ISC Bald Eagle Osprey Kingfisher River Otter Mink Loon
2.7E-01 1.2E+00 38% 7% 54% 4.4E-02 5.4E-02 1.4E-01 7.4E-02 5.4E-02 5.4E-02
1.8E-01 7.6E-01 58% 11% 31% 2.9E-02 3.6E-02 8.9E-02 4.8E-02 3.6E-02 3.6E-02
1.4E-01 6.0E-01 73% 14% 13% 2.3E-02 2.8E-02 7.1E-02 3.9E-02 2.8E-02 2.8E-02
1.5E-01 6.4E-01 68% 13% 18% 2.5E-02 3.0E-02 7.6E-02 4.1E-02 3.0E-02 3.0E-02
1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 3.6E-02 2.6E-02 2.6E-02
1.3E-01 5.3E-01 83% 16% 2% 2.1E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-02
1.5E-01 6.5E-01 68% 13% 19% 2.5E-02 3.1E-02 7.7E-02 4.2E-02 3.1E-02 3.1E-02
1.3E-01 5.4E-01 82% 16% 3% 2.1E-02 2.5E-02 6.4E-02 3.5E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
3.1E-01 1.3E+00 34% 6% 60% 5.0E-02 6.2E-02 1.5E-01 8.4E-02 6.2E-02 6.2E-02
1.5E-01 6.4E-01 69% 13% 18% 2.5E-02 3.0E-02 7.5E-02 4.1E-02 3.0E-02 3.0E-02
1.3E-01 5.5E-01 80% 15% 5% 2.1E-02 2.6E-02 6.5E-02 3.5E-02 2.6E-02 2.6E-02
1.4E-01 5.8E-01 76% 15% 9% 2.2E-02 2.7E-02 6.8E-02 3.7E-02 2.7E-02 2.7E-02
1.3E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
1.3E-01 5.5E-01 80% 15% 4% 2.1E-02 2.6E-02 6.5E-02 3.5E-02 2.6E-02 2.6E-02
1.2E-01 5.3E-01 84% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
2.1E-01 9.1E-01 48% 9% 42% 3.5E-02 4.3E-02 1.1E-01 5.8E-02 4.3E-02 4.3E-02
1.4E-01 5.9E-01 75% 14% 10% 2.3E-02 2.8E-02 6.9E-02 3.8E-02 2.8E-02 2.8E-02
1.3E-01 5.5E-01 81% 15% 4% 2.1E-02 2.6E-02 6.4E-02 3.5E-02 2.6E-02 2.6E-02
1.6E-01 6.9E-01 64% 12% 24% 2.7E-02 3.2E-02 8.1E-02 4.4E-02 3.2E-02 3.2E-02
1.3E-01 5.6E-01 78% 15% 7% 2.2E-02 2.7E-02 6.6E-02 3.6E-02 2.7E-02 2.7E-02
1.3E-01 5.4E-01 81% 16% 3% 2.1E-02 2.6E-02 6.4E-02 3.5E-02 2.6E-02 2.6E-02
1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 3.6E-02 2.6E-02 2.6E-02
1.3E-01 5.4E-01 82% 16% 2% 2.1E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-02
1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02
3-26
-------
Table 3-7 (continued)
Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Percentile)
Medium Oil-fired Utility
Boiler
Chlor-alkali plant
2.5km
10km
25km
2.5km
10km
25km
MHg Concentration (ug/g)
MHg Dissolved
Concentration (ng/L)
7.8E-02
7.8E-02
7.7E-02
l.OE+00
1.8E-01
l.OE-01
Tier3
1.2E-01
1.2E-01
1.2E-01
1.6E+00
2.8E-01
1.6E-01
Tier4
5.3E-01
5.3E-01
5.3E-01
6.8E+00
1.2E+00
6.8E-01
Background
83%
84%
84%
6%
37%
65%
RELMAP
16%
16%
16%
1%
7%
12%
ISC
1%
0%
0%
92%
56%
23%
Predicted MHg Exposure from Ingestion of Fish (mg/kg/day)
Bald Eagle
2.0E-02
2.0E-02
2.0E-02
2.6E-01
4.6E-02
2.6E-02
Osprey Kingfisher River Otter
2.5E-02 6.2E-02 3.4E-02
2.5E-02 6.2E-02 3.4E-02
2.5E-02 6.2E-02 3.4E-02
3.2E-01 8.0E-01 4.4E-01
5.7E-02 1.4E-01 7.7E-02
3.2E-02 8.0E-02 4.4E-02
Mink
2.5E-02
2.5E-02
2.5E-02
3.2E-01
5.7E-02
3.2E-02
Loon
2.5E-02
2.5E-02
2.5E-02
3.2E-01
5.7E-02
3.2E-02
3-27
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Table 3-8
Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th percentile)
Variant b: Large
Municipal Waste
Combustor
Variant b: Small
Municipal Waste
Combustor
Large Commercial HMI
Large Hospital HMI
Small Hospital HMI
Large Hospital HMI (wet
scrubber)
Small Hospital HMI (wet
scrubber)
Large Coal-fired Utility
Boiler
Medium Coal-fired Utility
Boiler
Small Coal-fired Utility
Boiler
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
2.5km
10km
25km
MHg Dissolved
Concentration (ng/L)
8.8E-02
5.5E-02
2.7E-02
3.3E-02
1.9E-02
1.6E-02
3.4E-02
1.7E-02
1.5E-02
1.4E-01
3.1E-02
1.8E-02
2.3E-02
1.5E-02
1.4E-02
1.8E-02
1.5E-02
1.4E-02
1.5E-02
1.4E-02
1.4E-02
3.1E-02
1.9E-02
1.8E-02
2.3E-02
2.0E-02
1.8E-02
1.9E-02
1.6E-02
1.5E-02
MHg Concentration (ug/g) Predicted MHg Exposure from Ingestion of Fish (mg/kg/day)
Tier3 Tier4 Background RELMAP IS Bald Eagle Osprey Kingfisher River Otter Mink Loon
1.4E-01 6.0E-01 15% 1% 84% 2.3E-02 2.8E-02 7.1E-02 3.8E-02 2.8E-02 2.8E-02
8.8E-02 3.7E-01 24% 2% 74% 1.4E-02 1.8E-02 4.4E-02 2.4E-02 1.8E-02 1.8E-02
4.4E-02 1.9E-01 48% 4% 48% 7.1E-03 8.7E-03 2.2E-02 1.2E-02 8.7E-03 8.7E-03
5.3E-02 2.3E-01 40% 3% 57% 8.7E-03 1.1E-02 2.7E-02 1.5E-02 1.1E-02 1.1E-02
3.1E-02 1.3E-01 68% 6% 26% 5.1E-03 6.2E-03 1.5E-02 8.4E-03 6.2E-03 6.2E-03
2.5E-02 1.1E-01 84% 7% 9% 4.1E-03 5.0E-03 1.3E-02 6.8E-03 5.0E-03 5.0E-03
5.4E-02 2.3E-01 39% 3% 58% 8.8E-03 1.1E-02 2.7E-02 1.5E-02 1.1E-02 1.1E-02
2.7E-02 1.1E-01 80% 7% 14% 4.3E-03 5.3E-03 1.3E-02 7.2E-03 5.3E-03 5.3E-03
2.4E-02 l.OE-01 89% 8% 3% 3.9E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-03
2.3E-01 9.6E-01 9% 1% 90% 3.7E-02 4.5E-02 1.1E-01 6.1E-02 4.5E-02 4.5E-02
5.0E-02 2.1E-01 42% 4% 54% 8.2E-03 l.OE-02 2.5E-02 1.4E-02 l.OE-02 l.OE-02
2.9E-02 1.2E-01 73% 6% 20% 4.7E-03 5.8E-03 1.4E-02 7.8E-03 5.8E-03 5.8E-03
3.6E-02 1.5E-01 58% 5% 37% 6.0E-03 7.3E-03 1.8E-02 9.9E-03 7.3E-03 7.3E-03
2.4E-02 l.OE-01 87% 7% 6% 4.0E-03 4.9E-03 1.2E-02 6.6E-03 4.9E-03 4.9E-03
2.3E-02 9.9E-02 91% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03
2.9E-02 1.2E-01 74% 6% 20% 4.7E-03 5.7E-03 1.4E-02 7.8E-03 5.7E-03 5.7E-03
2.4E-02 l.OE-01 90% 8% 3% 3.8E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-03
2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03
2.3E-02 9.9E-02 91% 8% 2% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.7E-03 4.6E-03
2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 6.2E-03 4.6E-03 4.6E-03
2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 6.2E-03 4.6E-03 4.6E-03
4.9E-02 2.1E-01 43% 4% 53% 8.0E-03 9.8E-03 2.4E-02 1.3E-02 9.8E-03 9.8E-03
3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 8.2E-03 6.1E-03 6.0E-03
2.9E-02 1.2E-01 73% 6% 21% 4.8E-03 5.8E-03 1.5E-02 7.9E-03 5.8E-03 5.8E-03
3.6E-02 1.5E-01 58% 5% 37% 5.9E-03 7.3E-03 1.8E-02 9.9E-03 7.3E-03 7.3E-03
3.2E-02 1.4E-01 66% 6% 28% 5.2E-03 6.4E-03 1.6E-02 8.7E-03 6.4E-03 6.4E-03
2.8E-02 1.2E-01 74% 6% 19% 4.6E-03 5.7E-03 1.4E-02 7.7E-03 5.7E-03 5.7E-03
3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 8.2E-03 6.1E-03 6.0E-03
2.6E-02 1.1E-01 81% 7% 13% 4.3E-03 5.2E-03 1.3E-02 7.1E-03 5.2E-03 5.2E-03
2.4E-02 l.OE-01 88% 7% 4% 3.9E-03 4.8E-03 1.2E-02 6.5E-03 4.8E-03 4.8E-03
3-28
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Table 3-8 (continued)
Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th percentile)
Medium Oil-fired Utility
Boiler
Chlor-alkali plant
2.5km
10km
25km
2.5km
10km
25km
MHg Dissolved
Concentration (ng/L)
1.5E-02
1.5E-02
1.4E-02
l.OE+00
1.2E-01
3.7E-02
MHg Concentration (ug/g) Predicted MHg Exposure from Ingestion of Fish (mg/kg/day)
Tier3 Tier4 Background RELMAP IS Bald Eagle Osprey Kingfisher River Otter Mink Loon
2.3E-02 l.OE-01 90% 8% 2% 3.8E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-03
2.3E-02 9.9E-02 91% 8% 2% 3.8E-03 4.7E-03 1.2E-02 6.3E-03 4.7E-03 4.7E-03
2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03
1.6E+00 6.9E+00 1% 0% 99% 2.7E-01 3.3E-01 8.1E-01 4.4E-01 3.3E-01 3.3E-01
1.9E-01 8.0E-01 11% 1% 88% 3.1E-02 3.8E-02 9.5E-02 5.2E-02 3.8E-02 3.8E-02
5.9E-02 2.5E-01 36% 3% 61% 9.7E-03 1.2E-02 3.0E-02 1.6E-02 1.2E-02 1.2E-02
3-29
-------
estimates intercompartmental fluxes and resulting concentrations in abiotic and biotic components of the
watershed and waterbody. Finally, exposure predictions are modeled as simplified daily average estimates.
Seasonal variability among other important exposure factors are not taken into account. Each of these models has
parameter inputs that are variable and uncertain. Collectively, these result in uncertainty in the quantitative
predictions of the models.
The current scientific understanding of the environmental cycling of mercury (regardless of source) is
incomplete. As described in Volume III, areas of uncertainty include emissions speciation, the atmospheric
chemistry of emitted mercury, canopy interactions, factors that affect the aquatic mercury cycle (including both
the magnitude of effect exhibited by a given factor as well as potential interactions among different factors), and
the metabolism of mercury in different piscivorous species.
3-30
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4. EFFECTS OF MERCURY ON AVIAN AND MAMMALIAN WILDLIFE
Perhaps better than any other metal, mercury illustrates the point that toxicity depends on the chemical species
in question. As indicated previously, mercury can exist in an elemental form, as divalent inorganic mercury, or
as any one of several organic forms. Of the possible organic forms that may be present in natural systems,
methylmercury generally predominates. Both inorganic and methylmercury can accumulate in aquatic biota.
However, the proportion of total mercury that exists as the methylated form generally increases with trophic
level, often approaching 100% at trophic levels 3 and 4. It is appropriate, therefore, to focus attention on the
toxicity of methylmercury to piscivorous avian and mammalian wildlife. A review of mercury toxicity to
mammalian systems is provided by Goyer (1993). The toxicity of mercury to birds is reviewed by Scheuhammer
(1987). It is not our intention to duplicate these efforts. Instead, a brief summary of methylmercury toxicity to
vertebrate systems is presented, with the goal of providing guidance on selection of appropriate toxicological
endpoints. This general discussion is followed by brief reviews of several toxicity studies involving avian and
mammalian wildlife species (Sections 4.1 and 4.2). Information relating mercury residues in tissues to observed
toxic effects is summarized in Section 4.4. Research on selenium/mercury interactions and the activity of
endogenous demethylating systems is described in Section 4.5. A single study on the interactive effects of
mercury and PCBs on reproduction in mink is reviewed in Section 4.6, emphasizing the point that wild animals
are often exposed to multiple chemical stressors.
4.1 Mechanism of Toxicity
Methylmercury in the diet is absorbed with high efficiency in the vertebrate digestive tract and associates
rapidly with sulfhydryl-containing molecules in blood, including both free amino acids (primarily cysteine) and
glutathione (Carty and Malone, 1979). These mobile complexes transport methylmercury to tissues and organs
and may facilitate its movement across cell membranes. In particular, there is good evidence for saturable
transport of methylmercury-cysteine complexes across both the blood-brain and placental barriers (Kerper et al.,
1992; Kajiwara et al., 1996). Although it exhibits a range of toxic effects in several target tissues, the primary
effects of methylmercury are on the central nervous system. Neurotoxicity occurs in both adults and developing
animals. In the latter case, this effect appears to be linked to a disturbance of microtubule function in dividing
cells, resulting in anti-mitotic activity (Rodier, 1995). The mode-of-action of methylmercury in the differentiated
nervous system is less well known, but may involve selective effects on astrocytes and other neuroglial cells
(Cranmer et al., 1996).
In chronic toxicity evaluations with mammals, including humans, the most sensitive indicator of toxic
effect is cognitive impairment of animals exposed during development (see Volume V of this Report). In
general, the sophisticated methods employed in such studies have not been used in toxicological evaluations with
wildlife. Instead, less "subtle" endpoints are generally employed, including reduced hatching success and
diminished mobility. The work of Heinz with mallard ducklings (Heinz 1976a,b, 1979) represents a notable
exception to this general rule (see Section 4.2). For wildlife, therefore, it is difficult to establish whether
reproductive or behavioral endpoints are most "sensitive" to methylmercury exposure. Efforts to distinguish
between these endpoints are complicated further by the fact that reproductive impacts can occur as a result of
direct effects on the developing nervous system, impaired behavior of adults (e.g., unsuccessful matings or
diminished quality of parental caregiving), or a combination of both.
4-1
-------
4.2 Toxicity Tests with Avian Wildlife Species
Most studies of chronic exposure to birds have been conducted using mercury-contaminated grain.
Fimreite (1970) identified a LOAEL of 1.1 yug/g/d for growth inhibition in leghorn cockerel chicks (Gallus)
based upon 6 //g/g methylmercury dicyandiamide in the feed. Fimreite (1971) also identified a LOAEL of
0.18 //g/g/d for reproductive effects (reduced survival, reduced egg production, and defective shells) in ring-
necked pheasant (Phasianus colchicus) fed seed treated with methylmercury dicyandiamide. Scott (1977)
identified a LOAEL of 4.9 //g/g/d for reproductive effects (reduced fertility, reduced egg number, reduced
survival, defective shells) in domestic chickens.
The most comprehensive studies of the effect of mercury on birds were conducted by Heinz (1974, 1975,
1976a,b, 1979). Heinz assessed the effects of dietary methylmercury dicyandiamide (0, 0.5 and 3.0 //g/g as
elemental mercury) over three generations of mallard ducks. In the first generation, treatment began in adult
ducks. Subsequent generations received treatment beginning at nine days of age. Initially, Heinz (1974)
identified aNOAEL of 0.5//g/g based upon reproductive effects in a 21 week study. In a later study (Heinz,
1976a,b), reproduction in first and second generation ducks was evaluated, and the NOAEL for the first
generation was again determined to be 0.5//g/g. The second generation, however, suffered adverse reproductive
effects including eggs laid outside the nest box (p<0.05), reduced number of ducklings surviving to one week of
age (p<0.05), and reduced growth of ducklings (p<0.05) at the 0.5//g/g dose. Consequently, the LOAEL was
0.5/ug/g for reproductive effects for the second generation; no NOAEL was identified. A third generation of
mallards also demonstrated adverse reproductive effects at 0.5/ug/g mercury in the diet. Effects observed
included reduced number of viable eggs laid per day (p<0.01) and thinner egg shells (p<0.05).
Heinz (1975, 1979) also examined behavioral effects of mercury exposure on the approach response of
chicks to maternal calls and avoidance of frightening stimuli. In third generation ducklings there was a reduction
in response rate and speed of response to maternal calls (p<0.01). When data were pooled from all studies and
subject to analysis of variance (ANOVA) with multiple comparisons, alterations of behavior were observed in the
lowest dose groups in all generations (0.5//g/g). These alterations included reduction in the number of ducklings
which approached maternal calls (p<0.01) and an increase in the distance traveled to avoid a threatening stimulus
(p<0.05). In summary, no NOAEL could be determined for behavioral effects, and the NOAEL for reproductive
effects could only be demonstrated for the first generation.
For the determination of an appropriate LOAEL in this Report, it was concluded that effects observed in
second and third generation ducks at 0.5/ug/g should not be discounted. It seems likely that the effects observed
in the second and third generations were a result of the earlier onset of dosing. For this reason, 0.5/ug/g was
selected as a LOAEL for mallard ducks. Assuming a feeding rate of 156 g/kg bw/d for adult mallards, the
LOAEL is 78 //g Hg/kg bw/d for reproduction and behavior.
4.3 Toxicity Tests with Mammalian Wildlife Species
River otters (Lutra canadensis) fed 2/ug/g methylmercury for six months suffered from anorexia and
ataxia (O'Connor and Nielson, 1981). In mink, 27//g/g of dietary phenylmercuric chloride caused lethality in
40% of the males and 31% of the females within six weeks of exposure (Borst and Lieshout, 1977).
Wobeser et al. (1976a,b) studied the effects of dietary consumption of methylmercury on ranch mink.
There were two parts to this study, which together formed the basis of Wobeser's dissertation research (Wobeser,
1973). In the first part (Wobeser et al., 1976a), 25 adult female mink and their litters were divided into three
4-2
-------
groups: Group I contained five females and 19 kits (control); Group II contained 10 females and 34 kits (50%
fish diet); and Group III contained 10 females and 29 kits (75% fish diet). The ration was prepared using
mercury-contaminated freshwater drum from Lake Winnipeg, Manitoba; mercury in fish tissue was assumed for
the purposes of the present analysis to consist primarily of methylmercury. The fish was supplied in a ground,
frozen form and was then mixed with cereal and uncontaminated chow to a desired composition of 50 or 75 kg
fish/100 kg of food. All mink were fed once daily in slight excess of consumption. The three exposure groups
were observed for 145 days. Assuming a food consumption rate of 160 g/kg bw/d (appropriate to captive
animals) (Bleavins and Aulerich, 1981) and an average weight of 0.8 kg for the mink, these treatments
corresponded to dosing levels of approximately 35 and 55 //g Hg/kg bw/d. One female and 3-6 kits were
euthanized every 15 (treatment) or 30 (control) days. Complete necropsies were then performed. No clinical
signs of disease were observed in any of the mink within the experimental period, and no mortality or growth
impairment occurred which could be attributed to the feeding of mercury-contaminated fish.
In a second experiment (Wobeser et al., 1976b), 30 adult female mink were assigned to one of six groups
of five animals each. The animals were fed chow spiked with methylmercuric chloride at 0.0 (control), 1.1, 1.8,
4.8, 8.3, or 15.0 //g/g (by analysis), corresponding to dosing levels of 180, 290, 770, 1330, and 2400 //g/kg bw/d.
Two mink from each group were allowed to die of intoxication or were euthanized after 93 days (the end of the
experiment). Animals were necropsied and the tissues analyzed for mercury content. All animals in the control
group remained clinically normal, and the only clinical sign in the 1.1 //g/g dose group was a slight tendency for
two of the animals to move more slowly than the others during the last few days of the experiment. Anorexia,
posterior ataxia, and lateral recumbency were observed in the other four dose groups. Death occurred within
26-36 days at 4.8 //g/g and within 19-26 days at 8.3 //g/g. Histopathological abnormalities were seen at 1.1 //g/g,
including pale, yellow livers, lesions in the central nervous system, and axonal degeneration.
Based upon a review of the Wobeser studies (Wobeser, 1973; Wobeser et al., 1976a,b), it can be
concluded that the LOAEL for subchronic exposure of mink to methylmercury is 180 //g/kg bw/d (1.1 //g/g dose
group), using nerve tissue lesions as an effects endpoint. The NOAEL derived from these studies is 55 //g/kg
bw/d. Importantly, it was Wobeser's opinion that had the studies been carried out for a longer duration, nervous
tissue damage observed in the 1.1 //g/g dose group would have become manifested as impaired motor function.
Charbonneau et al. (1974) fed random-bred domestic cats (Felis domesticus) 3, 8.4, 20, 46, 74 or 176
//g/kg/d of mercury, either as methylmercuric chloride in food or as methylmercury-contaminated fish, 7 d/week
for 2 years. Clinical examinations of the animals were conducted periodically. Neurological examinations, using
a modification of the method of McGrath (1960), were conducted prior to the test, monthly throughout the test,
and more frequently as clinical signs of methylmercury toxicosis became apparent. Neurological impairment,
including hindrance of the hopping reaction and hypalgesia, was observed in animals exposed to 46, 74, or 176
//g/kg/d, regardless of whether casts were fed contaminated fish or spiked food. No treatment-related effects
were observed in three lower dosage groups. Overt signs of toxicity, including ataxia, loss of balance, and motor
incoordination, were observed in animals fed 74 or 176 //g/kg/d. These findings suggest that 20 //g/kg/d is the
NOAEL and 46 //g/kg/d is the LOAEL for chronic dietary exposure to methylmercury in domestic cats.
Charbonneau et al. (1974) also concluded that there was no difference in toxicity or bioavailability between
naturally contaminated fish and fish spiked with methylmercuric chloride.
4-3
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4.4 Tissue Mercury Residues Corresponding to Adverse Effects
Mercury residues associated with toxic effects in birds are reviewed by Scheuhammer (1987). Adult
pheasants fed a methylmercury-spiked diet for 12 weeks accumulated liver residues of 2 (ig/g but exhibited no
discernable adverse effects. However, there was a decrease in hatchability of fertilized eggs due to embryonic
mortality and an increase in the number of unfertilized eggs. Unhatched eggs contained 0.5 to 1.5 (ig/g as
mercury. In a multigenerational study, hen mallards fed methylmercury in the diet accumulated liver residues of
approximately 1.5 (ig/g without apparent adverse effect (Heinz, 1979). Ducklings born to these hens exhibited
behavioral effects including reduced response to maternal calls and hyper-responsiveness to a frightening stimuli.
Mercury residues in the eggs from which these ducklings hatched were approximately 0.8 (ig/g. Kidney residues
considerably higher (>20 (ig/g) than those just reviewed were measured at death in mercury-dosed birds of
several species (Finley et al., 1979).
Wobeser et al. (1976b) reported that mercury residues in the liver and kidney of mink that died during a
93-day feeding study were 24.3 and 23.1 //g/g, respectively. Somewhat higher values were reported in toxicity
studies with mink (55.6 and 37.7 //g/g) by Aulerich et al. (1974) and with otter (39.0 and 33.0 //g/g) by O'Connor
and Nielson (1980). Interestingly, mercury residues in tissues from wild animals that are suspected to have died
from mercury poisoning are about twice those of animals that died from experimental intoxication (Wren, 1985,
1991). Such discrepancies may be due to kinetic-based differences among exposed animals (see Section 2.3.1.3
of this Volume). Perhaps the most valid comparison that can be made at this time is that between apparently
unaffected wild animals and wild animals that have died from mercury poisoning.
4.5 Factors Relevant to the Interpretation and Use of Mercury Toxicity Data
Although several excellent studies of methylmercury toxicity to selected wildlife species have been
carried out, the available data are, in general, quite limited, and the extent to which these results can be
extrapolated from the laboratory to the field and from one species to another remains in question. Two related
issues that may contribute substantially to this uncertainty are singled out for special attention. These are hepatic
demethylation as a mechanism for detoxification of methylmercury and the ameliorative effects of dietary
selenium.
The protective effect of selenium against methylmercury toxicity to birds has been known for over
twenty-five years (Ganther et al., 1972). Koeman et al. (1973) found that mercury and selenium occur in a 1:1
molar ratio in the livers of several marine mammal species. Previously, it had been shown that much of the
mercury in the livers in marine mammals existed in an inorganic form. It is now known that these observations
are related. Although efforts to elucidate the exact mechanism continue, selenium has been shown to bind
mercury after hepatic demethylation of methylmercury. The compounds formed in this manner probably include
both mercury-selenoproteins and HgSe (Palmisano et al., 1995; Cavalli and Cardellicchio, 1995).
Thus, it appears that many vertebrate species possess a capability to detoxify and sequester mercury
originating as methylmercury in the diet. Moreover, the extent to which this capability is developed appears to
be related to an animal's feeding habits and is most highly developed in fish-eating marine mammals and the
carnivorous polar bear (Dietz et al., 1990). Correlations between selenium and mercury have also been reported
for several seabirds, although the Se/Hg ratio may be higher than 1:1 (Elliott et al., 1992). The capacity of this
system to detoxify methylmercury is largely unknown. Variable detoxification among individuals of a single
species (pilot whales) has been demonstrated; lactating females demonstrated a significantly diminished
detoxifying capability (Caurant et al., 1996).
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The demethylating capabilities of birds and mammals that inhabit terrestrial and freshwater ecosystems
are less well known. Methylmercury constituted 46% of total mercury in the livers of mink fed a diet of
methylmercury-contaminated fish (Jernelov et al., 1976). There was no obvious relationship between levels of
liver mercury and selenium. Similar values were reported by Wren et al. (1986) for mink (53%) and otter (34%).
Barr (1986) found that methylmercury comprised 4-27% of total mercury in livers from loons taken from
mercury-contaminated waters in northwestern Ontario. Selenium concentrations were not measured.
Interestingly, the percentage of methylmercury did not vary with the gradient of site contamination, as might be
expected if the demethylating system was saturated at particularly high exposure levels. A positive correlation
between liver mercury and selenium was reported in the goldeneye, but no attempt was made to identify mercury
species (Eriksson et al., 1989). Although limited to a single study, evidence suggests that demethylation of
methylmercury also occurs in some birds of prey (Norheim and Forslic, 1978).
Additional evidence that this detoxifying pathway is related to animal feeding habits is provided by
Fimreite (1974). Among adult ducks, fish-eating mergansers exhibited the lowest levels of methylmercury as a
percent of total (12% in the liver). Methylmercury constituted 32%, 38% and 52% of total mercury in the livers
of goldeneyes, mallards and pintails. Moreover, this detoxifying ability appears to develop early in life.
Methylmercury levels as a percent of total in livers taken from ducklings were 27%, 49%, 53% and 58% in the
merganser, mallard, goldeneye and pintail. Methylmercury levels in breast muscle from all four species as a
percent of total were essentially identical, averaging about 60%.
The protective effect of selenium against mercury toxicosis may vary with lifestage and the chemical
form of selenium. Selenium as selenomethionine (10//g/g) protected adult male mallards against the toxic effects
of methylmercury (10//g/g) in the diet. However, a combination of these treatments in hen mallards resulted in
adverse reproductive effects greater than those seen with mercury or selenium alone. These effects included
reduced hatching success and survival of ducklings, including an increase in teratogenic impacts (Heinz and
Hoffman, 1996). Methylmercury in the diet greatly increased selenium storage in tissues. The livers of male
mallards fed only selenium contained 9.6//g/g selenium, whereas in mallards fed both selenium and
methylmercury, the livers contained an average of 114//g/g selenium. This observation is important because high
concentrations of selenium are known to produce teratogenic effects in wild birds (Ohlendorf et al., 1986). The
ecological significance of these findings remains to be determined. Data summarized above suggest that, among
duck species, mallards possess less capability to detoxify methylmercury than piscivorous mergansers and
goldeneyes. In addition, the levels of mercury and selenium employed in this study are well above those known
to cause toxic effects when applied separately.
To summarize, many, if not most, birds and mammals possess a capability to detoxify methylmercury,
and the activity of this system appears to be related to an animal's feeding habits. This conclusion is significant
for at least two reasons: (1) the toxicity of methylmercury to birds and mammals may be highly dependent upon
the availability of dietary selenium and (2) most toxicity tests with birds conducted to date have been carried out
using non-piscivorous species that may not possess a well-developed demethylating capability.
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4.6 Combined Effects of Mercury and Other Chemical Stressors
In most aquatic systems mercury is but one of many potential chemical stressors. Using current
assessment methods, there is a general tendency to evaluate the toxic potential of compounds applied
individually. A notable exception is the use of toxic equivalency factors (TEQs) to predict the combined impact
of compounds that act through an Ah receptor-mediated mode of action (PCBs, dioxins). Applying this approach
to a mixture of mercury and PCBs would be difficult, however, due to differences in chemical modes of action.
It is of interest, therefore, to note that the effects of PCBs and methylmercury, singly and in combination,
have been evaluated in mink (Wren et al., 1987a,b). Growth and survival of kits were reduced by a combined
exposure to PCBs (Arochlor® 1254) and methylmercury at concentrations that individually produced no
response. The authors of these studies described this outcome as a "synergistic effect." Given the limited
number of dose levels (0.0, 0.5 and 1.0 (ig/g), however, it would be difficult to rule out an additive response.
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5. ASSESSMENT OF THE RISK POSED BY AIRBORNE MERCURY EMISSIONS
TO PISCIVOROUS AVIAN AND MAMMALIAN WILDLIFE
5.1 Scope of the Assessment
As described in Chapter 2 of this Volume, mercury bioconcentrates, bioaccumulates and biomagnifies in
aquatic food chains. These processes result in mercury residues in fish that are much higher than concentrations
in the water in which they live, thereby providing an enriched contaminant source for piscivorous avian and
mammalian wildlife. Existing data permit a general treatment of mercury exposure and effects on such
populations. A more accurate assessment of the risk posed by mercury to a specific group of animals occupying
a given location requires the collection of necessary supporting information such as food habits, migratory
behavior, breeding biology, and mercury residues in preferred
prey items.
A general summary of ecological risk assessment methods is provided by U.S. EPA (1996) in its
Proposed Guidelines for Ecological Risk Assessment. The data needs of these methods vary widely and dictate
to a considerable degree which methods can be applied to a given situation. Guidance is provided in Section 5.2
on the risk assessment methods that may be most applicable to airborne mercury emissions, given the nature and
extent of currently existing information. Additional guidance is provided in Section 5.3 based on a review of
published assessments for piscivorous species living in the Great Lakes region, south Florida, central Ontario,
and coastal regions of Georgia, South Carolina and North Carolina.
The scope of the present Report was intended to be national in scale. It was determined, therefore, that
any effort to assess the risk of mercury to a given species living in a defined location would be inappropriate.
Instead, an effort was made to compare mercury exposure and effects in a general way using data collected from
throughout the country and in so doing to develop qualitative statements about risk.
Consistent with this broader-scale approach, an effort is made in Section 5.4 to derive a wildlife criterion
level (WC) for mercury that is protective of piscivorous wildlife. This WC is defined as the concentration of
mercury in water that, if not exceeded, protects avian and mammalian wildlife populations from adverse effects
resulting from ingestion of surface waters and from ingestion of aquatic life taken from these surface waters. The
health of wildlife populations may, therefore, be considered the assessment endpoint of concern. Although not
generally derived for the purpose of ecological risk assessment, WC values incorporate the same type of exposure
and effects information used in more standard approaches. Such calculations also provide for a simple
assessment of risk in any given situation, i.e., by determining whether the concentration of mercury in water
exceeds the criterion value.
Calculation of a WC for mercury is based upon the use of a wildlife reference dose approach, combined
with knowledge of the extent to which mercury becomes concentrated in aquatic food chains. The methods used
to calculate this criterion value are based on those described in the Proposed Great Lakes Water Quality
Guidance for the Great Lakes Water Quality Initiative (U.S. EPA, 1993c) and implemented in the final Water
Quality Guidance for the Great Lakes System (U.S. EPA, 1995b), henceforth referred to as the "Proposed
Guidance" and "Final Guidance," respectively. When originally implemented in support of the Great Lakes
Water Quality Initiative (GLWQI), this approach yielded a single measurement endpoint, which was the total
mercury concentration in water that was believed to be protective of piscivorous wildlife. In the present
assessment, an effort is made to update the WC for mercury by calculating its value using data for
methylmercury. It should be noted that a methylmercury-based WC can still be related to total mercury residues
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in fish or water through the use of appropriate conversion factors. By convention, mercury concentrations in
environmental media (and in dosing solutions) are usually expressed as //g/g of elemental mercury, regardless of
the identity of the mercury species. This convention is retained throughout the present analysis.
Methylmercury BAFs for trophic levels 3 and 4 (forage fish and larger, piscivorous fish, respectively) are
estimated in Appendix D of Volume III. This information is summarized in Section 5.4.2 of the present Volume.
It is recognized that there is considerable natural variability with respect to the accumulation of mercury in
aquatic food chains, which contributes in turn to variability in trophic relationships and BAFs. In addition, there
is a lack of understanding of fundamental processes that contribute to methylation of mercury and subsequent
bioaccumulation in aquatic organisms. Additional uncertainty derives from ongoing improvements in sampling
technique and analytical methodology. A review of uncertainties associated with the derivation of WC values is
provided in Section 5.4.11. In general, the same uncertainties apply to any risk assessment effort for mercury in
wildlife.
Tempering these uncertainties is a large and growing volume of both laboratory and field data for
mercury. From the perspective of WC development, field data are of particular interest. The GLWQI stipulates
that when sufficient field data are available, field-derived BAFs should take precedence over values estimated
from laboratory studies or by employing empirical relationships (e.g., correlation with chemical hydrophobicity).
The focus of the BAF analysis in this Volume is on incorporating recent field data into the revised GLWQI
approach. The results of this effort are summarized in Section 5.4.2.3.
5.2 Summary of Relevant Risk Assessment Methodologies
Perhaps the most comprehensive type of risk assessment that can be attempted is a comparison of
statistical distributions of exposure and effects information. In essence, risk is determined from the degree of
overlap of these distributions. Linearization of the effects and exposure distributions simplifies such
comparisons. This is generally accomplished by log transformation of the cumulative exposure and effects
distributions (U.S. EPA, 1996; SETAC, 1994). A particularly good example of such an assessment is provided
by Solomon et al. (1996) for atrazine in aquatic systems.
The data requirements of such an approach are extensive. Moreover, it is critically important that effects
information be collected under conditions that are comparable to the exposure data. For this reason, the approach
is most easily applied in circumstances where the effects are expressed after a relatively short period of exposure
and the compound of interest does not bioaccumulate. Both of these criteria are satisfied for a compound like
atrazine.
Mercury presents a far greater challenge by virtue of the fact that it bioaccumulates for extended periods
of time and because toxic effects occur only after sufficient body residues are attained. Moreover, the limited
data collected to date permit the characterization of a dose-response curve for only three or four wildlife species.
A more feasible approach to assessing chemical risk to wildlife species involves the comparison of a
point estimate of effect with a statistical distribution of exposure (U.S. EPA, 1996). The data needs of this
approach include one or a few toxicity studies from which an appropriate toxicity endpoint can be determined
and sufficient exposure data to define the distribution. In the simplest application of this approach for a
compound such as mercury (for which the diet is the primary route of uptake), exposure would be expressed as a
residue concentration in prey. Risk would then be characterized as the probability that exposure (prey
concentration) would exceed a given effect level. Alternatively, exposure can be characterized as a contact rate
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(mass of compound consumed/kg bw/d). Although more data intensive, this latter approach is preferred because
it better reflects the long-term nature of the exposure.
An even simpler approach to wildlife risk assessment expresses risk as the ratio of exposure and effects
point estimates. Often referred to as the "hazard quotient" method, this approach is by far the most commonly
used of all current techniques. It may also be the most intuitive, since risk is inferred by the simple fact of a ratio
approaching or exceeding 1.0. The disadvantage of this approach is that is does not permit a probabilistic
assessment of risk. Moreover, because this approach is generally used when more detailed data are lacking, risk
assessors often adjust the effect level downward using one or more "safety factors."
In the following Section, several published efforts to assess the risk of mercury to wildlife are reviewed.
These efforts illustrate the point that while information needed to perform such assessments are extremely
limited, effects information are in general more limited than exposure data.
5.3 Review of Published Efforts to Estimate the Risk of Mercury to Wildlife
5.3.1 Risk of Mercury to Bald Eagles in the Great Lakes Region
Bowerman et al. (1994) compared feather mercury data with measures of reproductive performance to
evaluate the risk of mercury to bald eagles in the Great Lakes Region. Although no attempt was made to develop
a quantitative estimate of risk, it was determined that there was no association between mercury residues in
feathers and either productivity or nesting success. On this basis, it was concluded that mercury was not
affecting bald eagle reproduction. A conclusion of this type may be characterized as a qualitative statement of
risk.
5.3.2 Risk of Mercury to Bald Eagles in Michigan
Giesy et al. (1995) used a hazard quotient approach to characterize the risk to bald eagles posed by
mercury and several organic compounds at locations above and below dams on three Michigan rivers. An
exposure point estimate for mercury was calculated from measured concentrations in fish and an egg:fish
biomagnification factor (set equal to 1.0). Hazard quotients ranging from 0.15 to 0.98 were calculated for
mercury at study sites on the three rivers. The highest quotients were calculated for sites above the dams due to
the presence of higher mercury levels in fish. The authors concluded that mercury does not pose a significant
threat to eagles living in this region. This conclusion was based upon the opinion that the NOAEC level used in
the analysis (0.5 (ig mercury/g egg) was conservative, as well as the suggestion that eagles consume only small
quantities of the most contaminated fish species (yellow perch and walleye) living in these rivers. Hazard
quotients for PCBs and TCDD (equivalents) were much greater than 1.0 (ranging from 7.6 to 76) at all sites
downstream from the dams.
5.3.3 Risk of Mercury to Loons in Central Ontario
Scheuhammer and Blancher (1994) assessed the risk of mercury to loons by comparing residues in fish
collected from central Ontario lakes with a threshold value for reproductive impairment. A strength of this
assessment is that the toxic effects point estimate was also determined in a study of wild loons (Barr, 1986). The
fish selected for this analysis were of a size appropriate to predation by loons. Care was also taken to survey
lakes of the type preferred by breeding loons. Among the lakes surveyed, up to 30% contained fish which
exceeded the toxicity threshold, depending upon the species offish chosen.
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5.3.4 Risk of Mercury to Mink in Georgia. North Carolina, and South Carolina
Osowski et al. (1995) assessed the risk of mercury, PCBs and several chlorinated organic pesticides to
mink in the coastal regions of southeastern U.S. The risk associated with mercury was determined by comparing
residue levels in kidney tissue with levels that had been associated previously with toxic effects. Unfortunately,
the threshold effect level (tissue residue) was not given. It is difficult, therefore, to critically evaluate the
author's conclusion that residues "were in the range of those known to cause impacts to reproduction, growth,
and behavior in wild mink."
5.3.5 Risk of Mercury to Mink in Michigan
A second assessment for mink was conducted by Giesy et al. (1994) for animals living on three rivers in
lower Michigan. In this assessment, an effort was made to calculate a hazard quotient using published toxicity
data for mink (Wobeser, 1976a,b) and measured residues in fish collected from the study sites. Interestingly,
hazard quotients greater than 1.0 were calculated at all three sites (range of 1.2-6.6). However, the significance
of this finding was minimized because hazard quotients calculated for PCBs and TCDD-like compounds tended
to be higher. In this regard, it is of interest to note previous studies in which mercury and PCBs appeared to act
"synergistically" in toxicity studies with mink (see Section 4.6 of this volume).
5.3.6 Risk of Mercury to Great Egrets in south Florida
Sundlof et al. (1994) reported on another researcher's use of the hazard quotient method to assess the risk
of mercury to great egrets in south Florida. The actual assessment was conducted as part of a Masters degree
research program (Jurczyk, 1993). For this assessment, a published LOAEL for reproductive effects in loons
(Scheuhammer, 1991) was compared to a methylmercury consumption rate calculated using measured residues in
local fish and shellfish. Based upon this analysis, it was concluded that great egrets were consuming 3.9 times
the LOAEL, thus placing the population at risk.
5.4 Calculation of a Criterion Value for Protection of Piscivorous Wildlife
5.4.1 Procedure Used to Develop Criterion Values for Wildlife in the Water Quality Guidance for the Great
Lakes System
The WC for mercury is defined as the concentration of total mercury in surface water that, if not
exceeded, protects both avian and mammalian wildlife that use the water as a drinking or foraging source. Thus,
the WC is the highest aqueous concentration of mercury that causes no significant reduction in growth,
reproduction, viability or usefulness (in a commercial or recreational sense) of a population of animals exposed
over multiple generations. For the purpose of this analysis, the term "aqueous concentration" refers to the
concentration of methylmercury in filtered water, including both the freely dissolved form and methylmercury
that is associated with dissolved organic material.
The equation used in this analysis to calculate a WC for mercury is identical to that described in the
Proposed Guidance (U.S. EPA, 1993c) and implemented in the final Water Quality Guidance for the Great Lakes
System (U.S. EPA, 1995b):
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(TD x \\IUF]) x Wt,
we = A
WA + [(FD,)(FA x BAF,) + (FD4)(FA x BAF4)]
where
WC = wildlife criterion value (pg/L; after converting from //g/L)
WtA = average species weight (g)
WA = average daily volume of water consumed (L/d)
FA = average daily amount of food consumed (g/d)
FD3 = fraction of the diet derived from trophic level 3
FD4 = fraction of the diet derived from trophic level 4
BAF3 = aquatic life bioaccumulation factor for trophic level 3 (L/g; methylmercury
concentration in fish/methylmercury in water)
BAF4 = aquatic life bioaccumulation factor for trophic level 4 (L/g; methylmercury
concentration in fish/methylmercury in water)
TD = tested dose (//g/g bw/d)
UF = uncertainty factor
A similar equation was first used by the State of Wisconsin to set Wild and Domestic Animal Criteria
(State of Wisconsin, 1989). The entire approach, including both the equation and data requirements for its
parameterization, was later modified by U.S. EPA for incorporation into the Proposed Guidance (U.S. EPA,
1993c) and Final Guidance (U.S. EPA, 1995b). The method, in its current form, was reviewed in 1992 at a
workshop entitled "The National Wildlife Criteria Methodologies Meeting," which was sponsored by U.S. EPA
(U.S. EPA, 1994). Subsequently, the method was used to develop interim Tier I WC for four compounds (PCBs,
DDT, dieldrin, and mercury) in the Great Lakes Basin (U.S. EPA, 1993b). These criteria have received public
comment. The method has been reviewed by EPA's Science Advisory Board on two occasions, most recently in
June of 1994. Detailed descriptions of the method, including comparisons with other proposed methods for
setting wildlife criterion values, are given elsewhere (U.S. EPA 1993c, 1994).
An examination of the GLWQI equation reveals both a hazard and an exposure component. The
equation includes a term TD for "tested dose." In this Report, data were reviewed to determine an appropriate
NOAEL, which was used for the TD. In the absence of a NOAEL, a LOAEL was used with the addition of an
appropriate factor (UFL) to indicate uncertainty around the toxic threshold. An uncertainty factor (UFA) also may
be used to provide a margin of safety when applying data from a species other than the species of concern. A
third uncertainty factor (UFS) may be used to extrapolate from subchronic to chronic exposures. Additional
adjustments may be warranted by toxicokinetic or toxicodynamic considerations. Collectively, the application of
the UF to the TD results in the estimation of a "reference dose" (RfD) for subsequent calculation of the WC.
The WC for mercury derived in support of the GLWQI was expressed as the total mercury concentration
in filtered water. Although it was recognized at the time that methylmercury is the form of mercury that
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bioaccumulates in fish, few laboratories possessed the analytical capability to speciate mercury in water from
natural sources.
A WC for mercury was calculated in the Proposed Guidance using fixed values for all parameters in the
equation. Species-specific WC values (WC) were calculated for each of the wildlife species of concern (eagle,
herring gull, kingfisher, mink, otter). Intermediate WC values (WCj) were then obtained for avian and
mammalian wildlife by calculating the geometric mean of values for contributing species. The final WC (WCf)
was set equal to the lowest of the two resulting intermediate values and, for mercury, was driven by the
calculations for avian species.
The WCf for mercury derived in the Proposed Guidance is 1300 pg/L. A comparison of the GLWQI
criteria for birds and mammals with those derived in this Report is presented in Section 5.4.8 of this Volume.
For the present analysis, a decision was made to consider all but one of the wildlife species considered in
the Proposed Guidance. Herring gulls, which are indigenous to the Great Lakes region, are not evaluated in this
Report. The herring gull was replaced in the present analysis by the common loon (Gavia immef). The other
avian wildlife for which WC values are calculated are the bald eagle (Haliaeetus leucocephalus), osprey
(Pandion haliaetus) and belted kingfisher (Ceryle alcyori). The mammalian wildlife for which WC are calculated
are the mink (Mustela visori) and river otter (Lutra canadensis). Each of these species was originally selected
after consideration of the following: (1) their exposure to bioaccumulative contaminants; (2) their relevance to
Great Lakes ecosystems; (3) the availability of information with which to calculate criterion values; and (4) the
evidence for accumulation and/or adverse effects.
Several other wildlife species would satisfy most or all of the selection criteria presented in the GLWQI.
Notable examples include the double-crested cormorant (Phalacrocorax auritus), Forster's tern (Sterna forsterf),
wood stork (Mycteria americand), raccoon (Procyon lotof), snapping turtle (Chelydra serpentind), and American
alligator (Alligator mississippiensis). Exposure factors for a large number of wildlife species are available in a
recently published handbook (U.S. EPA, 1993a). A critical evaluation of these data as they pertain to the
development of WC is also available (U.S. EPA, 1995a). Allometric equations may also be used to calculate
both feeding and drinking requirements (see for example Calder and Braun, 1983; Nagy, 1987). In time, the
inclusion of other species, including both amphibians and reptiles, may be appropriate, particularly if an effort is
made to calculate WC on a regional basis or if the species used in the present analysis are not representative of
the ecosystem of concern. The present analysis is intended, however, to be national in scope. Each of the species
selected for this analysis is distributed over large portions of the country (see species distributions in Section 3.3
of this Volume), and in these locations each species is closely tied to water resources via aquatic food chains.
Finally, this analysis differs from that of the GLWQI insofar as WC values are calculated on a
"dissolved" (freely dissolved and associated with DOC) methylmercury basis. A review of literature collected
over the last several years suggests that there is now sufficient information available to estimate BAFs for
mercury on a methylmercury basis. Previously, it was thought that much of the variation around BAFs estimated
on a total mercury basis could be attributed to differences among water bodies in the proportion of total mercury
existing as the methylated form. The goal of the present analysis was to calculate a WC for the bioaccumulating
form of mercury, thereby yielding an estimate with the lowest possible variation around the mean.
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5.4.2 Bioaccumulation Factors (BAFs) for Magnification of Methylmercury in Aquatic Food Chains
5.4.2. 1 Definition of BAFs and Overview
The bioaccumulation factor (BAF) for any given trophic level is defined as the ratio of methylmercury
concentration in fish flesh divided by the concentration of dissolved methylmercury in the water column. The
BAF represents the accumulation of mercury in fish of a specific trophic level from both direct uptake from water
and predation on contaminated organisms. The BAF is a principal input variable in the GAS ISC3 exposure
model used in Volume III of this Report to link estimates of mercury deposition to exposure levels for fish-
consuming species.
In this Report, BAFs are estimated for trophic level 3 (foraging fish) and trophic level 4 (piscivorous
fish), which are designated as BAF3 and BAF4, respectively. BAF4 is estimated by three different methods and
BAF3 is estimated by two different methods. The result, or output, of each estimation method is a distribution of
BAF values, each associated with some degree of likelihood. The three methods by which BAF4 is estimated are:
a modified GLWQI method, a BAF x ppp method, and a direct field-derived method from measured BAFs at
trophic level 4. BAF3 is estimated by the modified GLWQI method and directly from measured BAFs at trophic
level 3. These methods are summarized in Section 5.4.2.2 of this Volume and described in detail in Appendix D
to Volume III (Appendix D also describes two BAF approaches for total mercury). BAF4 is intended to be
representative of the random selection of a trophic level 4 fish from a random lake in a random geographical
location. It is meant to be used to estimate the concentration of methylmercury in such a randomly-selected fish
when multiplied by the dissolved methylmercury concentration. BAF3 performs the same function for trophic
level 3 fish.
The general approach used in this analysis was based on probabilistic methods, as described in Appendix
D to Volume III. This approach was taken to allow quantitative expression of the overall variability surrounding
the various estimates of the BAFs and to determine the relative sensitivity of the estimates to specific individual
variables.
5.4.2.2 BAF Estimation Methods
Modified GLWQI Method
The GLWQI method is essentially the same as that in the Proposed Guidance (U.S. EPA, 1993c),
modified to consider only methylmercury, and based entirely on field-derived BCFs and PPFs. The formula is
given in equation 1 .
BAFn = BCFx FCMn (1)
where
n is the trophic level for which the BAF is estimated,
BCF is the weighted-average bioconcentration factor (BCF) for dissolved methylmercury at
trophic level 1, and
FCMn is the food-chain multiplier representing the cumulative biomagnification of
methylmercury from trophic level 2 to trophic level n, n=[3,4].
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The formulas for FCM3 and FCM4 are given in equations 2 and 3, respectively.
FCM3 = PPF2 x PPF3 (2)
FCM4 = PPF2 x PPF3 x ppp4 (3)
where
PPF2 is the predator-prey factor at trophic level 2 representing the biomagnification of
methylmercury in zooplankton as a result of feeding on contaminated phytoplankton,
PPF3 is the same for trophic level 3 fish feeding on contaminated organisms, and
PPF4 is the same for trophic level 4 fish feeding on trophic level 3 fish.
Distributions were assigned to each of the variables in equations 1-3 based on data available in the
published literature. The basis and description of the distribution for each variable are described in Appendix D
of Volume III. The nominal values for some of the variables are not the same as presented in the Proposed
Guidance (U.S. EPA, 1993c) due to differing assumptions and approaches to data analysis.
BAF x PPFMethod
The formula for the calculation of BAF4 by this method is given in equation 4.
BAF4 = BAF3 x PPF4 (4)
where
BAF3 is the field-measurement-derived distribution for the BAF at trophic level 3 and
PPF4 is the same as for the GLWQI method.
Field-derived (Direct) Method
This method estimates BAF3 and BAF4 directly from measurements of BAFs in field studies. The
derivation of the BAF distributions is described in Appendix D of Volume III.
5.4.2.3 Results of BAF Simulations and Recommended Values
Results of the probabilistic simulations for each of the methods are given in Table 5-1, which shows
representative statistics for each BAF output distribution. All of the statistics are given as the geometric
equivalents (antilogs) of the actual values generated by the simulations. There is a large variance in the
distributions, which cannot be separated into variability in BAFs and uncertainty in their estimation.
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Table 5-1
Summary of Methylmercury Bioaccumulation Factors for Trophic Levels 3 and 4
(mean, 5%, and 95% values)
Recommended
Method
Median (GMa)
5th pctl
95th pctl
GSDb
BAF3
1,600,000
Direct
Field-derived
1,600,000
461,000
5,410,000
2.12
GLWQI
1,300,000
71,500
2,440,000
5.88
BAF4
6,800,000
BAF3x
PPF4
7,820,000
1,960,000
31,100,000
2.32
Direct
Field-derived
6,800,000
3,260,000
14,200,000
1.56
GLWQI
6,500,000
331,000
129,000,000
6.13
a Geometric Mean
b Geometric Standard Deviation
The recommended BAFs are those developed from field data at each trophic level. Values estimated
using the GLWQI methodology are similar in each case to those estimated from field data but show much greater
variability. This greater variability is not surprising given the greater number of variables and paucity of data for
the GLWQI approach (see Appendix D of Volume III). Only four field-derived data points were available to
characterize the BAF3 and BAF4 distributions. In each case, however, these data points were in relatively good
agreement, resulting in narrower statistical distributions that those associated with the GLWQI and BAF3 x PPF4
approaches.
The GLWQI stipulates that when high quality field data are available, BAFs developed from these data
should take precedence over values estimated using laboratory data. At the time of its development, the field
data needed to estimate BAFs for the GLWQI were not available. Recently collected field data are thought to be
sufficient to generate accurate estimates of mean BAFs for trophic levels 3 and 4. Confidence in estimates of the
geometric standard deviations is lower. Additional data from a broader array of ecosystem types are needed to
better characterize the shapes of these distributions.
5.4.2.4 Sensitivity Analysis
A limited sensitivity analysis was conducted to examine the influence of distribution form on the BAFs
estimated by the direct field-derived method. The analysis investigated the impact on the output of assuming the
BAFs were distributed normally rather than lognormally. The difference in the two assumptions was small, with
slightly higher median estimates for the normal distributions and slightly higher upper percentiles for the
lognormal. The empirical data more closely matched the lognormal form. This analysis is presented in
Appendix D of Volume III.
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5.4.2.5 Uncertainty and Variability
Generally, in the representation of the input and output distributions, there are no distinctions as to size
or species offish, location or type of lake (eutrophic or oligotrophic), water column pH, or absolute mercury
concentrations (in fish or water). The available data are insufficient to make these distinctions. Field data are
heavily biased towards northern (oligotrophic) lakes and somewhat towards smaller (younger) fish.
There is no distinction between variability and uncertainty in the BAF4 distributions. That is, the
variability in the output distributions reflects both naturally variable processes and the uncertainty around those
processes. For example, the BAF4 distributions include variability in the BAF associated with variations in fish
size combined with measurement uncertainties.
Perhaps the greatest source of variability is that of model uncertainty; i.e., uncertainty introduced by
failure of the model to account for significant real-world processes. In lake surveys conducted within a relatively
restricted geographic region, large differences can exist between lakes with respect to mercury concentrations in
a given species offish (see for example Cope et al, 1990; Grieb et al, 1990; Sorenson et al., 1990; Jackson,
1991; Lange et al., 1993). Although much of this variability can be attributed to local biogeochemical processes
that determine the percentage of total mercury that exists as the methylated form, additional sources of variability
undoubtedly exist. In addition, it has been repeatedly shown that mercury in fish accumulates throughout the
lifetime of the individual (Scott and Armstrong, 1972; MacCrimmon et al., 1983; Wren et al., 1983; Mathers and
Johansen, 1985; Skurdal et al., 1985, Wren and MacCrimmon, 1986; Sorenson et al., 1990; Jackson, 1991;
Gutenmann et al., 1992; Glass et al., 1993, Suchanek et al., 1993; Lange et al., 1993). Reported BAF values for a
given species may, therefore, vary as a function of the ages of the animals examined. As a result, some
researchers have suggested that comparisons between lakes should be made using "standardized" fish values
(e.g., a value for a hypothetical 1 kg northern pike), typically derived by linear regression of residue data
collected from individuals of varying size and/or age (Wren and MacCrimmon, 1986; Sorenson et al., 1990;
Meili et al., 1991). An additional source of variability is seasonal variation of dissolved methylmercury in the
water column. While the concentration of methylmercury in fish flesh is presumably a function of the varying
water concentration, specific values for BAF4 and BAF3 are generally calculated from single representative
values.
5.4.2.6 Conclusions
BAFs derived from adequate data collected at a site of concern should be used in lieu of the estimated
values presented in this Report. The criteria for defining the adequacy of data are discussed in the Data Quality
Objectives section of Appendix D in Volume III. When such values are not available, the use of the geometric
mean values from the BAF3 and BAF4 output distributions generated from the direct field-derived distributions is
the recommended approach. Use of the geometric mean, rather than the arithmetic mean, is a consequence of the
assumption that BAFs are distributed in nature as the logarithm of the observed value. The recommended
approach is more direct and less variable than the GLWQI method and involves fewer assumptions. The
recommendation as to the use of the (geometric) mean value of these distributions is based on the inability to
distinguish among various sources of uncertainty and variability in the output distributions, with consequent
problems of interpretation of specific percentiles. Because the exposure concern is for repeated ingestion of
contaminated fish, the mean, rather than the median, is the appropriate value. The median is only useful when
the concern is the random selection of a single fish.
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Reducing the uncertainty in the BAFs generated by these methods will require the collection of more data
representative of the critical factors underlying the observed variability and the inclusion of additional terms to
explicitly model those factors. For example, the inclusion of an age/size regression term would account for a
substantial portion of the variability in both BAF4 and PPF4.
5.4.3 Exposure Parameters
Exposure parameters for the present analysis are shown in Table 5-2. The scientific basis for parameters
that apply to the mink, otter, kingfisher, osprey and eagle is reviewed elsewhere (U.S. EPA 1993a, 1995a). The
weight of loons was calculated as the average of values reported by Barr (1986) for adult males and females, and
the feeding rate was taken from Barr (1973). Data provided by Barr (1996) suggest that, when given the
opportunity, loons feed almost exclusively on live fish and that these fish belong almost exclusively to trophic
level 3.
Table 5-2
Exposure Parameters for Mink, Otter, Kingfisher, Osprey, and Eagle
Species
Mink
Otter
Kingfisher
Loon
Osprey
Eagle
Body Wt.
(WtA)
kg
0.80
7.40
0.15
4.00
1.50
4.60
Ingestion Rate
(FJ
kg/d
0.178
1.220
0.075
0.800
0.300
0.500
Drinking Rate
(WA)
L/d
0.081
0.600
0.017
0.120
0.077
0.160
Trophic Level of
Wildlife Food
Source
3
3,4
3
3
3
3,4
% Diet at
Each
Trophic
Level
90
80,20
100
100
100
74,18
For this analysis, it was assumed that prey not attributed to trophic levels 3 and 4 were derived from non-
aquatic origins and do not contain mercury. Were these prey to contain mercury, WC values calculated for the
relevant species would decrease. BAFs for trophic levels 3 and 4 were assigned the values recommended in
Section 5.4.2.3 of this Volume.
5.4.4 Summary of Health Endpoints for Avian and Mammalian Wildlife
The avian chronic TD value was derived from studies by Heinz (1975, 1976a,b, 1979) in which three
generations of mallard ducks (Anas platyrhynchos) were dosed with methylmercury dicyandiamide (0, 0.5 and
3.0 ppm) (see Section 4 of this Volume). The lowest dose, 0.5 ppm (78 //g/kg bw/d), resulted in adverse effects
on reproduction and behavior and was designated as a chronic LOAEL. As no NOAEL was reported, a UFL of 3
was used according to methodology described in U.S. EPA (1995b). In a departure from the GLWQI, a decision
was made not to adjust this value further using a species-to-species uncertainty factor (UF^ greater than 1.0.
Although no toxicity data are available for any of the bird species of interest, a review of the literature suggests
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that piscivorous birds possess a greater capability to detoxify methylmercury than do non-piscivorous birds (see
Section 4 of this volume). Adjusting the TD for mallards even lower is, therefore, unjustified.
The mammalian chronic NOAEL was derived from studies of subchronic exposure by Wobeser (1973,
1976a,b) in which mink were dosed with mercury in the form of mercury-contaminated fish (0.22 and 0.33 ppm,
naturally incorporated into fish; 1.1, 1.8, 4.8, 8.3 and 15.0 ppm, spiked into the diet). Effects observed include
histopathologic lesions in nerve tissue at 1.1 ppm and higher doses. Anorexia, ataxia and death occurred at 1.8
ppm and higher doses. The dose of 0.33 ppm (55 //g/kg bw/d) was selected as the NOAEL for subchronic
exposure. As this was a less than lifetime study, a UFS of 3 was applied to the TD or NOAEL. The value of this
uncertainty factor is less than the value employed in the GLWQI (10). However, the authors of the GLWQI also
identified 1.1 ppm as the NOAEL, whereas this analysis considers the histopathological lesions seen in the 1.1
ppm dose group an adverse toxic effect. The subchronic NOAEL/UFS is 18.3 //g/kg bw/d, which is
approximately equal to the chronic NOAEL (20 //g/kg bw/d) estimated from long-term feeding studies with
domestic cats (Charbonneau et al., 1974).
Based on the information above, the TDs used for calculation of a WC for mercury were:
For avian wildlife - A LOAEL of 78 //g/kg bw/d.
For mammalian wildlife - A NOAEL of 55 //g/kg bw/d.
Dividing the avian TD by a UFL of 3 yields an avian RfD of 26 (ig/kg bw/d. A mammalian RfD of 18 (ig/kg bw/d
was calculated by dividing the mammalian TD by a UFS of 3.
5.4.5 Calculation of Wildlife Criterion Values
WC values were calculated for each of the wildlife species of concern using exposure values
recommended in Section 5.4.4.4. Calculations of WC values for each of the selected species follow.
The mean of the two WCS values calculated for mammals is 50 pg/L. The mean of the four avian values
is 74 pg/L. The lowest of these is the WC; calculated for mammalian species. Therefore, the WCf for
methylmercury is 50 pg/L.
For the mink:
wc _ (TD x [\I(UFA x UFS x UFL}}} x WtA
S TT7- FA
wc = (0.055 mglkgld x [11(1 x 3 x 1)]) x 0.8kg
s 0.081 L/d + [(0.9) (0.178 kgld x 1,600,000)]
WCS = 57 pg/L
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For the otter:
(TD x [\I(UFA x UFS x UFL)]) x WtA
WCS =
WA + [ (0.8) (FA x BAFJ + (0.2) (FA x BAFJ ]
= _ (0.055 mglkgld x [1/(1 x 3 x 1)]) x 7Akg _
s 0.60 Lid + [(0.8) (1.22 kgld x 1,600,000) + (0.2) (1.22 kgld x 6,800,000)]
WCS = 42 pg/L
For the kingfisher:
(TD x [1/(UFA x UFS x UFL)D x WtA
wcs =
WA + [(l.O)(FAxBAF3)]
wc = (0.078 mglkgld x [11(1 x 1 x 3)]) x 0.15 kg
s 0.017 + [(1.0) (0.075 x 1,600,000)]
WCS = 33 pg/L
For the loon:
(TD x [l/(UFA x UFS x UFL)]) x WtA
wcs-
WA + [(l.O)(FAxBAF3)]
wc = (0.078 mglkgld x [11(1 x 1 x 3)]) x 4.0 kg
s 0.012 Lid + [(1.0) (0.8 kgldx 1,600,000)]
, = 82 pg/L
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For the osprey:
(TD x [\I(UFA x UFS x UFL)]) x WtA
WCS =
WA + [(1.0)(FAxBAF3)]
wc = (0.078 mg/kg/d x [1/(1 x 1 x 3)]) x 1.5 kg
s 0.077 Lid + [(1.0) (0.3 kg/d x 1,600,000)]
, = 82 pg/L
For the bald eagle:
(TD x [1/(UFA x UFS x UFL)]) x WtA
wcs =
WA + [(0.74) (FA x BAFJ + (0.18) (FA x BAF4]
wc = (0.078 mglkgld x [17(1 x 1 x 3)]) x 4.6 kg
s 0.16 L/d + [ (0.74) (0.5 kgld x 1,600,000) + (0.18) (0.5 kgld x 6,800,000)]
WCS = 100 pg/L
5.4.6 Calculation of Mercury Residues in Fish Corresponding to the Wildlife Criterion Value
The WC for methylmercury, along with appropriate BAFs, can be used to calculate corresponding
mercury residues in fish. Using the recommended BAFs presented in Table 5-1, a WC of 50 pg/L corresponds to
methylmercury concentrations in fish of 0.077 //g/g and 0.346 //g/g for trophic levels 3 and 4, respectively.
5.4.7 Calculation of the Wildlife Criterion Value for Total Mercury in Water
A WC for total mercury can be calculated using an estimate of dissolved methylmercury as a proportion
of total dissolved mercury in water. Mercury speciation data from filtered water samples are reviewed in
Appendix D of Volume III. Based upon a survey of these data, the best current estimate of methylmercury as a
proportion of total is 0.078. Using this value, a methylmercury WC of 50 pg/L corresponds to a total dissolved
mercury concentration of 641 pg/L. An additional correction is needed if the WC is to be expressed as the
amount of total mercury in unfiltered water. The available data, although highly variable, suggest that on average
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total dissolved mercury comprises about 70 percent of that contained in unfiltered water (Back and Watras, 1995;
Driscoll et al., 1995; Mason and Sullivan, 1997; Watras et al., 1995a). Making this final correction results in a
WC of 910 pg/L (unfiltered, total mercury), which is approximately 70 percent of the value published previously
in the GLWQI.
5.4.8 Calculation of a Wildlife Criterion for the Florida Panther
Estimates of the NOAEL and LOAEL in domestic cats were not used in the derivation of a WC for
Florida panthers, but were presented instead to provide a comparison with other mammals. The chronic NOAEL
for cats (20 //g/kg bw/d) is close to that derived from mink data (18.3 //g/kg bw/d). Cats, therefore, do not appear
to be uniquely sensitive or insensitive to the toxic effects of mercury.
Derivation of a WC to protect the panther is complicated by the possibility that prey items (e.g., the
raccoon) accumulate mercury to an even greater extent than the fish represented by trophic level 4. Other prey
(e.g., deer) probably contain relatively lower levels of mercury. Calculation of a WC protective of the panther,
therefore, requires collection of additional information on the diet of this species and mercury residues contained
therein. These residues would then have to be related to corresponding levels in water through the use of PPFs
(e.g., raccoon/fish or other aquatic biota) and BAFs (aquatic biota/water). Existing data are insufficient to
support such an analysis but could be collected and developed for this purpose.
5.4.9 Comparison of GLWQI Criteria with WC Derived in this Report
The evaluation of data and calculation of WC values in this Report was done in accordance with the
methods published in the draft GLWQI (U.S. EPA 1993a). The availability of additional data and differences in
interpretation of those data led to differences in the calculated values of the WC in this Report and those
published in the final GLWQI (U.S. EPA 1995b). Both evaluations employed the same methodology as
described in Section 5.4.1 of this Volume. Both used the same studies as the basis for WC calculation: for birds,
the three generation reproduction study in mallards (Heinz, 1974, 1975, 1976a,b, 1979) and, for mammals, the
subchronic dietary studies in mink (Wobeser et al., 1976a,b). In addition to these studies, this Report also relies
on Wobeser's dissertation (Wobeser, 1973), which provided some additional information that was augmented by
discussions with the author.
To provide a basis for comparing methylmercury WC values derived in this Report with values
calculated in the GLWQI, it was necessary to convert all methylmercury values to corresponding total mercury
estimates (see Section 5.4.6 of this Volume). Table 5-3 presents a comparison between the WC values calculated
in the GLWQI (U.S. EPA, 1995b) and this Report (converted to total mercury in unfiltered water). All of the
WC values calculated in this Report are lower (i.e., more conservative) than those published in the GLWQI. All
species-specific WC values, however, differ by a factor of three or less. Expressed as total mercury, the WC
derived in this Report is approximately 70 percent of the WC derived in the GLWQI.
In the evaluation of effects in birds, both the GLWQI and this Report identified a LOAEL for
reproductive effects in the second generation of mallards exposed to 0.5 ppm mercury in diet (Heinz 1976b,
1979). This LOAEL was adjusted to 0.078 mg/kg bw/d by applying an average food ingestion rate for treated
mallards of 0.156 kg/kg/d. In calculating the wildlife reference dose, the GLWQI used a UFA of 3 and a UFL of
2. This Report used a UFA of 1 andaUFLof3 (see Section 5.4.11.2 for a discussion of UFL).
In the effects assessment for piscivorous mammals, both the GLWQI and this Report used data on mink
administered mercury in the diet. The GLWQI identified a NOAEL of 1.1 ppm. At this dietary
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Table 5-3
Species-specific Wildlife Criteria Calculated in the Great Lakes Water Quality Initiative
(GLWQI)3 and in the Mercury Study Report to Congress
Species
Mink
Otter
Kingfisher
Osprey
Eagle
Wildlife Criterion
(Pg/L)
GLWQI
2880
1930
1040
Not done
1920
Mercury Study Report to Congress
1038
764
598
1498
1818
'U.S. EPA, 1995b
exposure, there were changes in the liver, lesions in the central nervous system, and axonal degeneration;
moreover, two of the animals in this treatment group were observed at the end of treatment to move slowly by
comparison to other mink. The study authors reported their opinion that mink treated at 1.1 ppm in the diet for
longer than the study would be expected to show clinical signs of nervous system damage. Animals treated at the
next dose, 1.8 ppm, were observed with anorexia, ataxia and increased mortality. Based on these considerations,
this Report considered 1.1 ppm to be a LOAEL and, as described in Section 4.3, used data from the first part of
the study to identify aNOAEL of 0.33 ppm. This Report also used data from Wobeser (1973) to establish the
weights of female mink and kits used in this part of the study; this resulted in slight differences in conversion of
dose in ppm diet to //g/kg bw/d
In its assessment of exposure to birds through consumption of prey, the GLWQI made assumptions that
were appropriate to the Great Lakes region. In particular the GLWQI assumed that mercury contaminated
herring gulls constitute 6% of the diet of bald eagles. As this Report is a nationwide assessment, use of this
region-specific assumption was not considered appropriate; eagles were assumed to consume non-fish prey, with
no mercury contamination, as 8% of the total diet. The largest numerical difference in the exposure assessment
between the GLWQI and this Report is in the calculation of BAFs. The GLWQI used a BAF of 27,000 for
trophic level 3 and a BAF of 140,000 for trophic level 4. Total mercury BAFs corresponding to the
methylmercury-based values reported in Table 5-1 (and assuming that methylmercury constitutes 7.8 % of total
mercury) are 124,800 and 530,400 for trophic levels 3 and 4, respectively.
Thus, the differences between the WC in the GLWQI and in this Report are a result of several factors.
First, this Report uses more recent data to derive BAFs. The Supplementary Information Document to the final
Water Quality Guidance for the Great Lakes System noted that a preliminary draft of the Mercury Report to
Congress was available but was not used because it had not been completed at the time the final guidance was
published (U.S. EPA 1995b, p. 144). Second, the GLWQI appropriately used some region-specific assumptions
that were not used in this nationwide assessment (e.g., consumption of herring gulls by eagles). Third, different
toxicity endpoints were used in this Report. In the GLWQI, a risk-management decision was made to base the
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WC on endpoints that comprise direct effects on growth, reproduction, or development. In this Report, more
sensitive endpoints were considered with the goal of assessing a greater range of toxic effects. Finally, different
uncertainty factors were employed in the two assessments. In general, uncertainty factors used in the GLWQI are
more conservative than those used in this Report.
5.4.10 Uncertainty Analysis
A formal analysis of uncertainty around the WC estimate was not attempted. Such an analysis would
require specification of numeric distributions for each of the parameters in the equation. Data for several of the
parameters in the equation, in particular the NOAEL and UF estimates, are presently sufficient to generate point
estimates only. A partial uncertainty analysis has been conducted for the bioaccumulation part of the WC
approach (see Appendix D of Volume III).
5.4.11 Sensitivity Analysis
In a sensitivity analysis, an attempt is made to characterize the extent to which a calculated value changes
with changes in the parameters upon which its calculation depends. Examination of the equation for calculation
of WC values suggests that a proportional relationship exists between the WC and the NOAEL, UF or WtA. The
relationships between the WC and parameters that appear in the denominator are not as apparent and must be
explored by varying these parameters one-by-one in systematic fashion. The analysis is also complicated by the
variable relationship that exists between FD3 and FD4. In the otter and eagle, FD3 and FD4 tend to be reciprocal
(although in the eagle these values do not add up to 1). In the mink, however, FD3 is assigned a value of less than
1, and the remainder of the diet is assumed to consist of prey that are not aquatic in origin and are not
contaminated with mercury.
Nevertheless, general conclusions can be reached regarding the sensitivity of WC estimates to changes in
these parameters. These can be described as follows:
• A decrease in any parameter that appears in the denominator will have a larger effect on WC
than an equivalent percentage-wise increase.
• When BAF3 appears alone in the denominator, a percentage-wise increase in BAF3 or FD3 will
cause a less than proportional decrease in the WC; conversely a decrease in BAF3or FD3 will
cause a greater than proportional increase in the WC.
• When both BAF3 and BAF4 appear in the denominator, an equivalent percentage-wise change in
BAF4 (and by extension PPF4) has a greater impact on the WC than a change in BAF3, but in
either case, the effect is less than proportional.
• If BAF3 and BAF4 are both allowed to change (holding PPF4 constant), a percentage-wise
increase in BAF3 (and by extension BAF4) will have a less than proportional effect on WC, while
a decrease in BAF3 will have a greater than proportional impact.
• Under all circumstances, a percentage-wise increase in FA will cause a less than proportional
decrease in WC, while a decrease in FA will cause a greater than proportional increase in WC.
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• Owing to its small contribution to the analysis as a whole, large changes in WA have a very small
impact on WC.
With the exception of FA, it is not possible to conclude that, for all species, the WC is most sensitive to
one or the other of the parameters in the denominator of the equation. For species that feed at one trophic level,
all parameters other than FA have the potential to change WC in a proportional or greater than proportional
manner. For species that feed at two trophic levels, the BAF at the lower trophic level becomes relatively less
important, but it may still have a large impact on WC if the percentage of the diet represented by this lower
trophic level is large (e.g., in the mink).
5.4.12 Uncertainties Associated with the Wildlife Criteria Methodology
Efforts to develop WC values for the protection of piscivorous wildlife are relatively recent in origin, and
the methods employed for this purpose continue to undergo modification and refinement. Owing to the
complexity of natural systems, uncertainties associated with the development of WC values are to be expected.
Additional uncertainties derive from the relative scarcity of wildlife toxicity information and the necessity of
extrapolating individual-based effects to higher levels of biological organization (e.g., populations).
Uncertainties associated with the WC methodology have been reviewed elsewhere (U.S. EPA, 1994).
Rather than repeat this information, this Report attempts to focus on those areas that are especially pertinent to
the development of a WC for mercury. These uncertainties are described below in no particular order.
5.4.12.1 Limitations of the Toxicity Database
Substantial uncertainties underlie most of the toxicity data for mercury in wildlife. Comparison of
NOAELs and LOAELs between species requires adoption of unproven assumptions about the uptake,
distribution, elimination, and toxic effects of mercury. Conclusions based upon extrapolation from one species to
another are, therefore, tenuous. Additional uncertainties are a result of extrapolating from LOAELs to NOAELs
and from subchronic endpoints to chronic endpoints. In some instances, there may also be a need to account for
the possibility that test results do not adequately protect the most sensitive individuals. This may be particularly
germane to the case of the Florida panther, where there is concern for individual animals.
Toxicity studies utilizing "naturally incorporated" mercury are complicated by the possibility that
mercury is accompanied by other contaminants that are exerting some or all of the observed effect. Ideally, it is
desirable to compare the effects of mercury that has been incorporated naturally with effects that are due to
mercury that has been spiked into a prepared diet. By spiking mercury into the diet, the researcher can better
control the dose to the animal. The bioavailability of mercury in such a formulation may be different from that
which exists naturally. However, Charbonneau et al. (1976) demonstrated that the bioavailability and toxicity of
methylmercury to cats is equivalent whether given in contaminated fish or spiked in the diet.
EPA cannot test all wildlife species of interest. The use of uncertainty factors for species extrapolation is
likely, therefore, to continue. Existing information can be used, however, to suggest which species should be
singled out for testing. Information of this type is reviewed in this document in several locations and includes
species distribution, natural history considerations, and exposure factors.
Finally, comparisons between wildlife and human NOAELs are complicated by differences in the ability
of a given study to reveal an adverse effect when it occurs. For wildlife, most of the endpoints selected can be
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considered severely adverse or frank effects. Very few studies to date have been designed to study subtle adverse
effects or precursors to adverse effects in wildlife. Developmental neurotoxicity endpoints are of particular
interest due to their demonstrated sensitivity in humans. The question, therefore, arises: what would the LOAEL
or NOAEL for a given wildlife species be if the researcher was looking for (or was able to detect) these more
subtle effects? One approach to this question is to examine the results of studies in which both frank and more
subtle effects were observed and determine the corresponding difference between dosage levels.
5.4.12.2 LOAEL-to-NOAEL Uncertainty Factor UFL
In determining the WC for mercury exposure in wildlife, a chronic NOAEL is the preferred value for the
TD. In cases where studies do not identify a NOAEL, the data are examined to identify a LOAEL. This LOAEL
is then adjusted using a LOAEL-to-NOAEL uncertainty factor (UFj) to estimate a wildlife RfD. A UFL of 3 or
10 (based on EPA reference dose methodology) is typically applied when a LOAEL is used in the absence of a
NOAEL.
In determining the RfD for human exposure to methylmercury, a large number of laboratory animal
studies on methylmercury toxicity were summarized as supporting data. Results from many of these studies
permitted estimation of both a LOAEL and a NOAEL. These studies were examined in an effort to determine the
most appropriate UFL for wildlife exposure to mercury.
The studies examined are summarized in Volume V of this Report. Nineteen studies were selected as
being the most relevant and appropriate for determining a UFL. Selection criteria included the following:
• methylmercury toxicity to nonhuman mammals;
• oral exposure (with preference given to dosing in food or drinking water); and
• chronic or subchronic exposure durations (with exceptions for reproductive and developmental
toxicity where such distinctions are less relevant).
Cancer and genotoxic endpoints were not included because tumors are not often reported in wildlife toxicity
studies. Endpoints included in the analysis included lethality, neurotoxicity, renal toxicity, gastrointestinal
toxicity, immunotoxicity, developmental toxicity and reproductive toxicity (see Table 5-4). Data abstracted from
the studies include the species and sex of the test subjects, toxicologic endpoint, LOAEL, NOAEL and the ratio
between them. The LOAEL:NOAEL ratios were not segregated by endpoint because there was an insufficient
number of studies at most endpoints to determine statistical significance.
The ratios of LOAEL-to-NOAELs for laboratory animal studies are plotted versus frequency in Figure 5-
1. These ratios can be thought of as the reduction in the LOAEL necessary to estimate the corresponding
NOAEL. Figure 5-1 illustrates that the majority of ratios lie between one and two (n=6) and between four and
five (n=9). Only one ratio of the 19 plotted was greater than 10. A ratio of five indicates that the NOAEL
observed following exposure to methylmercury is 5-fold less than the
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Table 5-4
Analysis of LOAEL-to-NOAEL Uncertainty Factor
Endpoint
Species and Sex
LOAEL
(mg/kg/day)
NOAEL
(mg/kg/day)
RATIO
LOAEL:NOAEL
Study
Lethality
B6C3F1 Mouse M
0.69
0.60
1.15
Mitsumori et al., 1990
Neurotoxicity
Rat (Wistar) M & F
Cat sexNS
Monkey (Macaco, fasicularis) M & F
Monkey (Macaco, artoides andM. nemestrina) M & F
0.25
0.046
0.03
0.5
0.05
0.020
0.02
0.4
5.0
2.3
1.5
1.25
Munro et al., 1980
Charbonneauetal., 1976
Sato and Ikuta, 1975
Evans etal., 1977
Renal Toxicity
Mouse (ICR) M
F
Mouse (B6C3F1) M
F
0.72
0.62
0.14
0.6
0.15
0.11
0.03
0.13
4.8
5.6
4.7
4.6
Hiranoetal., 1986
Mitsumori etal., 1990
Gastrointestinal Toxicity
Mouse (B6C3F1) M
0.69
0.14
4.9
Mitsumori et al., 1990
Immunotoxicity
Rabbit (New Zealand White) M&F
0.4
0.04
10.0
Kolleretal, 1977
Developmental Toxicity
Rat (Charles River) F
Rat (Wistar) F
Rat (Charles River) F
Rat (Wistar) offspring of both sexes
4.0
0.25
1.4
0.6
0.2
0.05
0.7
0.2
20.0
5.0
2.0
3.0
Nolenetal., 1972
Khera and Tabacova, 1973
Fowler and Woods, 1977
Schreineretal., 1986
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Table 5-4 (continued)
Analysis of LOAEL-to-NOAEL Uncertainty Factor
Endpoint
Species and Sex
LOAEL
(mg/kg/day)
NOAEL
(mg/kg/day)
RATIO
LOAEL:NOAEL
Study
Reproductive Toxicity
Rat (Wistar) M
Mouse (ICR) M
Mouse (B6C3F1) M
Monkey (Macaco, facicularis) M
Monkey (M. facicularis) F
0.5
0.72
0.68
0.065
0.06
0.1
0.15
0.14
0.047
0.04
5.0
4.8
4.9
1.4
1.5
Khera, 1973
Hiranoetal., 1986
Mitsumorietal., 1990
Mohamed et al., 1987
Burbacheretal., 1988
NS - Not stated.
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.&
+->
t/3
5
•A «
T tf
z
6
a; ^
•r,
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corresponding LOAEL. These data imply that most ratios between LOAELs and their corresponding NOAELs
will be less than 10.
A similar analysis of animal toxicity data (Weil and McCollister, 1963) was provided by Dourson and
Stara (1983). None of the LOAEL-to-NOAEL ratios from studies of 52 chemical substances exceeded 10. Only
two of the 52 ratios exceeded five. The Dourson and Stara (1983) analysis has been cited in support of the use of
a variable UFL of as much as 10 in deriving reference doses for humans. Dourson and Stara (1983) recommended
the application of a relatively large UFL when estimating a NOAEL from a LOAEL for a severe or frank
toxicological effect. Conversely, a low UFL could be applied when the toxicological effect was considered to be
relatively mild.
The distribution of LOAEL:NOAEL ratios around two and five primarily reflect the dose spacing
selected for the study designs. Two-fold, 5-fold and 10-fold spacing are common in experiments of this type.
The most appropriate interpretation of the ratios reported here and by Dourson and Stara (1983) is that the
threshold for the toxicologic effects, defined by each study, lies within the bounds of the experimentally derived
LOAEL divided by a UFL and that most of the effects thresholds will be encompassed by using a UFL of 10 or
less. It is also likely that the most appropriate UFL will vary with the toxicological endpoint selected. For studies
that identify only a LOAEL, the principal assumption is that the next lower dose, had it been tested, would be a
NOAEL. This assumption is best applied to studies that identify a LOAEL for mild effects. LOAELs for severe
or frank effects (which are generally no used for human health risk assessment) require a high degree of
professional judgment in applying a UFL.
The analysis by Dourson and Stara (1983) and the analysis reported here support the UFL of three
selected by the authors of this Report for use with the avian LOAEL. In deriving an RfD for avian species, the
authors of the GLWQI used a UFL of two. Given the substantial uncertainties in all the values used to calculate
the WC for mercury exposure, neither two nor three can be considered to be the only correct value.
5.4.12.3 Validity of BCF/BAF Paradigm
A significant shortcoming of the WC for mercury calculated in the GLWQI is its reliance upon BCF
values determined in the laboratory. This methodology is based on a bioaccumulation paradigm (steady-state
BCF x FCM) that was developed for neutral hydrophobic organic compounds and that may be inappropriate for
application to mercury. In addition, the laboratory studies available for estimating BCFs were conducted with
fish and not with organisms at the first trophic level (phytoplankton) that begin the bioaccumulation process. The
modified GLWQI method uses field data for directly determining BCFs in phytoplankton but must rely on other
uncertain assumptions, such as dry weight to wet weight conversion factors, to obtain the appropriate values.
The result is increased uncertainty in the results of the GLWQI methodology when compared to direct estimation
of BAFs from field data.
Field studies indicate that many, if not most, fish accumulate mercury throughout their lives, often in a
nearly linear fashion with age (see for example Scott and Armstrong, 1972; MacCrimmon et al., 1983; Wren et
al., 1983; Mathers and Johansen, 1985; Skurdal et al., 1985; Wren and MacCrimmon, 1986; Sorenson et al.,
1990; Jackson, 1991; Gutenmann et al., 1992; Glass et al., 1993; Suchanek, 1993; Lange et al., 1993). Moreover,
most of the mercury accumulated by fish at trophic level 4 is thought to be taken up from dietary sources. Thus,
particularly for long-lived piscivorous fish, a relatively short (one year or less) waterborne exposure cannot
duplicate the extent of accumulation that takes place in nature. In addition, the relationship between a
concentration of an applied mercury species in the laboratory and the concentrations of multiple species present
in the environment (some of which may not be bioavailable) is completely unknown.
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The apparent progress to "steady-state" observed in several chronic laboratory studies (see McKim et al.,
1976) should not be misinterpreted as an actual steady-state condition, but instead probably reflects growth
dilution with rapidly growing fish. Growth dilution will tend to depress BCF values during periods of rapid
growth, but as growth rate slows, continued accumulation of mercury will result in an increase in whole-body
concentration with age.
5.4.12.4 Selection of Species of Concern
The species identified for the present analysis were selected because they were considered likely to be
exposed and not due to their inherent sensitivity to mercury. Lacking toxicity information, little guidance is
available concerning which wildlife species are most sensitive to mercury. In addition, there are problems
associated with any comparison of laboratory and field data. For example, laboratory data suggest that mercury
residues in eggs exceeding 0.5 //g/g are associated with impaired reproduction in mallard ducks (Heintz, 1974,
1976a,b, 1979) and ring-necked pheasant (Fimreite, 1971). In contrast, reproduction in herring gulls appears to
be unaffected even when egg residues exceed 10 //g/g (Vermeer et al., 1973). Taken alone, these data suggest
that mallards and pheasant are more sensitive to the toxic effects of mercury than are gulls. This may in fact be
true; however, such comparisons are complicated by the presence/absence of additional stressors such as
confinement, handling and weather, differences between natural and prepared diets, the possible ameliorative
effect of selenium, and the interplay between "inherited" (egg) residues and that which the chick consumes.
Toxicity can be difficult to observe in a field study, even when it is occurring. In 18 of 38 nests under study by
Vermeer et al. (1973), hatching success could not be evaluated for one reason or another.
Clearly, exposure and sensitivity are related. If, for example, a species was, on a delivered dose basis, 10
times more sensitive than the eagle but, due to its dietary habits, received less than 10% of the dose, it would not
be expected to show adverse effects at water concentrations protective of the eagle. Pharmacokinetic
considerations may also be important. Thus, it has been suggested that birds eliminate a substantial amount of
mercury through incorporation into plumage. The frequency and extent to which birds molt may, therefore,
impact their apparent sensitivity in an environmental setting. Finally, it has been shown that most, if not all,
wildlife possess some capability to detoxify methylmercury by hepatic demethylation. Enhanced demethylation
would be particularly important if it represented an adaptive strategy for piscivorous species. The need for
toxicity information has already been noted. As such information becomes available, it may be necessary to
revise the WC for mercury.
There is also a need to consider animals other than birds and mammals. In particular, there is a need to
characterize the exposure of carnivorous reptiles, such as the alligator, that are known to consume considerable
quantities offish and feed on animals (e.g., raccoon) that themselves feed on aquatic biota and are known to
accumulate mercury (Roelke et al., 1991).
5.4.12.5 Trophic Levels at Which Wildlife Feed
The dietary preferences of the wildlife species identified for this analysis are shown in Table 5-2.
Justification for these assignments can be found in two recent U.S. EPA publications that were developed for the
purpose of supporting WC calculations (U.S. EPA 1993a, 1995a). It can be expected, however, that
representatives of the same species will be exposed to different levels of mercury due to different feeding habits
and/or differences in the availability of specific prey items. For example, bald eagles living on the shores of the
Great Lakes may consume significant numbers of herring gulls (Kozie and Anderson, 1991). Since the gulls
themselves are piscivores, feeding primarily at trophic level 3, it has been argued that when an eagle consumes a
gull, it is feeding at trophic level 4 or higher; the gull/forage fish PPF is thought to be about 10, while the PPF for
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fish at trophic level 4 is believed to be approximately 5 (U.S. EPA, 1995a). Eagles living in other parts of the
country or migrating into an area during a particular time of year may consume relatively few fish, feeding
instead on carrion, including rabbits, squirrels, and dead domestic livestock such as pigs and chickens (Harper et
al., 1988). Other populations, however, are critically dependent upon the seasonal availability offish,
particularly spawning salmonids.
The feeding habits of bald eagles are reviewed extensively elsewhere (U.S. EPA, 1993a, 1995a). The
intent of this discussion is not to characterize the food preferences of the eagle, but instead to demonstrate how
difficult it is to characterize wildlife feeding habits on a nationwide, year-around basis. For some species, such
as the kingfisher and river otter, it can be reasonably assumed that fish always comprise a high percentage of the
diet. For others, such as the eagle and mink, considerable variations in diet are likely to exist. Still others, such
as the Florida panther, consume prey (e.g., the raccoon) that, as a species, consume variable amounts of aquatic
biota but that, in south Florida, are thought to represent a close link to the aquatic food chain.
5.4.12.6 Variability in BAFs at each Trophic Level
A concern related to the issue of feeding preference is the possibility that trophic levels presently
assigned to the wildlife species in this analysis overestimate the actual extent to which they are exposed to
mercury. This is because BAFs are developed to represent the average value for a trophic level when, in fact,
piscivorous birds and mammals may be more likely to target prey at the lower end of the size (age) distribution.
Thus, eagles are more likely to consume a 1 kg northern pike than a 10 kg individual, yet both are represented in
the BAF for trophic level 4. Similarly, kingfishers are probably limited to smaller representatives of trophic level
3 than would be true of an osprey. The reason that these differences are important is that mercury tends to
accumulate throughout the life of an individual fish, such that concentrations in an older individual at a given
trophic level may far exceed those in a younger individual.
The need to apply BAF estimates on a nationwide basis in this study precludes further refinement. It
may, however, be possible to explore this issue by using a probabilistic approach to analyze individual data sets.
Specifically, it would be of interest to determine whether percentile information from the resulting output
distributions can be related to fish of known size. Eventually, it may be possible to use this or another approach
to refine BAF estimates for mercury.
5.4.12.7 Natural History Considerations
Natural exposures are likely to vary in both spatial and temporal domains. This is particularly true of
species that migrate, including the bald eagle, osprey, and belted kingfisher. The necessity of incorporating this
type of information and the means by which this can be accomplished are open questions.
5.4.12.8 Individuals Versus Populations
The methods used to develop a WC for mercury are based on effects data from individual organisms.
The stated assessment endpoint for this Report, however, is the health of wildlife populations. The relationship
between individuals and populations is likely to vary with the species and a large number of environmental
factors. For some populations, the loss of a significant number of individuals may have little effect, particularly
if environmental factors (like carrying capacity) limit population size. Animals that are capable of dispersing
over large areas present an additional complication. It is possible, for example, that negative impacts could occur
within a given location but would be difficult to observe due to a continuous influx of as yet unaffected
individuals. For other populations, in particular those with low fecundity, loss of a relatively few individuals
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could have a large impact. Clearly, there is a need to be able to extrapolate toxic effects on individuals to effects
on populations. Unfortunately, this type of analysis is complicated by numerous factors and is essentially
impossible to apply on a national scale.
Finally, a focus on populations may not always be appropriate, particularly when endangered species are
involved. The same may also be true when various factors contribute to the possibility of regional effects. For
example, 95% of eagles nationwide might be protected by a WC for avian species, but in a given region mortality
could approach 100% if attributes of lakes and rivers in that region contributed to higher than average
accumulation of mercury in the aquatic food chain.
5.4.12.9 Species Versus Taxa
The WC developed for mercury in birds was calculated as the geometric mean of values for four species.
Similarly, the geometric mean of values for two species was used to represent all mammals. This approach is
reasonable if the WC calculated for each species within a taxa are similar, but it would fail to protect species for
which the WC value is much lower than the others with which it was averaged.
In the present analysis, WC values calculated for eagles, osprey, loon and kingfisher were within a factor
of three of one another. WC values for mink and otter agreed to within a factor of about one and a half. As
additional data are gathered, there is a need to identify species that, by virtue of sensitivity and/or exposure, are
particularly vulnerable to mercury. Decisions could then be made concerning the advisability of special
measures to insure their protection.
5.4.12.10 Discussion of Uncertainties Associated with the Wildlife Criteria Methodology
The existing limited data suggest that BAF values represent an important source of uncertainty in present
efforts to calculate water-based WC values, although a lack of toxicity information and incomplete knowledge of
what wildlife eat contribute substantially. Considerable progress has been made in understanding and predicting
how chemical and biological factors affect mercury bioaccumulation in aquatic biota, and, in time, it may be
possible to adjust BAF predictions as needed to represent specific surface waters of concern. The prospect for
continuing uncertainty surrounding these estimates argues, however, for adoption of a residue-based approach;
i.e., the use of measured mercury residues in fish and wildlife to identify populations at risk.
It is important to recognize that BAF values are calculated as the ratio of a tissue concentration and a
water concentration. Emphasis has been placed on problems associated with obtaining the numerator in this
equation. However, considerable uncertainty may also exist with respect to the denominator. In several
instances, it has been shown that, with improved analytical methods, mercury levels in a given water body tend to
come "down," resulting in an increase in the apparent BAF. This "decline" is usually not thought to be real but
instead reflects improvements in sampling technique and analytical methods.
It is also unclear which of the mercury species are bioaccumulative and should, therefore, appear in the
denominator. The present analysis considers dissolved methylmercury to be the best estimator of
bioaccumulation potential in a given water body. Speciation data from a variety of systems suggest that most of
the methylmercury in the water column exists as the dissolved form (mean of about 70%) (see Appendix D of
Volume III). Nevertheless, questions remain concerning the bioavailability of dissolved methylmercury
associated with DOC. Additional refinement of the BAF approach may require methods to identify the "freely
dissolved" fraction of methylmercury. A similar approach is now used routinely in BAF calculations with high
log Kow organic compounds.
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An effort was made to treat the uncertainty in BAF estimates by using a probabilistic approach. The
advantage of this approach is that it explicitly treats known variation in these parameters, thereby providing for
the statistical possibility of a high or low end result. In addition, the distributions themselves follow from the
processes at work. As more information about mercury is obtained, the distributions themselves can be
improved. For example, a skewed BAF distribution for trophic level 4 would be expected from random sampling
of a fish population due to the relative scarcity of the oldest individuals. Based upon a survey of published data,
the distribution of methylmercury values as a percent of total also appears to be highly skewed. With respect to
the definition of these distributions, it is important to recall the possibility of regional bias introduced previously.
It could be argued that FCMs based on regression of data for a large number of lakes should be given greater
weight (perhaps equal to the number of lakes) than data from a single location. This, however, would only serve
to increase the degree of regional bias that is already present.
5.5 Risk of Mercury from Airborne Emissions to Piscivorous Avian and Mammalian Wildlife
5.5.1 Lines of Evidence
Barr (1986) found that 0.3 ppm of mercury in trophic level 3 fish caused adverse effects on reproduction
in common loons. In the present Report, an effort was made to calculate a WC for mercury which, if not
exceeded, would be protective of piscivorous birds and mammals. The mercury residue in trophic level 3 fish
that corresponds to this WC is 0.077 ppm, or about one-fourth the effect level identified by Barr (1986). Based
upon a review of two national surveys, the average value for trophic level 3 fish in the continental U.S. was
estimated to be 0.052 ppm; however, these surveys may have overestimated the true national average due to a
bias toward waters receiving municipal and industrial waste. Nevertheless, recent surveys of lakes that do not
receive point source loadings have yielded residue values in forage fish exceeding 0.077 ppm, particularly in
regions already impacted by acid deposition (see for example Gerstenberger et al., 1993; Simonin et al., 1994;
Driscoll et al., 1994; Lange et al., 1994; Cabana et al., 1994). Although it is difficult to precisely determine an
adverse effects level for mercury in forage fish consumed by piscivorous wildlife, this value appears to lie in the
range 0.077-0.30 ppm. The exact level may also vary to some degree depending upon the species in question and
specific environmental factors.
The effects data, though limited, are remarkable for their consistency; RfDs derived for birds and
mammals (mink and domestic cats) are essentially identical. Very few uncertainty factors were used in these
calculations, and the uncertainty factor values were small. In addition, the estimated value of UFL(used to adjust
the TD for avian species) was supported by several sources of data. Finally, it should be noted that all wildlife
RfDs are greater than the RfD for human health by a factor of about 200 (RfD for human health = 0.1 (ig/kg
bw/d; see Volume IV). As noted previously, the human health assessment differs from the wildlife assessment in
its consideration of subtle cognitive impacts. The possibility also exists that humans are more sensitive than
piscivorous wildlife on a delivered dose basis, perhaps due to differences in ability to detoxify methylmercury.
Nevertheless, the WC for mercury is unlikely to be grossly "overprotective" (i.e., too low) and may, in some
instances, be "underprotective."
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5.5.2 Risk Statements
Given the national-scale scope of this Report, quantitative estimates of risk are not possible or
appropriate. It is notable, however, that hazard quotients derived by other authors for mink (Giesy et al., 1994)
and great egrets (Jurczck, 1993) ranged from 1.2 to 6.6. Such calculations suggest the possibility of local impacts
on these two highly exposed populations. As indicated previously, fish residues in some areas exceed calculated
WC values for trophic levels 3 and 4. It should be emphasized that these WC values were calculated using
geometric mean BAF values; thus, BAFs were higher in approximately half of the systems for which field-data
were available. For this reason, and given the small difference between effect (0.3 ppm) and no-effect (0.077
ppm) residue levels, it is likely that individuals of some highly exposed subpopulations (birds and mammals) are
consuming fish at or very near adverse effect levels. Additional work is required to establish whether and to
what extent impacts are occurring, and what effect local-scale impacts may have on larger species populations.
Existing data are insufficient to speculate on the spatial or temporal scale of these possible adverse effects or the
potential for recovery. However, the risk of adverse effects is great enough to warrant intensified study of highly
exposed wildlife subpopulations, particularly in areas near mercury emissions point sources. Finally, the data
suggest that special attention should be given to the possibility that mercury acts in concert with other
bioaccumulative contaminants (e.g., PCBs, TCDD) to produce toxic effects at residue levels that, when evaluated
separately, would not indicate a problem.
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6. CONCLUSIONS
The following conclusions are presented in approximate order of degree of certainty, based on the quality
of the underlying database. The conclusions progress from those with greater certainty to those with
lesser certainty.
• Mercury emitted to the atmosphere deposits on watersheds and is translocated to waterbodies. A variable
proportion of this mercury is transformed by abiotic and biotic chemical reactions to organic derivatives,
including methylmercury. Methylmercury bioaccumulates in individual organisms, biomagnifies in
aquatic food chains and is the most toxic form of mercury to which wildlife are exposed.
• The proportion of total mercury in aquatic biota that exists as methylmercury tends to increase with
trophic level. Greater than 90% of the mercury contained in freshwater fish exists as methylmercury.
Methylmercury accumulates in fish throughout their lifetime, although changes in concentration as a
function of time may be complicated by growth dilution and changing dietary habits.
• Piscivorous avian and mammalian wildlife are exposed to mercury primarily through consumption of
contaminated fish and accumulate mercury to levels above those in prey items.
• Toxic effects on piscivorous avian and mammalian wildlife due to the consumption of contaminated fish
have been observed in association with point source releases of mercury to the environment.
• Concentrations of mercury in the tissues of wildlife species have been reported at levels associated with
adverse health effects in laboratory studies with the same species.
• Piscivorous birds and mammals receive a greater exposure to mercury than any other known component
of aquatic ecosystems.
• BAFs for mercury in fish vary widely; however, field data are sufficient to calculate representative means
for different trophic levels. These means are believed to be better estimates of mercury bioaccumulation
in natural systems than values derived from laboratory studies. The recommended methylmercury BAFs
for tropic levels 3 and 4 are 1,600,000 and 6,800,000, respectively (dissolved basis).
• Based upon knowledge of mercury bioaccumulation in fish, feeding rates, and the identity of prey items
consumed by piscivorous wildlife, it is possible to rank the relative exposure of different piscivorous
wildlife species. Of the six wildlife species selected for detailed analysis, the relative ranking of
exposure to mercury is: kingfisher > otter > loon = osprey = mink > bald eagle. Existing data are
insufficient to estimate the exposure of the Florida panther relative to that of the selected species.
• Local emissions sources (<50 km from receptors) have the potential to increase the exposure of
piscivorous wildlife well above that due to sources located more than 50 km from the receptors (i.e.,
"remote" sources).
• Field data are insufficient to conclude whether the mink, otter, or other piscivorous mammals have
suffered adverse effects due to airborne mercury emissions.
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• Field data are insufficient to conclude whether the loon, wood stork, great egret, or other piscivorous
wading birds have suffered adverse effects due to airborne mercury emissions.
• Field data are suggestive of adverse toxicological effects in the Florida panther due to mercury; however,
the interpretation of these data is complicated by the co-occurrence of several other potentially toxic
compounds, habitat degradation, and loss of genetic diversity. Field data suggest that bald eagles have
not suffered adverse toxic effects due to airborne mercury emissions
• Reference doses (RfDs) for methylmercury, defined as chronic NOAELs, were determined for avian and
mammalian wildlife. Each RfD was calculated as the toxic dose (TD) from laboratory toxicity studies,
divided by appropriate uncertainty factors. The RfD for avian species is 21 (ig/kg bw/d (mercury basis).
The RfD for mammalian wildlife is 18 (ig/kg bw/d (mercury basis).
• Based upon knowledge of mercury exposure to wildlife and its toxicity in long-term feeding studies,
criterion values can be calculated for the protection of piscivorous avian and mammalian wildlife. A
wildlife criterion (WC) value is defined as the concentration of total mercury in water which, if not
exceeded, protects avian and mammalian wildlife populations from adverse effects resulting from
ingestion of surface waters and from ingestion of aquatic life taken from these surface waters.
• The methylmercury criterion for protection of piscivorous avian wildlife is 74 pg/L (mercury basis).
• The methylmercury criterion for protection of piscivorous mammalian wildlife is 50 pg/L (mercury
basis).
• The final methylmercury criterion for protection of piscivorous wildlife species is 50 pg/L. This value
corresponds to a total dissolved mercury concentration in the water column of 641 pg/L and
methylmercury concentrations in fish of 0.077 ppm (trophic level 3) and 0.346 ppm (trophic level 4).
• Modeled estimates of mercury concentration in fish around hypothetical mercury emissions sources
predict exposures within a factor of two of the WC. The WC, like the human RfD, is predicted to be a
safe dose over a lifetime. It should be noted, however, that the wildlife effects used as the basis for the
WC are gross clinical manifestations. Expression of subtle adverse effects at these doses cannot be
excluded.
• The adverse effect level (population impacts on piscivorous wildlife) for methylmercury in fish that
occupy trophic level 3 lies between 0.077 and 0.3 ppm. A comparison of this range of values with
published residue levels in fish suggests that it is probable that individuals of some highly exposed
wildlife subpopulations are experiencing adverse toxic effects due to airborne mercury emissions.
There are many uncertainties associated with this analysis, due to an incomplete understanding of the
biogeochemistry and toxicity of mercury and mercury compounds. The sources of uncertainty include the
following:
• Variability in the calculated BAFs is a source of uncertainty. BAFs given in this Report relate
methylmercury in fish to dissolved methylmercury levels in the water column. Methods for the
speciation of mercury in environmental samples are rapidly improving but remain difficult to perform.
Questions also remain concerning the bioavailability of methylmercury associated with suspended
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participates and dissolved organic material. Local biogeochemical factors that determine net methylation
rates are not fully understood. The food webs through which mercury moves are poorly defined in many
ecosystems, and may not be adequately represented by a four-tiered food chain model.
The representativeness of field data used in establishing the BAFs is a source of uncertainty. The degree
to which the analysis is skewed by the existing data set is unknown. A disproportionate amount of data is
from north-central and northeastern lakes. The applicability of these data to a national-scale assessment
is unknown.
Limitations of the toxicity database present a source of uncertainty. Few controlled studies of
quantifiable effects of mercury exposure in wildlife are available. These are characterized by limited
numbers of dosage levels, making it difficult to establish NOAEL and LOAEL values. The toxic
endpoints reported in most such studies can be considered severe, raising questions as to the degree of
protection against subtle effects offered by reference doses and WC values. Use of less than lifetime
studies for prediction of effects from lifetime exposure is a source of uncertainty.
Concerns exist regarding the possibility of toxic effects in species other than the piscivorous birds and
mammals evaluated in this Report. Uncertainty exists about mercury effects in birds and mammals that
prey upon aquatic invertebrates and about possible effects on amphibians and aquatic reptiles.
Uncertainty also exists about mercury effects in fish. Toxicity to terrestrial ecosystems, in particular soil
communities, represents another source of uncertainty.
Lack of knowledge of wildlife feeding habits is a source of uncertainty. Existing information frequently
is anecdotal or confined to evaluations of a particular locality; the extent to which this information can be
generalized is open to question. In some instances wherein feeding habits are relatively well
characterized (e.g., Florida panther), the extent of mercury contamination of prey is poorly known (e.g.,
in raccoons).
While the methods used to assess toxicity focus on individual-level effects, the stated goal of the
assessment is to characterize the potential for adverse effects in wildlife populations. Factors that
contribute to uncertainty in population-based assessments include these: variability in the relationship
between individuals and populations; lack of data on carrying capacity; and relationships of one
population, of the same or different species, to another population.
A focus on populations may not always be appropriate. This could be true for endangered species, which
may be highly dependent for the survival of the species on the health of a few individuals. This may also
be true for some regional or local populations of widespread species; the local population may be
"endangered" and, thus, dependent on the survival of individuals.
Multiple stressor interactions involving chemical effects are in general poorly known. Even less well
known are the possible effects of land and water use practices as they impact water quality and large-
scale ecosystem attributes (e.g., community structure and biodiversity).
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7. RESEARCH NEEDS
Mercury is unusual among environmental contaminants in that levels that are likely to cause significant
environmental damage exceed those thought to be present "naturally" by less than two (and perhaps closer to
one) order(s) of magnitude. Conservative use of uncertainty factors can, therefore, lead to calculation of WC or
other similar criterion values that are lower than mercury residues present in even the most pristine systems.
With this in mind, there are two general areas within which research progress must be made if environmental
assessments are to be improved. The first area pertains to basic information on the fate and effects of mercury in
the environment, which would result in reduced use of uncertainty factors and ensure that WC, BAFs, and other
estimates are based on a mechanistic understanding of the relevant processes. The second area is an
improvement in the ability to detect ecological damage when it is in fact occurring. The present assessment of
the "ecological impacts" of anthropogenic mercury emissions is largely limited to consideration of toxic effects
on individuals. Models that would permit extrapolation of these results to populations (the simplest extrapolation
of individual-based information) do not exist for most species. Further extrapolation to communities and
ecosystems is presently out of the question.
Throughout this assessment, uncertainties, discussed above and elsewhere in the text, have limited the
scope of possible conclusions. Although lack of sufficient data is a limiting factor in all phases of this
assessment, a number of research needs have emerged as being especially important. These needs are presented
below in no particular order.
7.1 Process-based Research
Mechanistic information is needed to understand the variability that presently typifies the mercury
literature. Laboratory and field studies must be conducted to identify the determinants of mercury accumulation
in aquatic food chains and to collect kinetic information that would allow researchers to describe the dynamics of
these systems. Areas of uncertainty include: (1) translocation of mercury from watersheds to waterbodies; (2)
factors that determine net rates of methylation and demethylation; (3) dietary absorption efficiency from natural
food sources; (4) effect of dietary choice; and (5) bioavailability of methylmercury in the presence of dissolved
organic material and other potential ligands.
In time, it is anticipated that this information can be used to develop process-based models for mercury
bioaccumulation in fish and other aquatic biota. Significant progress in this direction is represented by the
Mercury Cycling Model (MCM) (Hudson et al., 1994) and by the GAS-ISC3 model described in Volume III of
this Report and employed in the wildlife exposure characterization.
7.2 Wildlife Toxicity Data
There is a need to reduce the present reliance on a relatively few toxicity studies for WC development.
Additional data are needed for wildlife that constitute the most exposed organisms in various parts of the country,
and in particular there is need to evaluate whether dietary selenium and endogenous demethylating pathways
confer protection to piscivorous birds and mammals. Toxicity studies should examine endpoints relevant to the
mode of action of methylmercury, including assessments of both reproductive and behavioral effects. There is
also a critical requirement for toxicity data (e.g., growth and fecundity) that can be related to effects on
populations, including effects on organisms that comprise the lower trophic levels.
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7.3 Improved Analytical Methods
Efforts to develop and standardize methods for analysis of total mercury and methylmercury in
environmental samples should be continued. Such methods must recognize the importance of contamination,
both during the collection of such samples and during their analysis. It is particularly important that mercury
measurements, which at present tend to be operationally defined (e.g., "soluble" or "adsorbed to organic
material"), be made in such a way that mercury residues in fish can be correlated with the bioavailable mercury
pool. Whenever possible, water samples should be filtered to obtain a measure of dissolved mercury species. As
validated methods become available, it is important to analyze for both total and methylmercury so that
differences between aquatic systems can be definitively linked to differences in methylmercury levels. Analyzing
the two mercury species together will contribute to an understanding of existing data, much of which is reported
as total mercury.
7.4 Complexity of Aquatic Food Webs
Present efforts to develop WC values for mercury are based on linear, four-tiered food chain models.
Research is needed to determine whether this simple paradigm is appropriate and to develop alternatives if field
data suggest otherwise. Of particular interest is whether zooplankton and phytoplankton should be modeled as
two different trophic levels. Current information for detritivores and benthic invertebrates is extremely limited,
even though their importance in mobilizing hydrophobic organic contaminants has been demonstrated.
7.5 Accumulation in Trophic Levels 1 and 2
Ongoing efforts to understand mercury bioaccumulation in aquatic systems continue to be focused on
trophic levels 3 and 4, despite the fact that uncertainties in PPFs are relatively small. Additional emphasis should
be placed on research at the lower trophic levels. In particular, there is a need to understand the determinants of
mercury accumulation in phytoplankton and zooplankton and how rapid changes in plankton biomass impact
these values.
7.6 Field Residue Data
High-quality field data are needed to support process-based research efforts and to determine residue
concentrations in the fish and other aquatic biota that wildlife eat. Whenever possible, it is desirable to collect
residue data at all trophic levels and to analyze mercury levels in the abiotic compartments of a system (e.g.,
water and sediments). It is particularly important that such measurements be made in a broader array of aquatic
ecosystem types (including both lakes and rivers) so that a better understanding of mercury cycling and
accumulation can be obtained.
Residue data from wildlife are needed to identify populations that are potentially at risk. Feathers and
fur hold considerable promise in this regard due to the potential for "non-invasive" determination of mercury
residues. Laboratory research is required, however, to allow interpretation of these data. Factors such as age,
sex, and time to last molt are likely to result in variability among individuals of a single population and need to
be understood. Whenever possible, tissue samples should be analyzed for both total and methylmercury, as well
as selenium. This is especially true of the liver. More attention should be given to analysis of mercury levels in
brain tissue, since this is the primary site of toxic action. Sampling efforts with wildlife should be accompanied
by analyses of likely food items.
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7.7 Natural History Data
The development of WC values requires knowledge of what wildlife eat. Fish sampling efforts are
frequently focused on species that are relevant to human consumers but that may be of little significance to
wildlife. There is an additional need to collect information for macroinvertebrates and amphibians. Seasonal and
spatial effects on predation should be explored and methods developed to describe this information adequately.
Additional life history data is needed to characterize fully the nature and extent of exposure to mercury.
Complicating factors must be considered, including migratory behaviors and sex-specific differences in
distribution and resource allocation. It is particularly important that information be collected to support the
development of predictive population models for sensitive species. Such models must account for immigration
and emigration, density dependent factors, and the observation that mercury often bioaccumulates as animals age
resulting in variable residues in breeding animals from a single population.
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8. REFERENCES
Allard, B. and I. Arsenic (1991). Abiotic reduction of mercury by humic substances in aquatic system - An
important process for the mercury cycle. Water Air Soil Pollut. 56:457-464.
Allard, M. and P.M. Stokes (1989). Mercury in crayfish species from thirteen Ontario lakes in relation to water
chemistry and smallmouth bass (Micropterus dolomieui) mercury. Can. J. Fish. Aquat. Sci. 46:1040-1046.
Andersson, A. (1979). Mercury in soils. In: The Biogeochemistry of Mercury in the Environment. J.O. Nriagu
(Ed.), Elsevier/North Holland Biomedical Press, Amsterdam, The Netherlands, pp. 79-106.
Anthony, R.G., M.G. Garrett and C.A. Schuler (1993). Environmental contaminants in bald eagles in the
Columbia River estuary. J. Wildl. Manage. 57:10-19.
Aulerich, R.J., R.K. Ringer and S. Iwamoto (1974). Effects of dietary mercury in mink. Arch. Environ. Contam.
Toxicol. 2(1):43-51.
Back, R.C. and C.J. Watras (1995). Mercury in zooplankton of northern Wisconsin lakes: Taxomomic and site-
specific trends. Water Air Soil Pollut. 80:931-938.
Bahnick, D., C. Sauer, B. Butterworth and D. Kuehl (1994). A national study of mercury contamination in fish.
Chemosphere 29:537-546.
Bakir, F., S.F. Damluji, L. Amin-Zaki, M. Murtadha, A. Khalidi, N.Y. Al-Rawi, S. Tikriti, and H.E. Dhahir
(1973). Methylmercury poisoning in Iraq. Science 181: 230-240.
Barr, J.F. (1973). Feeding biology of the common loon (Gavia immer) in oligotrophic lakes of the Canadian
Shield. Ph.D. dissertation, University of Guelph, Canada.
Barr, J.F. (1986). Population dynamics of the common loon (Gavia immer) associated with
mercury-contaminated waters in northwestern Ontario. Occasional Paper No. 56, Canadian Wildlife Service.
Barr, J.F. (1996). Aspects of common loon (Gavia immer) feeding biology on its breeding ground.
Hydrobiologia 321:119-144.
Beck, D.L. (1977). Pesticide and heavy metal residues in Louisiana river otter. M.S. thesis, University of Texas,
Houston, TX.
Becker, P.H., D. Henning and R.W. Furness (1994). Differences in mercury contamination and elimination
during feather development in gull and tern broods. Arch. Environ. Contam. Toxicol. 27:162-167.
Becker, D.S. and G.N. Bigham (1995). Distribution of mercury in the aquatic food web of Onondaga Lake, New
York. Water Air Soil Pollut. 80:563-571.
Belant, J.L. and R.K Anderson (1990). Environmental contaminants in common loons from northern Wisconsin.
Pass. Pigeon 52:306-310.
8-1
-------
Beyer, W.N., E. Cromartie and G.B. Moment (1985). Accumulation of methylmercury in the earthworm, Eisenia
foetida, and its effect on regeneration. Bull. Environ. Contam. Toxicol. 35:157-162.
Bigler, W.J., R.H. Jenkins, R.M. Cumbie, G.L. Hoff and E. Prather (1975). Wildlife and environmental health.
Raccoons as indicators of zoonoses and pollutants in southeastern U.S.A. J. Amer. Med. Assoc. 167:592-597.
Bishop, C.A., M.D. Koster, A.A. Chek, D.J.T. Hussell and K. Jock (1995). Chlorinated hydrocarbons and
mercury in sediments, red-winged blackbirds (Agelaius phoeniceus) and tree swallows (Tachycineta biocolof)
from wetlands in the Great Lakes-St. Lawrence River basin. Environ. Toxicol. Chem. 14:491-501.
Bleavins, M.R. and R.J. Aulerich (1981). Feed consumption and food passage in mink (Mustela vison) and
European ferrets (Mustelaputorius furo). Lab. Animal Sci. 31:268-269.
Bloom, N.S (1992). On the chemical form of mercury in edible fish and marine invertebrate tissue. Can. J. Fish.
Aquat.Sci.49:WW-W\7.
Bloom, N.S. and S.W. Effler (1990). Seasonal variability in the mercury speciation of Onondaga Lake (New
York). Water Air Soil Pollut. 53:251-265.
Bloom, N.S., C.J. Watras and J.P. Hurley (1991). Impact of acidification on the methylmercury cycle of remote
seepage lakes. Water Air Soil Pollut. 56:477-491.
Bodaly, R.A., J.W.M. Rudd, RJ.P. Fudge and C.A. Kelly (1993). Mercury concentrations in fish related to size
of remote Canadian shield lakes. Can. J. Fish. Aquat. Sci. 50:980-987.
Boney, A.D. (1971). Sub-lethal effects of mercury on marine algae. Mar. Pollut. Bull. 2:69-71.
Borst, H.A. and C.G. Lieshout (1977). Phenylmercuric acetate intoxication in mink. Tijdschr. Diergeneesk
102:495-503.
Boudou, A. and F. Ribeyre (1985). Experimental study of trophic contamination ofSalmo gairdneri by two
mercury compounds - HgCl2 and CH3HgCl - analysis at the organism and organ levels. Water Air Soil Pollut.
26:137-148.
Bowerman, W.W. IV (1993). Regulation of bald eagle (Haliaeetus leucocephalus) productivity in the Great
Lakes basin: An ecological and toxicological approach. Ph.D. dissertation, Michigan State University, East
Lansing, MI.
Bowerman, W.W. IV., E.D. Evans, J.P. Giesy and S. Postupalsky (1994). Using feathers to assess risk of
mercury and selenium to bald eagle reproduction in the Great Lakes region. Arch. Environ. Contam. Toxicol.
27:294-298.
Boyer, H.A. (1982). Trace elements in the water, sediments, and fish of the upper Mississippi River, twin cities
metropolitan area. In: Contaminants in the Upper Mississippi River. J.G. Wiener, R.V. Anderson and D.R.
McConville (Eds.). Butterworth Publishers, Boston, MA, pp. 195-230.
8-2
-------
Braune, B.M. and D.E. Gaskin (1987). Mercury levels in Bonaparte's gulls (LarusPhiladelphia) during autumn
molt in the Quoddy region, New Brunswick, Canada. Arch. Environ. Contam. Toxicol. 16:539-549.
Braune, B.M. and R.J. Norstrom (1989). Dynamics of organochlorine compounds in herring gulls: III. Tissue
distribution and bioaccumulation in Lake Ontario gulls. Environ. Toxicol. Chem. 8:957-968.
Burbacher, T.M., M.K. Mohamed and N.K. Mottett (1988). Methylmercury effects on reproduction and
offspring size at birth. Reprod. Toxicol. l(4):267-278.
Burger, J., J.A. Rodgers, Jr. and M. Gochfeld (1993). Heavy metal and selenium levels in endangered wood
storks Mycteria americana from nesting colonies in Florida and Costa Rica. Arch. Environ. Contam. Toxicol.
24:417-420.
Burger, J., I.C.T. Nisbet and M. Gochfeld (1994). Heavy metal and selenium levels in feathers of known-aged
common terns (Sterna hirundo). Arch. Environ. Contam. Toxicol. 26:351-355.
Cabana, G. and J.B. Rasmussen (1994). Modelling food chain structure and contaminant bioaccumulation using
stable nitrogen isotopes. Nature. 372:255-257.
Cabana, G., A. Tremblay, J. Kalff and J.B. Rasmussen (1994). Pelagic food chain structure in Ontario lakes: a
determinant of mercury levels in lake trout (Salvelinus namaycush). Can. J. Fish. Aquat. Sci. 51:381-389.
Calder, W.A. and E.J. Braun (1983). Scaling of osmotic regulation in mammals and birds. Am. J. Physiol.
244:R601-R606.
Carty, A.J. and S.F. Malone (1979). The chemistry of mercury in biological systems. In: The Biogeochemsitry of
Mercury in the Environment. J.O. Nriagu (Ed.), Elsevier/North-Holland Biomedical Press, Amsterdam, The
Netherlands, pp. 433-479.
Caurant, F., M. Navarro and J.-C. Amiard (1996). Mercury in pilot whales: possible limits to the detoxification
process. Sci. Tot. Environ. 186:95-104.
Cavalli, S. and N. Cardellicchio (1995). Direct determination of seleno-amino acids in biological tissues by
anion-exchange separation and electrochemical detection. J. Chromatog. 706(A):429-436.
Charbonneau, S.M., I.C. Munro, E.A. Nera, R.F. Willes, T. Kuiper-Goodman, F. Iverson, C.A. Moodie, D.R.
Stoltz, F.A.J. Armstrong, J.F. Uthe, H.C. Grice (1974). Subacute toxicities of methylmercury in the adult cat.
Toxic. Appl. Pharm. 27:569-581.
Charbonneau, S.M., I.C. Munro, E.A. Nera, F.A.J. Armstrong, R.F. Willes, F. Bryce and R.F. Nelson (1976).
Chronic toxicity of methylmercury in the adult cat. Interim report. Toxicol. 5:337-349.
Choi, M.H., J.J. Cech Jr. and M.C. Lagunas-Solar (1997). Bioavailability of methyl mercury to Sacramento
blackfish (Orthodon microlepidotus}: dissolved organic carbon (DOC) effects. Environ. Toxicol. Chem. (In
press).
8-3
-------
Clark, K.E., F.A.P.C. Gobas and D. Mackay (1990). Model of organic chemical uptake and clearance by fish
from food and water. Environ. Sci. Technol. 24:1203-1213.
Clarkson, T.W. (1972). The pharmacology of mercury compounds. Ann. Rev. Pharmacol Toxicol. 12:375-406.
Clarkson, T.W. (1990). Human health risks from methylmercury in fish. Environ. Toxicol. Chem. 9:957-961.
Colborn, T.I. (1991). Epidemiology of Great Lakes bald eagles. J. Environ. Health Toxicol. 4:395-453.
Cope, W.G., J.G. Wiener and R.G. Rada (1990). Mercury accumulation in yellow perch in Wisconsin seepage
lakes: Relation to lake characteristics. Environ. Toxicol. Chem. 9:931-940.
Cranmer, M., S. Gilbert, and J. Cranmer (1996). Neurotoxicity of mercury - indicators and effects of low-level
exposure: overview. Neurotoxicol. 17:9-14.
Crowder, A. (1991). Acidification, metals and macrophytes. Environ. Pollut. 71:171-203.
Crowder, A.A., W. Dushenko and J. Grieg (1988). Metal contamination of wetland food chains in the Bay of
Quinte, Ontario. Environment Ontario, Nov. 28-29, 1988. Toronto, Canada, pp. 133-153.
Cumbie, P.M. (1975). Mercury levels in Georgia otter, mink, and freshwater fish. Bull. Environ. Contam.
Toxicol. 14:193-196.
Dietz, R., C.O. Nielsen, M.M. Hansen and C.T. Hansen (1990). Organic mercury in Greenland birds and
mammals. Sci. Tot. Environ. 95:41-51.
Dillon, T.M. (1977). Mercury and the estuarine marsh clam, Rangia cuneata Gray. I. Toxicity. Arch. Environ.
Contam. Toxicol. 6:249-255.
Dorfman, D. (1977). Tolerance ofFundulus heteroclitus to different metals in salt waters. Bull. New Jersey
Acad. Sci. 22:21.
Dourson, M.L. and J.F. Stara (1983). Regulatory history and experimental support of uncertainty (safety) factors.
Reg. Toxicol. Pharmacol. 3:224-238.
Driscoll, C.T., C. Yan, C.L. Schofield, R. Munson and J. Holsapple (1994). The mercury cycle and fish in the
Adirondack lakes. Environ. Sci. Technol. 28:136A-143A.
Driscoll, C.T., V. Blette, C. Yan, C.L. Schofield, R. Munson and J. Holsapple (1995). The role of dissolved
organic carbon in the chemistry and bioavailability of mercury in remote Adirondack lakes. Water Air Soil
Pollut. 80:499-508.
Dukerschein, J.T., J.G. Wiener, R.G. Rada and M.T. Steingraeber (1992). Cadmium and mercury in emergent
mayflies (Hexagenia bilineatd) from the upper Mississippi River. Arch. Environ. Contam. Toxicol. 23:109-116.
Eisler, R. (1987). Mercury hazards to fish, wildlife, and invertebrates: A synoptic review. Publication No. 85
(1.10), U.S. Fish and Wildlife Service, Department of the Interior, Washington, DC.
8-4
-------
Eisler, R. and R.J. Hennekey (1977). Acute toxicities of Cd+2, Cr+6, Hg+2, Ni+2, and Zn+2to estuarine macrofauna.
Arch. Environ. Contam. Toxicol 6:315-323.
Elliott, J.E., A.M. Scheuhammer, F.A. Leighton and P.A. Pearce (1992). Heavy metal and metallothionein
concentrations in Atlantic Canadian seabirds. Arch. Environ. Contam. Toxicol. 22:63-73.
Elliott, J.E., R.J. Norstrom and G.E.J. Smith (1996). Patterns, trends, and toxicological significance of
chlorinated hydrocarbon and mercury contaminants in bald eagle eggs from the Pacific coast of Canada, 1990-
1994. Arch. Environ. Contam. Toxicol. 31:354-367.
Ensor, K.L., D.D. Helwig and L.C. Wemmer (1992). Environmental mercury and lead in Minnesota common
loons (Gavia immef). Minnesota Pollution Control Agency, Water Quality Division, St. Paul, MN.
Environment Canada (1991). Toxic chemicals in the Great Lakes and associated effects: Volume I -
Contaminant levels and trends. Department of Fisheries and Oceans, Health and Welfare Canada, Toronto,
Canada.
Eriksson, M.O.G., L. Henrikson and H.G. Oscarson (1989). Metal contents in liver tissues of non-fledged
goldeneye, Bucephala clangula, ducklings: a comparison between samples from acidic, circumneutral, and limed
lakes in south Sweden. Arch. Environ. Contam. Toxicol. 18:255-260.
Evans, R.D. (1986). Sources of mercury contamination in the sediments of small headwater lakes in
south-central Ontario, Canada. Arch. Environ. Contam. Toxicol. 15:505-512.
Evans, H.L., R. Garman and B. Weiss (1977). Methylmercury: Exposure duration and regional distribution as
determinants of neurotoxicity in nonhuman primates. Toxicol. Appl. Pharmacol. 41:15-33.
Facemire, C.F., T.S. Gross and L.J. Guillette, Jr. (1995). Reproductive impairment in the Florida panther: Nature
orNuture? Environ. Health Perspect. 103(suppl. 3):79-86.
Fimreite, N. (1970). Effects of methylmercury treated feed on the mortality and growth of leghorn cockerels.
Can. J. Anim. Sci. 50:387-389.
Fimreite, N. (1971). Effects of methylmercury on ring-necked pheasants. Canadian Wildlife Service Occasional
Paper Number 9. Department of the Environment. 39pp.
Fimreite, N. (1974). Mercury contamination of aquatic birds in northwestern Ontario. J. Wildl. Manage. 38:120-
131.
Fimreite, N. (1979). Accumulation and effects of mercury on birds. In: The Biogeochemistry of Mercury in the
Environment. J.O. Nriagu (Ed.), Elsevier/North-Holland Biomedical Press, Amsterdam, The Netherlands, pp.
601-628.
Finley, M.T. and R.C. Stendell (1978). Survival and reproductive success of black ducks fed methyl mercury.
Environ. Pollu. 16:51-64.
8-5
-------
Finley, M.T., W.H. Stickel and R.E. Christensen (1979). Mercury residues in tissues of dead and surviving birds
fed methylmercury. Bull. Environ. Contam. Toxicol. 21:105-110.
Fischer, R.G., S. Rapsomanikis, M.O. Andreae and F. Baldi (1995). Bioaccumulation of methylmercury and
transformation of inorganic mercury by macrofungi. Environ Sci.Technol. 29:993-999.
Fjeld, E. and S. Rognerud (1993). Use of path analysis to investigate mercury accumulation in brown trout
(Salmo truttd) in Norway and the influence of environmental factors. Can. J. Fish. Aquat. Sci. 50:1158-1167.
Fleming, W.J., J.A. Rodgers, J.A., Jr., and C.J. Stafford, C.J. (1984). Contaminants in wood stork eggs and their
effects on reproduction, Florida, 1982. Colonial Waterbirds 7:88-93.
Florida Department of Environmental Regulation (FDER, 1990). Mercury, largemouth bass, and water quality:
A preliminary report. Department of Environmental Regulation, Florida.
Florida Panther Interagency Committee (FPIC, 1989). Mercury contamination in Florida panthers. Status Report
of the Technical Subcommittee.
Foley, R.E., S.J. Tackling, R.J. Sloan and M.K. Brown (1988). Organochlorine and mercury residues in wild
mink and otter: Comparison with fish. Environ. Toxicol. Chem. 7:363-374.
Fowler, B.A. and J.S. Woods (1977). The transplacental toxicity of methylmercury to fetal rat liver
mitochondria. Lab. Invest. 36:122-130.
Francis, D.R. and K.A. Bennett (1994). Additional data on mercury accumulation in northern Michigan river
otters. J. Freshwat. Ecol. 9:1-5.
Friedmann, A.S., M.C. Watzin, T. Brinck-Johnsen and J.C. Leiter (1996). Low levels of dietary methylmercury
inhibit growth and gonadal development in juvenile walleye (Stizostedion vitreum). Aquat. Toxicol. 35:265-278.
Putter, M.N. (1994). Pelagic food-web structure influences probability of mercury contamination in lake trout
(Salvelinus namaycush). Sci. Tot. Environ. 145:7-12.
Ganther, H.E., C. Goudie, M.L. Sunde, M.J. Kipecky, P. Wagner, S.H. Oh and W.G. Hoekstra (1972). Selenium
relation to decreased toxicity of methyl mercury added to diets containing tuna. Science 175:1122-1124.
Giesy, J.P., W.W. Bowerman, M.A. Mora, D.A. Verbugge, R.A. Othoudt, J.L. Newsted, C.L. Summer, R.J.
Aulerich, S.J. Bursian, J.P. Ludwig, G.A. Dawson, T.J. Kubiak, D.A. Best, and D.E. Tillitt (1995). Contaminants
in fishes from Great Lakes-influenced sections and above dams of three Michigan rivers: III. Implications for
health of bald eagles. Arch. Environ. Contam. Toxicol. 29:309-321.
Giesy, J.P., D.A. Verbrugge, RA. Othout, W.W. Bowerman, M.A. Mora, P.O. Jones, J.L. Newsted, C.
Vandervoort, S.N. Heaton, R.J. Aulerich, S.J. Bursian, J.P. Ludwig, G.A. Dawson, T.J. Kubiak, D.A. Best and
D.E. Tillitt (1994). Contaminants in fishes from Great Lakes-influenced sections and above dams of three
Michigan rivers. II: Implications for health of mink. Arch. Environ. Contam. Toxicol. 27:213-223.
8-6
-------
Gilbertson, M., T. Kubiak, J. Ludwig and G. Fox (1991). Great Lakes embryo mortality, edema, and deformities
syndrome (GLEMEDS) in colonial fish-eating birds: Similarity to chick-edema disease. J. Toxicol. Environ.
Health 33:455-520.
Gilmour, C.C. and E.A. Henry (1991). Mercury methylation in aquatic systems affected by acid deposition.
Environ. Pollut. 71:131-169.
Glass, G.E., J.A. Sorensen, K.W. Schmidt, J.K. Huber and G.R. Rapp, Jr. (1993). Mercury sources and
distribution in Minnesota's aquatic resources: Precipitation, surface water, sediments, plants, plankton, and fish.
Final report to Minnesota Pollution Control Agency and Legislative Commission on Minnesota Resources,
1989-1991 (Contract Nos. 831479 and WQ/PDS020).
Gobas, F.A.P.C. (1993). A model for predicting the bioaccumulation of hydrophobic organic chemicals in
aquatic food webs: Application to Lake Ontario. Ecol. Model. 69:1-17.
Godbold, D.L. (1991). Mercury-induced root damage in spruce seedlings. Water Air Soil Pollut. 56:823-831.
Goyer, R.A. (1993). Toxic effects of metals. In: Casarett andDoull's Toxicology. The Basic Science of
Poisons, 4th Ed. M.O. Amdur, J. Doull, and C.D. Klaassen (Eds.), McGraw-Hill, Inc., New York, NY, pp. 623-
680.
Grieb, T.M., C.T. Driscoll, S.P. Gloss, C.L. Schofield, G.L. Bowie and D.B. Porcella (1990). Factors affecting
mercury accumulation in fish in the upper Michigan peninsula. Environ. Toxicol. Chem. 9:919-930.
Grier, J.W. (1974). Reproduction, organochlorines, and mercury in northwestern Ontario bald eagles. Can.
Field Nat. 88:469-475.
Grubb, T.G., S.N. Wiemeyer and L.F. Kiff (1990). Eggshell thinning and contaminant levels in bald eagle eggs
from Arizona, 1977 to 1985. The Southwestern Naturalist 35:298-301.
Gutenmann, W.H., J.G. Ebel, Jr., H.T. Kuntz, K.S. Yourstone and D.J. Lisk (1992). Residues of p,p'-DDE and
mercury in lake trout as a function of age. Arch. Environ. Contam. Toxicol. 22:452-455.
Halbrook, R.S., J.H. Jenkins, P.B. Bush and N.D. Seabolt (1994). Sublethal concentrations of mercury in river
otters: Monitoring environmental contamination. Arch. Environ. Contam. Toxicol. 27:306-310.
Harper, R.G., D.S. Hopkins and T.C. Dunstan (1988). Nonfish prey of wintering bald eagles in Illinois. Wilson
Bull. 100:688-690.
Harrison, S.E., J.F. Klaverkamp and R.H. Hesslein (1990). Fates of metal radiotracers added to a whole lake:
accumulation in fathead minnow (Pimephales promelas} and lake trout (Salvelinus namaycush). Water Air Soil
Pollut. 52:277-293.
Heinz, G.H. (1974). Effects of low dietary levels of methylmercury on mallard reproduction. Bull. Environ.
Contam. Toxicol. 11:386-392.
3-7
-------
Heinz, G.H. (1975). Effects of methylmercury on approach and avoidance behavior of mallard ducklings. Bull.
Environ. Contam. Toxicol. 13:554-564.
Heinz, G.H. (1976a). Methylmercury: Second-year feeding effects on mallard reproduction and duckling
behavior. J. Wildl. Manag. 40(1):82-90.
Heinz, G.H. (1976b). Methylmercury: Second-generation reproductive and behavioral effects on mallard ducks.
J Wildl Manag. 40(4):710-715.
Heinz, G.H. (1979). Methylmercury: Reproductive and behavioral effects on three generations of Mallard
ducks. J. Wildl. Manage. 43:394-401.
Heinz, G.H. and D.J. Hoffman (1996). The toxic interactions of mercury and selenium on mallard reproduction.
Presentation given at the Wildlife Mercury Workshop, Fairfax, VA, April 12-13, 1996. Co-sponsored by the
Wisconsin Department of Natural Resources and Electric Power Research Institute.
Helmke, P.A., W.P. Robarge, R.L. Korotev and P.J. Schomberg (1979). Effects of soil-applied sewage sludge on
concentrations of elements in earthworms. J. Environ. Qual. 8:322-327.
Hildebrand, S.G., R.H. Strand and J.W. Huckabee (1980). Mercury accumulation in fish and invertebrates of the
North Fork Holston River, Virginia and Tennessee. J. Environ. Qual. 9:393-400.
Hill, W.R., A.J. Stewart and G.E. Napolitano (1996). Mercury speciation and bioaccumulation in lotic primary
producers and primary consumers. Can. J. Fish. Aquat. Sci. 53:812-819.
Hintelmann, H., P.M. Welbourn and R.D. Evans (1995). Binding of methylmercury compounds by humic and
fulvic acids. Water Air Soil Pollut. 80:1031-1034.
Hirano, M., K. Mitsumori, K. Maita and Y. Shirasu (1986). Further carcinogenicity study on methylmercury
chloride in ICRmice. Jap. J. Vet. Sci. 48(1): 127-135.
Hongve, D., O.K. Skogheim, A. Hindar and H. Abrahamsen (1980). Effects of heavy metals in combination with
NTA, humic acid, and suspended sediment on natural phytoplankton photosynthesis. Bull. Environ. Contam.
Toxicol. 25:594-600.
Huckabee, J.W., J.W. Elwood and S.G. Hildebrand (1979). Accumulation of mercury in freshwater biota. In:
The Biogeochemistry of Mercury in the Environment. J.O. Nriagu (Ed.), Elsevier/North Holland Biomedical
Press, Amsterdam, The Netherlands, pp. 277-302.
Hudson, R.J.M., S.A. Gherini, C.J. Watras, and D.B. Porcella (1994). Modelling the biogeochemical cycle of
mercury in lakes: the mercury cycling model (MCM) and its application to the MTL study lakes. In: Mercury
Pollution: Integration and Synthesis. C.J. Watras and J.W. Huckabee (Eds.), Lewis Publishers, Boca Raton, FL,
pp. 473-523.
Hurley, J.P., J. M. Benoit, C.L. Babiarz, M.M. Shafer, A.W. Andren, J.R. Sullivan, R. Hammond and D.A. Webb
(1995). Environ.Sci. Techno. 29:1867-1875.
-------
Jackson, T.A. (1991). Biological and environmental control of mercury accumulation by fish in lakes and
reservoirs of northern Manitoba, Canada. Can. J. Fish. Aquat. Sci. 48:2449-2470.
Jernelov, A., A.-H. Johansson, L. Sorensen and A. Svenson (1976). Methyl mercury degradation in mink.
Toxicol. 315-321.
Johansson, K., M. Aastrup, A. Andersson, L. Bringmark and A. Iverfeldt (1991). Mercury in Swedish forest soils
and waters - Assessment of critical load. Water Air Soil Pollut. 56:267-281.
Johnston, T.A., R.A. Bodaly and J.A. Mathias (1991). Predicting fish mercury levels from physical
characteristics of boreal reservoirs. Can. J. Fish. Aquat. Sci. 48:1468-1475.
Jordan, D. (1990). Mercury contamination: Another threat to the Florida panther. Fish and Wildlife Service
Endangered Species Technical Bulletin 15(2): 1.
Joslin, J.D. (1994). Regional differences in mercury levels in aquatic ecosystems: A discussion of possible
causal factors with implications for the Tennessee River system and the northern hemisphere. Environ. Manage.
18:559-567.
Jurczyk, N.U. (1993). An ecological risk assessment of the impact of mercury contamination in the Florida
Everglades. Master thesis, University of Florida, Gainesville, FL.
Kajiwara, Y., A. Yasutake, T. Adachi, and K. Hirayama (1996). Methylmercury transport across the placenta via
neutral amino acid carrier. Arch. Toxicol. 70:310-314.
Kerper, L.E., N. Ballatori and T.W. Clarkson (1992). Methylmercury transport across the blood-brain barrier by
an amino acid carrier. Am. J. Physiol. 2<52:R761-R765.
Khera, S. (1973). Reproductive capability of male rats and mice treated with methyl mercury. Toxicol. Appl.
Pharm. 24:167-177.
Khera, K.S. and S.A. Tabacova (1973). Effects of methylmercuric chloride on the progeny of mice and rats
treated before or during gestation. Food. Cosmet. Toxicol. 11:245-254.
Kim, J.-H., S.E. Lindbert and T.P. Meyers (1995). Micrometeorological measurements of mercury fluxes over
background forest soils in eastern Tennessee. Atmos. Envir. 27:267-282.
Klaunig, J., S. Koepp, and M. McCormick (1975). Acute toxicity of a native mummichog population (Fundulus
heteroclitus) to mercury. Bull. Environ. Contam. Toxicol. 14:534-536.
Koeman, J.H., W.H.M. Peeters, C.H.M. Koudstaal-Hol, P.S. Thioe and J.J.M. De Goeij (1973). Mercury-
selenium correlations in marine mammals. Nature 245:385-386.
Koller, L.D., J.H. Exon and B. Arbogast. 1977. Methylmercury: Effect on serum enzymes and humoral
antibody. J. Toxicol. Environ. Health 2:1115-1123.
8-9
-------
Kozie, K.D. and R.K. Anderson (1991). Productivity, diet, and environmental contaminants in bald eagles
nesting near the Wisconsin shoreline of Lake Superior. Arch. Environ. Contam. Toxicol. 20:41-48.
Kucera, E. (1983). Mink and otters as indicators of mercury in Manitoba waters. Can. J. Zool. 61:2250-2256.
Kudo, A., H. Nagase and Y. Ose (1982). Proportion of methylmercury to the total amount of mercury in river
waters in Canada and Japan. Water Res. 16:1011-1015.
Kuiper, J. (1981). Fate and effects of mercury in marine plankton communities in experimental enclosures.
Ecotoxicol. Environ. Safety 5:106-134.
Landrum, P.P., M.D. Reinhold, S.R. Nihart and B.J. Eadie (1985). Predicting the bioavailability of organic
xenobiotics to Pontoporeia hoyi in the presence of humic and fulvic materials and natural dissolved oxygen.
Environ. Toxicol. Chem. 4:459-467.
Lange, T.R., H.E. Royals and L.L. Connor (1993). Influence of water chemistry on mercury concentration in
largemouth bass from Florida lakes. Trans. Am. Fish. Soc. 122:74-84.
Lathrop, R.C., P.W. Rasmussen and D.R. Knauer (1991). Mercury concentrations in walleyes from Wisconsin
(USA) lakes. Water Air Soil Pollut. 56:295-307.
Lee, Y.H., H. Hultberg and I. Andersson (1985). Catalytic effect of various metal ions on the methylation of
mercury in the presence of humic substances. Water Air Soil Pollut. 25:391-400.
Lee, Y.H. and H. Hultberg (1990). Methylmercury in some Swedish surface waters. Environ. Sci. Technol.
9:833-841.
Lindberg, S.E. (1996). Forests and the global biogeochemical cycle of mercury: the importance of understanding
air/vegetation exchange processes. In: Global and Regional Mercury Cycles: Sources, Fluxes and Mass
Balances. W. Baeyens et al. (Eds.), printed in the Netherlands, pp. 359-380.
Lindqvist, O. (1991). Mercury in the Swedish environment. Recent research on causes, consequences and
corrective measures. Water Air Soil Pollut. 55:1-261.
Lowe, T.P., T.W. May, W.G. Brumbaugh and D.A. Kane (1985). National contaminant biomonitoring program:
Concentrations of seven elements in freshwater fish, 1978-1981. Arch. Environ. Contam. Toxicol. 14:363-388.
MacCrimmon, H.R., C.D. Wren and B.L. Gots (1983). Mercury uptake by lake trout, Salvelinus namaycush,
relative to age, growth, and diet in Tadenac Lake with comparative data from other Precambrian shield lakes.
Can. J. Fish. Aquat. Sci. 40:114-120.
Maserti, B.E. and R. Ferrara (1991). Mercury in plants, soil and atmosphere near a chlor-alkali complex. Water
Air Soil Pollut. 56:15-20.
Mason, R.P., J.R. Reinfelder and F. M.M. Morel (1996). Uptake, toxicity and trophic transfer of mercury in a
coastal diatom. Environ. Sci. Technol. 30:1835-1845.
8-10
-------
Mason, R.P. and K.A. Sullivan (1997). Mercury in Lake Michigan. Environ. Sci. Technol. 31:942-947.
Mathers, R.A. and P.H. Johansen (1985). The effects of feeding ecology on mercury accumulation in walleye
(Stizostedion vitreum) and pike (Esox Indus) in Lake Simcoe. Can. J. Zool. 63:2006-2012.
May, K., M. Stoeppler and K. Reisinger (1987). Studies in the ratio total mercury/methylmercury in the aquatic
food chain. Tox. Environ. Chem. 13:153-159.
McGrath, J.T. (1960). Neurological Examination of the Dog with Clinicopathological Observations. 2nd ed.
Lea and Febiger, Philadelphia, PA.
McKim, J.M., G.F. Olson, G.W. Holcombe and E.P. Hunt (1976). Long-term effects of methylmercuric chloride
on three generations of brook trout (Salvelinus fontinalis): Toxicity, accumulation, distribution, and elimination.
J. Fish. Res. Ed. Can. 33:2726-2739.
McMurtry, M.J., D.L. Wales, W.A. Schneider, G.L. Beggs and P.E. Diamond (1989). Relationship of mercury
concentrations in lake trout (Salvelinus namaycush) and smallmouth bass (Micropterus dolomieui} to the physical
and chemical characteristics of Ontario lakes. Can. J. Fish. Aquat. Sci. 46:426-434.
Meili, M., A. Iverfeldt and L. Hakanson (1991). Mercury in the surface water of Swedish forest lakes -
concentrations, speciation and controlling factors. Water Air SoilPollut. 56:439-453.
Meyer, M.W., B.C. Evers, T. Daulton and W.E. Braselton (1995). Common loons (Gavia immef) nesting on low
pH lakes in northern Wisconsin have elevated blood mercury content. Water Air Soil Pollut. 80:871-880.
Meyer, M.W., B.C. Evers and J.H. Hartigan (1996). Relationship of mercury exposure to common loon
reproduction in Wisconsin. Presentation given at the Wildlife Mercury Workshop, Fairfax, VA, April 12-13,
1996. Co-sponsored by the Wisconsin Department of Natural Resources and the Electric Power Research
Institute.
Mhatre, G.N. and S.B. Chaphekar (1985). The effect of mercury on some aquatic plants. Environ. Pollut.
39:297-216.
Michigan Department of Natural Resources (MDNR, 1993). Mercury in Michigan's environment: Environmental
and human health concerns. A science report to Governor John Engler. R.D. Sills, Michigan Environmental
Science Board, Lansing, MI.
Miskimmin, B.M., J.W.M. Rudd and C.A. Kelly (1992). Influence of dissolved organic carbon, pH and
microbial respiration rates on mercury methylation and demethylation in lake water. Can. J. Fish. Aquat. Sci.
49:17-22.
Mitsumori, K., M. Hirano, H. Ueda, K. Maita, and Y. Shirasu. (1990). Chronic toxicity and carcinogenicity of
methylmercury chloride in B6C3F1 mice. Fund. Appl. Toxicol. 14:179-190.
Mohamed, M., T. Burbacher and N. Mottet (1987). Effects of methyl mercury on testicular functions in Macaca
fascicularis monkeys. Pharmacol. Toxicol. 60(l):29-36.
8-11
-------
Mosbaek, H., J.C. Tjell and T. Sevel (1988). Plant uptake of airborne mercury in background areas.
Chemosphere 17:1227-1236.
Munro, I.C., E.A. Nera and S.M. Charbonneau (1980). Chronic toxicity of methylmercury in the rat. J. Environ.
Path. Toxicol. 3:437-447.
Muramoto, S. and Y. Oki (1984). Influence of anionic surface-active agents on the uptake of heavy metals by
water hyacinth (Eichornia crassipes). Bull. Environ. Contam. Toxicol. 33:444-450.
Nagase, H., Y. Ose, T. Sato and T. Ishikawa (1984). Mercury methylation by compounds in humic material. Sci.
Tot. Environ. 32:147-156.
Nagy, K.A. (1987). Field metabolic rate and food requirement scaling in mammals and birds. Ecol. Monogr.
57:111-128.
National Acid Precipitation Assessment Program (NAPAP, 1990). Acidic deposition: State of science and
technology, volume II, aquatic processes and effects. National Acid Precipitation Program, Washington, B.C.
Nature Conservancy (1994). Heritage database. Eastern Heritage Task Force, Boston, MA. Developed under
U.S. EPA appropriation 683\40108 for the Office of Air Quality Planning and Standards, Emissions Standards
Division, Research Triangle Park, NC.
Niimi, A.J. and G.P. Kissoon (1994). Evaluation of the critical body burden concept based on inorganic and
organic mercury toxicity to rainbow trout (Oncorhynchus mykiss}. Arch. Environ. Contam. Toxicol. 26:169-178.
Nilsson, A. and L. Hakanson (1992). Relationships between mercury in lake water, water color and mercury in
fish. Hydrobiologia 235/236:675-683.
Nolen, G.A., E.V. Buchler, R.G. Geil and E.I. Goldenthal (1972). Effects of trisodium nitrotriacetate on
cadmium and methylmercury toxicity and teratogenicity in rats. Toxicol. Appl. Pharmacol. 23:222-237.
Norheim, G. and A. Froslic (1978). The degree of methylation and organ distribution in some birds of prey in
Norway. Ada. Pharmacol. Toxicol. 43:196-204.
Ohlendorf, H.M., D.J. Hoffman, M.K. Saiki, and T.W. Aldrich (1986). Embryonic mortality and abnormalities
of aquatic birds: apparent impacts of selenium from irrigation drainwater. Sci. Tot. Environ. 52:49-63.
O'Connor, D.J. and S.W. Nielsen (1980). Environmental survey of methylmercury levels in wild mink (Mustela
visoh) and otter (Lutra canadensis) from the northeastern United States and experimental pathology of
methylmercurialism in the otter. Worldwide Furbearer Conference Proceedings, pp. 1728-1745.
Odsjo, T. (1982). Eggshell thinning and levels of DDT, PCB and mercury in the eggs of osprey (Pandion
haliaetus L.) and marsh harrier (Circus aeruginosus L.) in relation to their breeding success and population status
in Sweden. Ph.D. dissertation, University of Stockholm, Sweden.
8-12
-------
Ogden, J.C. (1994). A comparison of wading bird nesting colony dynamics (1931-1946 and 1974-1989) as an
indication of ecosystem conditions in the southern Everglades. In: Everglades: The Ecosystem and its
Restoration. S.M. Davis and J.C. Ogden (Eds.), St. Lucie Press, Delray, FL, pp.533-570.
Olson, K.R. and R.C. Harrel (1973). Effect of salinity on acute toxicity of mercury, copper, and chromium for
Rangia cuneata (Pelecypoda, Mactridae). Contrib. Mar. Sci. 17:9-13.
Olson, K.R., K.S. Squibb and R.J. Cousins (1978). Tissue uptake, subcellular distribution, and metabolism of
14CH3HgCl and CH3203HgCl by rainbow trout, Salmo gairdneri. J. Fish. Res. Bd. Can. 35:381-390.
Osowski, S.L., L.W. Brewer, O.E. Baker and G.P. Cobb (1995). The decline of mink in Georgia, North Carolina,
and South Carolina: The role of contaminants. Arch. Environ. Contam. Toxicol. 29:418-423.
Palmisano, F., N. Cardellicchio and P.O. Zambonin (1995). Speciation of mercury in dolphin liver: a two-stage
mechanism for the demethylation accumulation process and role of selenium. Mar. Environ. Res. 40:109-121.
Parks, J.W., A. Lutz and J.A. Sutton (1989). Water column methylmercury in the Wabigoon/English River-Lake
system: Factors controlling concentrations, speciation, and net production. Can. J. Fish. Aquat. Sci.
46:2184-2202.
Pauling, L. (1963). College Chemistry, Third Edition. Freeman.
Peakall, D.B. (1988). Known effects of pollutants on fish-eating birds in the Great Lakes of North America. In:
Toxic Contamination in Large Lakes. Vol. I: Chronic Effects of Toxic Contaminants in Large Lakes. N.W.
Schmidtke (Ed.), Lewis Publishers, Inc., Chelsea, MI, pp. 39-54.
Porcella, D.B., C.J. Watras and N.S. Bloom (1991). Mercury species in lake water. In: The deposition and fate
of trace metals in our environment. Gen. Tech. Rep. NC-150, S. Verry and S.J. Vermette, U.S. Dept. Agric.,
Forest Service, North Central Forest Exp. Station, St. Paul, MN, pp. 127-138.
Post, J.R., R. Vandenbos and D.J. McQueen (1996). Uptake rates of food-chain and waterborne mercury by fish:
field measurements, a mechanistic model, and an assessment of uncertainties. Can. J. Fish. Aquat. Sci. 53:395-
407.
Rada, R.G., D.E. Powell and J.G. Wiener (1993). Whole-lake burdens and spatial distribution of mercury in
surficial sediments in Wisconsin seepage lakes. Can. J. Fish. Aquat. Sci. 50:865-873.
Ribeyre, R. and A. Boudou (1984). Bioaccumulation et repartition tissulaire du mercure - HgCl2et CF^gCl -
chez Salmo gairdneri apres contamination par voie directe. Water Air SoilPollut. 23:169-186.
Ribeyre, R. And A. Boudou (1994). Experimental study of inorganic and methylmercury bioaccumulation by
four species of freshwater rooted macrophytes from water and sediment contamination sources. Ecotoxicol.
Environ. Safety 28:270-286.
Richardson, G.M., M. Egyed and D.J. Currie (1995). Does acid rain increase human exposure to mercury? A
review and analysis of recent literature. Environ.Toxicol.Chem. 14:809-813.
8-13
-------
Rodier, P.M. (1995). Developing brain as a target of toxicity. Environ. Health Perspec. 103 (suppl. 6):73-76.
Roelke, M.E., D.P. Schultz, C.F. Facemire, S.F. Sundlof and H.E. Royals (1991a). Mercury contamination in
Florida panthers. Florida Game and Fresh Water Fish Commission, Gainesville, FL.
Roelke, M.E., D.P. Schultz, C.F. Facemire and S.F. Sundlof (1991b). Mercury contamination in the free-ranging
endangered Florida panther (Felis concolor coryf). Am. Assoc. Zoo. Vet. Annu. Proc. 277-283.
Roelke, M.M., J.S. Martenson and S.J. O'Brien (1993). The consequences of demographic reduction and genetic
depletion in the endangered Florida panther. Curr. Biol. 3:340-350.
Saouter, E., L. Hare, P.G.C. Campbell, A. Boudou and F. Ribeyre (1993). Mercury accumulation in the
burrowing mayfly (Hexagenia rigidd) (ephemeroptera) exposed to CHjHgCl or HgCl2 in water and sediment.
Water Res. 27:1041-1048.
Sarkar, A. and S. Jana (1986). Heavy metal pollutant tolerance ofAzollapitmata. Water Air Soil Pollut.
27:15-18.
Sato, T. and F. Ikuta (1975). Long-term studies on the neurotoxicity of small amount of methylmercury in
monkeys (first report). In: Tsubaki T, ed. Studies on the Health Effects of Alkylmercury in Japan. Japan:
Environment Agency, 63-70.
Scheuhammer, A.M. (1987). The chronic toxicity of aluminum, cadmium, mercury, and lead in birds: A review.
Environ. Pollut. 46:263-295.
Scheuhammer, A.M. (1988). Chronic dietary toxicity of methylmercury in the zebra finch, Poephila guttata.
Bull. Environ. Contam. Toxicol. 40:123-130.
Scheuhammer, A.M. (1991). Effects of acidification on the availability of toxic metals and calcium to wild birds
and mammals. Environ. Pollut. 71:329-375.
Scheuhammer, A.M. and P.J. Blancher (1994). Potential risk to common loons (Gavia immef) from
methylmercury exposure in acidified lakes. Hydrobiologia 279-289:445-455.
Schlegel, H., D.L. Godbold and A. Huttermann (1987). Whole plant aspects of heavy metal induced changes in
CO2 uptake and water relations of spruce (Picea abies) seedlings. Physiol. Plant. 69:265-270.
Schmidt, M. (1987). Atmospharischer eintrag und interner umsatz von schwermetallen in waldokosystemen. ber.
forschungszentr. Waldokosys./Waldst. A 34/37; Gottingen.
Schmitt, C.J. and W.G. Brumbaugh (1990). National contaminant biomonitoring program: Concentrations of
arsenic, cadmium, copper, lead, mercury, selenium, and zinc in U.S. freshwater fish, 1976-1984. Arch. Environ.
Contam. Toxicol. 19:731-747.
Schreiner, G., B. Ulbrich and R. Bass. 1986. Testing strategies in behavioral teratology: II. Discrimination
learning. Neurobehav. Toxicol. Teratol. 8:567-572.
8-14
-------
Scott, M.L. (1977). Effects of PCBs, DDT, and mercury compounds in chickens and Japanese quail. Fed. Proc.
36:1888-1893.
Scott, D.P. and F.A.J. Armstrong (1972). Mercury concentration in relation to size in several species of
freshwater fishes from Manitoba and Northwestern Ontario. J. Fish. Res. Bd. Can. 29:1685-1690.
Sellers, P., C.A. Kelly, J.W.M. Rudd and A.R. MacHutchon (1996). Photodegradation of methylmercury in
lakes. Nature 380:694-697.
SETAC (1994). Final Report: Aquatic Risk Assessment and Mitigation Dialogue Group. Society of
Environmental Toxicology and Chemistry, Pensacola, FL.
Sheffy, T.B. and J.R. St. Amant (1982). Mercury burdens in furbearers in Wisconsin. J. Wildl. Manage.
46:1117-1120.
Siegel, S.M., B.Z. Siegel, N. Puerner and T. Speitel (1975). Water and soil biotic relations in mercury
distribution. Water Air Soil Pollut. 4:9-18.
Siegel, S.M., B.Z. Siegel, C. Lipp, A. Kruckeberg, G.H.N. Towers and H. Warren (1985). Indicator plant-soil
mercury patterns in a mercury-rich mining area of British Columbia. Water Air Soil Pollut. 25:73-85.
Siegel, S.M., B.Z. Siegel, C. Barghigiani, K. Aratani, P. Penny and D. Penny (1987). A contribution to the
environmental biology of mercury accumulation in plants. Water Air Soil Pollut. 3 3:65 -72.
Simonin, H.A., S.P. Gloss, C.T. Driscoll, C.L. Schofield, W.A. Kretser, R.W. Karcher and J. Symula (1994).
Mercury in yellow perch from Adirondack drainage lakes (New York, U.S.). C.J. Watras and J.W. Huckabee
(Eds), In: Mercury Pollution Integration and Synthesis, Lewis Publishers, Boca Raton, FL., USA. pp. 457-469.
Singleton, F.L. and R.K. Guthrie (1977). Aquatic bacterial populations and heavy metals -1. Composition of
aquatic bacteria in the presence of copper and mercury salts. Water Res. 11:639-642.
Skurdal, J., T. Qvenild and O.K. Skogheim (1985). Mercury accumulation in five species of freshwater fish in
Lake Tyrifiorden, southeast Norway, with emphasis on their suitability as test organisms. Environ. Biol. Fish.
14:233-237.
Slotton, D.G., J.E. Reuter and C.R. Goldman (1995). Mercury uptake patterns of biota in a seasonally anoxic
Northern California reservoir. Water Air Soil Pollut. 80:841-850.
Solomon, K.R., D.B. Baker, R.P. Richards, K.R. Dixon, S.J. Klaine, T.W. La Point, RJ. Kendall, C.P.
Weisskopf, J.M. Giddings, J.P. Giesy, L.W. Hall Jr. and W.M. Williams (1996). Ecological risk assessment of
atrazine in North American surface waters. Environ. Toxicol. Chem. 15:31-76.
Sorensen, J.A., G.E. Glass, K.W. Schmidt, J.K. Huber and G.R. Rapp, Jr. (1990). Airborne mercury deposition
and watershed characteristics in relation to mercury concentrations in water, sediments, plankton, and fish of
eighty northern Minnesota lakes. Environ. Sci. Technol. 24:1716-1727.
8-15
-------
Spalding, M.G., R.D. Bjork, G.V.N. Powell and S.F. Sundlof (1994). Mercury and cause of death in great white
herons. J. Wildl. Manage. 58:735-739.
Spry, D.J. and J.G. Wiener (1991). Metal bioavailability and toxicity to fish in low-alkalinity lakes: A critical
review. Environ. Pollut. 71:243-304.
St. Louis, V.L., J.W.M. Rudd, C.A. Kelly, K.G. Beaty, N.S. Bloom, and R.J. Flett (1994). Importance of
wetlands as sources of methyl mercury to boreal forest ecosystems. Can. J. Fish. Aquat. Sci. 51:1065-1076.
Stanley, R.A. (1974). Toxicity of heavy metals and salts to Eurasian watermilfoil (Myriophyllum spicatum L.).
Arch. Environ. Contam. Toxicol. 2:331-341.
State of Wisconsin (1989). Technical support document for NR 105, 1988. Wisconsin Administrative Code NR
105.07, 1989.
Stickel, L.F., W.H. Stickel, M.A.R. McLane and M. Bruns (1977). Prolonged retention of methyl mercury by
mallard drakes. Bull. Environ. Contam. Toxicol. 18:393-400.
Stober, Q.J.. R.D. Jones and D.J. Scheidt (1995). Ultra trace level mercury in the everglades ecosystem, a multi-
media canal pilot study. Water Air Soil Pollut. 80:991-1001.
Stoewsand, G.S., C.A. Bache and D.J. Lisk (1974). Dietary selenium protection of methylmercury intoxication
of Japanese quail. Bull. Environ. Contam. Toxicol. 11:152-156.
Suchanek, T.H., P.J. Richerson, L.A. Woodward, D.G. Slotton, L.J. Holts and C.E.E. Woodmansee (1993). A
survey and evaluation of mercury in: sediment, water, plankton, periphyton, benthic invertebrates and fishes
within the aquatic ecosystem of Clear Lake, California. Preliminary Report, Prepared for the U.S. Environmental
Protection Agency, Region 9: Superfund Program, by the Institute of Ecology, University of California at Davis,
Davis, CA.
Sundlof, S.F., M.G. Spalding, J.D. Wentworth and C.K. Steible (1994). Mercury in livers of wading birds
(Ciconiiformes) in Southern Florida. Arch. Environ. Contam. Toxicol. 27:299-305.
Suns, K. and G. Hitchin (1990). Interrelationships between mercury levels in yearling yellow perch, fish
condition and water quality. Water Air Soil Pollut. 50:255-265.
Talmage S.S. and B.T. Walton (1993). Food chain transfer and potential renal toxicity of mercury to small
mammals as a contaminated terrestrial field site. Ecotoxicol. 2:243-256.
Thomann, R.V. (1989). Bioaccumulation model for organic chemical distribution in aquatic food chains.
Environ. Sci. Technol. 23:699-707.
Tremblay, A., M. Lucotte and D. Rowan (1995). Different factors related to mercury concentration in sediments
and zooplankton of 73 Canadian lakes. Water Air Soil Pollut. 80:961-970.
8-16
-------
Tremblay, A., M. Lucotte, M. Meili, L. Cloutier and P. Pichet (1996). Total mercury and methylmercury
contents of insects from boreal lakes: ecological, spatial and temporal patterns. Water Qual. Res. J. Can 31:851-873.
Tremblay, A., M. Lucotte and I. Rheault (1996). Methylmercury in a benthic food web of two hydroelectric
reservoirs and a natural lake of northern Quebec (Canada). Water Air Soil Pollut. 91:255-269.
U.S. Environmental Protection Agency (U.S. EPA, 1985). Ambient water quality criteria for mercury - 1984.
EPA/440/5-84/026. Office of Water, Washington, D.C.
U.S. Environmental Protection Agency (U.S. EPA, 1989). Ecological assessment of hazardous waste sites: A
field and laboratory reference. Corvallis, Oregon: Environmental Research Laboratory. EPA/600/3-89/013.
U.S. Environmental Protection Agency (U.S. EPA, 1992a). Peer review workshop on a framework for ecological
risk assessment. Risk assessment forum. EPA/625/3-91/002.
U.S. Environmental Protection Agency (U.S. EPA, 1992b). A national study of chemical residues in fish. EPA
823/R-92/008. Office of Water Regulations and Standards, Washington, D.C.
U.S. Environmental Protection Agency (U.S. EPA, 1993a). Wildlife exposure factors handbook. EPA/600/R-
93/187a. U.S. EPA Office of Research and Development, Washington, DC.
U.S. Environmental Protection Agency (U.S. EPA, 1993b). Great Lakes water quality initiative criteria
documents for the protection of wildlife (proposed) DDT; Mercury; 2,3,7,8-TCDD; PCBs. EPA/822/R-93/006.
U.S. EPA Office of Science and Technology, Washington, DC.
U.S. Environmental Protection Agency (U.S. EPA, 1993c). Water quality guidance for the Great Lakes system
and correction: Proposed rules. Fed. Regist. 58(72):20802-21047 (April 16, 1993).
U.S. Environmental Protection Agency (U.S. EPA, 1994). Draft proceedings of the national wildlife criteria
methodologies meeting, April 13-16, 1992, Charlottesville, VA. U.S. EPA Office of Water and Office of Science
and Technology, Washington, DC.
U.S. Environmental Protection Agency (U.S. EPA, 1995a). Trophic level and exposure analyses for selected
piscivorous birds and mammals. Volume I. Analysis for species of the Great Lakes Basin (Draft). U.S. EPA
Office of Science and Technology, Washington, DC.
U.S. Environmental Protection Agency (U.S. EPA, 1995b). Final water quality guidance for the Great Lakes
system: Final Rule. Fed. Regist. 60(56): 15366-15425 (March 23, 1995).
U.S. Environmental Protection Agency (U.S. EPA, 1996). Proposed guidelines for ecological risk assessment.
EPA/630/R-95/002B. Risk Assessment Forum, U.S. EPA, Washington, DC.
U.S. Fish and Wildlife Service (U.S. FWS, 1993). Mercury contamination in tissues of Florida bald eagles.
Final Project Report. Prepared for the U.S. Fish and Wildlife Service, Department of the Interior, Washington,
DC. (December, 1993)
8-17
-------
Vermeer, K., F.A.J. Armstrong and D.R.M. Hatch (1973). Mercury in aquatic birds at Clay Lake, Western
Ontario. J. WiM. Manage. 37:58-61.
Watras, C.J. and N.S. Bloom (1992). Mercury and methylmercury in individual zooplankton: Implications for
bioaccumulation. Limnol. Oceanogr. 37:1313-1318.
Watras, C.J., K.A. Morrison, J. Host and N.S. Bloom (1995a). Concentration of mercury species in relationship
to other site-specific factors in the surface waters of northern Wisconsin lakes. Limnol. Oceanogr. 40:556-565.
Watras, C.J., K.A. Morrison and N.S. Bloom (1995b). Mercury in remote Rocky Mountain lakes of Glacier
National Park, Montana, in comparison with other temperate North American regions. Can. J. Fish. Aquat. Sci.
52:1220-1228.
Watras, C.J., K.A. Morrison and N.S. Bloom (1995c). Chemical correlates of Hg and Methyl-Hg in northern
Wisconsin lake waters under ice-cover. Water Air Soil Pollution. 84:253-267.
Watras, C.J., K.A. Morrison, J.S. Host and N.S. Bloom (1995). Concentration of mercury species in relationship
to other site-specific factors in the surface waters of northern Wisconsin lakes. Limnol. Oceanogr. 40:556-565.
Weber, J.H. (1993). Review of possible paths for abiotic methylation of mercury (II) in the aquatic environment.
Chemosphere 26:2063.
Weil, C.S. and D.D. McCollister (1963). Relationship between short- and long-term feeding studies in designing
an effective toxicity test. Agric. Food Chem. 11:486-491.
Weis, J.S. and P. Weis (1989). Tolerance and stress in a polluted environment. BioScience 39:89-95.
Weis, J.S. and P. Weis (1995). Effects of embryonic exposure to methylmercury on larval prey-capture ability in
the mummichog, Fundulus heteroclitus. Environ. Toxicol. Chem. 14:153-156.
Welch, L.J. (1994). Contaminant burdens and reproductive rates of bald eagles breeding in Maine. Ph.D.
dissertation, University of Maine, Orono, ME.
Wells, J.R., P.B. Kaufman and J.D. Jones (1980). Heavy metal contents in some macrophytes from Saginaw Bay
(Lake Huron, USA). Aquat. Bot. 9:185-193.
Westermark, T., T. Odsjo, T. and A.G. Johnels (1975). Mercury in bird feathers before and after the Swedish
ban on alkyl mercury in agriculture. Ambio 4:87-97.
Wiemeyer, S.N., T.G. Lament, C.M. Bunck, C.R. Sindelar, F.J. Gramlich, J.D. Fraser and M.A. Byrd (1984).
Organochlorine pesticide, polychlorobiphenyl, and mercury residues in bald eagle eggs - 1969-1979 - and their
relationships to shell thinning and reproduction. Arch. Environ. Contam. Toxicol. 13:529-549.
Wiemeyer, S.N., D.M. Bunck and C.J. Stafford (1993). Environmental contaminants in bald eagle eggs - 1980-
1984 - and further interpretations of relationships to productivity and shell thickness. Arch. Environ. Contam.
Toxicol. 24:213-227.
8-18
-------
Wiener, J.G., G.A. Jackson, T.W. May and B.P. Cole (1982). Longitudinal distribution of trace elements (As,
Cd, Cr, Hg, Pb, and Se) in fishes and sediments in the upper Mississippi River. In: Contaminants in the Upper
Mississippi River. J.G. Wiener, R.V. Anderson and D.R. McConville (Eds.). Butterworth Publishers, Boston,
MA. p. 139-170.
Wiener, J.G., R.E. Martini, T.B. Sheffy and G.E. Glass (1990). Factors influencing mercury concentrations in
walleyes in northern Wisconsin lakes. Trans. Amer. Fish. Soc. 119:862-870.
Wiener, J.G. and D.J. Spry (1996). Toxicological significance of mercury in freshwater fish. In: Envrionmental
Contaminants in Wildlife: Interpreting Tissue Concentrations. W.N. Beyer, G.H. Heinz and A.W. Redman-
Norwood (Eds.), Special Publication of the Society of Environmental Toxicology and Chemistry, Lewis
Publishers, Boca Raton, FL, USA. pp. 297-339.
Winfrey, M.R. and J.W.M. Rudd (1990). Review - Environmental factors affecting the formation of
methylmercury in low pH lakes. Environ. Toxicol. Chem. 9:853-869.
Wobeser, G. (1973). Aquatic mercury pollution: studies of its occurrence and pathologic effects on fish and
mink. Ph.D. dissertation, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Wobeser, G. and M. Swift III (1976). Mercury poisoning in a wild mink. J. Wildl. Dis. 12:335-340.
Wobeser, G., N.D. Nielsen and B. Schiefer (1976a). Mercury and mink I: The use of mercury contaminated fish
as a food for ranch mink. Can. J. Comp. Med. 40:30-33.
Wobeser, G., N.D. Nielsen and B. Schiefer (1976b). Mercury and mink II: Experimental methyl mercury
intoxication. Can. J. Comp. Med. 40:34-45.
Wood, P.B., J.H. White, A. Steffer, J.M. Wood, C.F. Facemire, H.F. Percival (1996). Mercury concentrations in
tissues of Florida bald eagles. J. Wildl. Manage. 60:178-185.
World Health Organization (WHO, 1989). Environmental health criteria 86: Mercury - environmental aspects.
Wren, C.D. (1985). Probable case of mercury poisoning in a wild otter, Lutra canadensis, in northwestern
Ontario. Can. Field Nat. 99:112-114.
Wren, C.D. (1986). A review of metal accumulation and toxicity in wild mammals. I. Mercury. Environ. Res.
40:210-244.
Wren, C.D. (1991). Cause-effect linkages between chemicals and populations of mink (Mustela visoh) and otter
(Lutra canadensis) in the Great Lakes basin. J. Toxicol. Environ. Health 33:549-585.
Wren, C.D., H.R. MacCrimmon and B.R. Loescher (1983). Examination of bioaccumulation and
biomagnification of metals in aprecambrian shield lake. Water Air Soil Pollut. 19:277-291.
Wren, C.D. and H.R. MacCrimmon (1986). Comparative bioaccumulation of mercury in two adjacent freshwater
ecosystems. Water Res. 20:763-769.
8-19
-------
Wren, C.D., P.M. Stokes and K.L. Fischer (1986). Mercury levels in Ontario mink and otter relative to food
levels and environmental acidification. Can. J. Zool. 64:2854-2859.
Wren, C.D., D.B. Hunter, J.F. Leatherland, and P.M. Stokes (1987a). The effects of polychlorinated biphenyls
and methylmercury, singly and in combination on mink. I: Uptake and toxic responses. Arch. Environ. Contam.
Toxicol. 16:441-447.
Wren, C.D., D.B. Hunter, J.F. Leatherland, and P.M. Stokes (1987b). The effects of polychlorinated biphenyls
and methylmercury, singly and in combination on mink. II: Reproduction and kit development. Arch. Environ.
Contam. Toxicol. 16:449-454.
Wren, C.D. and G.L. Stephenson (1991). The effect of acidification on the accumulation and toxicity of metals
to freshwater invertebrates. Environ. Pollu. 71:205-241.
Wright, D.R. and R.D. Hamilton (1982). Release of methyl mercury from sediments: effects of mercury
concentration, low temperature, and nutrient addition. Can. J. Fish Aquat. Sci. 39:1459-1466.
Xun, L., N.E.R. Campbell and J.W.M. Rudd (1987). Measurements of specific rates of net methyl mercury
production in the water column and surface sediments of acidified and circumneutral lakes. Can. J. Fish. Aquat.
Sci. 44:750-757.
Yannai, S., I. Berdicevsky and L. Duek (1991). Transformations of inorganic mercury by Candida albicans and
Saccharomyces cerevisiae. Appl. Environ. Micro. 57:245-247.
Yin, Y., H.E. Allen, Y. Li, C.P. Huang and P.P. Saunders (1996). Adsorption of mercury (II) by soil: effects of
pH, chloride, and organic matter. J. Environ. Qual. 25:837-844.
Zalups, R.K. and L.H. Lash (1994). Advances in understanding the renal transport and toxicity of mercury. J.
Toxicol. Environ. Health 42:1-44.
Zelles, L., I. Scheunert and F. Korte (1986). Comparison of methods to test chemicals for side effects on soil
microorganisms. Ecotoxicol. Environ. Safety 12:53-69.
Zillioux, E.J., D.B. Porcella and J.M. Benoit (1993). Mercury cycling and effects in freshwater wetland
ecosystems. Environ. Toxicol. Chem. 12:2245-2264.
8-20
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