United States

Environmental Protection

Agency

Air

EPA-452/R-97-008

December 1997

Mercury Study

Report to Congress

c7o032-1-1

Office of Air Quality Planning & Standards

and

Office of Research and Development

Volume VI:

An Ecological Assessment for

Anthropogenic Mercury

Emissions in the United States
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
i

TABLE OF CONTENTS

Page

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
ii

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
iii

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
iv

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. Glenn E. Rice

Ecosystems Research Division National Center for Environmental AssessmentNational Exposure Research Laboratory Cincinnati

Athens, GA Office of Research and Development

Chris Cubbison, Ph.D.

National Center for Environmental Assessment- David J. Reisman

Cincinnati National Center for Environmental AssessmentOffice of Research and Development Cincinnati

Cincinnati, OH Office of Research and Development

Anne Fairbrother, Ph.D., D.V.M.

Environmental Research Laboratory-Corvallis Rita Schoeny, Ph.D.

Corvallis, OR National Center for Environmental Assessmentcurrently 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 AssessmentCincinnati

Office of Research and Development

Cincinnati, OH

Debdas Mukerjee, Ph.D.

National Center for Environmental AssessmentCincinnati

Office of Research and Development

Cincinnati, OH

Cincinnati, OH

Cincinnati, OH

Cincinnati

Office of Research and Development

Cincinnati, OH

Jeff Swartout

National Center for Environmental AssessmentCincinnati

Office of Research and Development

Cincinnati, OH

Michael Troyer

Office of Science, Planning and Regulatory

Evaluation

Cincinnati, OH
v

SCIENTIFIC PEER REVIEWERS

Dr. William J. Adams* Elizabeth Campbell

Kennecott Utah Corporation U.S. Department of Energy

Dr. Brian J. Allee

Harza Northwest, Incorporated Dr. Rick Canady

Dr. Thomas D. Atkeson Registry

Florida Department of Environmental Protection

Dr. Donald G. Barnes* U.S. Department of Agriculture

U.S. EPA Science Advisory Board

Dr. Steven M. Bartell Lawrence Berkeley National Laboratory

SENES Oak Ridge, Inc.

Dr. David Bellinger* Medical College of Wisconsin

Children’s Hospital, Boston

Dr. Nicolas Bloom* University of Cincinnati

Frontier Geosciences, Inc.

Dr. Mike Bolger Great Lakes Natural Resource Center

U.S. Food and Drug Administration National Wildlife Federation for the

Dr. Peter Botros

U.S. Department of Energy Dr. Katherine Flegal

Federal Energy Technology Center National Center for Health Statitistics

Thomas D. Brown Dr. Lawrence J. Fischer*

U.S. Department of Energy Michigan State University

Federal Energy Technology Center

Dr. Dallas Burtraw* University of Connecticut

Resources for the Future Avery Point

Dr. Thomas Burbacher* A. Robert Flaak*

University of Washington U.S. EPA Science Advisory Board

Seattle

Dr. James P. Butler University of Maryland at Baltimore

University of Chicago

Argonne National Laboratory Dr. Steven G. Gilbert*

Policy Office, Washington D.C.

Agency for Toxic Substances and Disease

Dr. Rufus Chaney

Dr. Joan Daisey*

Dr. John A. Dellinger*

Dr. Kim N. Dietrich*

Dr. Tim Eder

States of Michigan and Ohio

Dr. William F. Fitzgerald

Dr. Bruce A. Fowler*

Biosupport, Inc.
SCIENTIFIC PEER REVIEWERS (continued)

vi

Dr. Cynthia C. Gilmour* Dr. Steven E. Lindberg*

The Academy of Natural Sciences Oak Ridge National Laboratory

Dr. Robert Goyer Dr. Genevieve M. Matanoski*

National Institute of Environmental Health The Johns Hopkins University

Sciences

Dr. George Gray University of California

Harvard School of Public Health Berkeley

Dr. Terry Haines Dr. Malcolm Meaburn

National Biological Service National Oceanic and Atmospheric

Dr. Gary Heinz* U.S. Department of Commerce

Patuxent Wildlife Research Center

Joann L. Held Wisconsin Department of Natural Resources

New Jersey Department of Environmental

Protection & Energy Dr. Maria Morandi*

Dr. Robert E. Hueter*

Mote Marine Laboratory Dr. Paul Mushak

Dr. Harold E. B. Humphrey*

Michigan Department of Community Health Harvey Ness

Dr. James P. Hurley* Federal Energy Technology Center

University of Wisconsin

Madison Dr. Christopher Newland*

Dr. Joseph L. Jacobson*

Wayne State University Dr. Jerome O. Nriagu*

Dr. Gerald J. Keeler Ann Arbor

University of Michigan

Ann Arbor William O’Dowd

Dr. Ronald J. Kendall* Federal Energy Technology Center

Clemson University

Dr. Lynda P. Knobeloch* University of Florida

Wisconsin Division of Health Gainesville

Dr. Leonard Levin Dr. Jozef M. Pacyna

Electric Power Research Institute Norwegian Institute for Air Research

Dr. Thomas McKone*

Administration

Dr. Michael W. Meyer*

University of Texas Science Center at Houston

PB Associates

U.S. Department of Energy

Auburn University

The University of Michigan

U.S. Department of Energy

Dr. W. Steven Otwell*
SCIENTIFIC PEER REVIEWERS (continued)

vii

Dr. Ruth Patterson Dennis Smith

Cancer Prevention Research Program U.S. Department of Energy

Fred Gutchinson Cancer Research Center Federal Energy Technology Center

Dr. Donald Porcella Dr. Ann Spacie*

Electric Power Research Institute Purdue University

Dr. Deborah C. Rice* Dr. Alan H. Stern

Toxicology Research Center New Jersey Department of Environmental

Samuel R. Rondberg*

U.S. EPA Science Advisory Board Dr. David G. Strimaitis*

Charles Schmidt

U.S. Department of Energy Dr. Edward B. Swain

Dr. Pamela Shubat

Minnesota Department of Health Dr. Valerie Thomas*

Dr. Ellen K. Silbergeld*

University of Maryland Dr. M. Anthony Verity

Baltimore University of California

Dr. Howard A. Simonin*

NYSDEC Aquatic Toxicant Research Unit

Protection & Energy

Earth Tech

Minnesota Pollution Control Agency

Princeton University

Los Angeles

*With EPA’s Science Advisory Board, Mercury Review Subcommitte
viii

WORK GROUP AND U.S. EPA/ORD REVIEWERS

Core Work Group Reviewers: U.S. EPA/ORD Reviewers:

Dan Axelrad, U.S. EPA Robert Beliles, Ph.D., D.A.B.T.

Office of Policy, Planning and Evaluation National Center for Environmental Assessment

Angela Bandemehr, U.S. EPA

Region 5 Eletha Brady-Roberts

Jim Darr, U.S. EPA Cincinnati, OH

Office of Pollution Prevention and Toxic

Substances Annie M. Jarabek

Thomas Gentile, State of New York Research Triangle Park, NC

Department of Environmental Conservation

Arnie Kuzmack, U.S. EPA National Center for Environmental Assessment

Office of Water Washington, DC

David Layland, U.S. EPA Susan Braen Norton

Office of Solid Waste and Emergency Response National Center for Environmental Assessment

Karen Levy, U.S. EPA

Office of Policy Analysis and Review Terry Harvey, D.V.M.

Steve Levy, U.S. EPA Cincinnati, OH

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

Washington, DC

National Center for Environmental Assessment

National Center for Environmental Assessment

Matthew Lorber

Washington, DC

National Center for Environmental Assessment
ix

LIST OF TABLES

Page

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
x

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
xi

LIST OF SYMBOLS, UNITS AND ACRONYMS

BAF Bioaccumulation factor

BAF Aquatic life bioaccumulation factor for trophic level 3 3

BAF Aquatic life bioaccumulation factor for trophic level 4 4

BCF Bioconcentration factor

BSAF Biota-sediment accumulation factor

BMF 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

F Average daily amount of food consumed A

FCM Food chain multiplier

FD Fraction of the diet derived from trophic level 3 3

FD Fraction of the diet derived from trophic level 4 4

GAS-ISC3 Short range air dispersion model for mercury

GLWQI Great Lakes Water Quality Initiative

ha Hectare

Hg Elemental mercury 0

Hg Mercurous ion 2

2+

Hg Mercury II 2+

IEM-2M Indirect exposure model for mercury

IJC International Joint Commission

kg Kilogram

L Liter

LC Lethal concentration (for fifty percent of population) 50

LD Lethal dose (for fifty percent of population) 50

LCUB Large coal-fired utility boiler

LOAEL Lowest-observed-adverse-effect level

m Meter

m Cubic meter 3

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
LIST OF SYMBOLS, UNITS AND ACRONYMS (continued)

xii

PPF The observed ratio of the concentration at trophic level 4, divided by the 4

concentration at trophic level 3

ppm parts per million

RELMAP Regional Lagrangian Model of Air Pollution

SAB Science Advisory Board

sp. Species

UF Uncertainty factor for species extrapolation A

UF Uncertainty factor for use of less than lifetime study S

UF Uncertainty factor for use of a lowest adverse effect level L

U.S. EPA U.S. Environmental Protection Agency

g Microgram

M Micromole

W Average daily volume of water consumed A

WC Wildlife criterion level

WC Final wildlife criterion level f

WC Intermediate wildlife criterion level i

WC Species-specific wildlife criterion level s

Wt Average species weight A
ES-1

EXECUTIVE SUMMARY

Section 112(n)(1)(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-2

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 of fish 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 μg/m ) was characterized. 2

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-3

Table ES-1

Percent of Species Range Overlapping

 with Regions of High Mercury Deposition

Species

Percent of Range

Impacted

Kingfisher 29%

Bald Eagle 34%

Osprey 20%

Common Loon 40%

Florida Panther 100%

Mink 35%

River Otter 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 of fish. 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-4

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 chloralkali 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 of fish 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.
ES-5

Table ES-2

Percentiles of the Methylmercury Bioaccumulation Factor

Parameter

Percentile of Distribution

5th 25th 50th 75th 95th

Trophic 3 BAF 4.6 x 10 9.5 x 10 1.6 x 10 2.6x10 5.4x10 5 5 66 6

Trophic 4 BAF 3.3x10 5.0x10 6.8x10 9.2x10 1.4x 10 66 6 6 7

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 μg/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 μg/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 mercurycontaminated fish. The dose of 0.33 ppm (55 μg/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 μg/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
ES-6

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

μg/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 noncancer 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
ES-7

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 Wildlife Criterion (pg/L)

Mink 57

River otter 42

Kingfisher 33

Loon 82

Osprey 82

Bald eagle 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 μg/g and 0.346 μg/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.
ES-8

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-9

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

μg/kg bw/d (mercury basis). The RfD for mammalian wildlife is 18 μg/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 fourtiered 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
ES-10

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).
1-1

1. INTRODUCTION

Section 112(n)(1)(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
1-2

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 shortrange 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.
2-1

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; 0

2-3

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 o

generally is comprised of gaseous divalent (Hg ) mercury and mercury associated with particulates 2+

(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 Hg , which is thought to occur primarily as mercuric chloride (MDNR, 1993). 2+

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 o

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
2-4

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. Hg is the 2+

predominant form in precipitation (MDNR, 1993).

2.1.2 Mercury in Surface Water

Mercury can enter surface water as Hg , Hg , or methylmercury. Once in aquatic systems, o 2+

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 Hg or volatilized to the atmosphere. o 2+

Hg can be methylated in sediments and the water column to form methylmercury. 2+

Methylmercury can be alkylated to form dimethylmercury.

Hg and methylmercury can form organic and inorganic complexes with sediment and 2+

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).
2-5

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)

Hg in soils can be transformed to other mercury species. Bacteria and organic substances can 2+

reduce Hg to Hg , releasing volatile elemental mercury to the atmosphere. Alternatively, bacteria and 2+ o

organic substances can methylate mercury, and subsequently demethylate it, depending on environmental

conditions (Allard and Arsenie, 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 



Plants with roots, stems, and leaves, such as ferns and seed plants. 4

Stomata (plural of stoma) are the minute openings in the epidermis of leaves, stems, or other plant organs 5 

that allow gas to diffuse in and out.

2-9

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; Futter, 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 plants can occur through the roots or through the leaves, by way of 4

stomata (Mosbaek et al., 1988; Crowder, 1991; Maserti and Ferrara, 1991). A vascular plant's uptake of 5

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.

2-11

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 mercurycontaminated 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.
2-12

Table 2-1

Examples of Effects of Contaminants on Ecosystem Components

Component Examples of Effects

Individual Increased susceptibility to pathogens

Change in respiration

Change in behavior (e.g., migration, predator-prey interactions)

Inhibition or induction of enzymes

Decreased growth

Decreased reproduction

Death

Population Decreased recruitment of juveniles

Decreased genotypic and phenotypic diversity

Decreased biomass

Increased mortality rate

Decreased fecundity rate

Increased frequency of disease

Decreased yield

Change in age/size class structure

Extinction

Community Decreased food web diversity

Decreased species diversity

Change in species composition

Decreased productivity

Increased algal blooms

Ecosystem Altered nutrient cycling

Decreased diversity of communities

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.
2-13

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 BMF) 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). 
2-14

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, BSAFs, 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

HgCl and CH HgCl) (Mason et al., 1996). Factors that can alter the concentration of these neutral 2 3

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 Hg data) ranging from about 2,000 to 40,000 were 2+

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. 
2-15

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 of fish 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). 
2-16

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 of fish 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). 
2-17

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 Mercury Concentration Averaged Across

Sampling Sites (g/g wet weight)

Carp 0.11

Sucker (White, Redhorse and Spotted) 0.17

Catfish (Channel and Flathead) 0.16

Bass (Largemouth, Smallmouth and White) 0.38

Walleye pike 0.52

Northern pike 0.31

Crappie 0.22

Brown Trout 0.14

Mean of All Fish Sampled 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 μg/g) and largemouth bass (0.14 μg/g) contained more mercury

than co-collected non-piscivorous species (0.07 and 0.09 μg/g, respectively). The maximum mercury

concentration reported was 1.09 μg/g, and the mean across all fish and sites was 0.11 μg/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.
2-18

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 μg/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 μg/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 μg/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 (PPF ) can be estimated from existing field data. This calculation was made in Appendix D, Volume III of this 4

Report, resulting in a mean PPF of 4.9. Dividing this value into the average residue for trophic level 4 fish 4

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 freeliving birds greater than 50% of the total body burden of mercury may be 
2-19

Table 2-3

Mercury Residues in Tissues of Piscivorous Birds

Species Mercury Tissue Sampling Location Comments 

 (μg/g fresh weight)

Bald eagle 13.0 - 21.0 feathers Great Lakes region adults 

Bald eagle 3.7 - 20.0 feathers Great Lakes region nestlings 

Bald eagle 0.1 - 34.7 feathers N. Central Florida adults 

Bald eagle 0.8 - 14.3 feathers N. Central Florida nestlings 

Common loon 8.7 feathers Minnesota lakes adults Common loon 2.7 feathers Minnesota lakes juveniles 

Common loon 11.0 - 18.0 feathers Wisconsin lakes adults Common loon 2.0 - 5.0 feathers Wisconsin lakes juveniles Wood stork 1.9 feathers South Florida juveniles Bald eagle 0.15 - 0.29 eggs British Columbia 

Bald eagle 0.07 - 0.41 eggs 15 States (USA) Common loon 0.40 - 1.10 eggs Wisconsin lakes Common loon 2.0 - 3.0 eggs Northwestern Ontario polluted by point 

source; LOAEL -reproduction

Common tern 3.6 eggs Northwestern Ontario polluted by point 

source; LOAEL -reproduction

Herring gull 2.3 - 15.8 eggs Clay Lake, Ontario polluted by point 

source, no adverseeffects
Table 2-3 (continued)

Mercury Residues in Tissues of Piscivorous Birds

Species Mercury Tissue Sampling Location Comments 

 (μg/g fresh weight)

2-20

Wood stork 0.7 eggs South Florida 

Tree swallow 0.04 - 0.08 eggs Lower Great Lakes consume emergent 

aquatic insects

Common loon 1.6 - 47.7 liver Northwestern Ontario LOAEL - 

reproduction

Common loon 9.5 - 90.0 liver Wisconsin lakes adults found dead Common loon 5.6 liver Minnesota lakes adults found injured 

Great White Heron 0.6 - 59.4 liver South Florida mixed age birds 

found dead

Great Blue Heron 0.2 - 7.3 liver South Florida nestlings 

Great Blue Heron 0.1 - 74.5 liver South Florida fledglings/young 

adults

Common loon 0.2 - 6.9 breast muscle Northwestern Ontario polluted by point 

source

Common goldeneye 0.9 - 19.4 breast muscle Clay Lake, Ontario polluted by point 

source

Common merganser 4.4 - 13.1 breast muscle Clay Lake, Ontario polluted by point 

source

Hooded merganser 3.9 - 17.6 breast muscle Clay Lake, Ontario polluted by point 

source

Herring gull 0.7 - 4.0 breast muscle Tadenac Lake, Ontario 
Table 2-3 (continued)

Mercury Residues in Tissues of Piscivorous Birds

Species Mercury Tissue Sampling Location Comments 

 (μg/g fresh weight)

2-21

Common loon 1.5 breast muscle Tadenac Lake, Ontario 

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. Ensor et al., 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, respecti

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, respective

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.
2-22

present in the plumage (Braune and Gaskin, 1987). Natural background levels of mercury in feathers of nonpiscivorous 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 of ten 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.
2-23

Table 2-4

Mercury Residues in Tissues of Piscivorous Mammals

Species Mercury Tissue Sampling Location Comments 

(μg/g fresh weight)

Otter 6.5 (max. = 63.2) fur Wisconsin Otter 47.0 fur Clay Lake, Ontario polluted by point 

source; death due topoisoning

Otter 15.2 - 25.6 fur Georgia 

Mink 10.7 (max. = 17.3) fur Georgia Mink 7.6 (max. = 41.2) fur Wisconsin Mink 34.9 fur Saskatchewan polluted by point 

source; death due topoisoning

Raccoon 4.4 fur S. Florida Muskrat 0.06 fur Wisconsin Beaver 0.03 fur Wisconsin Otter 5.1 - 9.2 liver Georgia 

Otter 1.7 - 3.4 liver Manitoba males and females Otter 2.4 - 4.5 liver Winnipeg R. males and females; 

polluted by point

source

Otter 0.3 - 3.0 liver Louisiana Otter 0.9 - 3.5 liver Ontario residues correlated 

with acidity
Table 2-4 (continued)

Mercury Residues in Tissues of Piscivorous Mammals

Species Mercury Tissue Sampling Location Comments 

(μg/g fresh weight)

2-24

Otter 0.8 - 3.2 liver N. Michigan 

Otter 1.3 - 2.3 liver New York Otter 96.0 liver Clay Lake, Ontario polluted by point 

source; death due topoisoning

Otter 3.3 (max. = 23.6) liver Wisconsin Mink 0.4 - 1.7 liver Manitoba Mink 2.1 (max. = 17.4) liver Wisconsin Mink 0.1 - 2.6 liver Ontario residues correlated 

with acidity

Mink 58.2 liver Saskatchewan polluted by point 

source; death due topoisoning

Mink 0.9 - 2.9 liver New York Raccoon 2.0 liver Wisconsin Raccoon 1.5 - 24.0 liver S. Florida Muskrat < 0.02 liver Wisconsin Beaver 0.04 liver Wisconsin 

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.
Table 2-4 (continued)

Mercury Residues in Tissues of Piscivorous Mammals

2-25

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 valu

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 et al., 1988; range of means across sampling locations.

12. Roelke et al., 1991; range of means across sampling locations.
2-26

 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

Hg (HgCl or HgNO ) Methylmercury 2+

3

(g/L) (g/L)

Low End High End Low End High End

Fresh Water 53 (alga) 3,400 (submerged 0.8 (alga) 6.0 (alga)

aquatic vegetation)

Salt Water 10 (alga) 160 (seaweed) Not available 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 Hg . One to ten nM (nanomolar) mercuric 2+

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).
2-27

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 Hg compounds 2+

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 Hg to aquatic organisms. 2+

Table 2-6

Mercury Toxicity Increases With Temperature

Temperature (C) LC (g/l) 50

Rainbow Trout with HgCl

5 400

10 280

15 220

Juvenile Catfish with Phenylmercuric Acetate

10 1,960

16.5 1,360

24 233

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. LC values for fish range from 30 g/L for guppies to 1,000 g/L for 50

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
2-28

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 μg/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 mercuryimpacted "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 Hg , acute values 2+

(LC ) for invertebrates range from 2.2 g/L for the cladoceran Daphnia pulex to 2,000 g/L for the larval forms 50

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 LD values ranging from 2.2 to 23.5 g/g for 50

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 
2-29

Table 2-7

Toxicity Values for Fish and Aquatic Invertebrates

Organism Hg (HgCl or HgNO ) (g/L) Methylmercury (g/L) 2+

3

A C U T E (LC ) 50

Fresh water 2.2 (cladoceran) to 2,000 (insect larvae) Not available

invertebrates

Fresh water fish 30 (guppy) to 1,000 (tilapia) Not available

Rainbow trout 155 to 420 24 to 84

Fresh water AWQC 2.4 (total mercury) a

Salt water 3.5 (mysid) to 400 (soft clam) Not available

invertebrates

b

Salt water fish 36 (juvenile spot) to 1,678 (flounder) 51.1 (mummichog) c

Salt water AWQC 2.1 (total mercury) a

C H R O N I C

Fresh water 0.96 (cladoceran) to 1.287 (cladoceran) < 0.04 (cladoceran)

invertebrates

Fresh water fish < 0.23 (minnow) to < 0.26 (minnow) 0.29 (brook trout) to 0.93 (brook trout)

Fresh water AWQC 0.012 (total mercury) a

Salt water 1.131 (mysid) Not available

invertebrates

Salt water AWQC 0.025 (total mercury) a

 AWQCs are designed to be protective of the aquatic community as a whole. a

 As cited in U.S. EPA, 1985, LC s of 10,000 and 8,700 g/L for Atlantic clams (Rangia cuneata) were reported by Olson and Harrell b

50

(1973), but Dillon (1977) reported LC values of 58 and 122 g/L for the same clam species. 50

 As cited in U.S. EPA, 1985, an LC of 2,000 g/L for mummichogs was reported by Klaunig et al. (1975), but Dorfman (1977) and c

50

Eisler and Hennekey (1977) reported LC values of 800 g/L or less for the same fish species. 50

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 (Odsjö, 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
2-30

(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 vison) 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.
2-31

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 C1) 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 C1. 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 C1 habitat but were also elevated in the C2 habitat, presumably because loons were

feeding on contaminated prey which migrated from C1. 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 g/g. No loons reproduced successfully where prey species contained mercury at

levels greater than 0.4 g/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 g/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 g/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.
2-32

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
2-33

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 DDD, 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
2-34

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.
2-35

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. 
2-36

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 ) required to elicit toxic effects on natural aquatic +2

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 farreaching 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 et al., 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
2-37

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;
2-38

 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 of fish 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).
2-39

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 of fish 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;

Futter, 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. 
2-40

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).

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).

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 
2-41

Table 2-8

Examples of Assessment and Measurement Endpoints

Level of Organization Assessment Endpoints Measurement Endpoints

Ecoregion Regional production Regional production a

Biodiversity Habitat area

Landscape aesthetics Other landscape descriptors

Ecosystem

Productive capability Habitat area

Nutrient balance Biomass

Soil balance Productivity

Nutrient export

Community Market/sport value Species diversity

Recreational quality Species number

Change to less useful/desired type Species evenness

Market/sport value

Saprobic index

Population Frequent gross morbidity Fecundity

Extinction Occurrence

Abundance Numbers/density

Yield/production Age structure

Massive mortality Yield/production

Range Frequency of gross morbidity

Mortality rate

Individual Reproduction Fecundity

Survival Longevity

Growth and development Growth and development

Good physical condition Overt symptomology

Biomarkers

Abiotic

Habitat quality Temperature

Water flow

Soil characteristics

Sediment characteristics

 An ecoregion is an area (region) of relative homogeneity in ecological systems (based on elevation, soils, latitude, a

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
2-42

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. 
3-1

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 of fish 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). 
3-2

Table 3-1

Models Used to Predict Mercury Air Concentrations,

Deposition Fluxes and Environmental Concentrations

Model Description

RELMAP deposition flux for each 40 km grid in the U.S. due to all anthropocentric sources of

Predicts average annual atmospheric mercury concentration and wet and dry 2

mercury in the U.S. and a natural background atmospheric mercury concentration.

GAS-ISC3 Predicts average concentration and deposition fluxes within 50 km of emission

source.

IEM-2M 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 (Hg ), and methylmercury (MHg). The mass balances are performed for each 0 2+

mercury component, with internal transformation rates linking Hg , Hg , and MHg. Sources include wetfall and 0 2+

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 0

watershed soils, burial of each component in lake sediments, volatilization of Hg and MHg from the soil and 0

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
3-3

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 of fish (Futter, 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 10 and 1.6 x 10 . Methylmercury was estimated to constitute 7.8% of the total dissolved mercury in the 6 6

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

Percentile of Distribution

5th 25th 50th 75th 95th

Trophic 3 BAF 4.6 x 10 9.5 x 10 1.6 x 10 2.6x10 5.4x10 5 5 66 6

Trophic 4 BAF 3.3x10 5.0x10 6.8x10 9.2x10 1.4x 10 66 6 6 7

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 of fish is reasonable and appropriate.
3-4

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 of fish 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 of fish 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 of fish 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 of fish. 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 of fish 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 of fish 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 (Wt ) (F ) (W ) Wildlife Food

Body Wt. Ingestion Rate Drinking Rate Trophic Level of

A

kg kg/d L/d Source

A A

% Diet at

Each

Trophic

Level

Mink 0.80 0.178 0.081 3 90

Otter 7.40 1.220 0.600 3,4 80,20

Kingfisher 0.15 0.075 0.017 3 100

Loon 4.0 0.8 0.14 3 100

Osprey 1.50 0.300 0.077 3 100

Eagle 4.60 0.500 0.160 3,4 74,18,8
3-5

Table 3-4

Summary of Sample Calculations of

Wildlife Species Methylmercury Exposure

From Fish Ingestion, Based

on Average Fish Residue Values 

Species

Sample Estimated

Methylmercury Exposure from

Fish Ingestion (g/kg bw/d)

Kingfisher 25

Otter 15

Loon 10

Osprey 10

Mink 10

Eagle 9

The ratio of grams fish consumed per day to piscivore body weight is also significant in estimating

mercury exposure on a μg/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 of fish 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 μg/g and 0.26 μg/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).

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 km grid in the continental 2

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.
3-6

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/m . Highly industrialized northeastern states and south Florida are projected to receive more 2

than 20 g/m . RELMAP results are projections that may differ quantitatively from actual sampling data for a 2

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 



3-10

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 μg/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. 





3-16

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 of fish. 

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. 





3-22

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

Eastern Site Western Site

Air Concentration Annual Air Concentration Annual

ng/m Deposition Rate ng/m Deposition Rate 3

μg/m /yr μg/m /yr 2

3

2

Pre- 0.5 3 0.5 1

Anthropogenic

Current 1.6 10 1.6 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
3-23

Figure 3-14

Configuration of Hypothetical Water Body and Watershed Relative to Local Source

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 km . In each case, deposition information was used to estimate mercury 2

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).
3-24

Table 3-6

Process Parameters for the Model Plants Considered in the Local Impact Analysis

Model Plant Plant Size Capacity Height Diameter Rate Percent Velocit

 (% of year) (ft) (ft) (kg/yr) (Hg /Hg /Hg ) (m/sec

Stack Stack Hg Emission Speciation Exit 

0 2+

P

Large Municipal Waste 2,250 tons/day 90% 230 9.5 220 60/30/10 21.9 

CombustorsSmall Municipal Waste 200 tons/day 90% 140 5 20 60/30/10 21.9 CombustorsLarge Commercial HMI 1500 lb/hr capacity 88% 40 2.7 4.58 33/50/17 9.4 Waste Incinerator (1000 lb/hr actual)(Wetscrubber)Large Hospital HMI 1000 lb/hr capacity 39% 40 2.3 23.9 2/73/25 16 Waste Incinerators (667 lb/hr actual)(Good Combustion)Small Hospital HMI 100 lb/hr capacity 27% 40 0.9 1.34 2/73/27 10.4 Waste Incinerators (67 lb/hr actual)(1/4 sec Combustion)Large Hospital HMI 1000 lb/hr capacity 39% 40 2.3 0.84 33/50/17 9.0 Waste Incinerators (667 lb/hr actual)(Wet Scrubber)Small Hospital HMI 100 lb/hr capacity 27% 40 0.9 0.05 33/50/17 Waste Incinerators (Wet (67 lb/hr actual)Scrubber)

5.6

Large Coal-fired Utility 975 Megawatts 65% 732 27 230 50/30/20 31.1 

BoilerMedium Coal-fired 375 Megawatts 65% 465 18 90 50/30/20 26.7 Utility Boiler

Small Coal-fired Utility 100 Megawatts 65% 266 12 10 50/30/20 6.6 

BoilerMedium Oil-fired Utility 285 Megawatts 65% 290 14 2 50/30/20 20.7 BoilerChlor-alkali plant 300 tons 90% 10 0.5 380 70/30/0 0.1 

chlorine/day

 Hg = Elemental Mercury a 0

 Hg = Divalent Vapor Phase Mercury b 2+

 Hg = Particle-Bound Mercury c P
3-25

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 
3-26

Table 3-7

Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Pe

MHg Concentration (μg/g) Predicted MHg Exposure from In

MHg Dissolved Tier3 Tier4 Background RELMAP ISC Bald Eagle Osprey Kingfisher R

Concentration (ng/L)

Variant b:Large Municipal 2.5 km 1.7E-01 2.7E-01 1.2E+00 38% 7% 54% 4.4E-02 5.4E-02 1.4E-01 

Waste Combustor 10 km 1.1E-01 1.8E-01 7.6E-01 58% 11% 31% 2.9E-02 3.6E-02 8.9E-02 

25 km 8.9E-02 1.4E-01 6.0E-01 73% 14% 13% 2.3E-02 2.8E-02 7.1E-02 

Variant b:Small Municipal 2.5 km 9.5E-02 1.5E-01 6.4E-01 68% 13% 18% 2.5E-02 3.0E-02 7.6E-02 

Waste Combustor 10 km 8.2E-02 1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 

25 km 7.9E-02 1.3E-01 5.3E-01 83% 16% 2% 2.1E-02 2.5E-02 6.3E-02 

Large Commercial HMI 2.5 km 9.6E-02 1.5E-01 6.5E-01 68% 13% 19% 2.5E-02 3.1E-02 7.7E-02 

10 km 8.0E-02 1.3E-01 5.4E-01 82% 16% 3% 2.1E-02 2.5E-02 6.4E-02 25 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 

Large Hospital HMI 2.5 km 1.9E-01 3.1E-01 1.3E+00 34% 6% 60% 5.0E-02 6.2E-02 1.5E-01 

10 km 9.4E-02 1.5E-01 6.4E-01 69% 13% 18% 2.5E-02 3.0E-02 7.5E-02 25 km 8.1E-02 1.3E-01 5.5E-01 80% 15% 5% 2.1E-02 2.6E-02 6.5E-02 

Small Hospital HMI 2.5 km 8.5E-02 1.4E-01 5.8E-01 76% 15% 9% 2.2E-02 2.7E-02 6.8E-02 

10 km 7.8E-02 1.3E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.3E-02 25 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

Large Hospital HMI (wet 2.5 km 8.1E-02 1.3E-01 5.5E-01 80% 15% 4% 2.1E-02 2.6E-02 6.5E-02 

scrubber) 10 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 1% 2.0E-02 2.5E-02 6.2E-02 

25 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

Small Hospital HMI (wet 2.5 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

scrubber) 10 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

25 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

Large Coal-fired Utility 2.5 km 1.3E-01 2.1E-01 9.1E-01 48% 9% 42% 3.5E-02 4.3E-02 1.1E-01 

Boiler 10 km 8.6E-02 1.4E-01 5.9E-01 75% 14% 10% 2.3E-02 2.8E-02 6.9E-02 

25 km 8.0E-02 1.3E-01 5.5E-01 81% 15% 4% 2.1E-02 2.6E-02 6.4E-02 

Medium Coal-fired Utility 2.5 km 1.0E-01 1.6E-01 6.9E-01 64% 12% 24% 2.7E-02 3.2E-02 8.1E-02 Boiler 10 km 8.3E-02 1.3E-01 5.6E-01 78% 15% 7% 2.2E-02 2.7E-02 6.6E-02 

25 km 8.0E-02 1.3E-01 5.4E-01 81% 16% 3% 2.1E-02 2.6E-02 6.4E-02 

Small Coal-fired Utility 2.5 km 8.3E-02 1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 Boiler 10 km 7.9E-02 1.3E-01 5.4E-01 82% 16% 2% 2.1E-02 2.5E-02 6.3E-02 

25 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 
Table 3-7 (continued)

Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Pe

MHg Concentration (μg/g) Predicted MHg Exposure from In

MHg Dissolved Tier3 Tier4 Background RELMAP ISC Bald Eagle Osprey Kingfisher R

Concentration (ng/L)

3-27

Medium Oil-fired Utility 2.5 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 

Boiler 10 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

25 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 

Chlor-alkali plant 2.5 km 1.0E+00 1.6E+00 6.8E+00 6% 1% 92% 2.6E-01 3.2E-01 8.0E-01 

10 km 1.8E-01 2.8E-01 1.2E+00 37% 7% 56% 4.6E-02 5.7E-02 1.4E-01 25 km 1.0E-01 1.6E-01 6.8E-01 65% 12% 23% 2.6E-02 3.2E-02 8.0E-02 
3-28

Table 3-8

Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th pe

MHg Concentration (μg/g) Predicted MHg Exposure from In

MHg Dissolved Tier3 Tier4 Background RELMAP IS Bald Eagle Osprey Kingfisher R

Concentration (ng/L)

Variant b:Large 2.5 km 8.8E-02 1.4E-01 6.0E-01 15% 1% 84% 2.3E-02 2.8E-02 7.1E-02 

Municipal Waste

Combustor

10 km 5.5E-02 8.8E-02 3.7E-01 24% 2% 74% 1.4E-02 1.8E-02 4.4E-02 25 km 2.7E-02 4.4E-02 1.9E-01 48% 4% 48% 7.1E-03 8.7E-03 2.2E-02 

Variant b:Small 2.5 km 3.3E-02 5.3E-02 2.3E-01 40% 3% 57% 8.7E-03 1.1E-02 2.7E-02 Municipal WasteCombustor

10 km 1.9E-02 3.1E-02 1.3E-01 68% 6% 26% 5.1E-03 6.2E-03 1.5E-02 25 km 1.6E-02 2.5E-02 1.1E-01 84% 7% 9% 4.1E-03 5.0E-03 1.3E-02 

Large Commercial HMI 2.5 km 3.4E-02 5.4E-02 2.3E-01 39% 3% 58% 8.8E-03 1.1E-02 2.7E-02 

10 km 1.7E-02 2.7E-02 1.1E-01 80% 7% 14% 4.3E-03 5.3E-03 1.3E-02 25 km 1.5E-02 2.4E-02 1.0E-01 89% 8% 3% 3.9E-03 4.7E-03 1.2E-02 

Large Hospital HMI 2.5 km 1.4E-01 2.3E-01 9.6E-01 9% 1% 90% 3.7E-02 4.5E-02 1.1E-01 

10 km 3.1E-02 5.0E-02 2.1E-01 42% 4% 54% 8.2E-03 1.0E-02 2.5E-02 25 km 1.8E-02 2.9E-02 1.2E-01 73% 6% 20% 4.7E-03 5.8E-03 1.4E-02 

Small Hospital HMI 2.5 km 2.3E-02 3.6E-02 1.5E-01 58% 5% 37% 6.0E-03 7.3E-03 1.8E-02 

10 km 1.5E-02 2.4E-02 1.0E-01 87% 7% 6% 4.0E-03 4.9E-03 1.2E-02 25 km 1.4E-02 2.3E-02 9.9E-02 91% 8% 1% 3.8E-03 4.6E-03 1.2E-02 

Large Hospital HMI (wet 2.5 km 1.8E-02 2.9E-02 1.2E-01 74% 6% 20% 4.7E-03 5.7E-03 1.4E-02 

scrubber) 10 km 1.5E-02 2.4E-02 1.0E-01 90% 8% 3% 3.8E-03 4.7E-03 1.2E-02 

25 km 1.4E-02 2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 

Small Hospital HMI (wet 2.5 km 1.5E-02 2.3E-02 9.9E-02 91% 8% 2% 3.8E-03 4.6E-03 1.2E-02 

scrubber) 10 km 1.4E-02 2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 

25 km 1.4E-02 2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 

Large Coal-fired Utility 2.5 km 3.1E-02 4.9E-02 2.1E-01 43% 4% 53% 8.0E-03 9.8E-03 2.4E-02 

Boiler 10 km 1.9E-02 3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 

25 km 1.8E-02 2.9E-02 1.2E-01 73% 6% 21% 4.8E-03 5.8E-03 1.5E-02 

Medium Coal-fired Utility 2.5 km 2.3E-02 3.6E-02 1.5E-01 58% 5% 37% 5.9E-03 7.3E-03 1.8E-02 Boiler 10 km 2.0E-02 3.2E-02 1.4E-01 66% 6% 28% 5.2E-03 6.4E-03 1.6E-02 

25 km 1.8E-02 2.8E-02 1.2E-01 74% 6% 19% 4.6E-03 5.7E-03 1.4E-02 

Small Coal-fired Utility 2.5 km 1.9E-02 3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 Boiler 10 km 1.6E-02 2.6E-02 1.1E-01 81% 7% 13% 4.3E-03 5.2E-03 1.3E-02 

25 km 1.5E-02 2.4E-02 1.0E-01 88% 7% 4% 3.9E-03 4.8E-03 1.2E-02 
Table 3-8 (continued)

Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th pe

MHg Concentration (μg/g) Predicted MHg Exposure from In

MHg Dissolved Tier3 Tier4 Background RELMAP IS Bald Eagle Osprey Kingfisher R

Concentration (ng/L)

3-29

Medium Oil-fired Utility 2.5 km 1.5E-02 2.3E-02 1.0E-01 90% 8% 2% 3.8E-03 4.7E-03 1.2E-02 

Boiler 10 km 1.5E-02 2.3E-02 9.9E-02 91% 8% 2% 3.8E-03 4.7E-03 1.2E-02 

25 km 1.4E-02 2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 

Chlor-alkali plant 2.5 km 1.0E+00 1.6E+00 6.9E+00 1% 0% 99% 2.7E-01 3.3E-01 8.1E-01 

10 km 1.2E-01 1.9E-01 8.0E-01 11% 1% 88% 3.1E-02 3.8E-02 9.5E-02 25 km 3.7E-02 5.9E-02 2.5E-01 36% 3% 61% 9.7E-03 1.2E-02 3.0E-02 
3-30

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. 
4-1

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.

 
4-2

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 g/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 ringnecked 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 a NOAEL of 0.5g/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 0.5g/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 0.5g/g dose. Consequently, the LOAEL was

0.5g/g for reproductive effects for the second generation; no NOAEL was identified. A third generation of

mallards also demonstrated adverse reproductive effects at 0.5g/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 (0.5g/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 0.5g/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, 0.5g/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 2g/g methylmercury for six months suffered from anorexia and

ataxia (O'Connor and Nielson, 1981). In mink, 27g/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
4-3

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.
4-4

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 μg/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 μg/g as

mercury. In a multigenerational study, hen mallards fed methylmercury in the diet accumulated liver residues of

approximately 1.5 μg/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 μg/g. Kidney residues

considerably higher (>20 μg/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).
4-5

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 (Jernelöv 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 (10g/g) protected adult male mallards against the toxic effects

of methylmercury (10g/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 9.6g/g selenium, whereas in mallards fed both selenium and

methylmercury, the livers contained an average of 114g/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. 
4-6

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 μg/g), however, it would be difficult to rule out an additive response. 
5-1

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
5-2

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
5-3

(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 μg 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 of fish chosen. 
5-4

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):
WC  (TD x [1/UF]) x WtA

WA [(FD3)(FA x BAF3) (FD4)(FA x BAF4)]

5-5

where

WC = wildlife criterion value (pg/L; after converting from g/L) 

Wt = avera A ge species weight (g)

W = avera A ge daily volume of water consumed (L/d)

F = avera A ge daily amount of food consumed (g/d)

FD = fraction of the diet derived from tro 3 phic level 3

FD = fraction of the diet derived from tro 4 phic level 4

BAF = a 3 quatic life bioaccumulation factor for trophic level 3 (L/g; methylmercury

concentration in fish/methylmercury in water)

BAF = a 4 quatic 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 (UF ) to indicate uncertaint L y around the toxic threshold. An uncertainty factor (UF ) also ma A y

be used to provide a margin of safety when applying data from a species other than the species of concern. A

third uncertainty factor (UF ) may be used to extrapolate from subchronic to chronic exposures. Additional S

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
5-6

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, s

herring gull, kingfisher, mink, otter). Intermediate WC values (WC ) were then obtained for avian and i

mammalian wildlife by calculating the geometric mean of values for contributing species. The final WC (WC )f

was set equal to the lowest of the two resulting intermediate values and, for mercury, was driven by the

calculations for avian species.

The WC for mercury derived in the Proposed Guidance is 1300 pg/L. A comparison of the GLWQI f

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 immer). The other

avian wildlife for which WC values are calculated are the bald eagle (Haliaeetus leucocephalus), osprey

(Pandion haliaetus) and belted kingfisher (Ceryle alcyon). The mammalian wildlife for which WC are calculated

are the mink (Mustela vison) 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 forsteri),

wood stork (Mycteria americana), raccoon (Procyon lotor), snapping turtle (Chelydra serpentina), 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.

 
5-7

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 fishconsuming species.

In this Report, BAFs are estimated for trophic level 3 (foraging fish) and trophic level 4 (piscivorous

fish), which are designated as BAF and BAF , res 34 4 pectively. BAF is estimated by three different methods and

BAF is estimated by two different methods. The result, or output, of each estimation method is a distribution of 3

BAF values, each associated with some degree of likelihood. The three methods by which BAF is estimated are: 4

a modified GLWQI method, a BAF × PPF method, and a direct field-derived method from measured BAFs at

trophic level 4. BAF is estimated b 3 y 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). BAF is intended to be 4

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. BAF 3 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.

BAF = BCF × FCM (1) n n

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

FCM is the food-chain multiplier representing the cumulative biomagnification of n

methylmercury from trophic level 2 to trophic level n, n=[3,4].
5-8

The formulas for FCM and FCM are given in equations 2 and 3, respectively. 3 4

FCM = PPF × PPF (2) 323

FCM = PPF × PPF × PPF (3) 4234

where

PPF is the predator-prey factor at trophic level 2 representing the biomagnification of 2

methylmercury in zooplankton as a result of feeding on contaminated phytoplankton,

PPF is the same for tro 3 phic level 3 fish feeding on contaminated organisms, and

PPF is the same for trophic level 4 fish feeding on trophic level 3 fish. 4

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 × PPF Method

The formula for the calculation of BAF by this method is given in equation 4. 4

BAF = BAF × PPF (4) 4 3 4

where

BAF is the field-measurement-derived distribution for the BAF at tro 3 phic level 3 and

PPF is the same as for the GLWQI method. 4

Field-derived (Direct) Method

This method estimates BAF and BAF directl 3 4 y 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.
5-9

Table 5-1

Summary of Methylmercury Bioaccumulation Factors for Trophic Levels 3 and 4

(mean, 5%, and 95% values)

BAF BAF 3 4

Recommended 1,600,000 6,800,000

Method Direct GLWQI BAF x Direct GLWQI

Field-derived PPF Field-derived 3

4

Median (GM ) 1,600,000 1,300,000 7,820,000 6,800,000 6,500,000 a

5 pctl 461,000 71,500 1,960,000 3,260,000 331,000 th

95 pctl 5,410,000 2,440,000 31,100,000 14,200,000 129,000,000 th

GSD 2.12 5.88 2.32 1.56 6.13 b

 Geometric Mean a

 Geometric Standard Deviation b

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 BAF and BAF distributions. In each case, however, these data 3 4 points were in relatively good

agreement, resulting in narrower statistical distributions that those associated with the GLWQI and BAF x PPF 3 4

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.
5-10

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 of fish, 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 BAF distributions. That is, the 4

variability in the output distributions reflects both naturally variable processes and the uncertainty around those

processes. For example, the BAF distributions include variabilit 4 y 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 of fish (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 BAF and BAF are 4 3 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 BAF and BAF output distributions generated from the direct field-derived distributions is 3 4

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. 
5-11

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 BAF and PPF . 4 4

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 (WtA) (F ) (W ) Wildlife Food

Body Wt. Ingestion Rate Drinking Rate Trophic Level of

kg kg/d L/d Source

A A

% Diet at

Each

Trophic

Level

Mink 0.80 0.178 0.081 3 90

Otter 7.40 1.220 0.600 3,4 80,20

Kingfisher 0.15 0.075 0.017 3 100

Loon 4.00 0.800 0.120 3 100

Osprey 1.50 0.300 0.077 3 100

Eagle 4.60 0.500 0.160 3,4 74,18

For this analysis, it was assumed that prey not attributed to trophic levels 3 and 4 were derived from nonaquatic 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 UF of 3 L

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 ) A greater than 1.0. 

Although no toxicity data are available for any of the bird species of interest, a review of the literature suggests
WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [(0.9)(FA x BAF3)]

WCS  (0.055 mg/kg/d x [1/(1 x 3 x 1)]) x 0.8 kg

0.081 L/d [(0.9) (0.178 kg/d x 1,600,000)]

WCS  57 pg/L

5-12

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 UF of 3 was applied to the TD or NOAEL. The value of this S

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/UF is 18.3 g/kg bw/d, which is S

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 UF of 3 L yields an avian RfD of 26 μg/kg bw/d. A mammalian RfD of 18 μg/kg bw/d

was calculated by dividing the mammalian TD by a UF of 3. S

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 WC values calculated for mammals is 50 pg/L. The mean of the four avian values s

is 74 pg/L. The lowest of these is the WC calculated for mammalian species. Therefore, the WC for i f

methylmercury is 50 pg/L.

For the mink:
WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [ (0.8) (FA x BAF3) (0.2) (FA x BAF4) ]

WCS  (0.055 mg/kg/d x [1/(1 x 3 x 1)]) x 7.4 kg

0.60 L/d [ (0.8) (1.22 kg/d x 1,600,000) (0.2) (1.22 kg/d x 6,800,000)]

WCS  42 pg/L

WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [ (1.0) (FA x BAF3) ]

WCS  (0.078 mg/kg/d x [1/(1 x 1 x 3)]) x 0.15 kg

0.017 [ (1.0) (0.075 x 1,600,000) ]

WCS  33 pg/L

WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [ (1.0) (FA x BAF3) ]

WCS  (0.078 mg/kg/d x [1/(1 x 1 x 3)]) x 4.0 kg

0.012 L/d [ (1.0) (0.8 kg/d x 1,600,000) ]

WCS  82 pg/L

5-13

For the otter:

For the kingfisher:

For the loon:
WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [ (1.0) (FA x BAF3) ]

WCS  (0.078 mg/kg/d x [1/(1 x 1 x 3)]) x 1.5 kg

0.077 L/d [ (1.0) (0.3 kg/d x 1,600,000) ]

WCS  82 pg/L

WCS  (TD x [1/(UFA x UFS x UFL)]) x WtA

WA [ (0.74) (FA x BAF3) (0.18) (FA x BAF4 ]

WCS  (0.078 mg/kg/d x [1/(1 x 1 x 3)]) x 4.6 kg

0.16 L/d [ (0.74) (0.5 kg/d x 1,600,000) (0.18) (0.5 kg/d x 6,800,000)]

WCS  100 pg/L

5-14

For the osprey:

For the bald eagle:

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
5-15

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 UF of 3 and a UF of A L

2. This Report used a UF of 1 and a UF of 3 (see Section 5.4.11.2 for a discussion of UF ). A L L

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
5-16

Table 5-3

Species-specific Wildlife Criteria Calculated in the Great Lakes Water Quality Initiative

(GLWQI) and in the Mercury Study Report to Congress a

Species

Wildlife Criterion

(pg/L)

GLWQI Mercury Study Report to Congress

Mink 2880 1038

Otter 1930 764

Kingfisher 1040 598

Osprey Not done 1498

Eagle 1920 1818

 U.S. EPA, 1995b a

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 a NOAEL 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
5-17

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 Wt . The A

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 FD and FD . In the otter and eagle, FD and FD tend to be reciprocal 34 34

(although in the eagle these values do not add up to 1). In the mink, however, FD is assi 3 gned 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 BAF appears alone in the denominator, a percentage-wise increase in BAF or FD will 3 3 3

cause a less than proportional decrease in the WC; conversely a decrease in BAF or FD will 3 3

cause a greater than proportional increase in the WC.

When both BAF and BAF a 3 4 ppear in the denominator, an equivalent percentage-wise change in

BAF (and b 4 4 y extension PPF ) has a greater impact on the WC than a change in BAF , but in 3

either case, the effect is less than proportional.

If BAF and BAF are both allowed to chan 34 4 ge (holding PPF constant), a percentage-wise

increase in BAF (and b 3 4 y extension BAF ) will have a less than proportional effect on WC, while

a decrease in BAF will have a greater than proportional impact. 3

Under all circumstances, a percentage-wise increase in F will cause a less than A proportional

decrease in WC, while a decrease in F will cause a A greater than proportional increase in WC.
5-18

Owing to its small contribution to the analysis as a whole, large changes in W have a ver A y small

impact on WC.

With the exception of F , it is not A 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 F have the A 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
5-19

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 (UF ) to estimate a wildlife RfD. A UF of 3 or L L

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 UF for wildlife exposure to mercury. L

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 UF . Selection criteria included the following: L

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 
5-20

Table 5-4

Analysis of LOAEL-to-NOAEL Uncertainty Factor

Endpoint LOAEL NOAEL RATIO

Species and Sex (mg/kg/day) (mg/kg/day) LOAEL:NOAEL Stud

LethalityB6C3F1 Mouse M 0.69 0.60 1.15 Mitsumori et al., 1990NeurotoxicityRat (Wistar) M & F 0.25 0.05 5.0 Munro et al., 1980

Cat sex NS 0.046 0.020 2.3 Charbonneau et al., 1976Monkey (Macaca fasicularis) M & F 0.03 0.02 1.5 Sato and Ikuta, 1975

Monkey (Macaca artoides and M. nemestrina) M & F 0.5 0.4 1.25 Evans et al., 1977

Renal ToxicityMouse (ICR) M 0.72 0.15 4.8 Hirano et al., 1986

F 0.62 0.11 5.6

Mouse (B6C3F1) M 0.14 0.03 4.7 Mitsumori et al., 1990

F 0.6 0.13 4.6

Gastrointestinal ToxicityMouse (B6C3F1) M 0.69 0.14 4.9 Mitsumori et al., 1990ImmunotoxicityRabbit (New Zealand White) M & F 0.4 0.04 10.0 Koller et al., 1977Developmental ToxicityRat (Charles River) F 4.0 0.2 20.0 Nolen et al., 1972

Rat (Wistar) F 0.25 0.05 5.0 Khera and Tabacova, 19Rat (Charles River) F 1.4 0.7 2.0 Fowler and Woods, 1977Rat (Wistar) offspring of both sexes 0.6 0.2 3.0 Schreiner et al., 1986
Table 5-4 (continued)

Analysis of LOAEL-to-NOAEL Uncertainty Factor

Endpoint LOAEL NOAEL RATIO

Species and Sex (mg/kg/day) (mg/kg/day) LOAEL:NOAEL Stud

5-21

Reproductive ToxicityRat (Wistar) M 0.5 0.1 5.0 Khera, 1973

Mouse (ICR) M 0.72 0.15 4.8 Hirano et al., 1986Mouse (B6C3F1) M 0.68 0.14 4.9 Mitsumori et al., 1990Monkey (Macaca facicularis) M 0.065 0.047 1.4 Mohamed et al., 1987

Monkey (M. facicularis) F 0.06 0.04 1.5 Burbacher et al., 1988

NS - Not stated.

5-23

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 UF of as much as 10 in derivin L g reference doses for humans. Dourson and Stara (1983) recommended

the application of a relatively large UF when estimatin L g a NOAEL from a LOAEL for a severe or frank

toxicological effect. Conversely, a low UF could be a L pplied 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 UF and that most of the effects thresholds will be encompassed by using a UF of 10 or L L

less. It is also likely that the most appropriate UF will vary with the toxicological endpoint selected. For studies L

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 UF .L

The analysis by Dourson and Stara (1983) and the analysis reported here support the UF of three L

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 UF of two. Given the substantial uncertainties in all the values used to calculate L

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.
5-24

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 of fish 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
5-25

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 of fish,

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
5-26

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 K or OW ganic compounds. 
5-27

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 UF (used to adjust L 

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 μg/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.” 
5-28

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.
6-1

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.
6-2

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 μg/kg bw/d (mercury basis). 

The RfD for mammalian wildlife is 18 μg/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
6-3

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 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 largescale ecosystem attributes (e.g., community structure and biodiversity).
7-1

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. 
7-2

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. 
7-3

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.
8-1

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