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# V o l u m e V I : A n E c o l o g i c a l A s s e s s m e n t f o r A n t h r o p o g e n i c M e r c u r y E m i s s i o n s i n t h e U n i t e d S t a t e s

### 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 Agencyi 

### 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. . . . . . . . . . 3-6ii 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-17iii 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1iv 

### 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. RiceEcosystems 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. ReismanCincinnati 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 SwartoutNational Center for Environmental AssessmentCincinnati Office of Research and Development Cincinnati, OH Michael Troyer Office of Science, Planning and Regulatory Evaluation Cincinnati, OHv 

### 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 Subcommitteviii 

### 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 Assessmentix 

### 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-20x 

### 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-22xi 

### 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 AES-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 withmink (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 theES-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 WCES-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-8The 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-9Reference 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 mercurymoves 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. AES-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 mercury1-2 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 anindirect 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; 02-3 FOCUS ON METHYLMERCURY

Meth y lmercur y is the form of mercur y of particular concern in ecos y stems for three reasons. (1) All forms of mercur y can be converted to meth y lmercur y b y natural processes in the environment. (2) Meth y lmercur y bioaccumulates and bioma g nifies in aquatic food webs. (3) Meth y lmercur y is the most toxic form of mercury
. In the 1960s, researchers found meth y lmercur y in fish in Swedish lakes, althou g h no dischar g e of meth y lmercur y had occurred in those lakes (Bakir et al., 1973). Later research determined that the meth y lation of
mercur y in sediments b y anaerobic sulfur-reducin g bacteria was a ma j or source of meth y lmercur y in man y aquatic environments (Gilmour and Henr y , 1991; Zillioux et al., 1993). Aerobic bacteria and fun g i, includin g y easts that g row best in acid conditions, also can meth y late mercur y (Eisler, 1987; Yannai et al., 1991; Fischer et al., 1995). In addition, fulvic and humic material ma y abioticall y meth y late mercur y (Na g ase et al., 1984; Lee et al., 1985; Weber, 1993). The
ma j or site of meth y lation in aquatic s y stems is the sediment, but meth y lation also occurs in the water column (Wri g ht and Hamilton, 1982; Xun et al., 1987; Parks et al., 1989; Bloom and Effler, 1990; Winfre y and Rudd, 1990; Bloom et al., 1991; Gilmour and Henr y , 1991; Miskimmin et al., 1992). Wetlands may be particularl y active sites of meth y lation (St. Louis et al., 1994; Hurle y et al., 1995). The rate of mercury meth y lation varies with microbial activit y , mercur y loadin g s, suspended sediment load, DOC, nutrient content, pH, redox conditions, temperature, and other variables. Demeth y lation occurs via biotic and abiotic mechanisms, includin g photode g radation (Sellers et al., 1996). The net rate of mercur y meth y lation is determined b y competin g rates of meth y lation and demeth y lation.

Meth y lmercur y bioaccumulates and bioma g nifies in aquatic food webs at hi g her rates and to a g reater extent than an y other form of mercur y (Watras and Bloom, 1992). "Bioaccumulation" refers to the net uptake of a contaminant from the environment into biolo g ical tissue via all pathwa y s. It includes the accumulation that ma y occur b y direct contact of skin or g ills with mercury -contaminated water as well as in g estion of mercur y -contaminated food. "Bioma g nification" refers to the increase in chemical concentration in or g anisms at successivel y hi g her trophic levels in a food chain as a result of the in g estion of contaminated or g anisms at lower trophic levels. Meth y lmercur y can comprise from 10 percent to over 90 percent of the total mercur y in ph y toplankton and zooplankton (trophic levels 1 and 2) (May et al., 1987; Watras and Bloom, 1992), but g enerall y comprises over 90 percent of the total mercur y in fish (trophic levels 3 and 4) (Huckabee et al., 1979; Grieb et al., 1990; Bloom, 1992; Watras and Bloom, 1992). Fish absorb meth y lmercur y efficientl y from dietar y sources and store this material in or g ans and tissues. The biolo g ical half-life of meth y lmercur y in fish is difficult to determine but is g enerall y thou g ht to ran g e from months to y ears.
Meth y lmercur y is the most toxic form of mercury to birds, mammals, and aquatic or g anisms due to its stron g affinit y for sulfur-containin g or g anic compounds (e. g ., proteins). Biolo g ical membranes, includin g the blood-brain barrier and the placenta, that tend to discriminate a g ainst other forms of mercur y allow relativel y eas y passa g e of meth y lmercur y and dissolved mercur y vapor (Eisler, 1987). Meth y lmercur y can cause death, neurolo g ical disorders,
or g an dama g e, impaired immune response, impaired g rowth and development and reduced reproductive success (Klaassen, 1986). In mammals, fetuses are particularl y sensitive to mercury , experiencin g 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 of2-4 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 surfacePlants with roots, stems, and leaves, such as ferns and seed plants. 4 Stomata (plural of stoma) are the minute openin g s in the epidermis of leaves, stems, or other plant or g ans 5 that allow g as 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 tocontaminated 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 patho g ens Chan g e in respiration Chan g e in behavior (e. g ., mi g ration, predator-pre y interactions) Inhibition or induction of enz y mes
Decreased g rowth Decreased reproduction Death

Population Decreased recruitment of j uveniles Decreased g enot y pic and phenot y pic diversit y Decreased biomass Increased mortalit y rate Decreased fecundit y rate Increased frequenc y of disease Decreased y ield Chan g e in a g e/size class structure Extinction

Communit y Decreased food web diversit y Decreased species diversit y Chan g e in species composition Decreased productivit y Increased al g al blooms

Ecos y stem Altered nutrient c y clin g Decreased diversit y 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.2-13The 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 fouror 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 be2-19Table 2-3Mercury Residues in Tissues of Piscivorous BirdsSpecies MercuryTissue SamplingLocation Comments Reference(μg/gfresh weight)Bald eagle 13.0 - 21.0 feathers Great Lakes region adults 1Bald eagle 3.7 - 20.0 feathers Great Lakes region nestlings 1Bald eagle 0.1 - 34.7 feathers N. Central Florida adults 2Bald eagle 0.8 - 14.3 feathers N. Central Florida nestlings 2Common loon 8.7 feathers Minnesota lakes adults 3Common loon 2.7 feathers Minnesota lakesjuveniles 3Common loon 11.0 - 18.0 feathers Wisconsin lakes adults 4Common loon 2.0 - 5.0 feathers Wisconsin lakesjuveniles 4Wood stork 1.9 feathers South Floridajuveniles 5Bald eagle 0.15 - 0.29 eggs British Columbia 6Bald eagle 0.07 - 0.41 eggs 15 States (USA) 7Common loon 0.40 - 1.10 eggs Wisconsin lakes 4Common loon 2.0 - 3.0 eggs Northwestern Ontario polluted bypoint 8source; LOAEL -reproductionCommon tern 3.6 eggs Northwestern Ontario polluted bypoint 9source; LOAEL -reproductionHerringgull 2.3 - 15.8 eggs ClayLake, Ontario polluted bypoint 10source, no adverseeffectsTable 2-3 (continued)Mercury Residues in Tissues of Piscivorous BirdsSpecies MercuryTissue SamplingLocation Comments Reference(μg/gfresh weight)2-20Wood stork 0.7 eggs South Florida 11Tree swallow 0.04 - 0.08 eggs Lower Great Lakes consume emergent 12aquatic insectsCommon loon 1.6 - 47.7 liver Northwestern Ontario LOAEL - 8reproductionCommon loon 9.5 - 90.0 liver Wisconsin lakes adults found dead 4Common loon 5.6 liver Minnesota lakes adults found injured 3Great White Heron 0.6 - 59.4 liver South Florida mixed age birds 13found deadGreat Blue Heron 0.2 - 7.3 liver South Florida nestlings 14Great Blue Heron 0.1 - 74.5 liver South Florida fledglings/young14adultsCommon loon 0.2 - 6.9 breast muscle Northwestern Ontario polluted bypoint 8sourceCommongoldeneye 0.9 - 19.4 breast muscle ClayLake, Ontario polluted bypoint 10sourceCommon merganser 4.4 - 13.1 breast muscle ClayLake, Ontario polluted bypoint 10sourceHooded merganser 3.9 - 17.6 breast muscle ClayLake, Ontario polluted bypoint 10sourceHerringgull 0.7 - 4.0 breast muscle Tadenac Lake, Ontario 15Table 2-3 (continued)Mercury Residues in Tissues of Piscivorous BirdsSpecies MercuryTissue SamplingLocation Comments Reference(μg/gfresh weight)2-21Common loon 1.5 breast muscle Tadenac Lake, Ontario 15References:1.Bowerman et al., 1994; range of means across samplinglocations.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 bynightlighting.4.Belant and Anderson, 1990; range of individual values. Means for feathers (adult andjuvenile), eggs and liver were 14.8, 4.0, 0.64 and 40.9, respectively.5.Burger et al., 1993; mean value.6.Elliott et al., 1996; range of means across samplinglocations7.Wiemeyer et al., 1993; range of means across samplinglocations (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 forgoldeneye, common merganser and hooded merganser were 7.8, 6.8 and 12.3, respectively.11.Fleminget al., 1984; mean value.12.Bishop et al., 1995; range of individual values, mean = 0.07.13.Spaldinget 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 = 1.7.2-22present 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.2-23Table 2-4Mercury Residues in Tissues of Piscivorous MammalsSpeciesMercuryTissue SamplingLocation Comments Reference(μg/gfresh weight)Otter 6.5 (max. = 63.2) fur Wisconsin 1Otter 47.0 fur ClayLake, Ontario polluted bypoint 2source; death due topoisoningOtter 15.2 - 25.6 fur Georgia 3Mink 10.7 (max. = 17.3) fur Georgia 4Mink 7.6 (max. = 41.2) fur Wisconsin 1Mink 34.9 fur Saskatchewan polluted bypoint 5source; death due topoisoningRaccoon 4.4 fur S. Florida 6Muskrat 0.06 fur Wisconsin 1Beaver 0.03 fur Wisconsin 1Otter 5.1 - 9.2 liver Georgia 3Otter 1.7 - 3.4 liver Manitoba males and females 7Otter 2.4 - 4.5 liver WinnipegR. males and females; 7polluted bypointsourceOtter 0.3 - 3.0 liver Louisiana 8Otter 0.9 - 3.5 liver Ontario residues correlated 9with acidityTable 2-4 (continued)Mercury Residues in Tissues of Piscivorous MammalsSpeciesMercuryTissue SamplingLocation Comments Reference(μg/gfresh weight)2-24Otter0.8 - 3.2 liver N. Michigan 10Otter 1.3 - 2.3 liver New York 11Otter 96.0 liver ClayLake, Ontario polluted bypoint 5source; death due topoisoningOtter 3.3 (max. = 23.6) liver Wisconsin 1Mink 0.4 - 1.7 liver Manitoba 7Mink 2.1 (max. = 17.4) liver Wisconsin 1Mink 0.1 - 2.6 liver Ontario residues correlated 9with acidityMink 58.2 liver Saskatchewan polluted bypoint 5source; death due topoisoningMink 0.9 - 2.9 liver New York 11Raccoon 2.0 liver Wisconsin 1Raccoon 1.5 - 24.0 liver S. Florida 12Muskrat < 0.02 liver Wisconsin 1Beaver 0.04 liver Wisconsin 1References:1. Sheffyand St. Amant, 1982; mean value.2. Wren, 1985; one individual.3. Halbrook et al., 1994; range of means across samplinglocations.Table 2-4 (continued)Mercury Residues in Tissues of Piscivorous Mammals2-254.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 samplinglocations. Data from the Winnipegriver are reported as a mean value.8. Beck, 1977; range of means across samplinglocations.9. Wren et al., 1986; range of means across samplinglocations.10. Francis and Bennett, 1994; range of individual values.11. Foleyet al., 1988; range of means across samplinglocations.12. Roelke et al., 1991; range of means across samplinglocations.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 T y pe H g (H g Cl or H g NO ) Meth y lmercur y 2+ 3 (  g /L) (  g /L)
Low End Hi g h End Low End Hi g h End

Fresh Water 53 (al g a) 3,400 (submer g ed 0.8 (al g a) 6.0 (al g a) aquatic ve g etation) Salt Water 10 (al g a) 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 0.12-28  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 levelused 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 ducklings2-29 Table 2-7 Toxicity Values for Fish and Aquatic Invertebrates

Or g anism H g (H g Cl or H g NO ) (  g /L) Meth y lmercur y (  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 ( g upp y ) to 1,000 (tilapia) Not available
Rainbow trout 155 to 420 24 to 84 Fresh water AWQC 2.4 (total mercur y ) a Salt water 3.5 (m y sid) to 400 (soft clam) Not available invertebrates b

Salt water fish 36 ( j uvenile spot) to 1,678 (flounder) 51.1 (mummicho g ) 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 mercur y ) a Salt water 1.131 (m y sid) Not available invertebrates Salt water AWQC 0.025 (total mercury ) a
AWQCs are desi g ned to be protective of the aquatic communit y 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 b y 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 mummicho g s was reported b y Klauni g et al. (1975), but Dorfman (1977) and c 50 Eisler and Henneke y (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 mercury2-30 (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 eggshell2-33 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 the2-34 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. The2-37 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. Uptake2-41 Table 2-8 Examples of Assessment and Measurement Endpoints

Level of Or g anization Assessment Endpoints Measurement Endpoints

Ecore g ion Re g ional production Re g ional production a Biodiversit y Habitat area Landscape aesthetics Other landscape descriptors

Ecos y stem Productive capabilit y Habitat area Nutrient balance Biomass Soil balance Productivity Nutrient export

Communit y Market/sport value Species diversity Recreational qualit y Species number Chan g e to less useful/desired t y pe Species evenness Market/sport value Saprobic index

Population Frequent g ross morbidit y Fecundit y Extinction Occurrence Abundance Numbers/densit y Yield/production A g e structure
Massive mortalit y Yield/production Ran g e Frequenc y of g ross morbidit y Mortalit y rate

Individual Reproduction Fecundity Survival Lon g evit y Growth and development Growth and development Good ph y sical condition Overt s y mptomolo gy Biomarkers

Abiotic Habitat qualit y Temperature Water flow Soil characteristics Sediment characteristics

An ecore g ion is an area (re g ion) of relative homo g eneit y in ecolo g ical s y stems (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 to2-42 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 g rid in the U.S. due to all anthropocentric sources of Predicts avera g e annual atmospheric mercur y concentration and wet and dry 2
mercur y in the U.S. and a natural back g round atmospheric mercury concentration.

GAS-ISC3 Predicts avera g e 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 bod y
.
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 and3-3 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 Bod y Wt. In g estion Rate Drinkin g Rate Trophic Level of

A k g k g /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
Kin g fisher 0.15 0.075 0.017 3 100
Loon 4.0 0.8 0.14 3 100 Ospre y 1.50 0.300 0.077 3 100

Ea g le 4.60 0.500 0.160 3,4 74,18,83-5 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 areas3-10 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 erosion3-23 

### 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).3-24Table 3-6Process Parameters for the Model Plants Considered in the Local Impact AnalysisModel Plant Plant Size CapacityHeight Diameter Rate PercentVelocityTemperature(% ofyear) (ft) (ft) (kg/yr) (Hg/Hg/Hg)(m/sec) (°F)Stack Stack HgEmission SpeciationExit Exit0 2+PLarge Municipal Waste 2,250 tons/day90% 230 9.5 220 60/30/10 21.9 285CombustorsSmall Municipal Waste 200 tons/day90% 140 5 20 60/30/10 21.9 375CombustorsLarge Commercial HMI 1500 lb/hr capacity88% 40 2.7 4.58 33/50/17 9.4 175Waste Incinerator (1000 lb/hr actual)(Wetscrubber)Large Hospital HMI 1000 lb/hr capacity39% 40 2.3 23.9 2/73/25 16 1500Waste Incinerators (667 lb/hr actual)(Good Combustion)Small Hospital HMI 100 lb/hr capacity27% 40 0.9 1.34 2/73/27 10.4 1500Waste Incinerators (67 lb/hr actual)(1/4 sec Combustion)Large Hospital HMI 1000 lb/hr capacity39% 40 2.3 0.84 33/50/17 9.0 175Waste Incinerators (667 lb/hr actual)(Wet Scrubber)Small Hospital HMI 100 lb/hr capacity27% 40 0.9 0.05 33/50/17 175Waste Incinerators (Wet (67 lb/hr actual)Scrubber)5.6Large Coal-fired Utility975 Megawatts 65% 732 27 230 50/30/20 31.1 273BoilerMedium Coal-fired 375 Megawatts 65% 465 18 90 50/30/20 26.7 275UtilityBoilerSmall Coal-fired Utility100 Megawatts 65% 266 12 10 50/30/20 6.6 295BoilerMedium Oil-fired Utility285 Megawatts 65% 290 14 2 50/30/20 20.7 322BoilerChlor-alkaliplant 300 tons 90% 10 0.5 380 70/30/0 0.1 Ambientchlorine/dayHg= Elemental Mercurya 0Hg= Divalent Vapor Phase Mercuryb 2+Hg = Particle-Bound MercurycP3-25 GAS-ISC3 was em p lo y ed to estimate de p osition ori g inatin g from local p oint sources (<50 km from the
rece p tor). The IEM-2M model was then utilized to estimate the fate of mercur y in the watershed and water bod y
. The estimated concentrations of dissolved meth y lmercur y in the water column were used to p redict meth y lmercur y concentrations in fish that occu py tro p hic levels 3 and 4. This was accom p lished b y multi p l y in g the p redicted meth y lmercur y dissolved water concentration b y the BAF at each tro p hic level. Wildlife rece p tors were assumed to in g est the fish at rates g iven p reviousl y (Table 3-3).

3.5.4 Results of H yp othetical Ex p osure Scenarios

Hi g h rates of mercur y de p osition were associated with p roximit y to industrial sources emittin g substantial levels of divalent mercur y (see Tables 3-7 and 3-8). Additional factors that contributed to hi g h local de p osition rates include low stack hei g ht and slow stack exit g as velocities. In g eneral, p redicted dissolved meth y lmercur y concentrations in lake waters located 2.5 km from the source were hi g her than levels p redicted at 10 or 25 km. This was due p rimaril y to the dilution of the mercury emissions in the atmos p here. Mercur y concentrations in fish (hence the mercury ex p osure to p iscivores) were p ro p ortional to dissolved meth y lmercur y levels in the local waters. When the two h yp othetical locations were com p ared (western and eastern), hi g her
mercur y concentrations were p redicted to occur in the environmental media at the eastern location. This was due p rimaril y to hi g her levels of p reci p itation at the eastern site, which tends to remove mercur y from the atmos p here. Also, the assump tions of back g round mercur y are hi g her for the eastern than the western site. On a p er kilo g ram of bod y wei g ht p er da y basis, the s p ecies p redicted to be most ex p osed were the kin g fisher and the otter.
3.5.5 Issues Related to Combinin g Models to Assess Environmental Fate of Mercury and Ex p osures to Wildlife

In modelin g the environmental fate and subse q uent ex p osure of p iscivorous wildlife to mercury emitted from a number of different sources, man y simp lif y in g assump tions have been made. Each sim p lif y in g assump tion is associated with some de g ree of uncertaint y ; the accumulation of these uncertainties results in uncertaint y in the
ex p osure levels p redicted b y the models. Man y of the in p ut p arameters to the models ma y also be q uite variable across time and location. This variabilit y leads to uncertainty in the modelin g results. While no effort is made here to q uantif y these variabilities and uncertainties, this section will attem p t to describe those deemed most si g nificant to this element of the assessment.

There is no consensus app roach for develo p in g ex p osure scenarios for p ollutants such as mercury , which have alwa y s been environmental constituents (i.e., how to incor p orate back g round concentrations into environmental fate modelin g ). The a pp roach develo p ed for this document is clearl y not the onl y app roach that could have been taken to account for environmental backg round concentrations; however, each p otential alternative a pp roach evaluated also p resented associated uncertaint y . If the error in estimate of back g round results in an overestimation of concentrations in environmental media from these sources, the p resented imp acts of anthro p o g enic sources will be underestimated, and vice versa.

Combinin g the outp uts of the different environmental fate models, while deemed necessar y for this p ollutant, clearl y comp ounds the uncertainty relatin g to individual model assum p tions and in p ut p arameter uncertainties. The chemical p ro p erties associated with elemental mercur y and divalent mercury s p ecies in the atmos p here are assumed to be very dissimilar. This necessitates an atmos p heric modelin g app roach that can account for lon g ran g e atmos p heric trans p ort of anthro p o g enic emissions as well as local trans p ort from a g iven source. The p rimar y im p acts of environmental mercury result from bioaccumulation and bioma g nification in the
a q uatic food chain. This necessitates the use of a model such as IEM-2M that3-26Table 3-7Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Percentile)MHgConcentration (μg/g)Predicted MHgExposure from Ingestion of Fish (mg/kg/day)MHgDissolved Tier3 Tier4 Background RELMAP ISC Bald Eagle OspreyKingfisher River Otter Mink LoonConcentration (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 7.4E-02 5.4E-02 5.4E-02Waste Combustor10 km 1.1E-01 1.8E-01 7.6E-01 58% 11% 31% 2.9E-02 3.6E-02 8.9E-02 4.8E-02 3.6E-02 3.6E-0225 km 8.9E-02 1.4E-01 6.0E-01 73% 14% 13% 2.3E-02 2.8E-02 7.1E-02 3.9E-02 2.8E-02 2.8E-02Variant 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 4.1E-02 3.0E-02 3.0E-02Waste Combustor10 km 8.2E-02 1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 3.6E-02 2.6E-02 2.6E-0225 km 7.9E-02 1.3E-01 5.3E-01 83% 16% 2% 2.1E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-02Large 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 4.2E-02 3.1E-02 3.1E-0210 km 8.0E-02 1.3E-01 5.4E-01 82% 16% 3% 2.1E-02 2.5E-02 6.4E-02 3.5E-02 2.5E-02 2.5E-0225 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Large 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 8.4E-02 6.2E-02 6.2E-0210 km 9.4E-02 1.5E-01 6.4E-01 69% 13% 18% 2.5E-02 3.0E-02 7.5E-02 4.1E-02 3.0E-02 3.0E-0225 km 8.1E-02 1.3E-01 5.5E-01 80% 15% 5% 2.1E-02 2.6E-02 6.5E-02 3.5E-02 2.6E-02 2.6E-02Small 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 3.7E-02 2.7E-02 2.7E-0210 km 7.8E-02 1.3E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-0225 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Large 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 3.5E-02 2.6E-02 2.6E-02scrubber)10 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-0225 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Small 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 3.4E-02 2.5E-02 2.5E-02scrubber)10 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-0225 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Large Coal-fired Utility2.5 km 1.3E-01 2.1E-01 9.1E-01 48% 9% 42% 3.5E-02 4.3E-02 1.1E-01 5.8E-02 4.3E-02 4.3E-02Boiler10 km 8.6E-02 1.4E-01 5.9E-01 75% 14% 10% 2.3E-02 2.8E-02 6.9E-02 3.8E-02 2.8E-02 2.8E-0225 km 8.0E-02 1.3E-01 5.5E-01 81% 15% 4% 2.1E-02 2.6E-02 6.4E-02 3.5E-02 2.6E-02 2.6E-02Medium Coal-fired Utility2.5 km 1.0E-01 1.6E-01 6.9E-01 64% 12% 24% 2.7E-02 3.2E-02 8.1E-02 4.4E-02 3.2E-02 3.2E-02Boiler10 km 8.3E-02 1.3E-01 5.6E-01 78% 15% 7% 2.2E-02 2.7E-02 6.6E-02 3.6E-02 2.7E-02 2.7E-0225 km 8.0E-02 1.3E-01 5.4E-01 81% 16% 3% 2.1E-02 2.6E-02 6.4E-02 3.5E-02 2.6E-02 2.6E-02Small Coal-fired Utility2.5 km 8.3E-02 1.3E-01 5.6E-01 79% 15% 6% 2.2E-02 2.6E-02 6.6E-02 3.6E-02 2.6E-02 2.6E-02Boiler10 km 7.9E-02 1.3E-01 5.4E-01 82% 16% 2% 2.1E-02 2.5E-02 6.3E-02 3.4E-02 2.5E-02 2.5E-0225 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Table 3-7 (continued)Predicted MHg Exposure to Ecological Receptors for Eastern Site (Local + RELMAP 50th Percentile)MHgConcentration (μg/g)Predicted MHgExposure from Ingestion of Fish (mg/kg/day)MHgDissolved Tier3 Tier4 Background RELMAP ISC Bald Eagle OspreyKingfisher River Otter Mink LoonConcentration (ng/L)3-27Medium Oil-fired Utility2.5 km 7.8E-02 1.2E-01 5.3E-01 83% 16% 1% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Boiler10 km 7.8E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-0225 km 7.7E-02 1.2E-01 5.3E-01 84% 16% 0% 2.0E-02 2.5E-02 6.2E-02 3.4E-02 2.5E-02 2.5E-02Chlor-alkaliplant 2.5 km 1.0E+00 1.6E+00 6.8E+00 6% 1% 92% 2.6E-01 3.2E-01 8.0E-01 4.4E-01 3.2E-01 3.2E-0110 km 1.8E-01 2.8E-01 1.2E+00 37% 7% 56% 4.6E-02 5.7E-02 1.4E-01 7.7E-02 5.7E-02 5.7E-0225 km 1.0E-01 1.6E-01 6.8E-01 65% 12% 23% 2.6E-02 3.2E-02 8.0E-02 4.4E-02 3.2E-02 3.2E-023-28Table 3-8Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th percentile)MHgConcentration (μg/g)Predicted MHgExposure from Ingestion of Fish (mg/kg/day)MHgDissolved Tier3 Tier4 Background RELMAP IS Bald Eagle OspreyKingfisher River Otter Mink LoonConcentration (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 3.8E-02 2.8E-02 2.8E-02Municipal WasteCombustor10 km 5.5E-02 8.8E-02 3.7E-01 24% 2% 74% 1.4E-02 1.8E-02 4.4E-02 2.4E-02 1.8E-02 1.8E-0225 km 2.7E-02 4.4E-02 1.9E-01 48% 4% 48% 7.1E-03 8.7E-03 2.2E-02 1.2E-02 8.7E-03 8.7E-03Variant 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 1.5E-02 1.1E-02 1.1E-02Municipal WasteCombustor10 km 1.9E-02 3.1E-02 1.3E-01 68% 6% 26% 5.1E-03 6.2E-03 1.5E-02 8.4E-03 6.2E-03 6.2E-0325 km 1.6E-02 2.5E-02 1.1E-01 84% 7% 9% 4.1E-03 5.0E-03 1.3E-02 6.8E-03 5.0E-03 5.0E-03Large 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 1.5E-02 1.1E-02 1.1E-0210 km 1.7E-02 2.7E-02 1.1E-01 80% 7% 14% 4.3E-03 5.3E-03 1.3E-02 7.2E-03 5.3E-03 5.3E-0325 km 1.5E-02 2.4E-02 1.0E-01 89% 8% 3% 3.9E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-03Large 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 6.1E-02 4.5E-02 4.5E-0210 km 3.1E-02 5.0E-02 2.1E-01 42% 4% 54% 8.2E-03 1.0E-02 2.5E-02 1.4E-02 1.0E-02 1.0E-0225 km 1.8E-02 2.9E-02 1.2E-01 73% 6% 20% 4.7E-03 5.8E-03 1.4E-02 7.8E-03 5.8E-03 5.8E-03Small 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 9.9E-03 7.3E-03 7.3E-0310 km 1.5E-02 2.4E-02 1.0E-01 87% 7% 6% 4.0E-03 4.9E-03 1.2E-02 6.6E-03 4.9E-03 4.9E-0325 km 1.4E-02 2.3E-02 9.9E-02 91% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03Large 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 7.8E-03 5.7E-03 5.7E-03scrubber)10 km 1.5E-02 2.4E-02 1.0E-01 90% 8% 3% 3.8E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-0325 km 1.4E-02 2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03Small 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 6.3E-03 4.7E-03 4.6E-03scrubber)10 km 1.4E-02 2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 6.2E-03 4.6E-03 4.6E-0325 km 1.4E-02 2.3E-02 9.7E-02 92% 8% 0% 3.7E-03 4.6E-03 1.1E-02 6.2E-03 4.6E-03 4.6E-03Large Coal-fired Utility2.5 km 3.1E-02 4.9E-02 2.1E-01 43% 4% 53% 8.0E-03 9.8E-03 2.4E-02 1.3E-02 9.8E-03 9.8E-03Boiler10 km 1.9E-02 3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 8.2E-03 6.1E-03 6.0E-0325 km 1.8E-02 2.9E-02 1.2E-01 73% 6% 21% 4.8E-03 5.8E-03 1.5E-02 7.9E-03 5.8E-03 5.8E-03Medium Coal-fired Utility2.5 km 2.3E-02 3.6E-02 1.5E-01 58% 5% 37% 5.9E-03 7.3E-03 1.8E-02 9.9E-03 7.3E-03 7.3E-03Boiler10 km 2.0E-02 3.2E-02 1.4E-01 66% 6% 28% 5.2E-03 6.4E-03 1.6E-02 8.7E-03 6.4E-03 6.4E-0325 km 1.8E-02 2.8E-02 1.2E-01 74% 6% 19% 4.6E-03 5.7E-03 1.4E-02 7.7E-03 5.7E-03 5.7E-03Small Coal-fired Utility2.5 km 1.9E-02 3.0E-02 1.3E-01 70% 6% 24% 4.9E-03 6.0E-03 1.5E-02 8.2E-03 6.1E-03 6.0E-03Boiler10 km 1.6E-02 2.6E-02 1.1E-01 81% 7% 13% 4.3E-03 5.2E-03 1.3E-02 7.1E-03 5.2E-03 5.2E-0325 km 1.5E-02 2.4E-02 1.0E-01 88% 7% 4% 3.9E-03 4.8E-03 1.2E-02 6.5E-03 4.8E-03 4.8E-03Table 3-8 (continued)Predicted MHg Exposure to Ecological Receptors for Western Site (Local + RELMAP 50th percentile)MHgConcentration (μg/g)Predicted MHgExposure from Ingestion of Fish (mg/kg/day)MHgDissolved Tier3 Tier4 Background RELMAP IS Bald Eagle OspreyKingfisher River Otter Mink LoonConcentration (ng/L)3-29Medium Oil-fired Utility2.5 km 1.5E-02 2.3E-02 1.0E-01 90% 8% 2% 3.8E-03 4.7E-03 1.2E-02 6.4E-03 4.7E-03 4.7E-03Boiler10 km 1.5E-02 2.3E-02 9.9E-02 91% 8% 2% 3.8E-03 4.7E-03 1.2E-02 6.3E-03 4.7E-03 4.7E-0325 km 1.4E-02 2.3E-02 9.8E-02 92% 8% 1% 3.8E-03 4.6E-03 1.2E-02 6.3E-03 4.6E-03 4.6E-03Chlor-alkaliplant 2.5 km 1.0E+00 1.6E+00 6.9E+00 1% 0% 99% 2.7E-01 3.3E-01 8.1E-01 4.4E-01 3.3E-01 3.3E-0110 km 1.2E-01 1.9E-01 8.0E-01 11% 1% 88% 3.1E-02 3.8E-02 9.5E-02 5.2E-02 3.8E-02 3.8E-0225 km 3.7E-02 5.9E-02 2.5E-01 36% 3% 61% 9.7E-03 1.2E-02 3.0E-02 1.6E-02 1.2E-02 1.2E-023-30 estimates intercom p artmental fluxes and resultin g concentrations in abiotic and biotic com p onents of the watershed and waterbod y . Finall y , ex p osure p redictions are modeled as sim p lified dail y avera g e estimates. Seasonal variabilit y amon g other imp ortant ex p osure factors are not taken into account. Each of these models has p arameter in p uts that are variable and uncertain. Collectivel y , these result in uncertainty in the q uantitative p redictions of the models.

The current scientific understandin g of the environmental c y clin g of mercur y (re g ardless of source) is incom p lete. As described in Volume III, areas of uncertainty include emissions s p eciation, the atmos p heric chemistr y of emitted mercur y , cano py interactions, factors that affect the a q uatic mercur y c y cle (includin g both the ma g nitude of effect exhibited b y a g iven factor as well as p otential interactions amon g different factors), and the metabolism of mercur y in different p iscivorous s p ecies.4-1 

### 4. EFFECTS OF MERCURY ON AVIAN AND MAMMALIAN WILDLIFE

Perha p s better than an y other metal, mercury illustrates the p oint that toxicit y de p ends on the chemical s p ecies in q uestion. As indicated p reviousl y , mercur y can exist in an elemental form, as divalent inor g anic mercur y , or as an y one of several or g anic forms. Of the p ossible or g anic forms that ma y be p resent in natural s y stems, meth y lmercur y g enerall y p redominates. Both inor g anic and meth y lmercur y can accumulate in a q uatic biota. However, the p ro p ortion of total mercur y that exists as the meth y lated form g enerall y increases with tro p hic level, often app roachin g 100% at tro p hic levels 3 and 4. It is a pp ro p riate, therefore, to focus attention on the toxicit y of meth y lmercur y to p iscivorous avian and mammalian wildlife. A review of mercur y toxicit y to mammalian s y stems is p rovided b y Go y er (1993). The toxicit y of mercur y to birds is reviewed b y Scheuhammer (1987). It is not our intention to du p licate these efforts. Instead, a brief summar y of meth y lmercur y toxicit y to vertebrate s y stems is p resented, with the g oal of p rovidin g g uidance on selection of a pp ro p riate toxicolo g ical end p oints. This g eneral discussion is followed b y brief reviews of several toxicity studies involvin g avian and mammalian wildlife s p ecies (Sections 4.1 and 4.2). Information relatin g mercur y residues in tissues to observed toxic effects is summarized in Section 4.4. Research on selenium/mercur y interactions and the activit y of endo g enous demeth y latin g s y stems is described in Section 4.5. A sin g le stud y on the interactive effects of
mercur y and PCBs on re p roduction in mink is reviewed in Section 4.6, em p hasizin g the p oint that wild animals are often ex p osed to multi p le chemical stressors. 4.1 Mechanism of Toxicity

Meth y lmercur y in the diet is absorbed with hi g h efficienc y in the vertebrate di g estive tract and associates
ra p idl y with sulfh y dr y l-containin g molecules in blood, includin g both free amino acids ( p rimaril y c y steine) and g lutathione (Cart y and Malone, 1979). These mobile com p lexes trans p ort meth y lmercur y to tissues and or g ans and ma y facilitate its movement across cell membranes. In p articular, there is g ood evidence for saturable trans p ort of meth y lmercur y -c y steine com p lexes across both the blood-brain and p lacental barriers (Ker p er et al., 1992; Ka j iwara et al., 1996). Althou g h it exhibits a ran g e of toxic effects in several tar g et tissues, the p rimar y effects of meth y lmercur y are on the central nervous s y stem. Neurotoxicit y occurs in both adults and develo p in g animals. In the latter case, this effect a pp ears to be linked to a disturbance of microtubule function in dividin g cells, resultin g in anti-mitotic activit y (Rodier, 1995). The mode-of-action of meth y lmercur y in the differentiated
nervous s y stem is less well known, but may involve selective effects on astroc y tes and other neuro g lial cells (Cranmer et al., 1996). In chronic toxicit y evaluations with mammals, includin g humans, the most sensitive indicator of toxic effect is co g nitive im p airment of animals ex p osed durin g develo p ment (see Volume V of this Re p ort). In g eneral, the so p histicated methods em p lo y ed in such studies have not been used in toxicolo g ical evaluations with wildlife. Instead, less "subtle" endp oints are g enerall y em p lo y ed, includin g reduced hatchin g success and diminished mobilit y . The work of Heinz with mallard ducklin g s (Heinz 1976a,b, 1979) re p resents a notable
exce p tion to this g eneral rule (see Section 4.2). For wildlife, therefore, it is difficult to establish whether
re p roductive or behavioral end p oints are most "sensitive" to meth y lmercur y ex p osure. Efforts to distin g uish between these end p oints are comp licated further b y the fact that re p roductive im p acts can occur as a result of direct effects on the develo p in g nervous s y stem, im p aired behavior of adults (e. g ., unsuccessful matin g s or diminished q ualit y of p arental care g ivin g ), or a combination of both.4-2 4.2 Toxicity Tests with Avian Wildlife Species

Most studies of chronic ex p osure to birds have been conducted usin g mercur y -contaminated g rain. Fimreite (1970) identified a LOAEL of 1.1  g / g /d for g rowth inhibition in le g horn cockerel chicks ( Gallus ) based u p on 6  g / g meth y lmercur y dic y andiamide in the feed. Fimreite (1971) also identified a LOAEL of 0.18  g / g /d for re p roductive effects (reduced survival, reduced e gg p roduction, and defective shells) in rin g
necked p heasant ( Phasianus colchicus ) fed seed treated with meth y lmercur y dic y andiamide. Scott (1977) identified a LOAEL of 4.9  g / g /d for re p roductive effects (reduced fertility , reduced e gg number, reduced survival, defective shells) in domestic chickens.

The most comp rehensive studies of the effect of mercury on birds were conducted b y Heinz (1974, 1975, 1976a,b, 1979). Heinz assessed the effects of dietary meth y lmercur y dic y andiamide (0, 0.5 and 3.0  g / g as elemental mercur y ) over three g enerations of mallard ducks. In the first g eneration, treatment be g an in adult ducks. Subse q uent g enerations received treatment be g innin g at nine da y s of a g e. Initiall y , Heinz (1974) identified a NOAEL of 0.5  g / g based u p on re p roductive effects in a 21 week stud y . In a later stud y (Heinz, 1976a,b), re p roduction in first and second g eneration ducks was evaluated, and the NOAEL for the first g eneration was a g ain determined to be 0.5  g / g . The second g eneration, however, suffered adverse re p roductive effects includin g e gg s laid outside the nest box ( p <0.05), reduced number of ducklin g s survivin g to one week of
a g e ( p <0.05), and reduced g rowth of ducklin g s ( p <0.05) at the 0.5  g / g dose. Conse q uentl y , the LOAEL was 0.5  g / g for re p roductive effects for the second g eneration; no NOAEL was identified. A third g eneration of mallards also demonstrated adverse re p roductive effects at 0.5  g / g mercur y in the diet. Effects observed included reduced number of viable e gg s laid p er da y ( p <0.01) and thinner e gg shells ( p <0.05). Heinz (1975, 1979) also examined behavioral effects of mercury ex p osure on the app roach res p onse of chicks to maternal calls and avoidance of fri g htenin g stimuli. In third g eneration ducklin g s there was a reduction in res p onse rate and s p eed of res p onse to maternal calls ( p <0.01). When data were p ooled from all studies and sub j ect to anal y sis of variance (ANOVA) with multi p le com p arisons, alterations of behavior were observed in the lowest dose g rou p s in all g enerations (0.5  g / g ). These alterations included reduction in the number of ducklin g s which app roached maternal calls ( p <0.01) and an increase in the distance traveled to avoid a threatenin g stimulus ( p <0.05). In summar y , no NOAEL could be determined for behavioral effects, and the NOAEL for re p roductive effects could onl y be demonstrated for the first g eneration.

For the determination of an a pp ro p riate LOAEL in this Re p ort, it was concluded that effects observed in second and third g eneration ducks at 0.5  g / g should not be discounted. It seems likel y that the effects observed in the second and third g enerations were a result of the earlier onset of dosin g . For this reason, 0.5  g / g was selected as a LOAEL for mallard ducks. Assumin g a feedin g rate of 156 g /k g bw/d for adult mallards, the LOAEL is 78  g H g /k g bw/d for re p roduction and behavior. 4.3 Toxicity Tests with Mammalian Wildlife Species River otters ( Lutra canadensis ) fed 2  g / g meth y lmercur y for six months suffered from anorexia and ataxia (O'Connor and Nielson, 1981). In mink, 27  g / g of dietar y p hen y lmercuric chloride caused lethalit y in 40% of the males and 31% of the females within six weeks of ex p osure (Borst and Lieshout, 1977). Wobeser et al. (1976a,b) studied the effects of dietar y consump tion of meth y lmercur y on ranch mink. There were two p arts to this stud y , which to g ether formed the basis of Wobeser's dissertation research (Wobeser, 1973). In the first p art (Wobeser et al., 1976a), 25 adult female mink and their litters were divided into three4-3 g rou p s: Grou p I contained five females and 19 kits (control); Grou p II contained 10 females and 34 kits (50% fish diet); and Grou p III contained 10 females and 29 kits (75% fish diet). The ration was p re p ared usin g mercur y -contaminated freshwater drum from Lake Winni p e g , Manitoba; mercur y in fish tissue was assumed for the p urp oses of the p resent anal y sis to consist p rimaril y of meth y lmercur y . The fish was su pp lied in a g round, frozen form and was then mixed with cereal and uncontaminated chow to a desired com p osition of 50 or 75 k g fish/100 k g of food. All mink were fed once dail y in sli g ht excess of consump tion. The three ex p osure g rou p s were observed for 145 da y s. Assumin g a food consump tion rate of 160 g /k g bw/d (a pp ro p riate to ca p tive animals) (Bleavins and Aulerich, 1981) and an avera g e wei g ht of 0.8 k g for the mink, these treatments
corres p onded to dosin g levels of app roximatel y 35 and 55  g H g /k g bw/d. One female and 3-6 kits were euthanized ever y 15 (treatment) or 30 (control) da y s. Comp lete necro p sies were then p erformed. No clinical si g ns of disease were observed in an y of the mink within the ex p erimental p eriod, and no mortalit y or g rowth im p airment occurred which could be attributed to the feedin g of mercur y -contaminated fish.

In a second ex p eriment (Wobeser et al., 1976b), 30 adult female mink were assi g ned to one of six g rou p s of five animals each. The animals were fed chow s p iked with meth y lmercuric chloride at 0.0 (control), 1.1, 1.8, 4.8, 8.3, or 15.0  g / g (b y anal y sis), corres p ondin g to dosin g levels of 180, 290, 770, 1330, and 2400  g /k g bw/d. Two mink from each g rou p were allowed to die of intoxication or were euthanized after 93 da y s (the end of the
ex p eriment). Animals were necro p sied and the tissues anal y zed for mercur y content. All animals in the control g rou p remained clinicall y normal, and the onl y clinical si g n in the 1.1  g / g dose g rou p was a sli g ht tendenc y for two of the animals to move more slowl y than the others durin g the last few da y s of the ex p eriment. Anorexia, p osterior ataxia, and lateral recumbenc y were observed in the other four dose g rou p s. Death occurred within 26-36 da y s at 4.8  g / g and within 19-26 da y s at 8.3  g / g . Histo p atholo g ical abnormalities were seen at 1.1  g / g , includin g p ale, y ellow livers, lesions in the central nervous s y stem, and axonal de g eneration.

Based u p on a review of the Wobeser studies (Wobeser, 1973; Wobeser et al., 1976a,b), it can be concluded that the LOAEL for subchronic ex p osure of mink to meth y lmercur y is 180  g /k g bw/d (1.1  g / g dose g rou p ), usin g nerve tissue lesions as an effects endp oint. The NOAEL derived from these studies is 55  g /k g bw/d. Im p ortantl y , it was Wobeser's o p inion that had the studies been carried out for a lon g er duration, nervous tissue dama g e observed in the 1.1  g / g dose g rou p would have become manifested as im p aired motor function. Charbonneau et al. (1974) fed random-bred domestic cats ( Felis domesticus ) 3, 8.4, 20, 46, 74 or 176  g /k g /d of mercur y , either as meth y lmercuric chloride in food or as meth y lmercur y -contaminated fish, 7 d/week for 2 y ears. Clinical examinations of the animals were conducted p eriodicall y . Neurolo g ical examinations, usin g a modification of the method of McGrath (1960), were conducted p rior to the test, monthl y throu g hout the test, and more fre q uentl y as clinical si g ns of meth y lmercur y toxicosis became a pp arent. Neurolo g ical im p airment, includin g hindrance of the ho pp in g reaction and h yp al g esia, was observed in animals ex p osed to 46, 74, or 176  g /k g /d, re g ardless of whether casts were fed contaminated fish or s p iked food. No treatment-related effects were observed in three lower dosa g e g rou p s. Overt si g ns of toxicit y , includin g ataxia, loss of balance, and motor incoordination, were observed in animals fed 74 or 176  g /k g /d. These findin g s su gg est that 20  g /k g /d is the NOAEL and 46  g /k g /d is the LOAEL for chronic dietar y ex p osure to meth y lmercur y in domestic cats. Charbonneau et al. (1974) also concluded that there was no difference in toxicit y or bioavailabilit y between naturall y contaminated fish and fish s p iked with meth y lmercuric chloride.4-4 4.4 Tissue Mercury Residues Corresponding to Adverse Effects

Mercur y residues associated with toxic effects in birds are reviewed b y Scheuhammer (1987). Adult p heasants fed a meth y lmercur y -s p iked diet for 12 weeks accumulated liver residues of 2 μg / g but exhibited no discernable adverse effects. However, there was a decrease in hatchabilit y of fertilized e gg s due to embr y onic mortalit y and an increase in the number of unfertilized e gg s. Unhatched e gg s contained 0.5 to 1.5 μg / g as mercur y . In a multi g enerational stud y , hen mallards fed meth y lmercur y in the diet accumulated liver residues of
app roximatel y 1.5 μg / g without app arent adverse effect (Heinz, 1979). Ducklin g s born to these hens exhibited behavioral effects includin g reduced res p onse to maternal calls and h yp er-res p onsiveness to a fri g htenin g stimuli. Mercur y residues in the e gg s from which these ducklin g s hatched were app roximatel y 0.8 μg / g . Kidne y residues considerabl y hi g her (>20 μg / g ) than those j ust reviewed were measured at death in mercur y -dosed birds of several s p ecies (Finle y et al., 1979). Wobeser et al. (1976b) re p orted that mercur y residues in the liver and kidne y of mink that died durin g a 93-da y feedin g stud y were 24.3 and 23.1  g / g , res p ectivel y . Somewhat hi g her values were re p orted in toxicit y studies with mink (55.6 and 37.7  g / g ) b y Aulerich et al. (1974) and with otter (39.0 and 33.0  g / g ) b y O'Connor and Nielson (1980). Interestin g l y , mercur y residues in tissues from wild animals that are sus p ected to have died from mercur y p oisonin g are about twice those of animals that died from ex p erimental intoxication (Wren, 1985, 1991). Such discre p ancies ma y be due to kinetic-based differences amon g ex p osed animals (see Section 2.3.1.3 of this Volume). Perhap s the most valid com p arison that can be made at this time is that between a pp arentl y unaffected wild animals and wild animals that have died from mercur y p oisonin g
. 4.5 Factors Relevant to the Interpretation and Use of Mercury Toxicity Data

Althou g h several excellent studies of meth y lmercur y toxicit y to selected wildlife s p ecies have been carried out, the available data are, in g eneral, q uite limited, and the extent to which these results can be extrap olated from the laborator y to the field and from one s p ecies to another remains in q uestion. Two related issues that ma y contribute substantiall y to this uncertainty are sin g led out for s p ecial attention. These are he p atic demeth y lation as a mechanism for detoxification of meth y lmercur y and the ameliorative effects of dietar y selenium.

The p rotective effect of selenium a g ainst meth y lmercur y toxicit y to birds has been known for over twent y -five y ears (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 s p ecies. Previousl y , it had been shown that much of the
mercur y in the livers in marine mammals existed in an inorg anic form. It is now known that these observations are related. Althou g h efforts to elucidate the exact mechanism continue, selenium has been shown to bind
mercur y after he p atic demeth y lation of meth y lmercur y . The comp ounds formed in this manner p robabl y include both mercur y -seleno p roteins and H g Se (Palmisano et al., 1995; Cavalli and Cardellicchio, 1995).
Thus, it app ears that man y vertebrate s p ecies p ossess a cap abilit y to detoxif y and se q uester mercur y ori g inatin g as meth y lmercur y in the diet. Moreover, the extent to which this ca p abilit y is develo p ed app ears to be related to an animal's feedin g habits and is most hi g hl y develo p ed in fish-eatin g marine mammals and the carnivorous p olar bear (Dietz et al., 1990). Correlations between selenium and mercur y have also been re p orted for several seabirds, althou g h the Se/H g ratio ma y be hi g her than 1:1 (Elliott et al., 1992). The ca p acit y of this
s y stem to detoxif y meth y lmercur y is lar g el y unknown. Variable detoxification amon g individuals of a sin g le
s p ecies ( p ilot whales) has been demonstrated; lactatin g females demonstrated a si g nificantl y diminished detoxif y in g cap abilit y (Caurant et al., 1996).4-5 The demeth y latin g cap abilities of birds and mammals that inhabit terrestrial and freshwater ecos y stems are less well known. Meth y lmercur y constituted 46% of total mercury in the livers of mink fed a diet of meth y lmercur y -contaminated fish (Jernelöv et al., 1976). There was no obvious relationshi p between levels of liver mercur y and selenium. Similar values were re p orted b y Wren et al. (1986) for mink (53%) and otter (34%). Barr (1986) found that meth y lmercur y comp rised 4-27% of total mercur y in livers from loons taken from
mercur y -contaminated waters in northwestern Ontario. Selenium concentrations were not measured. Interestin g l y , the p ercenta g e of meth y lmercur y did not var y with the g radient of site contamination, as mi g ht be
ex p ected if the demeth y latin g s y stem was saturated at p articularl y hi g h ex p osure levels. A p ositive correlation between liver mercur y and selenium was re p orted in the g oldene y e, but no attemp t was made to identif y mercur y s p ecies (Eriksson et al., 1989). Althou g h limited to a sin g le stud y , evidence su gg ests that demeth y lation of meth y lmercur y also occurs in some birds of p re y (Norheim and Forslic, 1978).

Additional evidence that this detoxif y in g p athwa y is related to animal feedin g habits is p rovided b y Fimreite (1974). Amon g adult ducks, fish-eatin g mer g ansers exhibited the lowest levels of meth y lmercur y as a p ercent of total (12% in the liver). Meth y lmercur y constituted 32%, 38% and 52% of total mercury in the livers of g oldene y es, mallards and p intails. Moreover, this detoxif y in g abilit y app ears to develo p earl y in life. Meth y lmercur y levels as a p ercent of total in livers taken from ducklin g s were 27%, 49%, 53% and 58% in the
mer g anser, mallard, g oldene y e and p intail. Meth y lmercur y levels in breast muscle from all four s p ecies as a p ercent of total were essentiall y identical, avera g in g about 60%. The p rotective effect of selenium a g ainst mercur y toxicosis ma y var y with lifesta g e and the chemical form of selenium. Selenium as selenomethionine (10  g / g ) p rotected adult male mallards a g ainst the toxic effects of meth y lmercur y (10  g / g ) in the diet. However, a combination of these treatments in hen mallards resulted in adverse re p roductive effects g reater than those seen with mercury or selenium alone. These effects included reduced hatchin g success and survival of ducklin g s, includin g an increase in terato g enic im p acts (Heinz and Hoffman, 1996). Meth y lmercur y in the diet g reatl y increased selenium stora g e in tissues. The livers of male mallards fed onl y selenium contained 9.6  g / g selenium, whereas in mallards fed both selenium and meth y lmercur y , the livers contained an avera g e of 114  g / g selenium. This observation is im p ortant because hi g h concentrations of selenium are known to p roduce terato g enic effects in wild birds (Ohlendorf et al., 1986). The ecolo g ical si g nificance of these findin g s remains to be determined. Data summarized above su gg est that, amon g duck s p ecies, mallards p ossess less ca p abilit y to detoxif y meth y lmercur y than p iscivorous mer g ansers and g oldene y es. In addition, the levels of mercury and selenium em p lo y ed in this stud y are well above those known to cause toxic effects when a pp lied se p aratel y
. To summarize, man y , if not most, birds and mammals p ossess a cap abilit y to detoxif y meth y lmercur y , and the activit y of this s y stem a pp ears to be related to an animal's feedin g habits. This conclusion is si g nificant for at least two reasons: (1) the toxicity of meth y lmercur y to birds and mammals may be hi g hl y de p endent u p on the availabilit y of dietar y selenium and (2) most toxicity tests with birds conducted to date have been carried out usin g non- p iscivorous s p ecies that ma y not p ossess a well-develo p ed demeth y latin g cap abilit y
.4-6 4.6 Combined Effects of Mercury and Other Chemical Stressors

In most a q uatic s y stems mercur y is but one of man y p otential chemical stressors. Usin g current assessment methods, there is a g eneral tendenc y to evaluate the toxic p otential of com p ounds app lied individuall y . A notable exce p tion is the use of toxic e q uivalenc y factors (TEQs) to p redict the combined im p act of com p ounds that act throu g h an Ah rece p tor-mediated mode of action (PCBs, dioxins). A pp l y in g this app roach to a mixture of mercur y 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 meth y lmercur y , sin g l y and in combination, have been evaluated in mink (Wren et al., 1987a,b). Growth and survival of kits were reduced b y a combined
ex p osure to PCBs (Arochlor® 1254) and meth y lmercur y at concentrations that individuall y p roduced no
res p onse. The authors of these studies described this outcome as a "s y ner g istic 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 res p onse.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 Chap ter 2 of this Volume, mercur y bioconcentrates, bioaccumulates and bioma g nifies in
a q uatic food chains. These p rocesses result in mercury residues in fish that are much hi g her than concentrations in the water in which the y live, thereb y p rovidin g an enriched contaminant source for p iscivorous avian and mammalian wildlife. Existin g data p ermit a g eneral treatment of mercury ex p osure and effects on such p o p ulations. A more accurate assessment of the risk p osed b y mercur y to a s p ecific g rou p of animals occu py in g a g iven location re q uires the collection of necessar y su pp ortin g information such as food habits, mi g rator y behavior, breedin g biolo gy , and mercur y residues in p referred p re y items.

A g eneral summar y of ecolo g ical risk assessment methods is p rovided b y U.S. EPA (1996) in its Pro p osed Guidelines for Ecolo g ical Risk Assessment. The data needs of these methods var y widel y and dictate to a considerable de g ree which methods can be a pp lied to a g iven situation. Guidance is p rovided in Section 5.2 on the risk assessment methods that may be most app licable to airborne mercury emissions, g iven the nature and extent of currentl y existin g information. Additional g uidance is p rovided in Section 5.3 based on a review of p ublished assessments for p iscivorous s p ecies livin g in the Great Lakes re g ion, south Florida, central Ontario, and coastal re g ions of Geor g ia, South Carolina and North Carolina.

The sco p e of the p resent Re p ort was intended to be national in scale. It was determined, therefore, that
an y effort to assess the risk of mercur y to a g iven s p ecies livin g in a defined location would be ina pp ro p riate. Instead, an effort was made to comp are mercur y ex p osure and effects in a g eneral wa y usin g data collected from throu g hout the countr y and in so doin g to develo p q ualitative statements about risk.

Consistent with this broader-scale a pp roach, an effort is made in Section 5.4 to derive a wildlife criterion level (WC) for mercur y that is p rotective of p iscivorous wildlife. This WC is defined as the concentration of
mercur y in water that, if not exceeded, p rotects avian and mammalian wildlife p o p ulations from adverse effects resultin g from in g estion of surface waters and from in g estion of a q uatic life taken from these surface waters. The health of wildlife p o p ulations ma y , therefore, be considered the assessment end p oint of concern. Althou g h not g enerall y derived for the p urp ose of ecolo g ical risk assessment, WC values incor p orate the same t yp e of ex p osure and effects information used in more standard a pp roaches. Such calculations also p rovide for a sim p le assessment of risk in an y g iven situation, i.e., b y determinin g whether the concentration of mercury in water exceeds the criterion value.

Calculation of a WC for mercury is based u p on the use of a wildlife reference dose a pp roach, combined with knowled g e of the extent to which mercury becomes concentrated in a q uatic food chains. The methods used to calculate this criterion value are based on those described in the Pro p osed Great Lakes Water Quality Guidance for the Great Lakes Water Quality Initiative (U.S. EPA, 1993c) and imp lemented in the final Water Qualit y Guidance for the Great Lakes S y stem (U.S. EPA, 1995b), henceforth referred to as the "Pro p osed Guidance" and "Final Guidance," res p ectivel y . When ori g inall y im p lemented in su pp ort of the Great Lakes Water Qualit y Initiative (GLWQI), this app roach y ielded a sin g le measurement end p oint, which was the total
mercur y concentration in water that was believed to be p rotective of p iscivorous wildlife. In the p resent assessment, an effort is made to u p date the WC for mercur y b y calculatin g its value usin g data for meth y lmercur y . It should be noted that a meth y lmercur y -based WC can still be related to total mercur y residues5-2 in fish or water throu g h the use of app ro p riate conversion factors. B y convention, mercur y concentrations in environmental media (and in dosin g solutions) are usuall y ex p ressed as  g / g of elemental mercur y , re g ardless of the identit y of the mercur y s p ecies. This convention is retained throu g hout the p resent anal y sis.

Meth y lmercur y BAFs for tro p hic levels 3 and 4 (fora g e fish and lar g er, p iscivorous fish, res p ectivel y ) are estimated in A pp endix D of Volume III. This information is summarized in Section 5.4.2 of the p resent Volume. It is reco g nized that there is considerable natural variabilit y with res p ect to the accumulation of mercur y in
a q uatic food chains, which contributes in turn to variabilit y in tro p hic relationshi p s and BAFs. In addition, there is a lack of understandin g of fundamental p rocesses that contribute to meth y lation of mercur y and subse q uent bioaccumulation in a q uatic or g anisms. Additional uncertainty derives from on g oin g im p rovements in samp lin g techni q ue and anal y tical methodolo gy . A review of uncertainties associated with the derivation of WC values is p rovided in Section 5.4.11. In g eneral, the same uncertainties a pp l y to an y risk assessment effort for mercur y in wildlife.

Tem p erin g these uncertainties is a lar g e and g rowin g volume of both laborator y and field data for
mercur y . From the p ers p ective of WC develo p ment, field data are of p articular interest. The GLWQI sti p ulates that when sufficient field data are available, field-derived BAFs should take p recedence over values estimated from laborator y studies or b y em p lo y in g em p irical relationshi p s (e. g ., correlation with chemical h y dro p hobicit y ). The focus of the BAF anal y sis in this Volume is on incor p oratin g recent field data into the revised GLWQI
app roach. The results of this effort are summarized in Section 5.4.2.3. 5.2 Summary of Relevant Risk Assessment Methodologies

Perha p s the most comp rehensive t yp e of risk assessment that can be attem p ted is a com p arison of statistical distributions of ex p osure and effects information. In essence, risk is determined from the de g ree of overlap of these distributions. Linearization of the effects and ex p osure distributions simp lifies such
com p arisons. This is g enerall y accom p lished b y lo g transformation of the cumulative ex p osure and effects distributions (U.S. EPA, 1996; SETAC, 1994). A p articularl y g ood examp le of such an assessment is p rovided b y Solomon et al. (1996) for atrazine in a q uatic s y stems.
The data re q uirements of such an app roach are extensive. Moreover, it is criticall y im p ortant that effects information be collected under conditions that are com p arable to the ex p osure data. For this reason, the a pp roach is most easil y app lied in circumstances where the effects are ex p ressed after a relativel y short p eriod of ex p osure and the com p ound of interest does not bioaccumulate. Both of these criteria are satisfied for a com p ound like atrazine.

Mercur y p resents a far g reater challen g e b y virtue of the fact that it bioaccumulates for extended p eriods of time and because toxic effects occur onl y after sufficient bod y residues are attained. Moreover, the limited data collected to date p ermit the characterization of a dose-res p onse curve for onl y three or four wildlife s p ecies.

A more feasible app roach to assessin g chemical risk to wildlife s p ecies involves the com p arison of a p oint estimate of effect with a statistical distribution of exp osure (U.S. EPA, 1996). The data needs of this
app roach include one or a few toxicity studies from which an app ro p riate toxicit y end p oint can be determined and sufficient ex p osure data to define the distribution. In the sim p lest a pp lication of this a pp roach for a
com p ound such as mercur y (for which the diet is the p rimar y route of u p take), ex p osure would be ex p ressed as a residue concentration in p re y . Risk would then be characterized as the p robabilit y that ex p osure ( p re y concentration) would exceed a g iven effect level. Alternativel y , ex p osure can be characterized as a contact rate5-3 (mass of comp ound consumed/k g bw/d). Althou g h more data intensive, this latter a pp roach is p referred because it better reflects the lon g -term nature of the ex p osure.
An even simp ler app roach to wildlife risk assessment ex p resses risk as the ratio of ex p osure and effects p oint estimates. Often referred to as the “hazard q uotient” method, this a pp roach is b y far the most commonl y used of all current techni q ues. It ma y also be the most intuitive, since risk is inferred b y the sim p le fact of a ratio
app roachin g or exceedin g 1.0. The disadvanta g e of this app roach is that is does not p ermit a p robabilistic assessment of risk. Moreover, because this a pp roach is g enerall y used when more detailed data are lackin g , risk assessors often ad j ust the effect level downward usin g one or more “safet y factors.”

In the followin g Section, several p ublished efforts to assess the risk of mercury to wildlife are reviewed. These efforts illustrate the p oint that while information needed to p erform such assessments are extremel y limited, effects information are in g eneral more limited than ex p osure data. 5.3 Review of Published Efforts to Estimate the Risk of Mercury to Wildlife

5.3.1 Risk of Mercur y to Bald Ea g les in the Great Lakes Re g ion Bowerman et al. (1994) comp ared feather mercur y data with measures of re p roductive p erformance to evaluate the risk of mercury to bald ea g les in the Great Lakes Re g ion. Althou g h no attemp t was made to develo p a q uantitative estimate of risk, it was determined that there was no association between mercur y residues in feathers and either p roductivit y or nestin g success. On this basis, it was concluded that mercur y was not affectin g bald ea g le re p roduction. A conclusion of this t yp e ma y be characterized as a q ualitative statement of risk.

5.3.2 Risk of Mercur y to Bald Ea g les in Michi g an
Gies y et al. (1995) used a hazard q uotient a pp roach to characterize the risk to bald ea g les p osed b y mercur y and several or g anic com p ounds at locations above and below dams on three Michi g an rivers. An
ex p osure p oint estimate for mercury was calculated from measured concentrations in fish and an e gg :fish bioma g nification factor (set e q ual to 1.0). Hazard q uotients ran g in g from 0.15 to 0.98 were calculated for
mercur y at stud y sites on the three rivers. The hi g hest q uotients were calculated for sites above the dams due to the p resence of hi g her mercur y levels in fish. The authors concluded that mercur y does not p ose a si g nificant threat to ea g les livin g in this re g ion. This conclusion was based u p on the o p inion that the NOAEC level used in the anal y sis (0.5 μg mercur y / g e gg ) was conservative, as well as the su gg estion that ea g les consume onl y small q uantities of the most contaminated fish s p ecies ( y ellow p erch and walle y e) livin g in these rivers. Hazard q uotients for PCBs and TCDD (e q uivalents) were much g reater than 1.0 (ran g in g from 7.6 to 76) at all sites downstream from the dams.

5.3.3 Risk of Mercur y to Loons in Central Ontario Scheuhammer and Blancher (1994) assessed the risk of mercur y to loons b y comp arin g residues in fish collected from central Ontario lakes with a threshold value for re p roductive im p airment. A stren g th of this assessment is that the toxic effects p oint estimate was also determined in a study of wild loons (Barr, 1986). The fish selected for this anal y sis were of a size app ro p riate to p redation b y loons. Care was also taken to surve y lakes of the t yp e p referred b y breedin g loons. Amon g the lakes surve y ed, u p to 30% contained fish which exceeded the toxicit y threshold, de p endin g u p on the s p ecies of fish chosen.5-4 5.3.4 Risk of Mercur y to Mink in Geor g ia, North Carolina, and South Carolina Osowski et al. (1995) assessed the risk of mercury , PCBs and several chlorinated or g anic p esticides to mink in the coastal re g ions of southeastern U.S. The risk associated with mercury was determined b y comp arin g residue levels in kidne y tissue with levels that had been associated p reviousl y with toxic effects. Unfortunatel y , the threshold effect level (tissue residue) was not g iven. It is difficult, therefore, to criticall y evaluate the author’s conclusion that residues “were in the ran g e of those known to cause imp acts to re p roduction, g rowth, and behavior in wild mink.”

5.3.5 Risk of Mercur y to Mink in Michi g an
A second assessment for mink was conducted b y Gies y et al. (1994) for animals livin g on three rivers in lower Michi g an. In this assessment, an effort was made to calculate a hazard q uotient usin g p ublished toxicit y data for mink (Wobeser, 1976a,b) and measured residues in fish collected from the study sites. Interestin g l y , hazard q uotients g reater than 1.0 were calculated at all three sites (ran g e of 1.2-6.6). However, the si g nificance of this findin g was minimized because hazard q uotients calculated for PCBs and TCDD-like com p ounds tended to be hi g her. In this re g ard, it is of interest to note p revious studies in which mercury and PCBs app eared to act “s y ner g isticall y ” in toxicit y studies with mink (see Section 4.6 of this volume).

5.3.6 Risk of Mercur y to Great E g rets in south Florida Sundlof et al. (1994) re p orted on another researcher’s use of the hazard q uotient method to assess the risk of mercur y to g reat e g rets in south Florida. The actual assessment was conducted as p art of a Masters de g ree research p ro g ram (Jurcz y k, 1993). For this assessment, a p ublished LOAEL for re p roductive effects in loons (Scheuhammer, 1991) was comp ared to a meth y lmercur y consump tion rate calculated usin g measured residues in local fish and shellfish. Based u p on this anal y sis, it was concluded that g reat e g rets were consumin g 3.9 times the LOAEL, thus p lacin g the p o p ulation at risk.
5.4 Calculation of a Criterion Value for Protection of Piscivorous Wildlife

5.4.1 Procedure Used to Develo p Criterion Values for Wildlife in the Water Qualit y Guidance for the Great Lakes S y stem
The WC for mercur y is defined as the concentration of total mercur y in surface water that, if not exceeded, p rotects both avian and mammalian wildlife that use the water as a drinkin g or fora g in g source. Thus, the WC is the hi g hest a q ueous concentration of mercury that causes no si g nificant reduction in g rowth,
re p roduction, viability or usefulness (in a commercial or recreational sense) of a p o p ulation of animals ex p osed over multi p le g enerations. For the p urp ose of this anal y sis, the term "a q ueous concentration" refers to the concentration of meth y lmercur y in filtered water, includin g both the freel y dissolved form and meth y lmercur y that is associated with dissolved or g anic material.

The e q uation used in this anal y sis to calculate a WC for mercury is identical to that described in the Pro p osed Guidance (U.S. EPA, 1993c) and imp lemented in the final Water Qualit y Guidance for the Great Lakes S y stem (U.S. EPA, 1995b):

### WC  ( TD x [1/ UF ]) x Wt A 

### W

A 

### [( FD 3 

### )( F A 

### x BAF 3 

### ) ( FD 4 

### )( F A 

### x BAF 4 

### )]

5-5 where
WC = wildlife criterion value ( pg /L; after convertin g from  g /L) Wt = avera g e s p ecies wei g ht ( g ) A W = avera g e dail y volume of water consumed (L/d) A F = avera g e dail y amount of food consumed ( g /d)

A FD = fraction of the diet derived from tro p hic level 3 3 FD = fraction of the diet derived from tro p hic level 4 4 BAF = a q uatic life bioaccumulation factor for tro p hic level 3 (L/ g ; meth y lmercur y 3 concentration in fish/meth y lmercur y in water) BAF = a q uatic life bioaccumulation factor for tro p hic level 4 (L/ g ; meth y lmercur y 4 concentration in fish/meth y lmercur y in water) TD = tested dose (  g / g bw/d) UF = uncertaint y factor

A similar e q uation was first used b y the State of Wisconsin to set Wild and Domestic Animal Criteria (State of Wisconsin, 1989). The entire a pp roach, includin g both the e q uation and data re q uirements for its p arameterization, was later modified b y U.S. EPA for incor p oration into the Pro p osed Guidance (U.S. EPA, 1993c) and Final Guidance (U.S. EPA, 1995b). The method, in its current form, was reviewed in 1992 at a worksho p entitled “The National Wildlife Criteria Methodolo g ies Meetin g ,” which was s p onsored b y U.S. EPA (U.S. EPA, 1994). Subse q uentl y , the method was used to develo p interim Tier I WC for four com p ounds (PCBs, DDT, dieldrin, and mercur y ) in the Great Lakes Basin (U.S. EPA, 1993b). These criteria have received p ublic comment. The method has been reviewed b y EPA’s Science Advisor y Board on two occasions, most recentl y in June of 1994. Detailed descri p tions of the method, includin g comp arisons with other p ro p osed methods for settin g wildlife criterion values, are g iven elsewhere (U.S. EPA 1993c, 1994). An examination of the GLWQI e q uation reveals both a hazard and an ex p osure comp onent. The
e q uation includes a term TD for “tested dose.” In this Re p ort, data were reviewed to determine an a pp ro p riate NOAEL, which was used for the TD. In the absence of a NOAEL, a LOAEL was used with the addition of an
app ro p riate factor (UF ) to indicate uncertainty around the toxic threshold. An uncertainty factor (UF ) also ma y L A be used to p rovide a mar g in of safet y when app l y in g data from a s p ecies other than the s p ecies of concern. A third uncertaint y factor (UF ) ma y be used to extrap olate from subchronic to chronic ex p osures. Additional S ad

j ustments ma y be warranted b y toxicokinetic or toxicod y namic considerations. Collectivel y , the a pp lication of the UF to the TD results in the estimation of a "reference dose" (RfD) for subse q uent calculation of the WC.

The WC for mercur y derived in su pp ort of the GLWQI was ex p ressed as the total mercury concentration in filtered water. Althou g h it was reco g nized at the time that meth y lmercur y is the form of mercur y that5-6 bioaccumulates in fish, few laboratories p ossessed the anal y tical cap abilit y to s p eciate mercur y in water from natural sources.

A WC for mercur y was calculated in the Pro p osed Guidance usin g fixed values for all p arameters in the
e q uation. S p ecies-s p ecific WC values (WC ) were calculated for each of the wildlife s p ecies of concern (ea g le, s herrin g g ull, kin g fisher, mink, otter). Intermediate WC values (WC ) were then obtained for avian and i mammalian wildlife b y calculatin g the g eometric mean of values for contributin g s p ecies. The final WC (WC ) f was set e q ual to the lowest of the two resultin g intermediate values and, for mercury , was driven b y the calculations for avian s p ecies.

The WC for mercur y derived in the Pro p osed Guidance is 1300 pg /L. A com p arison of the GLWQI f criteria for birds and mammals with those derived in this Re p ort is p resented in Section 5.4.8 of this Volume.

For the p resent anal y sis, a decision was made to consider all but one of the wildlife s p ecies considered in the Pro p osed Guidance. Herrin g g ulls, which are indi g enous to the Great Lakes re g ion, are not evaluated in this Re p ort. The herrin g g ull was re p laced in the p resent anal y sis b y the common loon ( Gavia immer ). The other avian wildlife for which WC values are calculated are the bald eag le ( Haliaeetus leucocephalus ), os p re y ( Pandion haliaetus ) and belted kin g fisher ( Ceryle alcyon ). The mammalian wildlife for which WC are calculated are the mink ( Mustela vison ) and river otter ( Lutra canadensis ). Each of these s p ecies was ori g inall y selected after consideration of the followin g : (1) their ex p osure to bioaccumulative contaminants; (2) their relevance to Great Lakes ecos y stems; (3) the availabilit y of information with which to calculate criterion values; and (4) the evidence for accumulation and/or adverse effects.

Several other wildlife s p ecies would satisf y most or all of the selection criteria p resented in the GLWQI. Notable exam p les include the double-crested cormorant ( Phalacrocorax auritus ), Forster's tern ( Sterna forsteri ), wood stork ( Mycteria americana ), raccoon ( Procyon lotor), sna pp in g turtle ( Chelydra serpentina ), and American alli g ator ( Alligator mississippiensis ). Ex p osure factors for a lar g e number of wildlife s p ecies are available in a recentl y p ublished handbook (U.S. EPA, 1993a). A critical evaluation of these data as the y p ertain to the develo p ment of WC is also available (U.S. EPA, 1995a). Allometric e q uations ma y also be used to calculate both feedin g and drinkin g re q uirements (see for examp le Calder and Braun, 1983; Na gy , 1987). In time, the inclusion of other s p ecies, includin g both amp hibians and re p tiles, ma y be app ro p riate, p articularl y if an effort is made to calculate WC on a re g ional basis or if the s p ecies used in the p resent anal y sis are not re p resentative of the ecos y stem of concern. The p resent anal y sis is intended, however, to be national in sco p e. Each of the s p ecies selected for this anal y sis is distributed over lar g e p ortions of the countr y (see s p ecies distributions in Section 3.3 of this Volume), and in these locations each s p ecies is closel y tied to water resources via a q uatic food chains.

Finall y , this anal y sis differs from that of the GLWQI insofar as WC values are calculated on a “dissolved” (freel y dissolved and associated with DOC) meth y lmercur y basis. A review of literature collected over the last several y ears su gg ests that there is now sufficient information available to estimate BAFs for
mercur y on a meth y lmercur y basis. Previousl y , it was thou g ht that much of the variation around BAFs estimated on a total mercur y basis could be attributed to differences amon g water bodies in the p ro p ortion of total mercur y existin g as the meth y lated form. The g oal of the p resent anal y sis was to calculate a WC for the bioaccumulatin g form of mercur y , thereb y y ieldin g an estimate with the lowest p ossible variation around the mean.5-7 5.4.2 Bioaccumulation Factors (BAFs) for Ma g nification of Meth y lmercur y in A q uatic Food Chains 5.4.2.1 Definition of BAFs and Overview The bioaccumulation factor (BAF) for an y g iven tro p hic level is defined as the ratio of meth y lmercur y concentration in fish flesh divided b y the concentration of dissolved meth y lmercur y in the water column. The BAF re p resents the accumulation of mercury in fish of a s p ecific tro p hic level from both direct u p take from water and p redation on contaminated or g anisms. The BAF is a p rinci p al in p ut variable in the GAS ISC3 ex p osure model used in Volume III of this Re p ort to link estimates of mercury de p osition to ex p osure levels for fishconsumin g s p ecies.

In this Re p ort, BAFs are estimated for tro p hic level 3 (fora g in g fish) and tro p hic level 4 ( p iscivorous fish), which are desi g nated as BAF and BAF , res p ectivel y . BAF is estimated b y three different methods and 34 4 BAF is estimated b y two different methods. The result, or out p ut, of each estimation method is a distribution of 3 BAF values, each associated with some de g ree of likelihood. The three methods b y which BAF is estimated are: 4 a modified GLWQI method, a BAF × PPF method, and a direct field-derived method from measured BAFs at tro p hic level 4. BAF is estimated b y the modified GLWQI method and directl y from measured BAFs at tro p hic 3 level 3. These methods are summarized in Section 5.4.2.2 of this Volume and described in detail in A pp endix D to Volume III (A pp endix D also describes two BAF a pp roaches for total mercur y ). BAF is intended to be 4 re p resentative of the random selection of a tro p hic level 4 fish from a random lake in a random g eo g rap hical location. It is meant to be used to estimate the concentration of meth y lmercur y in such a randoml y -selected fish when multi p lied b y the dissolved meth y lmercur y concentration. BAF p erforms the same function for tro p hic 3 level 3 fish.

The g eneral a pp roach used in this anal y sis was based on p robabilistic methods, as described in A pp endix D to Volume III. This a pp roach was taken to allow q uantitative ex p ression of the overall variability surroundin g the various estimates of the BAFs and to determine the relative sensitivit y of the estimates to s p ecific individual variables.

5.4.2.2 BAF Estimation Methods Modified GLWQI Method The GLWQI method is essentiall y the same as that in the Pro p osed Guidance (U.S. EPA, 1993c), modified to consider onl y meth y lmercur y , and based entirel y on field-derived BCFs and PPFs. The formula is g iven in e q uation 1.
BAF = BCF × FCM (1) n n where

n is the tro p hic level for which the BAF is estimated,

BCF is the wei g hted-avera g e bioconcentration factor (BCF) for dissolved meth y lmercur y at tro p hic level 1, and

FCM is the food-chain multi p lier re p resentin g the cumulative bioma g nification of n meth y lmercur y from tro p hic level 2 to tro p hic level n, n=[3,4].5-8 The formulas for FCM and FCM are g iven in e q uations 2 and 3, res p ectivel y
. 3 4 FCM = PPF × PPF (2) 323 FCM = PPF × PPF × PPF (3) 4234 where

PPF is the p redator- p re y factor at tro p hic level 2 re p resentin g the bioma g nification of 2 meth y lmercur y in zoo p lankton as a result of feedin g on contaminated p h y to p lankton,

PPF is the same for tro p hic level 3 fish feedin g on contaminated or g anisms, and 3 PPF is the same for tro p hic level 4 fish feedin g on tro p hic level 3 fish. 4 Distributions were assi g ned to each of the variables in e q uations 1-3 based on data available in the p ublished literature. The basis and descri p tion of the distribution for each variable are described in A pp endix D of Volume III. The nominal values for some of the variables are not the same as p resented in the Pro p osed Guidance (U.S. EPA, 1993c) due to differin g assump tions and app roaches to data anal y sis.

BAF × PPF Method

The formula for the calculation of BAF b y this method is g iven in e q uation 4. 4 BAF = BAF × PPF (4) 4 3 4 where

BAF is the field-measurement-derived distribution for the BAF at tro p hic level 3 and 3 PPF is the same as for the GLWQI method. 4 Field-derived (Direct) Method

This method estimates BAF and BAF directl y from measurements of BAFs in field studies. The 3 4 derivation of the BAF distributions is described in A pp endix D of Volume III.

5.4.2.3 Results of BAF Simulations and Recommended Values

Results of the p robabilistic simulations for each of the methods are g iven in Table 5-1, which shows
re p resentative statistics for each BAF out p ut distribution. All of the statistics are g iven as the g eometric
e q uivalents (antilo g s) of the actual values g enerated b y the simulations. There is a lar g e variance in the distributions, which cannot be se p arated into variabilit y in BAFs and uncertaint y 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 p ctl 461,000 71,500 1,960,000 3,260,000 331,000

th
95 p ctl 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 develo p ed from field data at each tro p hic level. Values estimated usin g the GLWQI methodolo gy are similar in each case to those estimated from field data but show much g reater variabilit y . This g reater variabilit y is not surp risin g g iven the g reater number of variables and p aucit y of data for the GLWQI a pp roach (see A pp endix D of Volume III). Onl y four field-derived data p oints were available to characterize the BAF and BAF distributions. In each case, however, these data p oints were in relativel y g ood 3 4 a g reement, resultin g in narrower statistical distributions that those associated with the GLWQI and BAF x PPF 3 4 app roaches. The GLWQI sti p ulates that when hi g h q ualit y field data are available, BAFs develo p ed from these data should take p recedence over values estimated usin g laborator y data. At the time of its develo p ment, the field data needed to estimate BAFs for the GLWQI were not available. Recentl y collected field data are thou g ht to be sufficient to g enerate accurate estimates of mean BAFs for tro p hic levels 3 and 4. Confidence in estimates of the g eometric standard deviations is lower. Additional data from a broader arra y of ecos y stem t yp es are needed to better characterize the sha p es of these distributions.

5.4.2.4 Sensitivit y Anal y sis

A limited sensitivit y anal y sis was conducted to examine the influence of distribution form on the BAFs estimated b y the direct field-derived method. The anal y sis investi g ated the im p act on the out p ut of assumin g the BAFs were distributed normall y rather than lo g normall y . The difference in the two assump tions was small, with sli g htl y hi g her median estimates for the normal distributions and sli g htl y hi g her u pp er p ercentiles for the lo g normal. The emp irical data more closel y matched the lo g normal form. This anal y sis is p resented in A pp endix D of Volume III.5-10 5.4.2.5 Uncertaint y and Variabilit y
Generall y , in the re p resentation of the in p ut and outp ut distributions, there are no distinctions as to size
or s p ecies of fish, location or typ e of lake (eutro p hic or oli g otro p hic), water column p H, or absolute mercur y concentrations (in fish or water). The available data are insufficient to make these distinctions. Field data are heavil y biased towards northern (oli g otro p hic) lakes and somewhat towards smaller ( y oun g er) fish.

There is no distinction between variabilit y and uncertaint y in the BAF distributions. That is, the 4 variabilit y in the outp ut distributions reflects both naturall y variable p rocesses and the uncertainty around those p rocesses. For examp le, the BAF distributions include variabilit y in the BAF associated with variations in fish 4 size combined with measurement uncertainties.

Perha p s the g reatest source of variability is that of model uncertainty ; i.e., uncertainty introduced b y failure of the model to account for si g nificant real-world p rocesses. In lake surve y s conducted within a relativel y restricted g eo g rap hic re g ion, lar g e differences can exist between lakes with res p ect to mercur y concentrations in
a g iven s p ecies of fish (see for examp le Co p e et al., 1990; Grieb et al., 1990; Sorenson et al., 1990; Jackson, 1991; Lan g e et al., 1993). Althou g h much of this variability can be attributed to local bio g eochemical p rocesses that determine the p ercenta g e of total mercur y that exists as the meth y lated form, additional sources of variabilit y undoubtedl y exist. In addition, it has been re p eatedl y shown that mercur y in fish accumulates throu g hout the lifetime of the individual (Scott and Armstron g , 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; Lan g e et al., 1993). Re p orted BAF values for a g iven s p ecies ma y , therefore, var y as a function of the a g es of the animals examined. As a result, some researchers have su gg ested that com p arisons between lakes should be made usin g "standardized" fish values (e. g ., a value for a h yp othetical 1 k g northern p ike), t yp icall y derived b y linear re g ression of residue data collected from individuals of vary in g size and/or a g e (Wren and MacCrimmon, 1986; Sorenson et al., 1990; Meili et al., 1991). An additional source of variabilit y is seasonal variation of dissolved meth y lmercur y in the water column. While the concentration of meth y lmercur y in fish flesh is p resumabl y a function of the var y in g water concentration, s p ecific values for BAF and BAF are g enerall y calculated from sin g le re p resentative 4 3 values.

5.4.2.6 Conclusions

BAFs derived from ade q uate data collected at a site of concern should be used in lieu of the estimated values p resented in this Re p ort. The criteria for definin g the ade q uac y of data are discussed in the Data Qualit y Ob j ectives section of A pp endix D in Volume III. When such values are not available, the use of the g eometric mean values from the BAF and BAF out p ut distributions g enerated from the direct field-derived distributions is 3 4 the recommended a pp roach. Use of the g eometric mean, rather than the arithmetic mean, is a conse q uence of the
assump tion that BAFs are distributed in nature as the lo g arithm of the observed value. The recommended
app roach is more direct and less variable than the GLWQI method and involves fewer assum p tions. The recommendation as to the use of the ( g eometric) mean value of these distributions is based on the inabilit y to distin g uish amon g various sources of uncertaint y and variabilit y in the outp ut distributions, with conse q uent p roblems of interp retation of s p ecific p ercentiles. Because the ex p osure concern is for re p eated in g estion of contaminated fish, the mean, rather than the median, is the a pp ro p riate value. The median is onl y useful when the concern is the random selection of a sin g le fish.5-11 Reducin g the uncertaint y in the BAFs g enerated b y these methods will re q uire the collection of more data
re p resentative of the critical factors underl y in g the observed variability and the inclusion of additional terms to
ex p licitl y model those factors. For examp le, the inclusion of an a g e/size re g ression term would account for a substantial p ortion of the variabilit y in both BAF and PPF . 4 4 5.4.3 Ex p osure Parameters

Ex p osure p arameters for the p resent anal y sis are shown in Table 5-2. The scientific basis for p arameters that a pp l y to the mink, otter, kin g fisher, os p re y and ea g le is reviewed elsewhere (U.S. EPA 1993a, 1995a). The wei g ht of loons was calculated as the avera g e of values re p orted b y Barr (1986) for adult males and females, and the feedin g rate was taken from Barr (1973). Data p rovided b y Barr (1996) su gg est that, when g iven the
o pp ortunit y , loons feed almost exclusivel y on live fish and that these fish belon g almost exclusivel y to tro p hic level 3.

Table 5-2 Exposure Parameters for Mink, Otter, Kingfisher, Osprey, and Eagle

S p ecies (WtA) (F ) (W ) Wildlife Food Bod y Wt. In g estion Rate Drinkin g Rate Tro p hic Level of

k g k g /d L/d Source A A % Diet at Each Tro p hic Level

Mink 0.80 0.178 0.081 3 90 Otter 7.40 1.220 0.600 3,4 80,20
Kin g fisher 0.15 0.075 0.017 3 100
Loon 4.00 0.800 0.120 3 100
Os p re y 1.50 0.300 0.077 3 100

Ea g le 4.60 0.500 0.160 3,4 74,18

For this anal y sis, it was assumed that p re y not attributed to tro p hic levels 3 and 4 were derived from nona q uatic ori g ins and do not contain mercury . Were these p re y to contain mercur y , WC values calculated for the relevant s p ecies would decrease. BAFs for tro p hic levels 3 and 4 were assi g ned the values recommended in Section 5.4.2.3 of this Volume.

5.4.4 Summar y of Health End p oints for Avian and Mammalian Wildlife

The avian chronic TD value was derived from studies b y Heinz (1975, 1976a,b, 1979) in which three g enerations of mallard ducks ( Anas platyrhynchos ) were dosed with meth y lmercur y dic y andiamide (0, 0.5 and 3.0 pp m) (see Section 4 of this Volume). The lowest dose, 0.5 pp m (78  g /k g bw/d), resulted in adverse effects
on re p roduction and behavior and was desi g nated as a chronic LOAEL. As no NOAEL was re p orted, a UF of 3 L was used accordin g to methodolo gy described in U.S. EPA (1995b). In a de p arture from the GLWQI, a decision was made not to ad j ust this value further usin g a s p ecies-to-s p ecies uncertaint y factor (UF ) g reater than 1.0. A Althou g h no toxicit y data are available for an y of the bird s p ecies of interest, a review of the literature su gg ests

### WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [(0.9)( F A 

### x BAF 3 

### )]

WC S 

###  (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)]

WC S 

###  57 pg / L

5-12 that p iscivorous birds p ossess a g reater cap abilit y to detoxif y meth y lmercur y than do non- p iscivorous birds (see Section 4 of this volume). Ad j ustin g the TD for mallards even lower is, therefore, un j ustified.
The mammalian chronic NOAEL was derived from studies of subchronic ex p osure b y Wobeser (1973, 1976a,b) in which mink were dosed with mercury in the form of mercur y -contaminated fish (0.22 and 0.33 pp m, naturall y incorp orated into fish; 1.1, 1.8, 4.8, 8.3 and 15.0 pp m, s p iked into the diet). Effects observed include histo p atholo g ic lesions in nerve tissue at 1.1 pp m and hi g her doses. Anorexia, ataxia and death occurred at 1.8 pp m and hi g her doses. The dose of 0.33 pp m (55  g /k g bw/d) was selected as the NOAEL for subchronic
ex p osure. As this was a less than lifetime stud y , a UF of 3 was app lied to the TD or NOAEL. The value of this S uncertaint y factor is less than the value em p lo y ed in the GLWQI (10). However, the authors of the GLWQI also identified 1.1 pp m as the NOAEL, whereas this anal y sis considers the histo p atholo g ical lesions seen in the 1.1 pp m dose g rou p an adverse toxic effect. The subchronic NOAEL/UF is 18.3  g /k g bw/d, which is S app roximatel y e q ual to the chronic NOAEL (20  g /k g bw/d) estimated from lon g -term feedin g studies with domestic cats (Charbonneau et al., 1974).
Based on the information above, the TDs used for calculation of a WC for mercur y were:
For avian wildlife - A LOAEL of 78  g /k g bw/d.

For mammalian wildlife - A NOAEL of 55  g /k g bw/d.

Dividin g the avian TD b y a UF of 3 y ields an avian RfD of 26 μg /k g bw/d. A mammalian RfD of 18 μg /k g bw/d L was calculated b y dividin g the mammalian TD b y a UF of 3. S 5.4.5 Calculation of Wildlife Criterion Values

WC values were calculated for each of the wildlife s p ecies of concern usin g ex p osure values recommended in Section 5.4.4.4. Calculations of WC values for each of the selected s p ecies 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 s p ecies. Therefore, the WC for i f meth y lmercur y is 50 pg /L.

For the mink:

### WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [ (0.8) ( F A 

### x BAF 3 

### ) (0.2) ( F A 

### x BAF 4 

### ) ]

WC S 

###  (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)]

WC S 

###  42 pg / L

WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [ (1.0) ( F A 

### x BAF 3 

### ) ]

WC S 

###  (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) ]

WC S 

###  33 pg / L

WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [ (1.0) ( F A 

### x BAF 3 

### ) ]

WC S 

###  (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) ]

WC S 

###  82 pg / L

5-13 For the otter:

For the kin g fisher:

For the loon:

### WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [ (1.0) ( F A 

### x BAF 3 

### ) ]

WC S 

###  (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) ]

WC S 

###  82 pg / L

WC S 

###  ( TD x [1/( UF A 

### x UFS 

### x UF L 

### )]) x Wt A 

### W

A 

### [ (0.74) ( F A 

### x BAF 3 

### ) (0.18) ( F A 

### x BAF 4 

### ]

WC S 

###  (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)]

WC S 

###  100 pg / L

5-14 For the os p re y :

For the bald ea g le:

5.4.6 Calculation of Mercury Residues in Fish Corres p ondin g to the Wildlife Criterion Value

The WC for meth y lmercur y , alon g with app ro p riate BAFs, can be used to calculate corres p ondin g mercur y residues in fish. Usin g the recommended BAFs p resented in Table 5-1, a WC of 50 pg /L corres p onds to meth y lmercur y concentrations in fish of 0.077  g / g and 0.346  g / g for tro p hic levels 3 and 4, res p ectivel y
. 5.4.7 Calculation of the Wildlife Criterion Value for Total Mercur y in Water

A WC for total mercur y can be calculated usin g an estimate of dissolved meth y lmercur y as a p ro p ortion of total dissolved mercury in water. Mercur y s p eciation data from filtered water sam p les are reviewed in A pp endix D of Volume III. Based u p on a surve y of these data, the best current estimate of meth y lmercur y as a p ro p ortion of total is 0.078. Usin g this value, a meth y lmercur y WC of 50 pg /L corres p onds to a total dissolved
mercur y concentration of 641 pg /L. An additional correction is needed if the WC is to be exp ressed as the amount of total mercury in unfiltered water. The available data, althou g h hi g hl y variable, su gg est that on avera g e5-15 total dissolved mercury comp rises about 70 p ercent of that contained in unfiltered water (Back and Watras, 1995; Driscoll et al., 1995; Mason and Sullivan, 1997; Watras et al., 1995a). Makin g this final correction results in a WC of 910 pg /L (unfiltered, total mercur y ), which is app roximatel y 70 p ercent of the value p ublished p reviousl y 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 p anthers, but were p resented instead to p rovide a comp arison with other mammals. The chronic NOAEL for cats (20  g /k g bw/d) is close to that derived from mink data (18.3  g /k g bw/d). Cats, therefore, do not app ear to be uni q uel y sensitive or insensitive to the toxic effects of mercur y
. Derivation of a WC to p rotect the p anther is comp licated b y the p ossibilit y that p re y items (e. g ., the raccoon) accumulate mercury to an even g reater extent than the fish re p resented b y tro p hic level 4. Other p re y (e. g ., deer) p robabl y contain relativel y lower levels of mercur y . Calculation of a WC p rotective of the p anther, therefore, re q uires collection of additional information on the diet of this s p ecies and mercury residues contained therein. These residues would then have to be related to corres p ondin g levels in water throu g h the use of PPFs (e. g ., raccoon/fish or other a q uatic biota) and BAFs (a q uatic biota/water). Existin g data are insufficient to
su pp ort such an anal y sis but could be collected and develo p ed for this p urp ose.
5.4.9 Comp arison of GLWQI Criteria with WC Derived in this Re p ort
The evaluation of data and calculation of WC values in this Re p ort was done in accordance with the methods p ublished in the draft GLWQI (U.S. EPA 1993a). The availabilit y of additional data and differences in interp retation of those data led to differences in the calculated values of the WC in this Re p ort and those p ublished in the final GLWQI (U.S. EPA 1995b). Both evaluations em p lo y ed the same methodolo gy 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 g eneration re p roduction stud y in mallards (Heinz, 1974, 1975, 1976a,b, 1979) and, for mammals, the subchronic dietar y studies in mink (Wobeser et al., 1976a,b). In addition to these studies, this Re p ort also relies on Wobeser's dissertation (Wobeser, 1973), which p rovided some additional information that was au g mented b y discussions with the author.

To p rovide a basis for comp arin g meth y lmercur y WC values derived in this Re p ort with values calculated in the GLWQI, it was necessar y to convert all meth y lmercur y values to corres p ondin g total mercur y estimates (see Section 5.4.6 of this Volume). Table 5-3 p resents a comp arison between the WC values calculated in the GLWQI (U.S. EPA, 1995b) and this Re p ort (converted to total mercury in unfiltered water). All of the WC values calculated in this Re p ort are lower (i.e., more conservative) than those p ublished in the GLWQI. All
s p ecies-s p ecific WC values, however, differ b y a factor of three or less. Ex p ressed as total mercury , the WC derived in this Re p ort is app roximatel y 70 p ercent of the WC derived in the GLWQI. In the evaluation of effects in birds, both the GLWQI and this Re p ort identified a LOAEL for
re p roductive effects in the second g eneration of mallards ex p osed to 0.5 pp m mercur y in diet (Heinz 1976b, 1979). This LOAEL was ad j usted to 0.078 m g /k g bw/d b y app l y in g an avera g e food in g estion rate for treated mallards of 0.156 k g /k g /d. In calculatin g the wildlife reference dose, the GLWQI used a UF of 3 and a UF of A L 2. This Re p ort 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 p iscivorous mammals, both the GLWQI and this Re p ort used data on mink administered mercury in the diet. The GLWQI identified a NOAEL of 1.1 pp m. At this dietar y5-16 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

S p ecies Wildlife Criterion ( pg /L) GLWQI Mercur y Stud y Re p ort to Con g ress
Mink 2880 1038
Otter 1930 764
Kin g fisher 1040 598
Os p re y Not done 1498
Ea g le 1920 1818

U.S. EPA, 1995b a

ex p osure, there were chan g es in the liver, lesions in the central nervous s y stem, and axonal de g eneration; moreover, two of the animals in this treatment g rou p were observed at the end of treatment to move slowl y b y com p arison to other mink. The stud y authors re p orted their o p inion that mink treated at 1.1 pp m in the diet for lon g er than the stud y would be ex p ected to show clinical si g ns of nervous s y stem dama g e. Animals treated at the next dose, 1.8 pp m, were observed with anorexia, ataxia and increased mortalit y . Based on these considerations, this Re p ort considered 1.1 pp m to be a LOAEL and, as described in Section 4.3, used data from the first p art of the stud y to identif y a NOAEL of 0.33 pp m. This Re p ort also used data from Wobeser (1973) to establish the wei g hts of female mink and kits used in this p art of the stud y ; this resulted in sli g ht differences in conversion of dose in pp m diet to  g /k g bw/d

In its assessment of ex p osure to birds throu g h consump tion of p re y , the GLWQI made assump tions that
were app ro p riate to the Great Lakes re g ion. In p articular the GLWQI assumed that mercury contaminated herrin g g ulls constitute 6% of the diet of bald ea g les. As this Re p ort is a nationwide assessment, use of this
re g ion-s p ecific assum p tion was not considered a pp ro p riate; ea g les were assumed to consume non-fish p re y , with
no mercur y contamination, as 8% of the total diet. The lar g est numerical difference in the ex p osure assessment between the GLWQI and this Re p ort is in the calculation of BAFs. The GLWQI used a BAF of 27,000 for tro p hic level 3 and a BAF of 140,000 for tro p hic level 4. Total mercur y BAFs corres p ondin g to the meth y lmercur y -based values re p orted in Table 5-1 (and assumin g that meth y lmercur y constitutes 7.8 % of total
mercur y ) are 124,800 and 530,400 for tro p hic levels 3 and 4, res p ectivel y
. Thus, the differences between the WC in the GLWQI and in this Re p ort are a result of several factors. First, this Re p ort uses more recent data to derive BAFs. The Su pp lementar y Information Document to the final Water Qualit y Guidance for the Great Lakes S y stem noted that a p reliminar y draft of the Mercur y Re p ort to Con g ress was available but was not used because it had not been com p leted at the time the final g uidance was p ublished (U.S. EPA 1995b, p . 144). Second, the GLWQI app ro p riatel y used some re g ion-s p ecific assum p tions that were not used in this nationwide assessment (e. g ., consump tion of herrin g g ulls b y ea g les). Third, different toxicit y end p oints were used in this Re p ort. In the GLWQI, a risk-mana g ement decision was made to base the5-17 WC on end p oints that com p rise direct effects on g rowth, re p roduction, or develo p ment. In this Re p ort, more sensitive end p oints were considered with the g oal of assessin g a g reater ran g e of toxic effects. Finall y , different uncertaint y factors were emp lo y ed in the two assessments. In g eneral, uncertainty factors used in the GLWQI are more conservative than those used in this Re p ort.
5.4.10 Uncertaint y Anal y sis

A formal anal y sis of uncertaint y around the WC estimate was not attem p ted. Such an anal y sis would
re q uire s p ecification of numeric distributions for each of the p arameters in the e q uation. Data for several of the p arameters in the e q uation, in p articular the NOAEL and UF estimates, are p resentl y sufficient to g enerate p oint estimates onl y . A p artial uncertaint y anal y sis has been conducted for the bioaccumulation p art of the WC
app roach (see A pp endix D of Volume III).

5.4.11 Sensitivit y Anal y sis

In a sensitivit y anal y sis, an attem p t is made to characterize the extent to which a calculated value chan g es with chan g es in the p arameters u p on which its calculation de p ends. Examination of the e q uation for calculation of WC values su gg ests that a p ro p ortional relationshi p exists between the WC and the NOAEL, UF or Wt . The A relationshi p s between the WC and p arameters that a pp ear in the denominator are not as a pp arent and must be
ex p lored b y var y in g these p arameters one-b y -one in s y stematic fashion. The anal y sis is also comp licated b y the variable relationshi p that exists between FD and FD . In the otter and ea g le, FD and FD tend to be reci p rocal 34 34 (althou g h in the ea g le these values do not add u p to 1). In the mink, however, FD is assi g ned a value of less than 3 1, and the remainder of the diet is assumed to consist of p re y that are not a q uatic in ori g in and are not contaminated with mercury
. Nevertheless, g eneral conclusions can be reached re g ardin g the sensitivit y of WC estimates to chan g es in these p arameters. These can be described as follows:

A decrease in an y p arameter that a pp ears in the denominator will have a lar g er effect on WC than an e q uivalent p ercenta g e-wise increase.

When BAF app ears alone in the denominator, a p ercenta g e-wise increase in BAF or FD will 3 3 3 cause a less than p ro p ortional decrease in the WC; conversel y a decrease in BAF or FD will 3 3 cause a g reater than p ro p ortional increase in the WC.

When both BAF and BAF app ear in the denominator, an e q uivalent p ercenta g e-wise chan g e in 3 4 BAF (and b y extension PPF ) has a g reater imp act on the WC than a chan g e in BAF , but in 4 4 3 either case, the effect is less than p ro p ortional.

If BAF and BAF are both allowed to chan g e (holdin g PPF constant), a p ercenta g e-wise 34 4 increase in BAF (and b y extension BAF ) will have a less than p ro p ortional effect on WC, while 3 4 a decrease in BAF will have a g reater than p ro p ortional im p act. 3

Under all circumstances, a p ercenta g e-wise increase in F will cause a less than p ro p ortional A decrease in WC, while a decrease in F will cause a g reater than p ro p ortional increase in WC. A5-18Owin g to its small contribution to the anal y sis as a whole, lar g e chan g es in W have a very small A im p act on WC.

With the exce p tion of F , it is not p ossible to conclude that, for all s p ecies, the WC is most sensitive to A one or the other of the p arameters in the denominator of the e q uation. For s p ecies that feed at one tro p hic level, all p arameters other than F have the p otential to chan g e WC in a p ro p ortional or g reater than p ro p ortional A manner. For s p ecies that feed at two tro p hic levels, the BAF at the lower tro p hic level becomes relativel y less im p ortant, but it ma y still have a lar g e im p act on WC if the p ercenta g e of the diet re p resented b y this lower tro p hic level is lar g e (e. g ., in the mink).

5.4.12 Uncertainties Associated with the Wildlife Criteria Methodolo gy
Efforts to develo p WC values for the p rotection of p iscivorous wildlife are relativel y recent in ori g in, and the methods em p lo y ed for this p urp ose continue to under g o modification and refinement. Owin g to the
com p lexit y of natural s y stems, uncertainties associated with the develo p ment of WC values are to be ex p ected. Additional uncertainties derive from the relative scarcit y of wildlife toxicit y information and the necessity of extrap olatin g individual-based effects to hi g her levels of biolo g ical or g anization (e. g ., p o p ulations).

Uncertainties associated with the WC methodolo gy have been reviewed elsewhere (U.S. EPA, 1994). Rather than re p eat this information, this Re p ort attem p ts to focus on those areas that are es p eciall y p ertinent to the develo p ment of a WC for mercur y . These uncertainties are described below in no p articular order.

5.4.12.1 Limitations of the Toxicity Database

Substantial uncertainties underlie most of the toxicit y data for mercur y in wildlife. Comp arison of NOAELs and LOAELs between s p ecies re q uires ado p tion of un p roven assump tions about the u p take, distribution, elimination, and toxic effects of mercur y . Conclusions based u p on extrap olation from one s p ecies to another are, therefore, tenuous. Additional uncertainties are a result of extra p olatin g from LOAELs to NOAELs and from subchronic end p oints to chronic end p oints. In some instances, there may also be a need to account for the p ossibilit y that test results do not ade q uatel y p rotect the most sensitive individuals. This ma y be p articularl y g ermane to the case of the Florida p anther, where there is concern for individual animals.

Toxicit y studies utilizin g "naturall y incorp orated" mercur y are comp licated b y the p ossibilit y that
mercur y is accomp anied b y other contaminants that are exertin g some or all of the observed effect. Ideall y , it is desirable to comp are the effects of mercur y that has been incor p orated naturall y with effects that are due to
mercur y that has been s p iked into a p re p ared diet. B y s p ikin g mercur y into the diet, the researcher can better control the dose to the animal. The bioavailabilit y of mercur y in such a formulation ma y be different from that which exists naturall y . However, Charbonneau et al. (1976) demonstrated that the bioavailabilit y and toxicit y of meth y lmercur y to cats is e q uivalent whether g iven in contaminated fish or s p iked in the diet.

EPA cannot test all wildlife s p ecies of interest. The use of uncertainty factors for s p ecies extra p olation is likel y , therefore, to continue. Existin g information can be used, however, to su gg est which s p ecies should be sin g led out for testin g . Information of this t yp e is reviewed in this document in several locations and includes
s p ecies distribution, natural history considerations, and ex p osure factors.

Finall y , comp arisons between wildlife and human NOAELs are com p licated b y differences in the ability of a g iven stud y to reveal an adverse effect when it occurs. For wildlife, most of the end p oints selected can be5-19 considered severel y adverse or frank effects. Ver y few studies to date have been desi g ned to stud y subtle adverse effects or p recursors to adverse effects in wildlife. Develo p mental neurotoxicit y end p oints are of p articular interest due to their demonstrated sensitivit y in humans. The q uestion, therefore, arises: what would the LOAEL or NOAEL for a g iven wildlife s p ecies be if the researcher was lookin g for (or was able to detect) these more subtle effects? One a pp roach to this q uestion is to examine the results of studies in which both frank and more subtle effects were observed and determine the corres p ondin g difference between dosa g e levels.

5.4.12.2 LOAEL-to-NOAEL Uncertaint y Factor UF L In determinin g the WC for mercur y ex p osure in wildlife, a chronic NOAEL is the p referred value for the TD. In cases where studies do not identif y a NOAEL, the data are examined to identif y a LOAEL. This LOAEL is then ad j usted usin g a LOAEL-to-NOAEL uncertaint y factor (UF ) to estimate a wildlife RfD. A UF of 3 or L L 10 (based on EPA reference dose methodolo gy ) is t yp icall y app lied when a LOAEL is used in the absence of a NOAEL.

In determinin g the RfD for human ex p osure to meth y lmercur y , a lar g e number of laborator y animal studies on meth y lmercur y toxicit y were summarized as su pp ortin g data. Results from man y of these studies p ermitted estimation of both a LOAEL and a NOAEL. These studies were examined in an effort to determine the most app ro p riate UF for wildlife ex p osure to mercur y
. L The studies examined are summarized in Volume V of this Rep ort. Nineteen studies were selected as bein g the most relevant and a pp ro p riate for determinin g a UF . Selection criteria included the followin g : L

meth y lmercur y toxicit y to nonhuman mammals;

oral ex p osure (with p reference g iven to dosin g in food or drinkin g water); and

chronic or subchronic ex p osure durations (with exce p tions for re p roductive and develo p mental toxicit y where such distinctions are less relevant).

Cancer and g enotoxic end p oints were not included because tumors are not often re p orted in wildlife toxicity studies. End p oints included in the anal y sis included lethalit y , neurotoxicit y , renal toxicit y , g astrointestinal toxicit y , immunotoxicit y , develo p mental toxicit y and re p roductive toxicit y (see Table 5-4). Data abstracted from the studies include the s p ecies and sex of the test sub j ects, toxicolo g ic end p oint, LOAEL, NOAEL and the ratio between them. The LOAEL:NOAEL ratios were not se g re g ated b y end p oint because there was an insufficient number of studies at most endp oints to determine statistical si g nificance.

The ratios of LOAEL-to-NOAELs for laborator y animal studies are p lotted versus fre q uenc y in Fi g ure 5- 1. These ratios can be thou g ht of as the reduction in the LOAEL necessary to estimate the corres p ondin g NOAEL. Fi g ure 5-1 illustrates that the ma j orit y of ratios lie between one and two (n=6) and between four and five (n=9). Onl y one ratio of the 19 p lotted was g reater than 10. A ratio of five indicates that the NOAEL observed followin g ex p osure to meth y lmercur y is 5-fold less than the5-20Table 5-4Analysis of LOAEL-to-NOAEL Uncertainty FactorEndpointLOAELNOAEL RATIOSpecies and Sex (mg/kg/day) (mg/kg/day) LOAEL:NOAEL StudyLethalityB6C3F1 Mouse M0.69 0.60 1.15 Mitsumori et al., 1990NeurotoxicityRat (Wistar) M & F0.25 0.05 5.0 Munro et al., 1980Cat sex NS 0.046 0.020 2.3 Charbonneau et al., 1976Monkey(Macaca fasicularis)M & F0.03 0.02 1.5 Sato and Ikuta, 1975Monkey(Macaca artoidesandM. nemestrina)M & F0.5 0.4 1.25 Evans et al., 1977Renal ToxicityMouse (ICR) M0.72 0.15 4.8 Hirano et al., 1986F 0.62 0.11 5.6Mouse (B6C3F1) M 0.14 0.03 4.7 Mitsumori et al., 1990F 0.6 0.13 4.6Gastrointestinal ToxicityMouse (B6C3F1) M0.69 0.14 4.9 Mitsumori et al., 1990ImmunotoxicityRabbit (New Zealand White) M & F0.4 0.04 10.0 Koller et al., 1977Developmental ToxicityRat (Charles River) F4.0 0.2 20.0 Nolen et al., 1972Rat (Wistar) F 0.25 0.05 5.0 Khera and Tabacova, 1973Rat (Charles River) F 1.4 0.7 2.0 Fowler and Woods, 1977Rat (Wistar) offspringof both sexes 0.6 0.2 3.0 Schreiner et al., 1986Table 5-4 (continued)Analysis of LOAEL-to-NOAEL Uncertainty FactorEndpointLOAELNOAEL RATIOSpecies and Sex (mg/kg/day) (mg/kg/day) LOAEL:NOAEL Study5-21Reproductive ToxicityRat (Wistar) M0.5 0.1 5.0 Khera, 1973Mouse (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)M0.065 0.047 1.4 Mohamed et al., 1987Monkey(M. facicularis)F0.06 0.04 1.5 Burbacher et al., 1988NS - Not stated.5-23 corres p ondin g LOAEL. These data imp l y that most ratios between LOAELs and their corres p ondin g NOAELs will be less than 10.

A similar anal y sis of animal toxicit y data (Weil and McCollister, 1963) was p rovided b y Dourson and Stara (1983). None of the LOAEL-to-NOAEL ratios from studies of 52 chemical substances exceeded 10. Onl y two of the 52 ratios exceeded five. The Dourson and Stara (1983) anal y sis has been cited in su pp ort of the use of a variable UF of as much as 10 in derivin g reference doses for humans. Dourson and Stara (1983) recommended L the a pp lication of a relativel y lar g e UF when estimatin g a NOAEL from a LOAEL for a severe or frank L toxicolo g ical effect. Conversel y , a low UF could be app lied when the toxicolo g ical effect was considered to be L relativel y mild.

The distribution of LOAEL:NOAEL ratios around two and five p rimaril y reflect the dose s p acin g selected for the stud y desi g ns. Two-fold, 5-fold and 10-fold s p acin g are common in ex p eriments of this t yp e. The most app ro p riate inter p retation of the ratios re p orted here and b y Dourson and Stara (1983) is that the threshold for the toxicolo g ic effects, defined b y each stud y , lies within the bounds of the ex p erimentall y derived LOAEL divided b y a UF and that most of the effects thresholds will be encom p assed b y usin g a UF of 10 or L L less. It is also likel y that the most a pp ro p riate UF will var y with the toxicolo g ical end p oint selected. For studies L that identif y onl y a LOAEL, the p rinci p al assum p tion is that the next lower dose, had it been tested, would be a NOAEL. This assum p tion is best app lied to studies that identif y a LOAEL for mild effects. LOAELs for severe or frank effects (which are g enerall y no used for human health risk assessment) re q uire a hi g h de g ree of p rofessional j ud g ment in a pp l y in g a UF . L The anal y sis b y Dourson and Stara (1983) and the anal y sis re p orted here su pp ort the UF of three L selected b y the authors of this Re p ort for use with the avian LOAEL. In derivin g an RfD for avian s p ecies, 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 mercur y ex p osure, neither two nor three can be considered to be the onl y correct value.

5.4.12.3 Validit y of BCF/BAF Paradi g m
A si g nificant shortcomin g of the WC for mercur y calculated in the GLWQI is its reliance u p on BCF values determined in the laboratory . This methodolo gy is based on a bioaccumulation p aradi g m (stead y -state BCF x FCM) that was develo p ed for neutral h y dro p hobic or g anic com p ounds and that ma y be inapp ro p riate for
app lication to mercur y . In addition, the laborator y studies available for estimatin g BCFs were conducted with fish and not with or g anisms at the first tro p hic level ( p h y to p lankton) that be g in the bioaccumulation p rocess. The modified GLWQI method uses field data for directl y determinin g BCFs in p h y to p lankton but must rel y on other uncertain assump tions, such as dr y wei g ht to wet wei g ht conversion factors, to obtain the a pp ro p riate values. The result is increased uncertainty in the results of the GLWQI methodolo gy when comp ared to direct estimation of BAFs from field data.

Field studies indicate that man y , if not most, fish accumulate mercury throu g hout their lives, often in a nearl y linear fashion with a g e (see for examp le Scott and Armstron g , 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; Lan g e et al., 1993). Moreover, most of the mercur y accumulated b y fish at tro p hic level 4 is thou g ht to be taken u p from dietar y sources. Thus, p articularl y for lon g -lived p iscivorous fish, a relativel y short (one y ear or less) waterborne ex p osure cannot du p licate the extent of accumulation that takes p lace in nature. In addition, the relationshi p between a concentration of an app lied mercur y s p ecies in the laborator y and the concentrations of multi p le s p ecies p resent in the environment (some of which ma y not be bioavailable) is com p letel y unknown.5-24 The app arent p ro g ress to "stead y -state" observed in several chronic laboratory studies (see McKim et al., 1976) should not be misinter p reted as an actual stead y -state condition, but instead p robabl y reflects g rowth dilution with rap idl y g rowin g fish. Growth dilution will tend to de p ress BCF values durin g p eriods of ra p id g rowth, but as g rowth rate slows, continued accumulation of mercur y will result in an increase in whole-bod y concentration with a g e.
5.4.12.4 Selection of S p ecies of Concern

The s p ecies identified for the p resent anal y sis were selected because the y were considered likel y to be
ex p osed and not due to their inherent sensitivit y to mercur y . Lackin g toxicit y information, little g uidance is available concernin g which wildlife s p ecies are most sensitive to mercur y . In addition, there are p roblems associated with an y comp arison of laborator y and field data. For examp le, laborator y data su gg est that mercur y residues in e gg s exceedin g 0.5  g / g are associated with im p aired re p roduction in mallard ducks (Heintz, 1974, 1976a,b, 1979) and rin g -necked p heasant (Fimreite, 1971). In contrast, re p roduction in herrin g g ulls app ears to be unaffected even when e gg residues exceed 10  g / g (Vermeer et al., 1973). Taken alone, these data su gg est that mallards and p heasant are more sensitive to the toxic effects of mercur y than are g ulls. This ma y in fact be true; however, such comp arisons are comp licated b y the p resence/absence of additional stressors such as confinement, handlin g and weather, differences between natural and p re p ared diets, the p ossible ameliorative effect of selenium, and the inter p la y between "inherited" (e gg ) residues and that which the chick consumes. Toxicit y can be difficult to observe in a field stud y , even when it is occurrin g . In 18 of 38 nests under stud y b y Vermeer et al. (1973), hatchin g success could not be evaluated for one reason or another.

Clearl y , ex p osure and sensitivity are related. If, for examp le, a s p ecies was, on a delivered dose basis, 10 times more sensitive than the ea g le but, due to its dietar y habits, received less than 10% of the dose, it would not be ex p ected to show adverse effects at water concentrations p rotective of the ea g le. Pharmacokinetic considerations ma y also be imp ortant. Thus, it has been su gg ested that birds eliminate a substantial amount of
mercur y throu g h incorp oration into p luma g e. The fre q uenc y and extent to which birds molt may , therefore, im p act their a pp arent sensitivit y in an environmental settin g . Finall y , it has been shown that most, if not all, wildlife p ossess some ca p abilit y to detoxif y meth y lmercur y b y he p atic demeth y lation. Enhanced demeth y lation would be p articularl y im p ortant if it re p resented an adap tive strate gy for p iscivorous s p ecies. The need for toxicit y information has alread y been noted. As such information becomes available, it ma y be necessar y to revise the WC for mercur y
. There is also a need to consider animals other than birds and mammals. In p articular, there is a need to characterize the ex p osure of carnivorous re p tiles, such as the alli g ator, that are known to consume considerable q uantities of fish and feed on animals (e. g ., raccoon) that themselves feed on a q uatic biota and are known to accumulate mercur y (Roelke et al., 1991).

5.4.12.5 Tro p hic Levels at Which Wildlife Feed

The dietar y p references of the wildlife s p ecies identified for this anal y sis are shown in Table 5-2. Justification for these assi g nments can be found in two recent U.S. EPA p ublications that were develo p ed for the p urp ose of su pp ortin g WC calculations (U.S. EPA 1993a, 1995a). It can be ex p ected, however, that
re p resentatives of the same s p ecies will be ex p osed to different levels of mercury due to different feedin g habits and/or differences in the availabilit y of s p ecific p re y items. For examp le, bald ea g les livin g on the shores of the Great Lakes ma y consume si g nificant numbers of herrin g g ulls (Kozie and Anderson, 1991). Since the g ulls themselves are p iscivores, feedin g p rimaril y at tro p hic level 3, it has been ar g ued that when an ea g le consumes a g ull, it is feedin g at tro p hic level 4 or hi g her; the g ull/fora g e fish PPF is thou g ht to be about 10, while the PPF for5-25 fish at tro p hic level 4 is believed to be a pp roximatel y 5 (U.S. EPA, 1995a). Ea g les livin g in other p arts of the countr y or mi g ratin g into an area durin g a p articular time of y ear ma y consume relativel y few fish, feedin g instead on carrion, includin g rabbits, s q uirrels, and dead domestic livestock such as p i g s and chickens (Har p er et al., 1988). Other p o p ulations, however, are criticall y de p endent u p on the seasonal availabilit y of fish, p articularl y s p awnin g salmonids.

The feedin g habits of bald ea g les are reviewed extensivel y elsewhere (U.S. EPA, 1993a, 1995a). The intent of this discussion is not to characterize the food p references of the ea g le, but instead to demonstrate how difficult it is to characterize wildlife feedin g habits on a nationwide, y ear-around basis. For some s p ecies, such as the kin g fisher and river otter, it can be reasonabl y assumed that fish alwa y s comp rise a hi g h p ercenta g e of the diet. For others, such as the ea g le and mink, considerable variations in diet are likel y to exist. Still others, such as the Florida p anther, consume p re y (e. g ., the raccoon) that, as a s p ecies, consume variable amounts of a q uatic biota but that, in south Florida, are thou g ht to re p resent a close link to the a q uatic food chain.

5.4.12.6 Variabilit y in BAFs at each Tro p hic Level

A concern related to the issue of feedin g p reference is the p ossibilit y that tro p hic levels p resentl y assi g ned to the wildlife s p ecies in this anal y sis overestimate the actual extent to which the y are ex p osed to
mercur y . This is because BAFs are develo p ed to re p resent the avera g e value for a tro p hic level when, in fact, p iscivorous birds and mammals may be more likel y to tar g et p re y at the lower end of the size (a g e) distribution. Thus, ea g les are more likel y to consume a 1 k g northern p ike than a 10 k g individual, y et both are re p resented in the BAF for tro p hic level 4. Similarl y , kin g fishers are p robabl y limited to smaller re p resentatives of tro p hic level 3 than would be true of an os p re y . The reason that these differences are im p ortant is that mercur y tends to accumulate throu g hout the life of an individual fish, such that concentrations in an older individual at a g iven tro p hic level ma y far exceed those in a y oun g er individual.

The need to app l y BAF estimates on a nationwide basis in this study p recludes further refinement. It
ma y , however, be p ossible to ex p lore this issue b y usin g a p robabilistic a pp roach to anal y ze individual data sets. S p ecificall y , it would be of interest to determine whether p ercentile information from the resultin g outp ut distributions can be related to fish of known size. Eventuall y , it ma y be p ossible to use this or another a pp roach to refine BAF estimates for mercury
. 5.4.12.7 Natural Histor y Considerations

Natural ex p osures are likel y to var y in both s p atial and tem p oral domains. This is p articularl y true of
s p ecies that mi g rate, includin g the bald ea g le, os p re y , and belted kin g fisher. The necessit y of incorp oratin g this t yp e of information and the means b y which this can be accom p lished are o p en q uestions.

5.4.12.8 Individuals Versus Po p ulations

The methods used to develo p a WC for mercur y are based on effects data from individual or g anisms. The stated assessment end p oint for this Re p ort, however, is the health of wildlife p o p ulations. The relationshi p between individuals and p o p ulations is likel y to var y with the s p ecies and a lar g e number of environmental factors. For some p o p ulations, the loss of a si g nificant number of individuals ma y have little effect, p articularl y if environmental factors (like carry in g cap acit y ) limit p o p ulation size. Animals that are ca p able of dis p ersin g over lar g e areas p resent an additional com p lication. It is p ossible, for examp le, that ne g ative im p acts could occur within a g iven location but would be difficult to observe due to a continuous influx of as y et unaffected individuals. For other p o p ulations, in p articular those with low fecundity , loss of a relativel y few individuals5-26 could have a lar g e im p act. Clearl y , there is a need to be able to extra p olate toxic effects on individuals to effects
on p o p ulations. Unfortunatel y , this t yp e of anal y sis is comp licated b y numerous factors and is essentiall y im p ossible to app l y on a national scale.

Finall y , a focus on p o p ulations ma y not alwa y s be app ro p riate, p articularl y when endan g ered s p ecies are involved. The same ma y also be true when various factors contribute to the p ossibilit y of re g ional effects. For
exam p le, 95% of ea g les nationwide mi g ht be p rotected b y a WC for avian s p ecies, but in a g iven re g ion mortalit y could app roach 100% if attributes of lakes and rivers in that re g ion contributed to hi g her than avera g e accumulation of mercury in the a q uatic food chain.

5.4.12.9 S p ecies Versus Taxa

The WC develo p ed for mercur y in birds was calculated as the g eometric mean of values for four s p ecies. Similarl y , the g eometric mean of values for two s p ecies was used to re p resent all mammals. This a pp roach is reasonable if the WC calculated for each s p ecies within a taxa are similar, but it would fail to p rotect s p ecies for which the WC value is much lower than the others with which it was avera g ed.

In the p resent anal y sis, WC values calculated for ea g les, os p re y , loon and kin g fisher were within a factor of three of one another. WC values for mink and otter a g reed to within a factor of about one and a half. As additional data are g athered, there is a need to identif y s p ecies that, b y virtue of sensitivit y and/or ex p osure, are p articularl y vulnerable to mercur y . Decisions could then be made concernin g the advisabilit y of s p ecial measures to insure their p rotection.

5.4.12.10 Discussion of Uncertainties Associated with the Wildlife Criteria Methodolo gy
The existin g limited data su gg est that BAF values re p resent an imp ortant source of uncertaint y in p resent efforts to calculate water-based WC values, althou g h a lack of toxicity information and incomp lete knowled g e of what wildlife eat contribute substantiall y . Considerable p ro g ress has been made in understandin g and p redictin g how chemical and biolo g ical factors affect mercury bioaccumulation in a q uatic biota, and, in time, it ma y be p ossible to ad j ust BAF p redictions as needed to re p resent s p ecific surface waters of concern. The p ros p ect for continuin g uncertaint y surroundin g these estimates ar g ues, however, for ado p tion of a residue-based app roach; i.e., the use of measured mercury residues in fish and wildlife to identif y p o p ulations at risk.

It is imp ortant to reco g nize that BAF values are calculated as the ratio of a tissue concentration and a water concentration. Emp hasis has been p laced on p roblems associated with obtainin g the numerator in this
e q uation. However, considerable uncertainty ma y also exist with res p ect to the denominator. In several instances, it has been shown that, with im p roved anal y tical methods, mercur y levels in a g iven water bod y tend to come "down," resultin g in an increase in the a pp arent BAF. This "decline" is usuall y not thou g ht to be real but instead reflects im p rovements in samp lin g techni q ue and anal y tical methods.

It is also unclear which of the mercury s p ecies are bioaccumulative and should, therefore, a pp ear in the denominator. The p resent anal y sis considers dissolved meth y lmercur y to be the best estimator of bioaccumulation p otential in a g iven water bod y . S p eciation data from a variet y of s y stems su gg est that most of the meth y lmercur y in the water column exists as the dissolved form (mean of about 70%) (see App endix D of Volume III). Nevertheless, q uestions remain concernin g the bioavailabilit y of dissolved meth y lmercur y associated with DOC. Additional refinement of the BAF a pp roach ma y re q uire methods to identif y the “freel y dissolved” fraction of meth y lmercur y . A similar app roach is now used routinel y in BAF calculations with hi g h lo g K or g anic com p ounds. OW5-27 An effort was made to treat the uncertainty in BAF estimates b y usin g a p robabilistic a pp roach. The advanta g e of this app roach is that it ex p licitl y treats known variation in these p arameters, thereb y p rovidin g for the statistical p ossibilit y of a hi g h or low end result. In addition, the distributions themselves follow from the p rocesses at work. As more information about mercury is obtained, the distributions themselves can be im p roved. For exam p le, a skewed BAF distribution for tro p hic level 4 would be ex p ected from random samp lin g of a fish p o p ulation due to the relative scarcit y of the oldest individuals. Based u p on a surve y of p ublished data, the distribution of meth y lmercur y values as a p ercent of total also a pp ears to be hi g hl y skewed. With res p ect to the definition of these distributions, it is im p ortant to recall the p ossibilit y of re g ional bias introduced p reviousl y
. It could be ar g ued that FCMs based on re g ression of data for a lar g e number of lakes should be g iven g reater wei g ht ( p erhap s e q ual to the number of lakes) than data from a sin g le location. This, however, would onl y serve to increase the de g ree of re g ional bias that is alread y p resent. 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 pp m of mercur y in tro p hic level 3 fish caused adverse effects on re p roduction in common loons. In the p resent Re p ort, an effort was made to calculate a WC for mercur y which, if not exceeded, would be p rotective of p iscivorous birds and mammals. The mercury residue in tro p hic level 3 fish that corres p onds to this WC is 0.077 pp m, or about one-fourth the effect level identified b y Barr (1986). Based
u p on a review of two national surve y s, the avera g e value for tro p hic level 3 fish in the continental U.S. was estimated to be 0.052 pp m; however, these surve y s ma y have overestimated the true national avera g e due to a bias toward waters receivin g munici p al and industrial waste. Nevertheless, recent surve y s of lakes that do not receive p oint source loadin g s have y ielded residue values in fora g e fish exceedin g 0.077 pp m, p articularl y in
re g ions alread y im p acted b y acid de p osition (see for examp le Gerstenber g er et al., 1993; Simonin et al., 1994; Driscoll et al., 1994; Lan g e et al., 1994; Cabana et al., 1994). Althou g h it is difficult to p recisel y determine an adverse effects level for mercury in fora g e fish consumed b y p iscivorous wildlife, this value a pp ears to lie in the
ran g e 0.077-0.30 pp m. The exact level ma y also var y to some de g ree de p endin g u p on the s p ecies in q uestion and
s p ecific environmental factors.
The effects data, thou g h limited, are remarkable for their consistenc y ; RfDs derived for birds and mammals (mink and domestic cats) are essentiall y identical. Ver y few uncertaint y factors were used in these calculations, and the uncertaint y factor values were small. In addition, the estimated value of UF (used to ad j ust L the TD for avian s p ecies) was su pp orted b y several sources of data. Finall y , it should be noted that all wildlife RfDs are g reater than the RfD for human health b y a factor of about 200 (RfD for human health = 0.1 μg /k g bw/d; see Volume IV). As noted p reviousl y , the human health assessment differs from the wildlife assessment in its consideration of subtle co g nitive im p acts. The p ossibilit y also exists that humans are more sensitive than p iscivorous wildlife on a delivered dose basis, p erhap s due to differences in ability to detoxif y meth y lmercur y
. Nevertheless, the WC for mercury is unlikel y to be g rossl y “overp rotective” (i.e., too low) and ma y , in some instances, be “under p rotective.”5-28 5.5.2 Risk Statements

Given the national-scale sco p e of this Re p ort, q uantitative estimates of risk are not p ossible or
app ro p riate. It is notable, however, that hazard q uotients derived b y other authors for mink (Gies y et al., 1994) and g reat e g rets (Jurczck, 1993) ran g ed from 1.2 to 6.6. Such calculations su gg est the p ossibilit y of local im p acts on these two hi g hl y ex p osed p o p ulations. As indicated p reviousl y , fish residues in some areas exceed calculated WC values for tro p hic levels 3 and 4. It should be em p hasized that these WC values were calculated usin g g eometric mean BAF values; thus, BAFs were hi g her in app roximatel y half of the s y stems for which field-data were available. For this reason, and g iven the small difference between effect (0.3 pp m) and no-effect (0.077 pp m) residue levels, it is likel y that individuals of some hi g hl y ex p osed sub p o p ulations (birds and mammals) are consumin g fish at or ver y near adverse effect levels. Additional work is re q uired to establish whether and to what extent im p acts are occurrin g , and what effect local-scale im p acts ma y have on lar g er s p ecies p o p ulations. Existin g data are insufficient to s p eculate on the s p atial or tem p oral scale of these p ossible adverse effects or the p otential for recover y . However, the risk of adverse effects is g reat enou g h to warrant intensified stud y of hi g hl y ex p osed wildlife sub p o p ulations, p articularl y in areas near mercur y emissions p oint sources. Finall y , the data
su gg est that s p ecial attention should be g iven to the p ossibilit y that mercur y acts in concert with other bioaccumulative contaminants (e. g ., PCBs, TCDD) to p roduce toxic effects at residue levels that, when evaluated
se p aratel y , would not indicate a p roblem.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.

Mercur y emitted to the atmos p here de p osits on watersheds and is translocated to waterbodies. A variable p ro p ortion of this mercur y is transformed b y abiotic and biotic chemical reactions to or g anic derivatives, includin g meth y lmercur y . Meth y lmercur y bioaccumulates in individual or g anisms, bioma g nifies in
a q uatic food chains and is the most toxic form of mercur y to which wildlife are ex p osed.

The p ro p ortion of total mercur y in a q uatic biota that exists as meth y lmercur y tends to increase with tro p hic level. Greater than 90% of the mercury contained in freshwater fish exists as meth y lmercur y
. Meth y lmercur y accumulates in fish throu g hout their lifetime, althou g h chan g es in concentration as a function of time ma y be comp licated b y g rowth dilution and chan g in g dietar y habits.

Piscivorous avian and mammalian wildlife are ex p osed to mercur y p rimaril y throu g h consump tion of contaminated fish and accumulate mercur y to levels above those in p re y items.

Toxic effects on p iscivorous avian and mammalian wildlife due to the consum p tion of contaminated fish have been observed in association with p oint source releases of mercury to the environment.

Concentrations of mercury in the tissues of wildlife s p ecies have been re p orted at levels associated with adverse health effects in laboratory studies with the same s p ecies.

Piscivorous birds and mammals receive a g reater ex p osure to mercur y than an y other known comp onent of a q uatic ecos y stems.

BAFs for mercur y in fish var y widel y ; however, field data are sufficient to calculate re p resentative means for different tro p hic levels. These means are believed to be better estimates of mercur y bioaccumulation in natural s y stems than values derived from laboratory studies. The recommended meth y lmercur y BAFs for tro p ic levels 3 and 4 are 1,600,000 and 6,800,000, res p ectivel y (dissolved basis).

Based u p on knowled g e of mercur y bioaccumulation in fish, feedin g rates, and the identity of p re y items consumed b y p iscivorous wildlife, it is p ossible to rank the relative ex p osure of different p iscivorous wildlife s p ecies. Of the six wildlife s p ecies selected for detailed anal y sis, the relative rankin g of
ex p osure to mercur y is: kin g fisher > otter > loon = os p re y = mink > bald ea g le. Existin g data are insufficient to estimate the ex p osure of the Florida p anther relative to that of the selected s p ecies.

Local emissions sources (<50 km from rece p tors) have the p otential to increase the ex p osure of p iscivorous wildlife well above that due to sources located more than 50 km from the rece p tors (i.e., "remote" sources).

Field data are insufficient to conclude whether the mink, otter, or other p iscivorous mammals have suffered adverse effects due to airborne mercury emissions.6-2Field data are insufficient to conclude whether the loon, wood stork, g reat e g ret, or other p iscivorous wadin g birds have suffered adverse effects due to airborne mercury emissions.

Field data are su gg estive of adverse toxicolo g ical effects in the Florida p anther due to mercur y ; however, the inter p retation of these data is com p licated b y the co-occurrence of several other p otentiall y toxic
com p ounds, habitat de g radation, and loss of g enetic diversit y . Field data su gg est that bald ea g les have not suffered adverse toxic effects due to airborne mercury emissions

Reference doses (RfDs) for meth y lmercur y , defined as chronic NOAELs, were determined for avian and mammalian wildlife. Each RfD was calculated as the toxic dose (TD) from laborator y toxicit y studies, divided b y app ro p riate uncertaint y factors. The RfD for avian s p ecies is 21 μg /k g bw/d (mercur y basis). The RfD for mammalian wildlife is 18 μg /k g bw/d (mercur y basis).

Based u p on knowled g e of mercur y ex p osure to wildlife and its toxicity in lon g -term feedin g studies, criterion values can be calculated for the p rotection of p iscivorous avian and mammalian wildlife. A wildlife criterion (WC) value is defined as the concentration of total mercur y in water which, if not exceeded, p rotects avian and mammalian wildlife p o p ulations from adverse effects resultin g from in g estion of surface waters and from in g estion of a q uatic life taken from these surface waters.

The meth y lmercur y criterion for p rotection of p iscivorous avian wildlife is 74 pg /L (mercur y basis).

The meth y lmercur y criterion for p rotection of p iscivorous mammalian wildlife is 50 pg /L (mercur y basis).

The final meth y lmercur y criterion for p rotection of p iscivorous wildlife s p ecies is 50 pg /L. This value
corres p onds to a total dissolved mercury concentration in the water column of 641 pg /L and meth y lmercur y concentrations in fish of 0.077 pp m (tro p hic level 3) and 0.346 pp m (tro p hic level 4).

Modeled estimates of mercury concentration in fish around h yp othetical mercur y emissions sources p redict ex p osures within a factor of two of the WC. The WC, like the human RfD, is p redicted 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 g ross clinical manifestations. Ex p ression of subtle adverse effects at these doses cannot be excluded.

The adverse effect level ( p o p ulation im p acts on p iscivorous wildlife) for meth y lmercur y in fish that
occu py tro p hic level 3 lies between 0.077 and 0.3 pp m. A comp arison of this ran g e of values with p ublished residue levels in fish su gg ests that it is p robable that individuals of some hi g hl y ex p osed wildlife sub p o p ulations are ex p eriencin g 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 :

Variabilit y in the calculated BAFs is a source of uncertaint y . BAFs g iven in this Re p ort relate meth y lmercur y in fish to dissolved meth y lmercur y levels in the water column. Methods for the
s p eciation of mercur y in environmental sam p les are rap idl y im p rovin g but remain difficult to p erform. Questions also remain concernin g the bioavailabilit y of meth y lmercur y associated with sus p ended6-3 p articulates and dissolved or g anic material. Local bio g eochemical factors that determine net meth y lation rates are not full y understood. The food webs throu g h which mercur y moves are p oorl y defined in man y ecos y stems, and ma y not be ade q uatel y re p resented b y a four-tiered food chain model.

The re p resentativeness of field data used in establishin g the BAFs is a source of uncertainty . The de g ree to which the anal y sis is skewed b y the existin g data set is unknown. A dis p ro p ortionate amount of data is from north-central and northeastern lakes. The a pp licabilit y of these data to a national-scale assessment is unknown.

Limitations of the toxicit y database p resent a source of uncertainty . Few controlled studies of q uantifiable effects of mercury ex p osure in wildlife are available. These are characterized b y limited numbers of dosa g e levels, makin g it difficult to establish NOAEL and LOAEL values. The toxic end p oints re p orted in most such studies can be considered severe, raisin g q uestions as to the de g ree of p rotection a g ainst subtle effects offered b y reference doses and WC values. Use of less than lifetime studies for p rediction of effects from lifetime ex p osure is a source of uncertainty
.

Concerns exist re g ardin g the p ossibilit y of toxic effects in s p ecies other than the p iscivorous birds and mammals evaluated in this Re p ort. Uncertaint y exists about mercury effects in birds and mammals that p re y u p on a q uatic invertebrates and about p ossible effects on amp hibians and a q uatic re p tiles. Uncertaint y also exists about mercury effects in fish. Toxicit y to terrestrial ecos y stems, in p articular soil communities, re p resents another source of uncertainty
.

Lack of knowled g e of wildlife feedin g habits is a source of uncertainty . Existin g information fre q uentl y is anecdotal or confined to evaluations of a p articular localit y ; the extent to which this information can be g eneralized is o p en to q uestion. In some instances wherein feedin g habits are relativel y well characterized (e. g ., Florida p anther), the extent of mercur y contamination of p re y is p oorl y known (e. g ., in raccoons).

While the methods used to assess toxicit y focus on individual-level effects, the stated g oal of the assessment is to characterize the p otential for adverse effects in wildlife p o p ulations. Factors that contribute to uncertainty in p o p ulation-based assessments include these: variabilit y in the relationshi p between individuals and p o p ulations; lack of data on carry in g cap acit y ; and relationshi p s of one p o p ulation, of the same or different s p ecies, to another p o p ulation.

A focus on p o p ulations ma y not alwa y s be app ro p riate. This could be true for endan g ered s p ecies, which
ma y be hi g hl y de p endent for the survival of the s p ecies on the health of a few individuals. This ma y also be true for some re g ional or local p o p ulations of wides p read s p ecies; the local p o p ulation ma y be "endan g ered" and, thus, de p endent on the survival of individuals.

Multi p le stressor interactions involvin g chemical effects are in g eneral p oorl y known. Even less well known are the p ossible effects of land and water use p ractices as the y im p act water q ualit y and lar g escale ecos y stem attributes (e. g ., communit y structure and biodiversit y ).7-1 

### 7. RESEARCH NEEDS

Mercur y is unusual amon g environmental contaminants in that levels that are likel y to cause si g nificant environmental dama g e exceed those thou g ht to be p resent "naturall y " b y less than two (and p erhap s closer to one) order(s) of ma g nitude. Conservative use of uncertainty factors can, therefore, lead to calculation of WC or other similar criterion values that are lower than mercur y residues p resent in even the most p ristine s y stems. With this in mind, there are two g eneral areas within which research p ro g ress must be made if environmental assessments are to be im p roved. The first area p ertains to basic information on the fate and effects of mercur y in the environment, which would result in reduced use of uncertaint y factors and ensure that WC, BAFs, and other estimates are based on a mechanistic understandin g of the relevant p rocesses. The second area is an im p rovement in the abilit y to detect ecolo g ical dama g e when it is in fact occurrin g . The p resent assessment of the "ecolo g ical im p acts" of anthro p o g enic mercur y emissions is lar g el y limited to consideration of toxic effects on individuals. Models that would p ermit extra p olation of these results to p o p ulations (the simp lest extra p olation of individual-based information) do not exist for most s p ecies. Further extrap olation to communities and
ecos y stems is p resentl y out of the q uestion.

Throu g hout this assessment, uncertainties, discussed above and elsewhere in the text, have limited the
sco p e of p ossible conclusions. Althou g h lack of sufficient data is a limitin g factor in all p hases of this assessment, a number of research needs have emer g ed as bein g es p eciall y im p ortant. These needs are p resented below in no p articular order.

7.1 Process-based Research

Mechanistic information is needed to understand the variabilit y that p resentl y t yp ifies the mercur y literature. Laborator y and field studies must be conducted to identif y the determinants of mercury accumulation in a q uatic food chains and to collect kinetic information that would allow researchers to describe the d y namics of these s y stems. Areas of uncertainty include: (1) translocation of mercury from watersheds to waterbodies; (2) factors that determine net rates of meth y lation and demeth y lation; (3) dietar y absorp tion efficienc y from natural food sources; (4) effect of dietar y choice; and (5) bioavailability of meth y lmercur y in the p resence of dissolved
or g anic material and other p otential li g ands.
In time, it is antici p ated that this information can be used to develo p p rocess-based models for mercur y bioaccumulation in fish and other a q uatic biota. Si g nificant p ro g ress in this direction is re p resented b y the Mercur y C y clin g Model (MCM) (Hudson et al., 1994) and b y the GAS-ISC3 model described in Volume III of this Re p ort and emp lo y ed in the wildlife ex p osure characterization. 7.2 Wildlife Toxicity Data

There is a need to reduce the p resent reliance on a relativel y few toxicit y studies for WC develo p ment. Additional data are needed for wildlife that constitute the most exp osed or g anisms in various p arts of the countr y , and in p articular there is need to evaluate whether dietar y selenium and endo g enous demeth y latin g p athwa y s confer p rotection to p iscivorous birds and mammals. Toxicity studies should examine endp oints relevant to the mode of action of meth y lmercur y , includin g assessments of both re p roductive and behavioral effects. There is also a critical re q uirement for toxicit y data (e. g ., g rowth and fecundit y ) that can be related to effects on p o p ulations, includin g effects on or g anisms that com p rise the lower tro p hic levels.7-2 7.3 Improved Analytical Methods

Efforts to develo p and standardize methods for anal y sis of total mercur y and meth y lmercur y in environmental sam p les should be continued. Such methods must reco g nize the im p ortance of contamination, both durin g the collection of such sam p les and durin g their anal y sis. It is p articularl y im p ortant that mercur y measurements, which at p resent tend to be o p erationall y defined (e. g ., "soluble" or "adsorbed to or g anic material"), be made in such a way that mercur y residues in fish can be correlated with the bioavailable mercur y p ool. Whenever p ossible, water samp les should be filtered to obtain a measure of dissolved mercur y s p ecies. As validated methods become available, it is im p ortant to anal y ze for both total and meth y lmercur y so that differences between a q uatic s y stems can be definitivel y linked to differences in meth y lmercur y levels. Anal y zin g the two mercur y s p ecies to g ether will contribute to an understandin g of existin g data, much of which is re p orted as total mercur y
. 7.4 Complexity of Aquatic Food Webs

Present efforts to develo p WC values for mercur y are based on linear, four-tiered food chain models. Research is needed to determine whether this sim p le p aradi g m is a pp ro p riate and to develo p alternatives if field data su gg est otherwise. Of p articular interest is whether zoo p lankton and p h y to p lankton should be modeled as two different tro p hic levels. Current information for detritivores and benthic invertebrates is extremel y limited, even thou g h their imp ortance in mobilizin g h y dro p hobic or g anic contaminants has been demonstrated. 7.5 Accumulation in Trophic Levels 1 and 2

On g oin g efforts to understand mercur y bioaccumulation in a q uatic s y stems continue to be focused on tro p hic levels 3 and 4, des p ite the fact that uncertainties in PPFs are relativel y small. Additional em p hasis should be p laced on research at the lower tro p hic levels. In p articular, there is a need to understand the determinants of
mercur y accumulation in p h y to p lankton and zoo p lankton and how rap id chan g es in p lankton biomass imp act these values.
7.6 Field Residue Data

Hi g h- q ualit y field data are needed to su pp ort p rocess-based research efforts and to determine residue concentrations in the fish and other a q uatic biota that wildlife eat. Whenever p ossible, it is desirable to collect residue data at all tro p hic levels and to anal y ze mercur y levels in the abiotic com p artments of a s y stem (e. g ., water and sediments). It is p articularl y im p ortant that such measurements be made in a broader arra y of a q uatic
ecos y stem t yp es (includin g both lakes and rivers) so that a better understandin g of mercur y c y clin g and accumulation can be obtained.

Residue data from wildlife are needed to identif y p o p ulations that are p otentiall y at risk. Feathers and fur hold considerable p romise in this re g ard due to the p otential for "non-invasive" determination of mercur y residues. Laborator y research is re q uired, however, to allow inter p retation of these data. Factors such as a g e, sex, and time to last molt are likel y to result in variability amon g individuals of a sin g le p o p ulation and need to be understood. Whenever p ossible, tissue sam p les should be anal y zed for both total and meth y lmercur y , as well as selenium. This is es p eciall y true of the liver. More attention should be g iven to anal y sis of mercur y levels in brain tissue, since this is the p rimar y site of toxic action. Sam p lin g efforts with wildlife should be accom p anied b y anal y ses of likel y food items.7-3 7.7 Natural History Data

The develo p ment of WC values re q uires knowled g e of what wildlife eat. Fish sam p lin g efforts are fre q uentl y focused on s p ecies that are relevant to human consumers but that ma y be of little si g nificance to wildlife. There is an additional need to collect information for macroinvertebrates and am p hibians. Seasonal and
s p atial effects on p redation should be ex p lored and methods develo p ed to describe this information ade q uatel y
. Additional life history data is needed to characterize full y the nature and extent of ex p osure to mercur y
. Com p licatin g factors must be considered, includin g mi g rator y behaviors and sex-s p ecific differences in distribution and resource allocation. It is p articularl y im p ortant that information be collected to su pp ort the develo p ment of p redictive p o p ulation models for sensitive s p ecies. Such models must account for immi g ration and emi g ration, densit y de p endent factors, and the observation that mercur y often bioaccumulates as animals a g e resultin g in variable residues in breedin g animals from a sin g le p o p ulation.8-1 

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